Biomarkers for predicting the effectiveness of cancer treatment

Abstract

This specification provides biomarkers useful for identifying patients for therapies including immune checkpoint inhibitors, and methods for using them. In particular, this disclosure provides techniques for using biomarker expression levels in biological samples obtained from patients for the treatment and prognosis prediction of cancer in patients, and for determining the likelihood that a patient will respond to therapies including immune checkpoint inhibitors. This disclosure provides biomarkers useful in many situations, in particular for identifying patients for the treatment of diseases, especially cancer, with regard to therapies including immune checkpoint inhibitors.

Description

[Technical Field]

[0001] (Cross-reference of related applications) This application claims interest in U.S. Provisional Application No. 63 / 470,660, filed 2 June 2023, U.S. Provisional Application No. 63 / 539,295, filed 19 September 2023, and U.S. Provisional Application No. 63 / 649,808, filed 20 May 2024, all of which are incorporated by reference in whole. [Background technology]

[0002] The following considerations are provided to help readers understand this disclosure and are not intended to describe or constitute prior art.

[0003] Cancer continues to pose a significant burden worldwide. Lung cancer is the most common form of cancer and the leading cause of cancer death globally. In 2018, more than 2 million cases of lung cancer were diagnosed, and it was responsible for 1.76 million deaths worldwide. Of the histological types, non-small cell lung cancer (NSCLC) accounts for approximately 80% of all lung cancer diagnoses. The majority of NSCLCs are advanced. Survival is poor for patients with metastatic NSCLC, with a 5-year survival rate of approximately 4%.

[0004] Globally, gastric and esophageal cancers are the fifth and seventh most frequently diagnosed cancers, respectively. While the incidence of these malignancies varies worldwide, survival rates for patients with locally advanced, unresectable disease and / or metastatic disease remain low regardless of geography. Gastric cancer is the third leading cause of cancer death worldwide, and esophageal cancer is the sixth leading cause of cancer death worldwide. Furthermore, in the United States, the proportion of esophageal adenocarcinoma is increasing, the incidence of gastric cancer may be increasing among people under 50 years of age, and the five-year survival rate for patients with metastatic esophageal or gastric cancer is approximately 5 percent (National Cancer Institute SEER Program, 2021a; National Cancer Institute SEER Program, 2021b).

[0005] Immunotherapy is a promising class of drugs for treating cancer. Immunotherapy treatments targeting programmed death receptor 1 (PD-1), programmed death ligand 1 (PD-L1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and lymphocyte-activation gene 3 (LAG-3) have received regulatory approval for a variety of cancer indications, including, but not limited to, lung cancer, head and neck cancer, gastric and esophageal cancer, bladder cancer, and hematological malignancies, with several new classes of immunotherapies targeting other immune checkpoint inhibitors currently in clinical trials. Recent advances in immunotherapy have or may change the treatment paradigm for many cancers, but many patients do not respond to immunotherapy or eventually relapse. Resistance can arise through various mechanisms, including the persistence of resistant clones or alterations in the tumor microenvironment (TME). Furthermore, because the immune system interacts with TME, inhibiting only one axis may not be a simple solution. Other regulators of the complex immune system may offer interesting additional mechanisms for advancing cancer treatment. Therefore, there is still a need for effective treatment regimens for immunotherapies, such as immune checkpoint inhibitors, that deliver meaningful clinical efficacy, as well as means to identify patients and predict which patients will respond. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] National Cancer Institute SEER Program,2021a;National Cancer Institute SEER Program,2021b [Overview of the project] [Means for solving the problem]

[0007] This disclosure provides biomarkers that are useful in many situations, particularly for identifying patients for the treatment of diseases, especially cancer, with therapies including immune checkpoint inhibitors.

[0008] In one embodiment, the Disclosure provides a use for identifying a patient for treatment with an immune checkpoint inhibitor, wherein the patient has cancer and a sample obtained from the patient contains (a) a PD-L1 expression level above or below the PD-L1 reference level, (b) a CD155 expression level above or below the CD155 reference level, (c) a CD226 expression level above or below the CD226 reference level, (d) an adenosine pathway biomarker expression level above or below the adenosine pathway biomarker reference level, (e) a CD73 expression level above or below the CD73 reference level, or (f) any combination of (a), (b), (c), (d), and (e), which is used to identify the patient for treatment with an immune checkpoint inhibitor. In some embodiments, a patient is identified for treatment with an immune checkpoint inhibitor if (a) PD-L1 expression level is equal to or greater than the PD-L1 reference level, (b) CD155 expression level is equal to or greater than the CD155 reference level, (c) CD226 expression level is equal to or greater than the CD226 reference level, (d) adenosine pathway biomarker expression level is lower than the adenosine pathway biomarker reference level, (e) CD73 expression level is lower than the CD73 reference level, or (f) any combination of (a), (b), (c), (d), and (e).

[0009] In one embodiment, the present disclosure provides a use for determining the prognosis of a patient with cancer, wherein the biomarker is selected from PD-L1, CD155, CD226, CD73, adenosine pathway biomarkers, and any combination thereof, and the patient is determined to have a good prognosis if a sample obtained from the patient includes (a) a PD-L1 expression level equal to or lower than the PD-L1 reference level, (b) a CD155 expression level equal to or lower than the CD155 reference level, (c) a CD226 expression level equal to or lower than the CD226 reference level, (d) an adenosine pathway biomarker expression level equal to or lower than the adenosine pathway biomarker reference level, (e) a CD73 expression level equal to or lower than the CD73 reference level, or (f) any combination of (a), (b), (c), (d), and (e).

[0010] In one embodiment, the present disclosure provides a method for treating cancer in a patient, comprising administering to the patient a therapy comprising an immune checkpoint inhibitor if a sample obtained from the patient comprises: (a) a PD-L1 expression level equal to or lower than the PD-L1 reference level; (b) a CD155 expression level equal to or lower than the CD155 reference level; (c) a CD226 expression level equal to or lower than the CD226 reference level; (d) an adenosine pathway biomarker expression level equal to or lower than the adenosine pathway biomarker reference level; (e) a CD73 expression level equal to or lower than the CD73 reference level; or (f) any combination of (a), (b), (c), (d), and (e). In some embodiments, the therapy is administered to a patient if (a) the PD-L1 expression level is equal to or greater than the PD-L1 reference level, (b) the CD155 expression level is equal to or greater than the CD155 reference level, (c) the CD226 expression level is equal to or greater than the CD226 reference level, (d) the adenosine pathway biomarker expression level is lower than the adenosine pathway biomarker reference level, or (e) the CD73 expression level is lower than the CD73 reference level, or (f) any combination of (a), (b), (c), (d), and (e).

[0011] In one embodiment, the present disclosure is a method for identifying a patient with cancer for treatment with a therapy comprising an immune checkpoint inhibitor, comprising: (a) measuring the level of one or more of PD-L1, CD155, CD226, adenosine pathway biomarkers, and CD73 in a sample obtained from the patient; (b) comparing the level measured in (a) to the respective reference level; and (c) (i) whether the measured PD-L1 level is equal to or greater than the PD-L1 reference level or lower than the PD-L1 reference level; or (ii) whether the measured CD155 level is equal to or greater than the CD155 reference level or CD15 The present invention provides a method for identifying a patient for treatment in therapy in any combination of (i), (ii), (iii), (iv), and (v) among (i), (ii), (iii), (iv), and (v) below the reference level, (iv) the measured CD226 level is above the CD226 reference level or below the CD226 reference level, (iv) the measured adenosine pathway biomarker level is above the adenosine pathway biomarker reference level or below the adenosine pathway biomarker reference level, (v) the measured CD73 level is above the CD73 reference level or below the CD73 reference level, and (vi). In some embodiments, a patient is identified for treatment if (i) the measured PD-L1 level is equal to or greater than the PD-L1 reference level, (ii) the measured CD155 level is equal to or greater than the CD155 reference level, (iii) the measured CD226 level is equal to or greater than the CD226 reference level, (iv) the measured adenosine pathway biomarker level is lower than the adenosine pathway biomarker reference level, (v) the measured CD73 level is lower than the CD73 reference level, or (vi) any combination of (i), (ii), (iii), (iv), and (v).

[0012] In any of the embodiments and models described above, the therapy may be monotherapy or combination therapy. In some embodiments, the therapy comprises an anti-PD-(L)1 antibody, an anti-TIGIT antibody (optionally, the anti-TIGIT antibody is domvanalimab), and / or an ATP-adenosine axis targeting agent. In some embodiments, the combination therapy comprises chemotherapy. In some embodiments, the chemotherapy comprises a platinum-containing agent.

[0013] The methods provided herein are useful for the treatment of cancers, including gastrointestinal cancers, genitourinary cancers, gynecological cancers, and lung cancers.

[0014] Both the above summary and the following descriptions of the drawings and detailed description are illustrative and descriptive. They are intended to provide further details of the disclosure, but should not be construed as limiting them. Other purposes, advantages, and novel features will be readily apparent to those skilled in the art from the following detailed description of the disclosure.

[0015] It should be understood that all combinations of the aforementioned concepts and any additional concepts discussed in more detail below are provided as part of the subject matter of the invention disclosed herein and may be used in any combination to achieve the benefits described herein.

[0016] A patent or application file shall include at least one drawing made in color. A copy of this patent or patent application containing the color drawing shall be provided by the Patent Office upon request and payment of the required fees. [Brief explanation of the drawing]

[0017] [Figure 1A]This graph shows that TIGIT, PD-1, CD226, and related ligands are expressed on a broad cell population in human NSCLC TIL suspension. Figure 1A shows the frequencies of Treg (CD4+FoxP3+), CD4+T (CD4+FoxP3-), CD8+T, CD3-CD19+B, CD3-CD56+NK, CD14+ and / or CD16+ monocytes, SSChi bone marrow / macrophages, and CD45- cancer or stromal subsets in NSCLC tumor-infiltrating lymphocyte (TIL) suspension. Figure 1B shows the frequencies of TIGIT (top), PD-1 (middle), and CD226 (bottom) in the CD4+, Treg, and CD8+T subsets (circles, left y-axis) and geometric mean fluorescence intensity (gMFI) (triangles, right y-axis). Figure 1C shows the frequencies of PD-1+TIGIT+CD226+ triple-positive cells in the CD4+, Treg, and CD8+T subsets. Figure 1D shows the frequencies of CD155 (top) or PD-L1 (bottom) (circles, left y-axis) and gMFI (triangles, right y-axis) in the subsets from (Figure 1A). PD-L1 gMFI is plotted as fold change (FC) against isotype (iso), due to dramatic differences in baseline expression between subsets. Data from n=6–10 NSCLC subjects were collected from two independent experiments. Symbols represent individual subjects. Bars and errors represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test: *p<0.05, **p<0.01, ***p<0.001, 894****p<0.0001. See gating strategies in Figures 7A–7C. [Figure 1B]This graph shows that TIGIT, PD-1, CD226, and related ligands are expressed on a broad cell population in human NSCLC TIL suspension. Figure 1A shows the frequencies of Treg (CD4+FoxP3+), CD4+T (CD4+FoxP3-), CD8+T, CD3-CD19+B, CD3-CD56+NK, CD14+ and / or CD16+ monocytes, SSChi bone marrow / macrophages, and CD45- cancer or stromal subsets in NSCLC tumor-infiltrating lymphocyte (TIL) suspension. Figure 1B shows the frequencies of TIGIT (top), PD-1 (middle), and CD226 (bottom) in the CD4+, Treg, and CD8+T subsets (circles, left y-axis) and geometric mean fluorescence intensity (gMFI) (triangles, right y-axis). Figure 1C shows the frequencies of PD-1+TIGIT+CD226+ triple-positive cells in the CD4+, Treg, and CD8+T subsets. Figure 1D shows the frequencies of CD155 (top) or PD-L1 (bottom) (circles, left y-axis) and gMFI (triangles, right y-axis) in the subsets from (Figure 1A). PD-L1 gMFI is plotted as fold change (FC) against isotype (iso), due to dramatic differences in baseline expression between subsets. Data from n=6–10 NSCLC subjects were collected from two independent experiments. Symbols represent individual subjects. Bars and errors represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test: *p<0.05, **p<0.01, ***p<0.001, 894****p<0.0001. See gating strategies in Figures 7A–7C. [Figure 1C]This graph shows that TIGIT, PD-1, CD226, and related ligands are expressed on a broad cell population in human NSCLC TIL suspension. Figure 1A shows the frequencies of Treg (CD4+FoxP3+), CD4+T (CD4+FoxP3-), CD8+T, CD3-CD19+B, CD3-CD56+NK, CD14+ and / or CD16+ monocytes, SSChi bone marrow / macrophages, and CD45- cancer or stromal subsets in NSCLC tumor-infiltrating lymphocyte (TIL) suspension. Figure 1B shows the frequencies of TIGIT (top), PD-1 (middle), and CD226 (bottom) in the CD4+, Treg, and CD8+T subsets (circles, left y-axis) and geometric mean fluorescence intensity (gMFI) (triangles, right y-axis). Figure 1C shows the frequencies of PD-1+TIGIT+CD226+ triple-positive cells in the CD4+, Treg, and CD8+T subsets. Figure 1D shows the frequencies of CD155 (top) or PD-L1 (bottom) (circles, left y-axis) and gMFI (triangles, right y-axis) in the subsets from (Figure 1A). PD-L1 gMFI is plotted as fold change (FC) against isotype (iso), due to dramatic differences in baseline expression between subsets. Data from n=6–10 NSCLC subjects were collected from two independent experiments. Symbols represent individual subjects. Bars and errors represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test: *p<0.05, **p<0.01, ***p<0.001, 894****p<0.0001. See gating strategies in Figures 7A–7C. [Figure 1D]This graph shows that TIGIT, PD-1, CD226, and related ligands are expressed on a broad cell population in human NSCLC TIL suspension. Figure 1A shows the frequencies of Treg (CD4+FoxP3+), CD4+T (CD4+FoxP3-), CD8+T, CD3-CD19+B, CD3-CD56+NK, CD14+ and / or CD16+ monocytes, SSChi bone marrow / macrophages, and CD45- cancer or stromal subsets in NSCLC tumor-infiltrating lymphocyte (TIL) suspension. Figure 1B shows the frequencies of TIGIT (top), PD-1 (middle), and CD226 (bottom) in the CD4+, Treg, and CD8+T subsets (circles, left y-axis) and geometric mean fluorescence intensity (gMFI) (triangles, right y-axis). Figure 1C shows the frequencies of PD-1+TIGIT+CD226+ triple-positive cells in the CD4+, Treg, and CD8+T subsets. Figure 1D shows the frequencies of CD155 (top) or PD-L1 (bottom) (circles, left y-axis) and gMFI (triangles, right y-axis) in the subsets from (Figure 1A). PD-L1 gMFI is plotted as fold change (FC) against isotype (iso), due to dramatic differences in baseline expression between subsets. Data from n=6–10 NSCLC subjects were collected from two independent experiments. Symbols represent individual subjects. Bars and errors represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test: *p<0.05, **p<0.01, ***p<0.001, 894****p<0.0001. See gating strategies in Figures 7A–7C.

[0018] [Figure 2A]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8. [Figure 2B]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8. [Figure 2C]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8. [Figure 2D]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8. [Figure 2E]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8. [Figure 2F]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8. [Figure 2G]In scRNA-seq datasets, TIGIT and PDCD1 are expressed on pre-exhausted Tpex cells, but CD226 is not. Conversely, TIGIT, PD-1, and CD226 are detected at protein levels in a Tex subset in commercially available human NSCLC TIL suspensions. TIGIT, PDCD1, and CD226 gene expression were evaluated in Tpex populations in two publicly available human NSCLC scRNA-seq datasets. Tpex was identified by filtering single-cell clusters in the following order: medium to high expression of PD-1 (PCDC1), negative expression of TIM-3 (HAVRC2), and positive expression of granzyme K (granzyme K, GZMK). Figure 2A shows UMAP plots mapping Tpex cells in the datasets of Guo et al. (top left) and Gueguen et al. (top right), as well as the percentage of Tpex relative to total CD8+ T cells in each dataset (bottom). Box (25th–75th percentile) and whisker (mixed to the maximum) plots with symbols representing each NSCLC subject. n=11–14. Figure 2B shows UMAP plots mapping PDCD1 (top), TIGIT (middle), and CD226 (bottom) expression relative to total CD8+ T cells in each dataset, as shown. Shading highlights Tpex cells. Figure 2C shows representative pseudocolor plots (top) and frequencies of Tpex (TCF-1+TIM-3-) and Ttex (TCF-1-TIM-3+) containing populations in the CD8+ T subset of NSCLC TIL suspension. Figure 2D shows representative histograms of PD-1, TIGIT, CD39, CD226, GzmK, GzmB, and CD103 in the TCF-1+TIM-3- and TCF-1-TIM-3+ populations. Figure 2E shows representative dot plots of TIGIT, CD226, and PD-1 expression (top) and the frequency of PD-1+TIGIT+CD226+ triple-positive cells (bottom) in the TCF-1+TIM-3 and TCF-1-TIM-3+ populations.Figure 2F shows an alternative method (top) for identifying functional (PD-1-), pre-exhausted Tpex (PD-1+), and terminally differentiated / dysfunctional Ttex (PD-1hi)-containing CD8+ T cell subsets in NSCLC TIL suspension, and the frequencies of the six subpopulations in the total CD8+ T subset (bottom). Figure 2G shows representative histograms (top left) and plotted gMFI (top right) for TIGIT and CD226 on the six populations from Figure 2F, as well as the frequencies of TIGIT+CD226+ double-positive cells in the six populations from Figure 2F (bottom). Figures 2C-2G show NSCLC subjects n=5-9. Symbols represent individual subjects, and lines connect identical subjects. Bars and error represent median ± range. Standard one-way ANOVA with Tukey's multiple comparison test, *p<0.05, ***p<0.001, ****p<0.0001. Only data with >100 events per group are shown. See gating strategies in Figures 7A-7C. See also Figure 8.

[0019] [Figure 3A]This study demonstrates that TIGIT, PD-1, and CD226 are co-expressed in MC38 mouse tumors and tdLNs. The expression of TIGIT, PD-1, CD226, CD155, and PD-L1 was examined by flow cytometry in MC38 tumors (50–150 mm3) and inguinal tdLNs. n=8–10. Symbols represent individual mice. Bars and error represent median ± range. Only data with >100 events per population are shown. Representative data from at least three independent studies are shown. Figure 3A shows the frequency of Tpex(TCF-1+TIM-3-) and Ttex(TCF-1-TIM-3+)-containing populations in tumors and tdLNs. Figure 3B shows the frequencies (left) of tumor (Tu)TCF-1-TIM-3+, Tu TCF-1+TIM-3-, and tdLN TCF-1+TIM-3-, as well as TIGIT+, PD-1+, and CD226+ single-positive and TIGIT+PD-1+CD226+ triple-positive (+++) cells in the population, and a representative histogram (right) in tumor samples. Figure 3C shows the frequencies of TIGIT+, PD-1+, CD226+, and triple-positive (+++) cells in tumor Treg, CD4+T, CD8+T, and NK subsets. Figure 3D shows the frequencies of CD11b+Ly6C+ monocytes (mono), macrophages (mac) in CD11b+F4 / 80+TAM (in tumors) or tdLN, CD11b+CD11c+MHCII+ myeloid dendritic cells (mDC), CD11b-CD11c+MHCII+CD11b+Ly6C+ conventional dendritic cells (cDC), CD11b+Ly6G+ neutrophils (ne), and CD155 and PD-L1 in CD45- cancer and stromal subsets (left). The CD45- and ne populations were not present in sufficient numbers to be investigated in tdLN. A representative histogram from tumor samples is shown on the right. [Figure 3B]This study demonstrates that TIGIT, PD-1, and CD226 are co-expressed in MC38 mouse tumors and tdLNs. The expression of TIGIT, PD-1, CD226, CD155, and PD-L1 was examined by flow cytometry in MC38 tumors (50–150 mm3) and inguinal tdLNs. n=8–10. Symbols represent individual mice. Bars and error represent median ± range. Only data with >100 events per population are shown. Representative data from at least three independent studies are shown. Figure 3A shows the frequency of Tpex(TCF-1+TIM-3-) and Ttex(TCF-1-TIM-3+)-containing populations in tumors and tdLNs. Figure 3B shows the frequencies (left) of tumor (Tu)TCF-1-TIM-3+, Tu TCF-1+TIM-3-, and tdLN TCF-1+TIM-3-, as well as TIGIT+, PD-1+, and CD226+ single-positive and TIGIT+PD-1+CD226+ triple-positive (+++) cells in the population, and a representative histogram (right) in tumor samples. Figure 3C shows the frequencies of TIGIT+, PD-1+, CD226+, and triple-positive (+++) cells in tumor Treg, CD4+T, CD8+T, and NK subsets. Figure 3D shows the frequencies of CD11b+Ly6C+ monocytes (mono), macrophages (mac) in CD11b+F4 / 80+TAM (in tumors) or tdLN, CD11b+CD11c+MHCII+ myeloid dendritic cells (mDC), CD11b-CD11c+MHCII+CD11b+Ly6C+ conventional dendritic cells (cDC), CD11b+Ly6G+ neutrophils (ne), and CD155 and PD-L1 in CD45- cancer and stromal subsets (left). The CD45- and ne populations were not present in sufficient numbers to be investigated in tdLN. A representative histogram from tumor samples is shown on the right. [Figure 3C]This study demonstrates that TIGIT, PD-1, and CD226 are co-expressed in MC38 mouse tumors and tdLNs. The expression of TIGIT, PD-1, CD226, CD155, and PD-L1 was examined by flow cytometry in MC38 tumors (50–150 mm3) and inguinal tdLNs. n=8–10. Symbols represent individual mice. Bars and error represent median ± range. Only data with >100 events per population are shown. Representative data from at least three independent studies are shown. Figure 3A shows the frequency of Tpex(TCF-1+TIM-3-) and Ttex(TCF-1-TIM-3+)-containing populations in tumors and tdLNs. Figure 3B shows the frequencies (left) of tumor (Tu)TCF-1-TIM-3+, Tu TCF-1+TIM-3-, and tdLN TCF-1+TIM-3-, as well as TIGIT+, PD-1+, and CD226+ single-positive and TIGIT+PD-1+CD226+ triple-positive (+++) cells in the population, and a representative histogram (right) in tumor samples. Figure 3C shows the frequencies of TIGIT+, PD-1+, CD226+, and triple-positive (+++) cells in tumor Treg, CD4+T, CD8+T, and NK subsets. Figure 3D shows the frequencies of CD11b+Ly6C+ monocytes (mono), macrophages (mac) in CD11b+F4 / 80+TAM (in tumors) or tdLN, CD11b+CD11c+MHCII+ myeloid dendritic cells (mDC), CD11b-CD11c+MHCII+CD11b+Ly6C+ conventional dendritic cells (cDC), CD11b+Ly6G+ neutrophils (ne), and CD155 and PD-L1 in CD45- cancer and stromal subsets (left). The CD45- and ne populations were not present in sufficient numbers to be investigated in tdLN. A representative histogram from tumor samples is shown on the right. [Figure 3D]This study demonstrates that TIGIT, PD-1, and CD226 are co-expressed in MC38 mouse tumors and tdLNs. The expression of TIGIT, PD-1, CD226, CD155, and PD-L1 was examined by flow cytometry in MC38 tumors (50–150 mm3) and inguinal tdLNs. n=8–10. Symbols represent individual mice. Bars and error represent median ± range. Only data with >100 events per population are shown. Representative data from at least three independent studies are shown. Figure 3A shows the frequency of Tpex(TCF-1+TIM-3-) and Ttex(TCF-1-TIM-3+)-containing populations in tumors and tdLNs. Figure 3B shows the frequencies (left) of tumor (Tu)TCF-1-TIM-3+, Tu TCF-1+TIM-3-, and tdLN TCF-1+TIM-3-, as well as TIGIT+, PD-1+, and CD226+ single-positive and TIGIT+PD-1+CD226+ triple-positive (+++) cells in the population, and a representative histogram (right) in tumor samples. Figure 3C shows the frequencies of TIGIT+, PD-1+, CD226+, and triple-positive (+++) cells in tumor Treg, CD4+T, CD8+T, and NK subsets. Figure 3D shows the frequencies of CD11b+Ly6C+ monocytes (mono), macrophages (mac) in CD11b+F4 / 80+TAM (in tumors) or tdLN, CD11b+CD11c+MHCII+ myeloid dendritic cells (mDC), CD11b-CD11c+MHCII+CD11b+Ly6C+ conventional dendritic cells (cDC), CD11b+Ly6G+ neutrophils (ne), and CD155 and PD-L1 in CD45- cancer and stromal subsets (left). The CD45- and ne populations were not present in sufficient numbers to be investigated in tdLN. A representative histogram from tumor samples is shown on the right.

[0020] [Figure 4A]In combination with anti-PD-1, Fcs anti-TIGIT promotes anti-tumor immunity associated with increased tumor-specific T cells in LN release-dependent TME and Tpex differentiation. Figures 4A and 4B graphically show data from mice with established MC38 tumors (70-80 mm3) that were administered with an optimized dosing regimen of 10 mg / kg αPD-1 (square on the x-axis) or 10 mg / kg αPD-1 + 10 mg / kg αTIG Fcs (inverted triangle on the x-axis) every 5 days (Q5D) throughout the course of the study. Figure 4A shows the mean tumor volume growth curve (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves (middle and bottom) with the number of CRs per treatment group. n=15 / group. In all graphs, the y-axis is tumor volume (mm3) and the x-axis is days after transplantation. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ****p<0.0001. Figure 4B shows Kaplan-Maier survival curve (right). Cox proportional hazards survival analysis, ****p<0.0001. Representative data from at least three independent experiments. Figures 4C, 4D, 4E, and 4F show data from MC38 tumor-bearing mice with established tumors (approximately 60 mm3) treated daily by oral gastric tube feeding with vehicle or 0.25 mg / kg FTY720, initiated one day prior to Q5D antibody treatment. Three days after the initial antibody dose, tumors were collected for flow cytometry analysis, as shown in Figures 4C, 4D, and 4E. Figure 4C shows a representative dot plot identifying tumor-specific p15e+CD8+ T cells (left). Figure 4D shows the frequency of p15e+ T cells in the tumor CD8+ T subset (top) and the number of p15e+ T cells per 1 mg of tumor relative to the mean of the isotype + vehicle group (bottom). Data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01, ****p<0.0001.Figure 4E shows representative dot plots illustrating the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / CD69 staining (top), and the frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E+CD8+ T cells relative to the mean of isotype + vehicle groups (bottom, legend below the graph). Data were compiled from three independent experiments with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Figure 4F shows mean tumor volume growth curves (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves with the number of CRs per treatment group (bottom). n=10 / group. In all graphs, the y-axis represents tumor volume (mm³) and the x-axis represents days after transplantation. A general linear model with baseline tumor volume and treatment duration as covariates, Tukey adjustments for multiple comparisons, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Representative data from four independent experiments are shown: iso, isotype control; FC, magnification change. See gating strategies in Figures 7D-7E. See also Figure 10. [Figure 4B]In combination with anti-PD-1, Fcs anti-TIGIT promotes anti-tumor immunity associated with increased tumor-specific T cells in LN release-dependent TME and Tpex differentiation. Figures 4A and 4B graphically show data from mice with established MC38 tumors (70-80 mm3) that were administered with an optimized dosing regimen of 10 mg / kg αPD-1 (square on the x-axis) or 10 mg / kg αPD-1 + 10 mg / kg αTIG Fcs (inverted triangle on the x-axis) every 5 days (Q5D) throughout the course of the study. Figure 4A shows the mean tumor volume growth curve (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves (middle and bottom) with the number of CRs per treatment group. n=15 / group. In all graphs, the y-axis is tumor volume (mm3) and the x-axis is days after transplantation. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ****p<0.0001. Figure 4B shows Kaplan-Maier survival curve (right). Cox proportional hazards survival analysis, ****p<0.0001. Representative data from at least three independent experiments. Figures 4C, 4D, 4E, and 4F show data from MC38 tumor-bearing mice with established tumors (approximately 60 mm3) treated daily by oral gastric tube feeding with vehicle or 0.25 mg / kg FTY720, initiated one day prior to Q5D antibody treatment. Three days after the initial antibody dose, tumors were collected for flow cytometry analysis, as shown in Figures 4C, 4D, and 4E. Figure 4C shows a representative dot plot identifying tumor-specific p15e+CD8+ T cells (left). Figure 4D shows the frequency of p15e+ T cells in the tumor CD8+ T subset (top) and the number of p15e+ T cells per 1 mg of tumor relative to the mean of the isotype + vehicle group (bottom). Data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01, ****p<0.0001.Figure 4E shows representative dot plots illustrating the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / CD69 staining (top), and the frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E+CD8+ T cells relative to the mean of isotype + vehicle groups (bottom, legend below the graph). Data were compiled from three independent experiments with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Figure 4F shows mean tumor volume growth curves (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves with the number of CRs per treatment group (bottom). n=10 / group. In all graphs, the y-axis represents tumor volume (mm³) and the x-axis represents days after transplantation. A general linear model with baseline tumor volume and treatment duration as covariates, Tukey adjustments for multiple comparisons, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Representative data from four independent experiments are shown: iso, isotype control; FC, magnification change. See gating strategies in Figures 7D-7E. See also Figure 10. [Figure 4C]In combination with anti-PD-1, Fcs anti-TIGIT promotes anti-tumor immunity associated with increased tumor-specific T cells in LN release-dependent TME and Tpex differentiation. Figures 4A and 4B graphically show data from mice with established MC38 tumors (70-80 mm3) that were administered with an optimized dosing regimen of 10 mg / kg αPD-1 (square on the x-axis) or 10 mg / kg αPD-1 + 10 mg / kg αTIG Fcs (inverted triangle on the x-axis) every 5 days (Q5D) throughout the course of the study. Figure 4A shows the mean tumor volume growth curve (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves (middle and bottom) with the number of CRs per treatment group. n=15 / group. In all graphs, the y-axis is tumor volume (mm3) and the x-axis is days after transplantation. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ****p<0.0001. Figure 4B shows Kaplan-Maier survival curve (right). Cox proportional hazards survival analysis, ****p<0.0001. Representative data from at least three independent experiments. Figures 4C, 4D, 4E, and 4F show data from MC38 tumor-bearing mice with established tumors (approximately 60 mm3) treated daily by oral gastric tube feeding with vehicle or 0.25 mg / kg FTY720, initiated one day prior to Q5D antibody treatment. Three days after the initial antibody dose, tumors were collected for flow cytometry analysis, as shown in Figures 4C, 4D, and 4E. Figure 4C shows a representative dot plot identifying tumor-specific p15e+CD8+ T cells (left). Figure 4D shows the frequency of p15e+ T cells in the tumor CD8+ T subset (top) and the number of p15e+ T cells per 1 mg of tumor relative to the mean of the isotype + vehicle group (bottom). Data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01, ****p<0.0001.Figure 4E shows representative dot plots illustrating the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / CD69 staining (top), and the frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E+CD8+ T cells relative to the mean of isotype + vehicle groups (bottom, legend below the graph). Data were compiled from three independent experiments with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Figure 4F shows mean tumor volume growth curves (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves with the number of CRs per treatment group (bottom). n=10 / group. In all graphs, the y-axis represents tumor volume (mm³) and the x-axis represents days after transplantation. A general linear model with baseline tumor volume and treatment duration as covariates, Tukey adjustments for multiple comparisons, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Representative data from four independent experiments are shown: iso, isotype control; FC, magnification change. See gating strategies in Figures 7D-7E. See also Figure 10. [Figure 4D]In combination with anti-PD-1, Fcs anti-TIGIT promotes anti-tumor immunity associated with increased tumor-specific T cells in LN release-dependent TME and Tpex differentiation. Figures 4A and 4B graphically show data from mice with established MC38 tumors (70-80 mm3) that were administered with an optimized dosing regimen of 10 mg / kg αPD-1 (square on the x-axis) or 10 mg / kg αPD-1 + 10 mg / kg αTIG Fcs (inverted triangle on the x-axis) every 5 days (Q5D) throughout the course of the study. Figure 4A shows the mean tumor volume growth curve (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves (middle and bottom) with the number of CRs per treatment group. n=15 / group. In all graphs, the y-axis is tumor volume (mm3) and the x-axis is days after transplantation. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ****p<0.0001. Figure 4B shows Kaplan-Maier survival curve (right). Cox proportional hazards survival analysis, ****p<0.0001. Representative data from at least three independent experiments. Figures 4C, 4D, 4E, and 4F show data from MC38 tumor-bearing mice with established tumors (approximately 60 mm3) treated daily by oral gastric tube feeding with vehicle or 0.25 mg / kg FTY720, initiated one day prior to Q5D antibody treatment. Three days after the initial antibody dose, tumors were collected for flow cytometry analysis, as shown in Figures 4C, 4D, and 4E. Figure 4C shows a representative dot plot identifying tumor-specific p15e+CD8+ T cells (left). Figure 4D shows the frequency of p15e+ T cells in the tumor CD8+ T subset (top) and the number of p15e+ T cells per 1 mg of tumor relative to the mean of the isotype + vehicle group (bottom). Data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01, ****p<0.0001.Figure 4E shows representative dot plots illustrating the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / CD69 staining (top), and the frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E+CD8+ T cells relative to the mean of isotype + vehicle groups (bottom, legend below the graph). Data were compiled from three independent experiments with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Figure 4F shows mean tumor volume growth curves (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves with the number of CRs per treatment group (bottom). n=10 / group. In all graphs, the y-axis represents tumor volume (mm³) and the x-axis represents days after transplantation. A general linear model with baseline tumor volume and treatment duration as covariates, Tukey adjustments for multiple comparisons, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Representative data from four independent experiments are shown: iso, isotype control; FC, magnification change. See gating strategies in Figures 7D-7E. See also Figure 10. [Figure 4E]In combination with anti-PD-1, Fcs anti-TIGIT promotes anti-tumor immunity associated with increased tumor-specific T cells in LN release-dependent TME and Tpex differentiation. Figures 4A and 4B graphically show data from mice with established MC38 tumors (70-80 mm3) that were administered with an optimized dosing regimen of 10 mg / kg αPD-1 (square on the x-axis) or 10 mg / kg αPD-1 + 10 mg / kg αTIG Fcs (inverted triangle on the x-axis) every 5 days (Q5D) throughout the course of the study. Figure 4A shows the mean tumor volume growth curve (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves (middle and bottom) with the number of CRs per treatment group. n=15 / group. In all graphs, the y-axis is tumor volume (mm3) and the x-axis is days after transplantation. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ****p<0.0001. Figure 4B shows Kaplan-Maier survival curve (right). Cox proportional hazards survival analysis, ****p<0.0001. Representative data from at least three independent experiments. Figures 4C, 4D, 4E, and 4F show data from MC38 tumor-bearing mice with established tumors (approximately 60 mm3) treated daily by oral gastric tube feeding with vehicle or 0.25 mg / kg FTY720, initiated one day prior to Q5D antibody treatment. Three days after the initial antibody dose, tumors were collected for flow cytometry analysis, as shown in Figures 4C, 4D, and 4E. Figure 4C shows a representative dot plot identifying tumor-specific p15e+CD8+ T cells (left). Figure 4D shows the frequency of p15e+ T cells in the tumor CD8+ T subset (top) and the number of p15e+ T cells per 1 mg of tumor relative to the mean of the isotype + vehicle group (bottom). Data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01, ****p<0.0001.Figure 4E shows representative dot plots illustrating the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / CD69 staining (top), and the frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E+CD8+ T cells relative to the mean of isotype + vehicle groups (bottom, legend below the graph). Data were compiled from three independent experiments with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Figure 4F shows mean tumor volume growth curves (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves with the number of CRs per treatment group (bottom). n=10 / group. In all graphs, the y-axis represents tumor volume (mm³) and the x-axis represents days after transplantation. A general linear model with baseline tumor volume and treatment duration as covariates, Tukey adjustments for multiple comparisons, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Representative data from four independent experiments are shown: iso, isotype control; FC, magnification change. See gating strategies in Figures 7D-7E. See also Figure 10. [Figure 4F]In combination with anti-PD-1, Fcs anti-TIGIT promotes anti-tumor immunity associated with increased tumor-specific T cells in LN release-dependent TME and Tpex differentiation. Figures 4A and 4B graphically show data from mice with established MC38 tumors (70-80 mm3) that were administered with an optimized dosing regimen of 10 mg / kg αPD-1 (square on the x-axis) or 10 mg / kg αPD-1 + 10 mg / kg αTIG Fcs (inverted triangle on the x-axis) every 5 days (Q5D) throughout the course of the study. Figure 4A shows the mean tumor volume growth curve (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves (middle and bottom) with the number of CRs per treatment group. n=15 / group. In all graphs, the y-axis is tumor volume (mm3) and the x-axis is days after transplantation. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ****p<0.0001. Figure 4B shows Kaplan-Maier survival curve (right). Cox proportional hazards survival analysis, ****p<0.0001. Representative data from at least three independent experiments. Figures 4C, 4D, 4E, and 4F show data from MC38 tumor-bearing mice with established tumors (approximately 60 mm3) treated daily by oral gastric tube feeding with vehicle or 0.25 mg / kg FTY720, initiated one day prior to Q5D antibody treatment. Three days after the initial antibody dose, tumors were collected for flow cytometry analysis, as shown in Figures 4C, 4D, and 4E. Figure 4C shows a representative dot plot identifying tumor-specific p15e+CD8+ T cells (left). Figure 4D shows the frequency of p15e+ T cells in the tumor CD8+ T subset (top) and the number of p15e+ T cells per 1 mg of tumor relative to the mean of the isotype + vehicle group (bottom). Data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01, ****p<0.0001.Figure 4E shows representative dot plots illustrating the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / CD69 staining (top), and the frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E+CD8+ T cells relative to the mean of isotype + vehicle groups (bottom, legend below the graph). Data were compiled from three independent experiments with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Figure 4F shows mean tumor volume growth curves (symbols and errors represent mean ± SEM) (top) and individual tumor volume growth curves with the number of CRs per treatment group (bottom). n=10 / group. In all graphs, the y-axis represents tumor volume (mm³) and the x-axis represents days after transplantation. A general linear model with baseline tumor volume and treatment duration as covariates, Tukey adjustments for multiple comparisons, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Representative data from four independent experiments are shown: iso, isotype control; FC, magnification change. See gating strategies in Figures 7D-7E. See also Figure 10.

[0021] [Figure 5A]This shows that lethal OXA chemotherapy concentrations upregulate PD-L1 and CD155 on MC38 cells in vitro. Figure 5A shows the cell viability (measured by ATP) of MC38 cells treated with the indicated concentrations of OXA for 72 hours. Shaded areas identify non-cytotoxic concentrations. Lines and errors represent the mean ± standard deviation (SD) of the biological triplicate. Figure 1B shows the gMFI (top) of CD155 (circles, left y-axis) and PD-L1 (squares, right y-axis) on MC38 cells treated with the indicated concentrations of OXA for 22 hours, as well as representative histograms of CD155 and PD-L1 on MC38 cells (bottom). Figure 5C shows the gMFI of CD155 (circles, left y-axis) and PD-L1 (squares, right y-axis) on MC38 cells treated with the indicated (non-cytotoxic) concentrations of OXA for 72 hours. In Figures 5B and 5C, the lines and errors represent the mean ± SD of the biological double series. The gray shading indicates the experimentally determined non-cytotoxic OXA concentration range (0.001–0.03 μM), and the horizontal dotted line indicates the baseline staining of PBS-treated cells (fold-change of gMFI relative to isotype control). Representative data from three independent experiments are shown: h, time (hour); iso, isotype control; FC, fold-change; OXA, oxaliplatin. [Figure 5B]This shows that lethal OXA chemotherapy concentrations upregulate PD-L1 and CD155 on MC38 cells in vitro. Figure 5A shows the cell viability (measured by ATP) of MC38 cells treated with the indicated concentrations of OXA for 72 hours. Shaded areas identify non-cytotoxic concentrations. Lines and errors represent the mean ± standard deviation (SD) of the biological triplicate. Figure 1B shows the gMFI (top) of CD155 (circles, left y-axis) and PD-L1 (squares, right y-axis) on MC38 cells treated with the indicated concentrations of OXA for 22 hours, as well as representative histograms of CD155 and PD-L1 on MC38 cells (bottom). Figure 5C shows the gMFI of CD155 (circles, left y-axis) and PD-L1 (squares, right y-axis) on MC38 cells treated with the indicated (non-cytotoxic) concentrations of OXA for 72 hours. In Figures 5B and 5C, the lines and errors represent the mean ± SD of the biological double series. The gray shading indicates the experimentally determined non-cytotoxic OXA concentration range (0.001–0.03 μM), and the horizontal dotted line indicates the baseline staining of PBS-treated cells (fold-change of gMFI relative to isotype control). Representative data from three independent experiments are shown: h, time (hour); iso, isotype control; FC, fold-change; OXA, oxaliplatin. [Figure 5C]This shows that lethal OXA chemotherapy concentrations upregulate PD-L1 and CD155 on MC38 cells in vitro. Figure 5A shows the cell viability (measured by ATP) of MC38 cells treated with the indicated concentrations of OXA for 72 hours. Shaded areas identify non-cytotoxic concentrations. Lines and errors represent the mean ± standard deviation (SD) of the biological triplicate. Figure 1B shows the gMFI (top) of CD155 (circles, left y-axis) and PD-L1 (squares, right y-axis) on MC38 cells treated with the indicated concentrations of OXA for 22 hours, as well as representative histograms of CD155 and PD-L1 on MC38 cells (bottom). Figure 5C shows the gMFI of CD155 (circles, left y-axis) and PD-L1 (squares, right y-axis) on MC38 cells treated with the indicated (non-cytotoxic) concentrations of OXA for 72 hours. In Figures 5B and 5C, the lines and errors represent the mean ± SD of the biological double series. The gray shading indicates the experimentally determined non-cytotoxic OXA concentration range (0.001–0.03 μM), and the horizontal dotted line indicates the baseline staining of PBS-treated cells (fold-change of gMFI relative to isotype control). Representative data from three independent experiments are shown: h, time (hour); iso, isotype control; FC, fold-change; OXA, oxaliplatin.

[0022] [Figure 6A]This study demonstrates that Fcs anti-TIGIT combines well with chemotherapy in an MC38 mouse model. Figures 6A and 6B show data from mice with established MC38 tumors (80–95 mm3) administered 10 mg / kg OXA (dose every 7 days, Q7D, gray triangles on the x-axis) either alone or in combination with 10 mg / kg αPD-1 or 10 mg / kg αPD-1 + 10 mg / kg αTIG FcsQ5D. Antibody treatment was initiated 3 days after the first OXA dose. Mean tumor volume growth curves (symbols and errors represent mean ± SEM) (Figure 6A, top) and individual tumor volume growth curves with number of CRs per treatment group (Figure 6B). n=14–15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, *p<0.05. Kaplain-Maier survival curve (Figure 6A, bottom). Cox proportional hazards survival analysis with pairwise comparisons using Benjamini-Hochberg adjustment for multiple comparisons. *p<0.05, **p<0.01, ****p<0.0001. Representative data from four independent experiments are shown. Figure 6C shows data from mice with established MC38 tumors administered as shown in Figure 6A with an additional treatment arm of αTIG Fcs + OXA. Mean tumor volume growth curve is shown, with symbols and errors representing mean ± SEM. n=15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ns, not significant, ****p<0.0001. Representative data from two independent experiments are shown. Figure 6D shows data from 3 days after OXA dose when tumors were collected for flow cytometry analysis. Frequency of CD11b+Ly6C+ monocytes (mono) and CD11b+Ly6G+ neutrophils (ne) in the CD45+ subset (left) or frequency of TCF-1+ / - cells in the CD8+T subset (right). n=8 / group. Standard two-way ANOVA with Sidak's multiple comparison test, *p<0.05, ****p<0.0001. Representative data from two independent experiments are shown. iso, isotype control; OXA, oxaliplatin.Please refer to the gating strategies in Figures 7D and 7E. [Figure 6B]This study demonstrates that Fcs anti-TIGIT combines well with chemotherapy in an MC38 mouse model. Figures 6A and 6B show data from mice with established MC38 tumors (80–95 mm3) administered 10 mg / kg OXA (dose every 7 days, Q7D, gray triangles on the x-axis) either alone or in combination with 10 mg / kg αPD-1 or 10 mg / kg αPD-1 + 10 mg / kg αTIG FcsQ5D. Antibody treatment was initiated 3 days after the first OXA dose. Mean tumor volume growth curves (symbols and errors represent mean ± SEM) (Figure 6A, top) and individual tumor volume growth curves with number of CRs per treatment group (Figure 6B). n=14–15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, *p<0.05. Kaplain-Maier survival curve (Figure 6A, bottom). Cox proportional hazards survival analysis with pairwise comparisons using Benjamini-Hochberg adjustment for multiple comparisons. *p<0.05, **p<0.01, ****p<0.0001. Representative data from four independent experiments are shown. Figure 6C shows data from mice with established MC38 tumors administered as shown in Figure 6A with an additional treatment arm of αTIG Fcs + OXA. Mean tumor volume growth curve is shown, with symbols and errors representing mean ± SEM. n=15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ns, not significant, ****p<0.0001. Representative data from two independent experiments are shown. Figure 6D shows data from 3 days after OXA dose when tumors were collected for flow cytometry analysis. Frequency of CD11b+Ly6C+ monocytes (mono) and CD11b+Ly6G+ neutrophils (ne) in the CD45+ subset (left) or frequency of TCF-1+ / - cells in the CD8+T subset (right). n=8 / group. Standard two-way ANOVA with Sidak's multiple comparison test, *p<0.05, ****p<0.0001. Representative data from two independent experiments are shown. iso, isotype control; OXA, oxaliplatin.Please refer to the gating strategies in Figures 7D and 7E. [Figure 6C]This study demonstrates that Fcs anti-TIGIT combines well with chemotherapy in an MC38 mouse model. Figures 6A and 6B show data from mice with established MC38 tumors (80–95 mm3) administered 10 mg / kg OXA (dose every 7 days, Q7D, gray triangles on the x-axis) either alone or in combination with 10 mg / kg αPD-1 or 10 mg / kg αPD-1 + 10 mg / kg αTIG FcsQ5D. Antibody treatment was initiated 3 days after the first OXA dose. Mean tumor volume growth curves (symbols and errors represent mean ± SEM) (Figure 6A, top) and individual tumor volume growth curves with number of CRs per treatment group (Figure 6B). n=14–15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, *p<0.05. Kaplain-Maier survival curve (Figure 6A, bottom). Cox proportional hazards survival analysis with pairwise comparisons using Benjamini-Hochberg adjustment for multiple comparisons. *p<0.05, **p<0.01, ****p<0.0001. Representative data from four independent experiments are shown. Figure 6C shows data from mice with established MC38 tumors administered as shown in Figure 6A with an additional treatment arm of αTIG Fcs + OXA. Mean tumor volume growth curve is shown, with symbols and errors representing mean ± SEM. n=15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ns, not significant, ****p<0.0001. Representative data from two independent experiments are shown. Figure 6D shows data from 3 days after OXA dose when tumors were collected for flow cytometry analysis. Frequency of CD11b+Ly6C+ monocytes (mono) and CD11b+Ly6G+ neutrophils (ne) in the CD45+ subset (left) or frequency of TCF-1+ / - cells in the CD8+T subset (right). n=8 / group. Standard two-way ANOVA with Sidak's multiple comparison test, *p<0.05, ****p<0.0001. Representative data from two independent experiments are shown. iso, isotype control; OXA, oxaliplatin.Please refer to the gating strategies in Figures 7D and 7E. [Figure 6D]This study demonstrates that Fcs anti-TIGIT combines well with chemotherapy in an MC38 mouse model. Figures 6A and 6B show data from mice with established MC38 tumors (80–95 mm3) administered 10 mg / kg OXA (dose every 7 days, Q7D, gray triangles on the x-axis) either alone or in combination with 10 mg / kg αPD-1 or 10 mg / kg αPD-1 + 10 mg / kg αTIG FcsQ5D. Antibody treatment was initiated 3 days after the first OXA dose. Mean tumor volume growth curves (symbols and errors represent mean ± SEM) (Figure 6A, top) and individual tumor volume growth curves with number of CRs per treatment group (Figure 6B). n=14–15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, *p<0.05. Kaplain-Maier survival curve (Figure 6A, bottom). Cox proportional hazards survival analysis with pairwise comparisons using Benjamini-Hochberg adjustment for multiple comparisons. *p<0.05, **p<0.01, ****p<0.0001. Representative data from four independent experiments are shown. Figure 6C shows data from mice with established MC38 tumors administered as shown in Figure 6A with an additional treatment arm of αTIG Fcs + OXA. Mean tumor volume growth curve is shown, with symbols and errors representing mean ± SEM. n=15 / group. General linear model with baseline tumor volume and treatment duration as covariates, Benjamini-Hochberg adjustment for multiple comparisons, ns, not significant, ****p<0.0001. Representative data from two independent experiments are shown. Figure 6D shows data from 3 days after OXA dose when tumors were collected for flow cytometry analysis. Frequency of CD11b+Ly6C+ monocytes (mono) and CD11b+Ly6G+ neutrophils (ne) in the CD45+ subset (left) or frequency of TCF-1+ / - cells in the CD8+T subset (right). n=8 / group. Standard two-way ANOVA with Sidak's multiple comparison test, *p<0.05, ****p<0.0001. Representative data from two independent experiments are shown. iso, isotype control; OXA, oxaliplatin.Please refer to the gating strategies in Figures 7D and 7E.

[0023] [Figure 7A-1] This paper presents a flow cytometry strategy for identifying cell populations in human NSCLC cell suspensions. Representative NSCLC samples are shown. [Figure 7A-2] Same as above.

[0024] [Figure 7B-1] The flow cytometry strategy shown in Figure 7A is shown in more detail below. [Figure 7B-2] Same as above.

[0025] [Figure 7C-1] The flow cytometry strategy shown in Figure 7B is shown in more detail below. [Figure 7C-2] Same as above.

[0026] [Figure 7D-1] This paper presents a flow cytometry strategy for identifying cell populations in mouse MC38 tumors and inguinal tdLN cell suspensions. A representative MC38 tumor sample is shown. [Figure 7D-2] Same as above. [Figure 7D-3] Same as above.

[0027] [Figure 7E-1] Figure 7D shows a continuation of the flow cytometry strategy. [Figure 7E-2] Same as above.

[0028] [Figure 8A-1]This provides additional characterization of circulating Tpex cells identified in scRNAseq datasets, the relationship between CD226 and TIGIT mRNA and protein expression in CD8+ T cells, and additional phenotypic determination of TIGIT, PD-1, and CD226 in exhausted T cell subsets in commercially available human NCSLC and gastroesophageal (GE)TIL suspensions. Figure 8A shows the expression of additional markers in CD8+ T cells from the Guo et al. (left) and Guegen et al. (right) datasets. Shading highlights Tpex cells. Figure 8B shows the frequency of TIGIT (left) and CD226 (right) protein (left y-axis) and relative mRNA (right y-axis) expression in isolated healthy human peripheral blood CD8+ T cells. Symbols represent individual subjects, and lines connect the same subjects. n=6 healthy donors collected from two independent experiments. Figure 8C shows the frequencies of the six CD8+T subpopulations described in Figure 2F within the total CD8+T subset of GE TIL. Figure 8D shows the frequencies of GzmK (left) and CD39+TIM-3+ co-expression (right) in the six CD8+T subpopulations in GE and NSCLC subjects. Figure 8E shows the frequencies of TIGIT and CD226 in the six CD8+T subpopulations in NSCLC TIL suspension. Figure 8F shows the frequencies of TIGIT+CD226+ double-positive cells in the six CD8+T subpopulations in GE TIL suspension. In Figures 8C, 8D, and 8F, n=4 were used for both GE and NSCLC subjects. In Figure 8E, n=10 were used for NSCLC subjects. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Symbols represent individual subjects. Only data with >100 events per group are shown. See also Figures 2 and 7A-7C. [Figure 8A-2] Same as above. [Figure 8A-3] Same as above. [Figure 8A-4] Same as above. [Figure 8A-5] Same as above. [Figure 8B]This provides additional characterization of circulating Tpex cells identified in scRNAseq datasets, the relationship between CD226 and TIGIT mRNA and protein expression in CD8+ T cells, and additional phenotypic determination of TIGIT, PD-1, and CD226 in exhausted T cell subsets in commercially available human NCSLC and gastroesophageal (GE)TIL suspensions. Figure 8A shows the expression of additional markers in CD8+ T cells from the Guo et al. (left) and Guegen et al. (right) datasets. Shading highlights Tpex cells. Figure 8B shows the frequency of TIGIT (left) and CD226 (right) protein (left y-axis) and relative mRNA (right y-axis) expression in isolated healthy human peripheral blood CD8+ T cells. Symbols represent individual subjects, and lines connect the same subjects. n=6 healthy donors collected from two independent experiments. Figure 8C shows the frequencies of the six CD8+T subpopulations described in Figure 2F within the total CD8+T subset of GE TIL. Figure 8D shows the frequencies of GzmK (left) and CD39+TIM-3+ co-expression (right) in the six CD8+T subpopulations in GE and NSCLC subjects. Figure 8E shows the frequencies of TIGIT and CD226 in the six CD8+T subpopulations in NSCLC TIL suspension. Figure 8F shows the frequencies of TIGIT+CD226+ double-positive cells in the six CD8+T subpopulations in GE TIL suspension. In Figures 8C, 8D, and 8F, n=4 were used for both GE and NSCLC subjects. In Figure 8E, n=10 were used for NSCLC subjects. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Symbols represent individual subjects. Only data with >100 events per group are shown. See also Figures 2 and 7A-7C. [Figure 8C]This provides additional characterization of circulating Tpex cells identified in scRNAseq datasets, the relationship between CD226 and TIGIT mRNA and protein expression in CD8+ T cells, and additional phenotypic determination of TIGIT, PD-1, and CD226 in exhausted T cell subsets in commercially available human NCSLC and gastroesophageal (GE)TIL suspensions. Figure 8A shows the expression of additional markers in CD8+ T cells from the Guo et al. (left) and Guegen et al. (right) datasets. Shading highlights Tpex cells. Figure 8B shows the frequency of TIGIT (left) and CD226 (right) protein (left y-axis) and relative mRNA (right y-axis) expression in isolated healthy human peripheral blood CD8+ T cells. Symbols represent individual subjects, and lines connect the same subjects. n=6 healthy donors collected from two independent experiments. Figure 8C shows the frequencies of the six CD8+T subpopulations described in Figure 2F within the total CD8+T subset of GE TIL. Figure 8D shows the frequencies of GzmK (left) and CD39+TIM-3+ co-expression (right) in the six CD8+T subpopulations in GE and NSCLC subjects. Figure 8E shows the frequencies of TIGIT and CD226 in the six CD8+T subpopulations in NSCLC TIL suspension. Figure 8F shows the frequencies of TIGIT+CD226+ double-positive cells in the six CD8+T subpopulations in GE TIL suspension. In Figures 8C, 8D, and 8F, n=4 were used for both GE and NSCLC subjects. In Figure 8E, n=10 were used for NSCLC subjects. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Symbols represent individual subjects. Only data with >100 events per group are shown. See also Figures 2 and 7A-7C. [Figure 8D]This provides additional characterization of circulating Tpex cells identified in scRNAseq datasets, the relationship between CD226 and TIGIT mRNA and protein expression in CD8+ T cells, and additional phenotypic determination of TIGIT, PD-1, and CD226 in exhausted T cell subsets in commercially available human NCSLC and gastroesophageal (GE)TIL suspensions. Figure 8A shows the expression of additional markers in CD8+ T cells from the Guo et al. (left) and Guegen et al. (right) datasets. Shading highlights Tpex cells. Figure 8B shows the frequency of TIGIT (left) and CD226 (right) protein (left y-axis) and relative mRNA (right y-axis) expression in isolated healthy human peripheral blood CD8+ T cells. Symbols represent individual subjects, and lines connect the same subjects. n=6 healthy donors collected from two independent experiments. Figure 8C shows the frequencies of the six CD8+T subpopulations described in Figure 2F within the total CD8+T subset of GE TIL. Figure 8D shows the frequencies of GzmK (left) and CD39+TIM-3+ co-expression (right) in the six CD8+T subpopulations in GE and NSCLC subjects. Figure 8E shows the frequencies of TIGIT and CD226 in the six CD8+T subpopulations in NSCLC TIL suspension. Figure 8F shows the frequencies of TIGIT+CD226+ double-positive cells in the six CD8+T subpopulations in GE TIL suspension. In Figures 8C, 8D, and 8F, n=4 were used for both GE and NSCLC subjects. In Figure 8E, n=10 were used for NSCLC subjects. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Symbols represent individual subjects. Only data with >100 events per group are shown. See also Figures 2 and 7A-7C. [Figure 8E]This provides additional characterization of circulating Tpex cells identified in scRNAseq datasets, the relationship between CD226 and TIGIT mRNA and protein expression in CD8+ T cells, and additional phenotypic determination of TIGIT, PD-1, and CD226 in exhausted T cell subsets in commercially available human NCSLC and gastroesophageal (GE)TIL suspensions. Figure 8A shows the expression of additional markers in CD8+ T cells from the Guo et al. (left) and Guegen et al. (right) datasets. Shading highlights Tpex cells. Figure 8B shows the frequency of TIGIT (left) and CD226 (right) protein (left y-axis) and relative mRNA (right y-axis) expression in isolated healthy human peripheral blood CD8+ T cells. Symbols represent individual subjects, and lines connect the same subjects. n=6 healthy donors collected from two independent experiments. Figure 8C shows the frequencies of the six CD8+T subpopulations described in Figure 2F within the total CD8+T subset of GE TIL. Figure 8D shows the frequencies of GzmK (left) and CD39+TIM-3+ co-expression (right) in the six CD8+T subpopulations in GE and NSCLC subjects. Figure 8E shows the frequencies of TIGIT and CD226 in the six CD8+T subpopulations in NSCLC TIL suspension. Figure 8F shows the frequencies of TIGIT+CD226+ double-positive cells in the six CD8+T subpopulations in GE TIL suspension. In Figures 8C, 8D, and 8F, n=4 were used for both GE and NSCLC subjects. In Figure 8E, n=10 were used for NSCLC subjects. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Symbols represent individual subjects. Only data with >100 events per group are shown. See also Figures 2 and 7A-7C. [Figure 8F]This provides additional characterization of circulating Tpex cells identified in scRNAseq datasets, the relationship between CD226 and TIGIT mRNA and protein expression in CD8+ T cells, and additional phenotypic determination of TIGIT, PD-1, and CD226 in exhausted T cell subsets in commercially available human NCSLC and gastroesophageal (GE)TIL suspensions. Figure 8A shows the expression of additional markers in CD8+ T cells from the Guo et al. (left) and Guegen et al. (right) datasets. Shading highlights Tpex cells. Figure 8B shows the frequency of TIGIT (left) and CD226 (right) protein (left y-axis) and relative mRNA (right y-axis) expression in isolated healthy human peripheral blood CD8+ T cells. Symbols represent individual subjects, and lines connect the same subjects. n=6 healthy donors collected from two independent experiments. Figure 8C shows the frequencies of the six CD8+T subpopulations described in Figure 2F within the total CD8+T subset of GE TIL. Figure 8D shows the frequencies of GzmK (left) and CD39+TIM-3+ co-expression (right) in the six CD8+T subpopulations in GE and NSCLC subjects. Figure 8E shows the frequencies of TIGIT and CD226 in the six CD8+T subpopulations in NSCLC TIL suspension. Figure 8F shows the frequencies of TIGIT+CD226+ double-positive cells in the six CD8+T subpopulations in GE TIL suspension. In Figures 8C, 8D, and 8F, n=4 were used for both GE and NSCLC subjects. In Figure 8E, n=10 were used for NSCLC subjects. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Symbols represent individual subjects. Only data with >100 events per group are shown. See also Figures 2 and 7A-7C.

[0029] [Figure 9A]Additional MC38 tumor and tdLN flow cytometry phenotyping data are presented. The frequencies of cell subsets in MC38 tumors or tdLNs are shown. For tumors, the frequencies of CD45+ immune cells and CD45- (cancer and stromal) cells in the living singlet population are shown: CD8+T (CD8), CD4+FoxP3+ (Treg), CD4+FoxP3-T (CD4), NK1.1+ (NK), CD11b+Ly6G+ neutrophils (ne), CD11b+Ly6C+ monocytes (mono), CD11b+F4 / 80+ macrophages (TAM in tumors, mac in tdLNs), CD11b+CD11c+MHCII+ bone marrow dendritic cells (mDC), and CD11b-CD11c+MHCII+ conventional DCs (cDC). [Figure 9B] Additional MC38 tumor and tdLN flow cytometry phenotyping data are shown. The frequencies of CD39 or GzmB in the TCF-1+TIM-3- and TCF-1+TIM-3+ subsets in the tumors are shown. [Figure 9C] Additional MC38 tumor and tdLN flow cytometry phenotyping data are shown. Frequencies of TIGIT, PD-1, CD226, and TIGIT+PD-1+CD226+ triple-positive (+++) cells are shown in the tdLN Treg, CD4+, CD8+, and NK subsets. n=10. [Figure 9D] Additional MC38 tumor and tdLN flow cytometry phenotyping data are shown. Overall changes in the immune cell population within the TME across treatment groups are shown. Individual mouse data per group are concatenated and presented as stacked bar graphs showing different tumor immune cell subsets. n=8 mice / group. See also Figures 3 and 7D–7E.

[0030] [Figure 10A]Additional in vivo MC38 phenotyping data are presented. Data are shown from naive C57BL / 6 mice administered FTY720 at 0.25, 1, or 3 mg / kg via oral gastric tube feeding. At 24 hours, the frequency of live single CD3+ in the blood was measured as a pharmacodynamic readout, with 0.25 mg / kg selected for the MOA study. n=5 / group. Standard one-way ANOVA with Dunnett's multiple comparison test against vehicle controls, p<0.0001. Representative data from two independent studies. [Figure 10B] Additional in vivo MC38 phenotyping data are shown. Figure 4 shows additional data from the MC38 study. The frequency of p15E+ T cells in the tdLN CD8+ T subset (left) and the number of p15E+ T cells per 1 mg of tdLN tissue relative to the mean of the isotype + vehicle group (right) are shown. The data were compiled from three independent experiments with n=8 / group. Kruskal-Wallis test with Dunn's multiple comparison test, *p<0.05, **p<0.01. [Figure 10C] Additional in vivo MC38 phenotyping data is shown. Figure 4 shows additional data from the MC38 study. Frequencies of resident Tpex (rTpex), circulating Tpex (cTpex), intermediate effector (Int), and terminally differentiated (Ttex) p15E-T cells are shown relative to the mean of isotype + vehicle group. Data were compiled from three independent experiments, each with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. [Figure 10D-1]Additional in vivo MC38 phenotyping data are shown. Additional data from the MC38 study shown in Figure 4 are presented. Analysis of data using TCF-1 / TIM-3 gating to identify Tpex and Ttex-containing populations in tumor tissue is shown. Representative dot plot (top) showing the differentiation status of exhausted CD8+ T cells in tumors based on TCF-1 / TIM-3 staining. Frequency of TCF-1+TIM-3- and TCF-1-TIM-3+ T cells in tumor p15E+CD8+ T subset relative to the mean of isotype + vehicle groups (bottom). Data were compiled from three independent experiments, each with n=8 / group. Two-way ANOVA with Tukey's multiple comparison test, *p<0.05, **p<0.01, ***p<0.001. See also Figure 4. [Figure 10D-2] Same as above.

[0031] [Figure 11] This is a Kaplan-Meier plot of 1L metastatic NSCLC patients (TPS PD-L1 expression 0-100%) grouped by CD155 expression (high vs. low). High CD155 (black line) is defined as CD155 gene expression above the median CD155 expression level. Low CD155 (blue line) is defined as CD155 gene expression below the median CD155 expression level.

[0032] [Figure 12A] This is a Kaplan-Meier plot of 1L metastatic NSCLC patients with PD-L1 expression <1% in TPS, grouped by CD155 expression (high vs. low). High CD155 (black line) is defined as CD155 gene expression above the median CD155 expression. Low CD155 (blue line) is defined as CD155 gene expression below the median CD155 expression.

[0033] [Figure 12B]This is a Kaplan-Meier plot of 1L metastatic NSCLC patients with PD-L1 expression of 1-49% in TPS, grouped by CD155 expression (high vs. low). High CD155 (black line) is defined as CD155 gene expression above the median CD155 expression. Low CD155 (blue line) is defined as CD155 gene expression below the median CD155 expression.

[0034] [Figure 12C] This is a Kaplan-Meier plot of 1L metastatic NSCLC patients with PD-L1 expression ≥50% in TPS patients, grouped by CD155 expression (high vs. low). High CD155 (black line) is defined as CD155 gene expression above the median CD155 expression level. Low CD155 (blue line) is defined as CD155 gene expression below the median CD155 expression level. [Modes for carrying out the invention]

[0035] Embodiments provided herein are described more fully below. However, aspects of this disclosure may be embodied in different forms and should not be construed as being limited to the embodiments described herein. Rather, these embodiments are provided to ensure that this disclosure is thorough and complete and fully conveys the scope of the invention to those skilled in the art. The technical terms used herein are for the sole purpose of describing specific embodiments and are not intended to be limiting.

[0036] This disclosure relates to biomarkers that are useful in many situations, particularly in identifying patients for the treatment of diseases, especially cancer, with therapies containing immune checkpoint inhibitors. It also provides methods for determining the prognosis of patients who have received or have not received therapies containing immune checkpoint inhibitors. The disclosure also relates to a technique for treating a patient identified as having cancer, comprising measuring the expression levels of one or more biomarkers in a sample obtained from the patient, and administering the patient a therapy containing immune checkpoint inhibitors if the sample obtained from the patient contains a particular biomarker expression profile. The disclosure relates to the finding that a particular biomarker expression profile, including but not limited to PD-L1, CD155, CD226, CD73, and / or adenosine pathway biomarkers, can be used to determine whether a patient is likely to be responsive or unresponsive to a therapy containing immune checkpoint inhibitors. In the embodiments described herein, it was surprisingly observed that a particular biomarker expression profile could be used to predict the therapeutic efficacy of a therapy containing immune checkpoint inhibitors. Exemplary immune checkpoint inhibitors include PD-(L)1 antagonists (e.g., anti-PD-L1 antibodies) and TIGIT antagonists (e.g., anti-TIGIT antibodies). definition

[0037] Unless otherwise defined, all technical terms, notations, and other scientific or technical terms used herein are intended to have meanings that are generally understood by those skilled in the art to whom this disclosure relates.

[0038] Where used herein, the term “approximately” has its original meaning of being approximate and is used to provide literal support for a number near or approximate to the number that precedes it, as well as the exact number that precedes it. Generally, the term “approximately” refers to the normal range of error of each value that is readily known to those skilled in the art. Where the degree of approximation is not evident from the context, “approximately” means either within ±10% of the given value or rounded to the nearest significant figure, and in all cases includes the given value. Where a range is provided, it includes boundary values.

[0039] As used interchangeably herein, “quantity,” “level,” or “expression level” of a biomarker refers to a detectable level in a biological sample. “Expression” generally refers to the process by which information (e.g., genetically encoded and / or epigenetic) is translated into structures that are present in and function within a cell. Thus, as used herein, “expression” may also refer to transcription into polynucleotides, translation into polypeptides, or even modification of polynucleotides and / or polypeptides (e.g., post-translational modification of polypeptides). Fragments of transcribed polynucleotides, translated polypeptides, or modified polynucleotides and / or polypeptides (e.g., post-translational modification of polypeptides) shall also be considered expressed, regardless of whether they originate from transcripts produced by alternative splicing or degraded transcripts, or from post-translational processing of polypeptides by, for example, proteolysis. “Expressed genes” include those transcribed into polynucleotides as mRNA and then translated into polypeptides, and those transcribed into RNA but not translated into polypeptides (e.g., transfer and ribosomal RNA). Expression levels are known to those skilled in the art and can be measured by methods disclosed herein. Expression levels or amounts of biomarkers (e.g., CD155, CD226, PD-L1, CD73) can be used to identify / characterize cancers that may respond to, benefit from, or not experience clinical benefit from a particular therapy.

[0040] As used herein, the term “biomarker” refers to an indicator that can be detected in a sample, for example, a predictive, diagnostic, and / or prognostic indicator. A biomarker may function as an indicator of a particular subtype of disease or disorder characterized by certain molecular, pathological, histological, and / or clinical features. Biomarkers include, but are not limited to, polypeptide, polynucleotide (e.g., DNA and / or RNA), polynucleotide copy number variations (e.g., DNA copy number), polypeptide and polynucleotide modifications (e.g., methylation, acetylation, oxidation, glycosylation), carbohydrate, and / or glycolipid-based molecular markers.

[0041] The terms “detection” and “detection” are used herein in their broadest sense to include both qualitative and quantitative measurements of a target molecule. Detection includes identifying the mere presence of a target molecule in a sample, as well as determining whether the target molecule is present in the sample at a detectable level. Detection may be direct or indirect.

[0042] As used herein, the term “sample” refers to a composition obtained from or derived from a subject that contains a biomarker identified and / or characterized based on, for example, physical, biochemical, chemical, and / or physiological characteristics. For example, the phrases “tumor sample,” “disease sample,” and variations thereof refer to any sample obtained from a subject of interest that is expected or known to contain a characterized biomarker. Other samples include, but are not limited to, primary or cultured cells or cell lines, cell supernatants, cell lysates, platelets, serum, plasma, vitreous fluid, lymph, synovial fluid, follicular fluid, semen, amniotic fluid, milk, whole blood, blood-derived cells, urine, cerebrospinal fluid, saliva, sputum, tears, sweat, mucus, feces, whole lymph nodes or lymph node biopsies, biopsy or excision-derived tissues, tumor biopsies, tumor lysates, and tissue culture media, homogenized tissues, tissue extracts, cell extracts, and combinations thereof.

[0043] As used herein, “reference sample,” “reference cell,” “reference tissue,” “control sample,” “control cell,” or “control tissue” refers to a sample, cell, tissue, standard, or level used for comparative purposes. In one embodiment, the reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from healthy and / or non-disease parts (e.g., tissue or cells) of the same body of the subject. For example, healthy and / or non-disease cells or tissue adjacent to diseased cells or tissue (e.g., cells or tissue adjacent to a tumor). In another embodiment, the reference sample is obtained from untreated tissue and / or cells of the same body of the subject. In yet another embodiment, the reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from healthy and / or non-disease parts (e.g., tissue or cells) of a body of a non-subject. In yet another embodiment, the reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from untreated tissue and / or cells of a body of a non-subject individual.

[0044] A "tumor sample" refers to a sample containing tumor cells. Typically, a tumor sample obtained from a solid tumor (e.g., tissue from a biopsy or excision) contains tumor cells and other cells of the tumor microenvironment (e.g., immune cells, stromal cells, fibroblasts, etc.).

[0045] The term "positive cell fraction" refers to the percentage of viable cells that, after staining a sample in an immunohistochemical (IHC) assay, show positive staining for the target protein at any intensity in one or more cellular locations (e.g., membrane, cytoplasm) within the sample. Positive cell fractions may be reported for all cell types or for certain subtypes (e.g., tumor cells, immune cells, other cells in the tumor microenvironment). The term "positive tumor cell fraction" may be abbreviated as "TC%" (positive tumor cell fraction) and refers to the percentage of viable tumor cells that show positive staining for the target protein at one or more cellular locations. As used herein, "tumor cells" refers to cancerous cells. Therefore, the positive tumor cell fraction is expressed by the formula...

number

[0046] The "H-score" is another means of characterizing protein expression levels, capturing both the intensity and percentage of the biomarker of interest from an image (e.g., IHC). Individual viable cells (e.g., tumor cells, immune cells, other cells in the tumor microenvironment, and combinations thereof), and in some embodiments, their intracellular compartments (e.g., nucleus, cytoplasm, cell membrane, etc.) are first detected, and the cells are classified as either positive or negative based on the relative expression of the biomarker of interest in the cell or in one or more intracellular compartments. Positive cells are further classified as high (3+), medium (2+), or low (1+) based on the biomarker signal intensity. The H-score (ranging from 0 to 300) is calculated using the following formula: (3 × 3+ stained cells %) + (2 × 2+ stained cells %) + (1 × 1+ stained cells %). The tumor H-score refers to the H-score calculated based on the relative expression of the biomarker of interest in viable tumor cells.

[0047] Another means of characterizing protein expression levels to capture both the intensity and percentage of the biomarker of interest from an image (e.g., IHC) is "2+ or 3+ TC%", which is the percentage of viable tumor cells that show positive staining for the protein of interest with either a medium (2+) or high (3+) signal intensity at one or more cellular locations (e.g., cell membrane, cytoplasm). Thus, 2+ or 3+ TC% is expressed by the formula

number

[0048] As used herein, the term “protein” encompasses “full-length” unprocessed proteins, as well as any form of protein resulting from processing in a subject (e.g., processing that may occur intracellular or extracellularly in the body). The term also encompasses naturally occurring variants of proteins, such as splice variants or allele variants.

[0049] As used interchangeably herein, “polynucleotide” or “nucleic acid” refers to a polymer of nucleotides of any length, including DNA and RNA. Nucleotides can be deoxyribonucleotides, ribonucleotides, modified nucleotides or bases, and / or analogs thereof, or any substrate that can be incorporated into the polymer by DNA or RNA polymerase or by synthetic reactions. Therefore, examples of polynucleotides as defined herein include, but are not limited to, single-stranded and double-stranded DNA, DNA containing single-stranded and double-stranded regions, single-stranded and double-stranded RNA, and RNA containing single-stranded and double-stranded regions, single-stranded, or more typically double-stranded, or hybrid molecules containing DNA and RNA that may contain single-stranded and double-stranded regions. Furthermore, as used herein, the term “polynucleotide” refers to a triple-stranded region containing RNA or DNA, or both RNA and DNA. The strands of such a region may originate from the same molecule or different molecules. A region may contain all of one or more molecules, but more typically, it contains only some of the regions of a molecule. One of the molecules in a triple-helix region is often an oligonucleotide. The terms "polynucleotide" and "nucleic acid" include, in particular, mRNA and cDNA.

[0050] The terms "patient" and "subject" are used interchangeably herein and refer to human beings.

[0051] The terms “to treat,” “to treat,” or “treatment” refer to the process of action to eliminate, reduce, suppress, alleviate, improve, or prevent the worsening of at least one of the diseases, disorders, or conditions, or symptoms associated therewith, whether temporarily or permanently. Treatment includes alleviating symptoms, reducing the severity of the disease, inhibiting (e.g., cessation of the onset or further onset of the disease, disorder, or condition, or associated clinical symptoms), or extending the survival of a subject compared to the survival expected without treatment, or compared to published standard treatment for a particular disease.

[0052] As used herein, the term “requiring treatment” refers to a judgment made by a physician or equivalent professional that the subject requires treatment or would benefit from treatment. This judgment is based on a variety of factors within the scope of the physician’s expertise and may include a positive diagnosis of disease, disorder, or condition.

[0053] As used herein, “administration” of a drug or substance to a subject includes any route through which the compound is introduced or delivered to the subject in order to perform its intended function. Administration may be carried out by any preferred route, including but not limited to oral, intranasal, parenteral (intravenous, intramuscular, intraperitoneal, or subcutaneous), rectal, intrathecal, intratumoral, or topical. Administration may include self-administration and administration by another person.

[0054] As used herein, “specifically bind” means a molecule that recognizes and binds to another molecule (e.g., an antigen) but substantially does not recognize and bind to other molecules (e.g., an antibody or its antigen-binding fragment). As used herein, the terms “specifically bind to,” “specifically bind to,” or “specific to” a particular molecule (e.g., a polypeptide or an epitope on a polypeptide) mean, for example, about 10 times the amount of the molecule it binds to. -4 M, 10 -5 M, 10 -6 M, 10 -7 M, 10 -8M, 10 -9 M, 10 -10 M, 10 -11 M or 10 -12 It can be presented by a molecule having the KD of M. The term "specifically binds" can also refer to a binding in which a molecule (e.g., an antibody or an antigen-binding fragment thereof) binds to a specific polypeptide or an epitope on a specific polypeptide without substantially binding to any other polypeptide or polypeptide epitope.

[0055] As used herein, the term "antibody" is used in the broadest sense and encompasses various antibodies and antibody-like structures (e.g., monospecific antibodies, multispecific antibodies, polyepitope antibodies, etc.) that specifically bind to a single antigen or multiple antigens, including, but not limited to, full-length antibodies, antigen-binding fragments, heavy-chain antibodies, single-chain antibodies, and higher-order variants of single-chain antibodies. Thus, any reference to an antibody should be understood to refer to an antibody in its complete form or an antigen-binding fragment (including an antigen-binding fragment derived from a full-length antibody) unless the context requires otherwise. Preferably, although not necessarily, antibodies useful herein can be isolated and recombinantly produced. The term "isolated antibody" refers to an antibody that has been separated from the components of its natural environment. In some embodiments, an isolated antibody is purified to greater than 95% or greater than 99% purity as determined by, for example, electrophoresis or chromatography (e.g., ion exchange or reverse phase HPLC).

[0056] The terms "full-length antibody", "complete antibody", and "whole antibody" are used interchangeably herein and refer to an antibody having a structure substantially similar to the native antibody structure or having a heavy chain containing an Fc region.

[0057] The term "antibody fragment" refers to a molecule other than a complete antibody, which contains a portion of a complete antibody that binds to an antigen to which the complete antibody binds. Examples of antigen-binding fragments include, but are not limited to, diabodies, Fab, Fab', F(ab')2, F(ab)c, Fv fragments, disulfide-stabilized Fv fragments (dsFv), (dsFv)2, bispecific dsFv (dsFv-dsFv'), disulfide-stabilized diabodies (ds-diabodies), triabodies, tetrabodies, single-chain antibody molecules, scFv, scFv dimers, single-domain antibodies, and multivalent domain antibodies. Typically, binding fragments compete with the complete antibody for specific binding. Binding fragments can be generated by recombinant DNA technology or by enzymatic or chemical separation of complete immunoglobulins.

[0058] The term “Fc region” is used herein to define the C-terminal region of an immunoglobulin heavy chain, including the native sequence Fc region and variant Fc regions. While the boundaries of the Fc region of an immunoglobulin heavy chain can vary, the human IgG heavy chain Fc region is typically defined as extending from the amino acid residue at position Cys226 or Pro230 to its carboxyl terminus. The C-terminal lysine (residue 447 according to the Eu numbering system) of the Fc region can be removed, for example, during antibody production or purification, or by recombination of the nucleic acid encoding the antibody heavy chain. Thus, a complete antibody composition may include antibody populations from which all Lys447 residues have been removed, antibody populations from which Lys447 residues have not been removed, and antibody populations containing mixtures of antibodies with and without Lys447 residues.

[0059] A "functional Fc region" possesses "effector function" of a native sequence Fc region. Exemplary "effector functions" include C1q binding, complement-dependent cytotoxicity (CDC), Fc receptor binding, antibody-dependent cell-mediated cytotoxicity (ADCC), phagocytosis, and downregulation of cell surface receptors (e.g., B cell receptor, BCR). Such effector functions generally require an Fc region combined with a binding domain (e.g., an antibody-variable domain) and can be evaluated using various assays disclosed herein or otherwise well-known in the art. Functional Fc regions may have substantially similar effector function to wild-type IgG, reduced (but still measurable) effector function compared to wild-type IgG, or enhanced effector function compared to wild-type IgG.

[0060] A “natural sequence Fc region” contains an amino acid sequence identical to the amino acid sequence of a naturally occurring Fc region. Natural sequence human Fc regions include natural sequence human IgG1 Fc regions (non-A and A allotypes), natural sequence human IgG2 Fc regions, natural sequence human IgG3 Fc regions, and natural sequence human IgG4 Fc regions, as well as their naturally occurring variants. A “variant Fc region” contains an amino acid sequence that differs from the amino acid sequence of a natural sequence Fc region by at least one amino acid modification (e.g., about 1 to about 10 amino acid modifications, and in some embodiments, about 1 to about 5 amino acid modifications), preferably by one or more amino acid substitutions. Variant Fc regions as used herein preferably have at least about 80% homology to the natural sequence Fc region and / or the Fc region of the parent polypeptide, preferably at least about 90% homology, or preferably at least about 95% homology. In some embodiments, variant Fc regions may have reduced effector function (including no effector function) compared to wild-type IgG. In other embodiments, the variant Fc region may have enhanced effector function compared to wild-type IgG.

[0061] As used herein, the term “therapeutic agent” is intended to mean a compound that, when present in an effective amount, produces a desired therapeutic effect on a target that requires it.

[0062] As used herein, the term “effective dose” means an amount sufficient to achieve the desired therapeutic and / or preventive effect, for example, an amount that results in the prevention or reduction of one or more signs or symptoms of the disease or condition described herein or associated with the disease or condition described herein. In the context of therapeutic or preventive application, the amount of composition administered to a subject will vary depending on the composition, the degree, type, and severity of the disease, as well as individual characteristics such as general health status, age, sex, weight, and tolerance to the drug. Those skilled in the art will be able to determine an appropriate dosage depending on these and other factors. The composition may also be administered in combination with one or more additional therapeutic compounds. In the methods described herein, the therapeutic composition may be administered to a subject having one or more signs or symptoms of the disease or condition described herein. As used herein, the “therapeutic effective dose” of the composition means the level of composition at which the physiological effects of the disease or condition are improved or eliminated. A therapeutic effective dose may be given in one or more doses.

[0063] Additionally, quantities, ratios, and other numerical values ​​are sometimes presented in range form as used herein. Such range forms are used for convenience and brevity and include numerical values ​​explicitly designated as limits to the range, but should be understood flexibly to also include all individual numerical values ​​or subranges contained within that range, as if each numerical value and subrange were explicitly designated. For example, values ​​in the range of about 1 to about 200 include the explicitly listed limits of about 1 and about 200, but should be understood to also include individual values ​​such as about 2, about 3, and about 4, as well as subranges such as about 10 to about 50, about 20 to about 100.

[0064] Furthermore, as used herein, "and / or" refers to and encompasses all possible combinations of one or more of the related enumerated items, as well as the absence of any combination when interpreted as an alternative ("or").

[0065] Where used herein, the term “including” is intended to mean that a composition and method includes the enumerated elements but does not exclude other elements. “Essentially consisting of” is intended, where used to define a composition and method, to exclude other elements having any essential importance to the composition or method. “Consists of” is intended to exclude other components beyond trace elements for a claimed composition and substantial method steps. Examples and embodiments defined by each of these conversion terms are within the scope of this disclosure. Thus, a method and composition may include additional steps and components (including), or alternatively, may include (essentially consisting of), non-essential steps and compositions, or alternatively, may intend (consist of), only the described method steps or compositions.

[0066] The terms “optional” or “optional” mean that the event or situation described thereafter may or may not occur, and that the description includes both cases in which such event or situation occurs and cases in which such event or situation does not occur. Biomarkers of this disclosure

[0067] This disclosure relates to biomarkers or combinations of biomarkers (e.g., two, three, four, five or more), and the use of these biomarkers individually or in combination in clinical and diagnostic settings that affect therapeutic action. In various embodiments, the biomarkers of this disclosure may be, relative to a reference level, a protein (e.g., cytokines, or proteins expressed by immune cells and / or by tumor cells and / or proteins expressed by other cell types in the tumor microenvironment, such as stromal cells, fibroblasts, and endothelial cells), or a nucleic acid encoding such a protein. For clarity, the term “expression level,” as used with respect to a protein (e.g., PD-L1 expression level, CD155 expression level, etc.), may refer to a detectable level of the protein and, in some cases, a polynucleotide (mRNA) encoding a fragment thereof, or a detectable level of the translated polypeptide and, in some cases, a fragment thereof. Polynucleotides and / or proteins may be tumor-related and, for example, detectable in or on tumor cells or other cells within the tumor microenvironment (e.g., immune cells, stromal cells, fibroblasts, endothelial cells, etc.), or circulate and, for example, detectable in or on complete cells or intracellular structures (e.g., exosomes) in blood or lymph or extracts thereof, or detectable in a soluble form in blood, lymph or extracts thereof. In other embodiments, the biomarkers of this disclosure may be the presence, absence, or amount of tumor genomic features (e.g., mutations, deletions, amplifications, rearrangements, copy number changes, etc.) relative to a reference level. An expression level or amount above the reference level is "high," and an expression level or amount below the reference level is "low." Thus, a biomarker-high tumor (e.g., a CD155-high tumor) is a tumor in which the expression level of the biomarker is equal to or greater than the reference level in a sample of the tumor. Similarly, high expression of peripheral biomarkers (e.g., high CXCL10 expression in blood-derived samples) refers to the expression level of the biomarker measured in the peripheral sample that is above the reference level.Non-limiting examples of the uses of the biomarkers disclosed herein as intended include identifying subjects with cancers with poor prognosis, improving outcomes in subjects with poor prognosis, determining the effectiveness of therapies (e.g., immune checkpoint inhibitors) for treating cancer in subjects, identifying subjects for treatment with immune checkpoint inhibitors or combinations of immune checkpoint inhibitors, identifying subjects for clinical trials, and / or stratifying subjects into treatment arms during clinical trials (e.g., based on prognosis and / or expected responsiveness to immune checkpoint inhibitors), and determining whether cancer is likely to respond to a therapy (e.g., immune checkpoint inhibitors). As described in more detail herein, the effectiveness of therapies including immune checkpoint inhibitors (e.g., PD-(L)1 antagonists, TIGIT antagonists) or combinations of immune checkpoint inhibitors (PD-(L)1 antagonists and TIGIT antagonists) for use as pharmaceuticals to treat cancer may be improved by administering the therapy to subjects with cancers characterized by one or more of the biomarkers disclosed herein. Improved efficacy can be demonstrated in a clinical trial setting, for example, by comparing outcomes measured in a cohort of experimentally treated subjects with the same outcomes measured in a biomarker-selected subset of that cohort (e.g., prospectively or retrospectively selected based on a biomarker or combination of biomarkers). Non-limiting examples of preferred outcomes include objective response rate (e.g., measures such as complete response, partial response, stable disease, progressive disease, and objective response rate), duration of response, time to response, progression-free survival, and overall survival. Improved efficacy does not necessarily require that the therapy is always effective when treating all individual subjects in a biomarker-selected cohort.

[0068] Biomarkers are protein expression levels (e.g., cytokines, PD-L1, PD-1, TIGIT, CD226, CD155, or proteins of the ATP-adenosine axis (e.g., CD39, CD73, TNAP, A)). 2aR、A 2bIf the expression level is R), the expression level can be measured in the sample by immunohistochemistry (IHC), immunocytochemistry, immunofluorescence microscopy, immunophenotyping by flow cytometry, ELISA, immunoassays or other immunoassays based on electrochemiluminescence, mass spectrometry, proximity extension assays (e.g., Olink assay), aptamer-based assays (e.g., SOMAscan assay), etc. Non-limiting examples of suitable samples include tissue, cells, and / or tissue extracts such as body fluids, tumor lysates, homogenized tissue, lymph, blood, blood-derived cells, plasma, and serum from biopsies (e.g., bone marrow biopsies, lymph node biopsies, skin biopsies, surgical biopsies, tumor biopsies, etc.) or excisions. Protein expression levels can be characterized in several different ways using different algorithms. For example, protein expression levels measured by IHC can be characterized by cell-positive percentage, cell-positive percentage relative to area, H score, positive percentage at a given intensity level, etc. For example, protein expression levels measured by ELISA, immunoassays, mass spectrometry, proximity extension assays, aptamer-based assays, etc., can be characterized by absolute, relative, or cyclic changes. Regarding methods that use antibodies to detect a protein of interest (e.g., IHC), it will be understood that any given antibody that specifically binds to the protein can be used, along with a specific assay protocol and / or scoring terminology, to derive protein expression levels. Sensitivity can vary between different antibodies, and therefore, a threshold defined by one particular assay may not be applicable to another assay, even when using the same scoring algorithm. For example, in an IHC assay, staining with anti-PD-L1 antibodies 28-8 or 22C3 and SP263 resulted in only about 64% of samples meeting the PD-L1 expression level threshold of 1% TC or 25% TC, as defined respectively, meeting the threshold when stained with anti-PD-L1 antibody SP142 (Hirsch et al., Journal of Thoracic Oncology 2016, 12(2):208-222).While there may be no agreement between absolute thresholds, different assays and algorithms may identify the same patient population when used with different thresholds, and agreement between different approaches can be empirically determined by those skilled in the art (Liu et al., "Tumor Area Positivity (TAP) score of programmed death-ligand 1 (PD-L1): a novel visual estimation method for combined tumor cell and immune cell scoring," doi.org / 10.21203 / rs.3.rs-2206120 / v1).

[0069] If the biomarker has a polynucleotide expression level above or below a reference level, the expression level can be measured by transcriptome profiling of tumor or immune cells or stromal cells and other cells present in the tumor microenvironment in the sample, for example by next-generation sequencing (NGS), RNA sequencing (RNA-Seq), microarrays, quantitative RT-PCR (qRT-PCR), etc. Non-limiting examples of suitable samples include tissue, cells, and / or tissue extracts such as body fluids, tumor lysates, homogenized tissue, lymph, blood, blood-derived cells, plasma, and serum from biopsies (e.g., bone marrow biopsies, lymph node biopsies, skin biopsies, surgical biopsies, tumor biopsies, etc.) or excisions.

[0070] If the biomarker is the presence, absence, or amount of tumor genomic features above or below a reference level, the genomic features may be detected and / or measured by next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), or whole exome sequencing (WES). Non-limiting examples of suitable samples include tissue, cells, and / or tissue extracts such as body fluids, tumor lysates, homogenized tissue, lymph, blood, blood-derived cells, plasma, and serum from biopsies (e.g., bone marrow biopsies, lymph node biopsies, skin biopsies, surgical biopsies, tumor biopsies, etc.) or excisions.

[0071] In some embodiments, the biomarkers of this disclosure are PD-L1 expression levels above or below the reference level. The terms “PD-L1” or “Programmed Cell Death Ligand 1” as used herein refer to the human protein encoded by the CD274 gene, and naturally occurring variants of PD-L1, such as splice variants or allele variants, or naturally occurring fragments of PD-L1, for example, derived from transcripts produced or degraded by alternative splicing, or, for example, from post-translational processing of polypeptides by proteolysis. An exemplary amino acid sequence of human PD-L1 can be found at UniProt accession number Q9NZQ7. When PD-L1 expression is detected by immunohistochemistry (IHC), for example by an IHC assay that stains PD-L1 using an antibody that specifically binds to PD-L1 (e.g., SP263, 22C3, SP142, 28-8, etc.), PD-L1 positive staining may refer to partial or complete membrane staining (excluding cytoplasmic staining) at any intensity, or to membrane, cytoplasmic, and punctate staining at any intensity, depending on the specific IHC assay and the type of tumor being evaluated.

[0072] In some embodiments, PD-L1 expression levels are measured using immunohistochemical (IHC) assays for PD-L1. For example, PD-L1 expression levels may be measured in samples stained with SP263, 22C3, SP142, or 28-8 using OPTIVIEW® detection on Benchmark ULTRA, EnVision Flex on AutostainerLink 48, OPTIVIEW® detection and amplification on Benchmark ULTRA, or EnVision Flex on AutostainerLink 48, respectively. In some embodiments, PD-L1 expression levels are measured using companion diagnostic tests regulated by health organizations (e.g., US Food & Drug Administration, European Medicines Agency, etc.), selected from the Ventana SP263 IHC assay, Ventana SP142 IHC assay, pharmDx 28-8 IHC assay, or pharmDx 22C3 IHC assay. As used herein, the "Ventana SP263 IHC assay" is a PD-L1 IHC assay performed according to the Ventana PD-L1 (SP263) assay package insert (Tucson, Ariz.: Ventana Medical Systems, Inc.), which is incorporated herein by reference in its entirety. As used herein, the "Ventana SP142 IHC assay" is a PD-L1 IHC assay performed according to the Ventana PD-L1 (SP142) assay package insert (Tucson, Ariz.: Ventana Medical Systems, Inc.), which is incorporated herein by reference in its entirety. As used herein, the "pharmDx 28-8 IHC assay" is a PD-L1 IHC assay performed according to the PH-L1 IHC 28-8 pharmDx package insert (Carpinteria, Calif.: Dako, Agilent Pathology Solutions), which is incorporated herein by reference in its entirety.As used herein, the "pharmDx 22C3 IHC assay" is a PD-L1 IHC assay performed according to the PD-L1 IHC 22C3 pharmDx package insert (Carpinteria, Calif.:Dako, Agilent Pathology Solutions), which is incorporated herein by reference in its entirety.

[0073] In some embodiments, the PD-L1 expression level of a sample is characterized by the percentage of PD-L1-positive tumor cells. As used herein, “PD-L1-positive tumor cell percentage,” “PD-L1 TC%,” or “tumor proportion score (TPS)” are used interchangeably and are the percentage of viable tumor cells that show partial or complete membrane staining at any intensity (1+ or greater), distinct from cytoplasmic staining, after staining a sample using an immunohistochemical (IHC) assay against PD-L1, e.g., an IHC assay using an anti-PD-L1 antibody such as SP263, 22C3, SP142, or 28-8. Thus, the PD-L1-positive tumor cell percentage is expressed by the formula

number

[0074] In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with less than 1% TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with 1% or more TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with 50% or more TC or 75% or more TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with less than 50% TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with 1 to 49% TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with 10% or more TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with more than 10% TC. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with 50% or more TC. In some embodiments, the sample is obtained from a subject having cancer (e.g., solid tumors, e.g., lung cancer, e.g., NSCLC, e.g., squamous or non-squamous NSCLC, e.g., locally advanced unresectable NSCLC (e.g., stage III NSCLC), or recurrent or metastatic NSCLC (e.g., stage IV NSCLC)), and the PD-L1 expression level of the sample is optionally characterized by the percentage of PD-L1-positive tumor cells using the pharmDx 22C3 IHC assay, the pharmDx 28-8 IHC assay, or the Ventana SP263 IHC assay.

[0075] In some embodiments, the PD-L1 expression level of a sample is characterized by PD-L1-positive immunocytochemistry, or by PD-L1-positive tumor cell staining and PD-L1-positive immunocytochemistry. In some embodiments, the PD-L1 expression level of a sample is characterized by the Combined Positive Score (CPS). In some embodiments, the PD-L1 expression level of a sample is characterized by the Tumor Area Proportion (TAP). In some embodiments, the PD-L1 expression level of a sample is characterized by the PD-L1-positive immune cell percentage (IC%).

[0076] "CPS" refers to the number of PD-L1-positive tumor cells and PD-L1-positive mononuclear immune cells (MICs, e.g., lymphocytes, macrophages) in the tumor lesion and adjacent supporting stroma that show partial or complete membrane staining at any intensity (i.e., staining with a score of 1+ or higher) different from cytoplasmic staining for all viable tumor cells present in the sample after staining the sample using an IHC assay for PD-L1, e.g., an IHC assay using antibodies SP263, 22C3, SP142, or 28-8. Therefore, the percentage of PD-L1-positive tumor cells is given by the formula:

number

[0077] In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of less than 1 CPS. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of 1 or more CPS. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of less than 5 CPS. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of 5 or more CPS. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of less than 10 CPS. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of 10 or more CPS. In some embodiments, the sample is obtained from / obtained from a subject having cancer (e.g., solid tumors, cancers other than lung cancer, e.g., upper GI cancer, e.g., stomach, gastroesophageal junction (GEJ), or esophageal adenocarcinoma (EAC), e.g., locally advanced unresectable stomach, GEJ, or EAC (e.g., stage III stomach, GEJ, or EAC), or recurrent or metastatic stomach, GEJ, or EAC (e.g., stage IV stomach, GEJ, or EAC)), and the PD-L1 expression level of the sample is optionally characterized by CPS using the pharmDx 22C3 IHC assay, the pharmDx 28-8 IHC assay, or the Ventana SP263 IHC assay.

[0078] "TAP" refers to the area percentage of PD-L1-positive tumor cells that exhibit partial or complete membrane staining at any intensity distinct from cytoplasmic staining, and the area percentage of PD-L1-positive tumor-associated immune cells that exhibit membrane, cytoplasmic, and punctate staining at any intensity relative to the tumor area. Therefore, the percentage of PD-L1-positive tumors and immune cells is given by the formula TAP = (PD-L1-positive TC and IC%) / Tumor Area

number

[0079] In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of less than 1% TAP. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of 1% or more TAP. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of less than 5% TAP. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of 5% or more TAP. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of less than 10% TAP. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level of 10% or more TAP. In some embodiments, the sample is obtained from / obtained from a subject having cancer (e.g., solid tumors, cancers other than lung cancer, e.g., upper GI cancer, e.g., stomach, gastroesophageal junction (GEJ), or esophageal adenocarcinoma (EAC), e.g., locally advanced unresectable stomach, GEJ, or EAC (e.g., stage III stomach, GEJ, or EAC), or recurrent or metastatic stomach, GEJ, or EAC (e.g., stage IV stomach, GEJ, or EAC)), and the PD-L1 expression level of the sample is optionally characterized by TAP using the pharmDx 22C3 IHC assay, the pharmDx 28-8 IHC assay, or the Ventana SP263 IHC assay.

[0080] The "PD-L1-positive immune cell fraction," abbreviated as "PD-L1 IC%", is the percentage of viable tumor-infiltrating immune cells that show membrane or cytoplasmic staining at any intensity (1+ or greater) as a percentage of the tumor area, including the associated intratumor and adjacent peritumoral stroma, after staining of a sample using an immunohistochemical (IHC) assay against PD-L1, for example, an IHC assay using an anti-PD-L1 antibody such as SP263, 22C3, SP142, or 28-8. In some embodiments, the reference level may be 1% IC, 5% IC, 10% IC, 50% IC, or 75% IC.

[0081] In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with an IC of less than 1%. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with an IC of 1% or more. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with an IC of less than 5%. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with an IC of 5% or more. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with an IC of less than 10%. In some embodiments, the biomarker of the Disclosure is a PD-L1 expression level with an IC of 10% or more.

[0082] In some embodiments, the biomarkers of this disclosure are CD155 expression levels above or below the reference level. The terms “CD155,” “poliovirus receptor,” and “PVR” refer to the protein encoded by the PVR gene in humans, and naturally occurring variants of PVR or CD155, such as splice variants or allele variants, or naturally occurring fragments of CD155 derived, for example, from transcripts produced or degraded by alternative splicing, or from post-translational processing of polypeptides by proteolysis. An exemplary amino acid sequence of human CD155 can be found at UniProt accession number P15151. When CD155 expression is detected by immunohistochemistry (IHC), for example by an IHC assay that stains CD155 using an antibody that specifically binds to CD155 (e.g., rabbit clone D3G7H (Cell Signaling), rabbit clone D8A5G (Cell Signaling)), CD155-positive staining may refer to partial or complete membrane staining distinct from cytoplasmic staining at any intensity, or to membrane and cytoplasmic staining at any intensity, depending on the specific IHC assay and the tumor type and cell type being evaluated. In various embodiments, the CD155 expression level of a sample may be characterized by tumor cell staining, immunocytostaining, staining of other cell types (e.g., normal adjacent tissue (NAT), endothelium, smooth muscle, fibroblasts, stromal cells), or any combination thereof. Exemplary methods for characterizing CD155 expression levels are described in further detail in Example 1. This disclosure describes the use of CD155 expression levels above or below a reference level as prognostic and / or predictive biomarkers. In these embodiments, CD155 expression can identify subjects having differentiated immunological or biological attributes. Methods for identifying these differentiated immunological and / or biological attributes are described herein, including in Example 2.

[0083] In some embodiments, the CD155 expression level of a sample is characterized by the percentage of CD155-positive tumor cells. As used herein, “CD155-positive tumor cell percentage” is the percentage of viable tumor cells in a sample that show positive staining at any intensity after staining the sample in an immunohistochemical (IHC) assay of CD155, for example, an IHC assay using an anti-CD155 antibody such as D3G7H. Thus, the CD155-positive tumor cell percentage is expressed by the formula

number

[0084] In some embodiments, the CD155 expression level of a sample is characterized by CD155 2+ or 3+ TC%. As used herein, “CD155 2+ or 3+ TC%” is, for example, the percentage of viable tumor cells in a sample that show moderate or high-intensity positive staining after staining in an immunohistochemical (IHC) assay of CD155, such as an IHC assay using an anti-CD155 antibody such as D3G7H. Thus, CD155 2+ or 3+ TC% is expressed by the formula

number

[0085] In some embodiments, the CD155 expression level of a sample is characterized by a tumor H score. The H score (ranging from 0 to 300) can be calculated based on the sum of the products of the percentages of cells stained at each intensity, using the following formula: (3×3+ cells %) + (2×2+ cells %) + (1×1+ cells %). When the CD155 expression level is characterized by a tumor H score, the reference level may be the median tumor H score in a control group having the same disease (e.g., cancer), or a value within a range above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median. In various embodiments, the reference level may be a tumor H score of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, or 300. In some embodiments, the reference level may be a tumor H score of 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, or 175. In some embodiments, the reference level may be a tumor H score of 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, or 160. In some embodiments, the reference level may be a tumor H score of 110, 115, 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, or 135. In some embodiments, the reference level may be a tumor H score of 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 95, 100, 105, 110, 115, 120, 125, or 130.In some embodiments, the reference level may be a tumor H score of 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, or 135. In some embodiments, the reference level may be a tumor H score of 25, 30, 35, 40, 45, 50, or 55. In some embodiments, the reference level may be a tumor H score of 95, 100, 105, 110, 115, 120, 125, or 130.

[0086] In some embodiments, the biomarker of the Disclosure is a CD155 expression level characterized by a tumor H score of less than 170, less than 160, less than 150, less than 140, less than 130, less than 120, less than 110, less than 100, or less than 90. In some embodiments, the biomarker of the Disclosure is a CD155 expression level characterized by a tumor H score of less than 150, less than 145, less than 140, less than 135, less than 130, less than 125, or less than 120. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of less than 140. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of 140 or higher. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of less than 135. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of 135 or higher. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of less than 130. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of 130 or higher. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of less than 125. In some embodiments, the biomarker of the Disclosure is a CD155 expression level of 125 or higher.

[0087] In some embodiments, CD155 expression levels are characterized relative to the tumor area. For example, in some embodiments, CD155 expression levels may be characterized by the number of CD155-positive tumor cells showing positive staining at any intensity, and / or the number of CD155-positive tumor-associated immune cells, and / or the number of stromal cells or other cells in the tumor microenvironment showing positive staining at any intensity relative to the tumor area. In some embodiments, positive staining refers to cells (tumor or immune) showing partial or complete membrane staining at any intensity distinct from cytoplasmic staining. In some embodiments, positive staining refers to cells (tumor or immune) showing partial or complete membrane staining and / or cytoplasmic staining at any intensity. Tumor-associated immune cells may be intratumoral and peritumoral, including those present within the tumor itself, between tumor foci, and within any tumor-associated reactive stroma. In lymph nodes with extremophilic or discrete tumor metastases, immune cells directly adjacent to the anterior edge of the metastatic tumor foci are typically defined as tumor-associated immune cells. When CD155 expression levels are used to characterize tumors, the reference level may be the median score in a control group having the same disease (e.g., cancer), or a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median.

[0088] In some embodiments, the CD155 expression level of a sample is characterized by cell membrane 2+ or 3+ TC% and is combined with positive staining in the membrane and cytoplasm. In some embodiments, the reference level may be 30%, 25%, 20%, 15%, 10%, or 5% above or below the median (e.g., 10% for gastrointestinal cancer). In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, or 18% cell membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, or 16% cell membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, or 15% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, or 14% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 9%, 10%, 11%, 12%, or 13% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 9%, 10%, 11%, or 12% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 9%, 10%, or 11% of cell membrane 2+ or 3+TC%.

[0089] In some embodiments, the CD155 expression level of a sample is characterized by membrane 2+ or 3+ TC%. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median (e.g., 10% for gastrointestinal cancer). In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, or 15% membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, or 14% membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 9%, 10%, 11%, 12%, or 13% membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 9%, 10%, 11%, or 12% of the film 2+ or 3+TC%.

[0090] In some embodiments, the CD155 expression level of a sample is characterized by a cell membrane H score, combined with positive staining in the membrane and cytoplasm. In some embodiments, the reference level may be ≤30%, ≤25%, ≤20%, ≤15%, ≤10%, or ≤5% above or below the median (e.g., 105 for gastrointestinal cancer). In various embodiments, the reference level may be a cell membrane H score of 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, or 115. In various embodiments, the reference level may be a cell membrane H score of 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, or 113. In various embodiments, the reference level may be a cell membrane H score of 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, or 112. In various embodiments, the reference level may be a cell membrane H score of 102, 103, 104, 105, 106, 107, 108, 109, or 110. In various embodiments, the reference level may be a cell membrane H score of 103, 104, 105, 106, 107, or 108. In various embodiments, the reference level may be a cell membrane H score of 104, 105, or 106.

[0091] In some embodiments, the CD155 expression level of a sample is characterized by a membrane H score. In some embodiments, the reference level may be 30%, 25%, 20%, 15%, 10%, or 5% above or below the median (e.g., 39 for gastrointestinal cancer). In various embodiments, the reference level may be a membrane H score of 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, or 50. In various embodiments, the reference level may be a membrane H score of 24, 26, 28, 30, 32, 34, 36, 38, 39, 40, 42, 44, 46, or 48. In various embodiments, the reference level may be a membrane H score of 26, 28, 30, 32, 34, 36, 38, 39, 40, 42, 44, or 46. In various embodiments, the reference level may be a membrane H score of 28, 30, 32, 34, 36, 38, 39, 40, 42, or 44. In various embodiments, the reference level may be a membrane H score of 32, 34, 36, 38, 39, 40, 42, or 44. In various embodiments, the reference level may be a membrane H score of 34, 36, 38, 39, 40, or 42. In various embodiments, the reference level may be a membrane H score of 38, 39, or 40.

[0092] In some embodiments, the biomarkers of this disclosure are CD226 expression levels above or below the reference level. The terms “CD226,” “DNAX accessory molecule-1,” and “DNAM-1” refer to the protein encoded by the CD226 gene in humans, and naturally occurring variants of CD226, such as splice variants or allele variants, or naturally occurring fragments of CD226, for example, derived from transcripts produced or degraded by alternative splicing, or, for example, from post-translational processing of polypeptides by proteolysis. An exemplary amino acid sequence of human CD226 can be found at UniProt accession number Q15762. When CD226 expression is detected by immunohistochemistry (IHC), for example by an IHC assay that stains CD226 using an antibody that specifically binds to CD226 (e.g., rabbit clone 102 (Sino Biological), rabbit clone E8L9G (Cell Signaling)), CD226-positive staining may refer to partial or complete membrane staining distinct from cytoplasmic staining at any intensity, or to both membrane and cytoplasmic staining at any intensity, depending on the specific IHC assay and the tumor type and cell type being evaluated. In various embodiments, the CD226 expression level of a sample may be characterized by immunocytostaining. Exemplary methods for characterizing CD226 expression levels are described in further detail in Example 1.

[0093] In some embodiments, the CD226 expression level of a sample is characterized by the percentage of CD226-positive immune cells. As used herein, “CD226-positive immune cell percentage” is the percentage of viable immune cells in a sample that show positive staining at any intensity after staining the sample, for example, in an immunohistochemical (IHC) assay of CD226, such as an IHC assay using an anti-CD226 antibody such as 102. Thus, the CD226-positive immune cell percentage is expressed by the formula

number

[0094] In some embodiments, the biomarker of the Disclosure is a CD226 expression level characterized by 1% or more IC, 5% or more IC, 10% or more IC, 15% or more IC, or 20% or more IC. In some embodiments, the biomarker of the Disclosure is a CD226 expression level characterized by 1% or more IC, 2% or more IC, 3% or more IC, 4% or more IC, 5% or more IC, 6% or more IC, 7% or more IC, 8% or more IC, 9% or more IC, or 10% or more IC. In some embodiments, the biomarker of the Disclosure is a CD226 expression level less than 5. In some embodiments, the biomarker of the Disclosure is a CD226 expression level of 5 or more.

[0095] In some embodiments, CD226 expression levels are characterized relative to the tumor area. For example, in some embodiments, CD226 expression levels may be characterized by the number of CD226-positive tumor-associated immune cells and / or stromal cells and other cells of the tumor microenvironment that show positive staining at any intensity relative to the tumor area. In some embodiments, positive staining refers to immune cells that show partial or complete membrane staining at any intensity distinct from cytoplasmic staining. In some embodiments, positive staining refers to immune cells that show partial or complete membrane staining and / or cytoplasmic staining at any intensity. Tumor-associated immune cells may be intratumor and peritumor, including those present within the tumor itself, between tumor foci, and within any tumor-associated reactive stroma. In lymph nodes with extremophilic or discrete tumor metastases, immune cells directly adjacent to the anterior edge of the metastatic tumor foci are typically defined as tumor-associated immune cells. When CD226 expression levels are characterized relative to a tumor, the reference level may be the median score in a control group with the same disease (e.g., cancer), or a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median.

[0096] In some embodiments, the biomarkers of this disclosure are adenosine pathway biomarkers. As used herein, the term “adenosine pathway biomarker” refers to an indicator of adenosine activity. In some embodiments, the adenosine pathway biomarker is a protein expression level above or below a reference level, where the protein is CD39, CD73, TNAP, or an adenosine receptor (e.g., A 2a R, A 2b R) is used, and optionally, the protein expression level is measured by immunohistochemical assay. In some embodiments, the adenosine pathway biomarker is the polynucleotide expression level of a polynucleotide that is above or below a reference level, and the polynucleotide is CD39, CD79, TNAP, or adenosine receptor (e.g., A) 2a R, A2b It is a transcribed polynucleotide (i.e., a transcript) that codes for R).

[0097] In some embodiments, the biomarkers of this disclosure are CD73 expression levels above or below the reference level. The term "CD73" as used herein refers to the human protein encoded by the NT5E gene, and naturally occurring variants of CD73, e.g., splice variants or allele variants, or naturally occurring fragments of CD73, e.g., derived from transcripts produced or degraded by alternative splicing, or e.g., from post-translational processing of polypeptides by proteolysis. An exemplary human CD73 amino acid sequence can be found at UniProt accession number P21589. When CD73 expression is detected by immunohistochemistry (IHC), e.g., by an IHC assay that stains CD73 using an antibody that specifically binds to CD73 (e.g., rabbit clone D7F9A (Cell Signaling)), CD73-positive staining may refer to partial or complete membrane staining distinct from cytoplasmic staining at any intensity, or to membrane and cytoplasmic staining at any intensity, depending on the specific IHC assay and the tumor type and cell type being evaluated. In various embodiments, the CD73 expression level of a sample may be characterized by tumor cell staining, immunocytostaining, staining of other cell types (e.g., normal adjacent tissue (NAT), endothelium, smooth muscle, fibroblasts, stromal cells), or any combination thereof. Exemplary methods for characterizing CD73 expression levels are described in further detail in Example 1.

[0098] The use of CD73 expression levels as a biomarker may or may not be for indicating or identifying tumors with immunosuppressive adenosine signaling. When CD73 acts as an indicator of immunosuppressive adenosine signaling (e.g., CD73 “high” tumor), CD73 expression levels may be referred to as an “adenosine pathway biomarker.” This disclosure also describes the use of CD73 expression levels lower than a reference level as a prognostic and predictive biomarker. In these embodiments, “low” CD73 expression may identify subjects with differentiated immunological or biological attributes. Methods for identifying these differentiated immunological and / or biological attributes are described herein, including in Example 2.

[0099] In some embodiments, the CD73 expression level of a sample is characterized by the percentage of CD73-positive tumor cells. As used herein, “CD73-positive tumor cell percentage” is the percentage of viable tumor cells in a sample that show positive staining at any intensity after staining the sample in an immunohistochemical (IHC) assay of CD73, for example, an IHC assay using an anti-CD73 antibody such as D7F9A. Thus, the CD73-positive tumor cell percentage is expressed by the formula

number

[0100] In some embodiments, the biomarker of the Disclosure is a CD73 expression level of less than 80% TC, less than 75% TC, less than 70% TC, less than 65% TC, less than 60% TC, less than 55% TC, less than 55% TC, or less than 40% TC. In some embodiments, the biomarker of the Disclosure is a CD73 expression level of less than 65% TC, less than 60% TC, less than 55% TC, or less than 45% TC. In some embodiments, the biomarker of the Disclosure is a CD73 expression level of less than 65% TC. In some embodiments, the biomarker of the Disclosure is a CD73 expression level of 65% or more TC. In some embodiments, the biomarker of the Disclosure is a CD73 expression level of less than 60% TC. In some embodiments, the biomarker of the Disclosure is a CD73 expression level of 60% or more TC. In some embodiments, the biomarker of the Disclosure is a CD73 expression level of less than 55% TC. In some embodiments, the biomarker of this disclosure is a CD73 expression level of 55% or greater TC.

[0101] In some embodiments, the CD73 expression level of a sample is characterized by a tumor H score. The H score (ranging from 0 to 300) can be calculated based on the sum of the products of the percentages of cells stained at each intensity, using the following formula: (3×3+ cells %) + (2×2+ cells %) + (1×1+ cells %). When the CD73 expression level is characterized by a tumor H score, the reference level may be the median tumor H score in a control group having the same disease (e.g., cancer), or a value within a range above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median. In various embodiments, the reference level may be 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, or 300.

[0102] In some embodiments, CD73 expression levels are characterized relative to the tumor area. For example, in some embodiments, CD73 expression levels may be characterized by the number of CD73-positive tumor cells showing positive staining at any intensity, and / or the number of CD73-positive tumor-associated immune cells showing positive staining at any intensity, and / or CD73-positive stromal cells or other cells in the tumor microenvironment showing positive staining at any intensity relative to the tumor area. In some embodiments, positive staining refers to cells (tumor or immune) showing partial or complete membrane staining at any intensity distinct from cytoplasmic staining. In some embodiments, positive staining refers to cells (tumor or immune) showing partial or complete membrane staining and / or cytoplasmic staining at any intensity. Tumor-associated immune cells may be intratumor and peritumor, including those present within the tumor itself, between tumor foci, and within any tumor-associated reactive stroma. In lymph nodes with extremophilic or discrete tumor metastases, immune cells directly adjacent to the anterior edge of the metastatic tumor foci are typically defined as tumor-associated immune cells. When CD73 expression levels are characterized relative to tumor area, the reference level may be the median score in a control group having the same disease (e.g., cancer), or a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median.

[0103] In some embodiments, the biomarkers of the Disclosure are cytokine expression levels (e.g., CCL4, CD163, CXCL9, CXCL10, CXCL11, IFNγ, IL-6, IL-12B, IL-18, NGAL, TNFα, etc.) above or below a reference level. In some embodiments, the cytokine expression levels are detected in tumor samples. In some embodiments, the cytokine expression levels are detected in blood samples (e.g., whole blood, plasma, or serum). In some embodiments, the biomarkers of the Disclosure are CXCL9 expression levels, CXCL10 expression levels, IL-6 expression levels, or IFNγ expression levels, TNFα expression levels, or any combination thereof, measured in a blood sample above a reference level. In some embodiments, the biomarkers of the Disclosure are CXCL9 expression levels or CXCL10 expression levels, measured in a blood sample above a reference level. In some embodiments, the biomarkers of this disclosure are CXCL11, IL-12B, IL-18, or TNFα expression levels, or any combination thereof, measured in a blood sample below a reference level. When cytokine protein levels are detected by immunoassays using antibodies that specifically bind to cytokines, for example, in singleplex or multiplex form, or by proximity extension assays, aptamer-based assays, or mass spectrometry, the detectable expression may be affected by the sensitivity of the method. An exemplary method for characterizing cytokine expression levels and establishing a reference value by immunoassay is described in Example 8. A given cutoff value may vary depending on the method used to measure the cytokine and the time at which the sample was collected. Alternative methods for measuring cytokines are known in the art (e.g., Guan et al., Nature, 2024, 627:646-655) and can be adapted to the disclosures herein.

[0104] In some embodiments, the biomarkers of this disclosure are CXCL9, CXCL10, IL-6, or IFNγ expression levels in a blood sample, or any combination thereof, that are above a reference level. In some embodiments, the reference level is the median (e.g., concentration) for a control group having the same disease (e.g., cancer), or the reference level is a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median. In some embodiments, the reference level may be 15% or less, 10% or less, or 5% or less above or below the median. In some embodiments, the expression level is characterized by an immunoassay.

[0105] In some embodiments, the biomarkers of this disclosure are CXCL11, IL-12B, IL-18, or TNFα expression levels in a blood sample, or any combination thereof, below a reference level. In some embodiments, the reference level is the median (e.g., concentration) for a control group having the same disease (e.g., cancer), or the reference level is a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median. In some embodiments, the reference level may be 15% or less, 10% or less, or 5% or less above or below the median. In some embodiments, the expression level is characterized by an immunoassay.

[0106] In some embodiments, blood samples are obtained before the initiation of treatment (e.g., baseline samples). High baseline CXCL9 and / or high baseline CXCL10 compared to low baseline expression may be associated with poor clinical outcomes (e.g., poor survival) in patients receiving PD-(L)1 antagonist therapy (e.g., treatment with anti-PD-(L)1 antibody ± chemotherapy). In contrast, high baseline CXCL9 and / or high baseline CXCL10 may predict the additional benefits associated with TIGIT antagonists (e.g., anti-TIGIT antibodies) over treatment with PD-(L)1 antagonists. Therefore, this disclosure provides the use of combinations including TIGIT antagonists and PD-(L)1 antagonists ± chemotherapy for treating cancer in patients with high baseline CXCL9 and / or high baseline CXCL10. In some embodiments, a high baseline CXCL9 is an amount of CXCL9 greater than or equal to the median amount derived from samples obtained from a group of patients known to have the same cancer, or an amount of CXCL9 greater than or equal to approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median. In some embodiments, a high baseline CXCL9 is an amount of CXCL9 greater than or equal to the median amount derived from samples obtained from a group of patients known to have the same cancer, or an amount of CXCL9 greater than or equal to approximately 15%, 10%, or 5% above or below the median. In some embodiments, a high baseline CXCL10 is an amount of CXCL10 greater than or equal to the median amount derived from samples obtained from a group of patients known to have the same cancer, or an amount of CXCL10 greater than or equal to approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median. In some embodiments, a high baseline CXCL10 is an amount of CXCL10 greater than or equal to the median amount derived from samples obtained from a group of patients known to have the same cancer, or an amount of CXCL10 greater than or equal to about 15%, about 10%, or about 5% above or below the median.

[0107] In some embodiments, cytokine levels are measured in two or more samples, e.g., a baseline sample and a second blood sample obtained after one or more treatment cycles (e.g., approximately 1, 2, 3, 4, 5, 6, or 7 days after the first treatment, or approximately 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 weeks, or more). The change in the amount of cytokines in the second sample compared to the first sample is referred to herein as “induction” or “post-treatment increase.” The term “high induction” means that the increase is above a reference value. The term “low induction” means that the change is below a reference value. Low induction of IL-18 expression levels, low induction of IL-12B expression levels, high induction of CXCL9 expression levels, high induction of CXCL10 expression levels, or high induction of IFNγ expression levels (or combinations thereof) after treatment with a PD-(L)1 antagonist (e.g., anti-PD-(L)1 antibody) ± chemotherapy is associated with poor clinical outcomes (e.g., low response rate, short PFS) in patients with cancer. In contrast, low induction of IL-18 expression levels, low induction of IL-12B expression levels, high induction of CXCL9 expression levels, high induction of CXCL10 expression levels, or high induction of IFNγ expression levels (or any combination thereof) after combination therapy including a TIGIT antagonist (e.g., anti-TIGIT antibody) and a PD-(L)1 antagonist (e.g., anti-PD-(L)1 antibody) ± chemotherapy may predict clinical benefit. Accordingly, in some embodiments, the Disclosure provides for the continued use of a combination including a TIGIT antagonist and a PD-(L)1 antagonist ± chemotherapy for treating cancer in patients having low induction of IL-18 expression levels, low induction of IL-12B expression levels, high induction of CXCL9 expression levels, high induction of CXCL10 expression levels, or high induction of IFNγ expression levels, or any combination thereof, after combination therapy (e.g., one or more cycles). In some embodiments, the reference level is the median of magnification changes derived from samples obtained from a group of patients known to have the same cancer, and the samples were obtained at approximately the same time before treatment and at approximately the same time after the first treatment.

[0108] In the embodiments described above, samples can be obtained from subjects with cancer, or optionally, solid tumors. In embodiments where therapy is selected using biomarkers, the expression of biomarkers was measured in the samples obtained before administration of therapy. In some embodiments, samples are obtained from subjects with cancers other than lung cancer, such as upper GI cancer, such as stomach, gastroesophageal junction (GEJ), or esophageal adenocarcinoma EAC, such as resectable stomach, GEJ, or EAC (e.g., stage II or stage III stomach, GEJ, or EAC), such as locally advanced unresectable stomach, GEJ, or EAC (e.g., stage III stomach, GEJ, or EAC), or recurrent or metastatic stomach, GEJ, or EAC (e.g., stage IV stomach, GEJ, or EAC). In some embodiments, the sample is obtained from a subject having lung cancer, for example, NSCLC, for example, squamous or non-squamous NSCLC, for example, resectable NSCLC (e.g., stage II or stage III NSCLC), for example, locally advanced unresectable NSCLC (e.g., stage III NSCLC), or recurrent or metastatic NSCLC (e.g., stage IV NSCLC).

[0109] The optimal biomarker cutoff (e.g., reference value) can be analyzed using the median described above, or using quartiles or triquartiles as reference points. Statistical methods, including but not limited to receiver operating characteristic (ROC) analysis and those described in the examples, can also be used to determine the best-fitting cutoff, thereby identifying the most significant difference in clinical benefit between high-biomarker and low-biomarker populations. Method and Use

[0110] In one aspect, this disclosure relates to the use of biomarkers described herein. The biomarkers described herein are useful in a variety of ways, including, but not limited to, methods for identifying patients for treatment in therapy; methods for treating diseases in patients (e.g., patients who need to be treated for a disease); methods for determining the prognosis of patients identified as having or being at risk of having a disease or condition (e.g., cancer); and methods for determining the prognosis of subjects or patients, such as subjects or patients who have received or have not received therapy (e.g., immune checkpoint inhibitors, e.g., PD-(L)1 antagonists, TIGIT antagonists, or therapies comprising PD-(L)1 antagonists and TIGIT antagonists).

[0111] In certain embodiments, biomarkers are evaluated, observed, measured, analyzed, or characterized in a sample obtained from a patient. The sample may contain tumor cells. The sample may contain immune cells. The sample may contain both tumor cells and immune cells. Methods for obtaining such samples are well known in the art. In particular, samples can be obtained by biopsy or excision.

[0112] Samples analyzed in the context of the methods of this disclosure may be obtained before, during, or after treatment of a disease described herein (e.g., cancer). In embodiments in which a therapy is selected using a biomarker, the expression of the biomarker was measured or measured in a sample obtained before treatment (e.g., administration of the therapy). Samples obtained before treatment may be obtained within one year, six, five, four, three, or two months, or one month, before the start of the treatment. It is also intended to obtain a sample within two weeks, or one week, before the treatment. Samples obtained after treatment may be obtained after the completion of the treatment. Samples obtained after treatment may be obtained within three years after the treatment, or within one year, six, five, four, three, or two months, or one month, after the treatment. It is also intended to obtain a sample within two weeks, or one week, after the treatment.

[0113] Determining the amount of biomarkers referred to herein relates to measuring, preferably qualitatively or quantitatively, a detectable level in a biological sample. Measurements can be performed directly or indirectly. Direct measurement relates to measuring a biomarker based on a signal obtained from the biomarker itself, the intensity of which directly correlates with the number of polypeptide molecules present in the sample. Such a signal, sometimes referred to herein as an intensity signal, can be obtained, for example, by measuring the intensity value of a particular physical or chemical property of the biomarker. Indirect measurement involves measuring a signal obtained from a secondary component (i.e., a component other than the biomarker itself) or a biological readout system, such as a measurable cellular response, ligand, label, or enzymatic reaction product.

[0114] According to this disclosure, determining the amount of a biomarker can be achieved by all known means for determining the amount of a biomarker in a sample. Non-limiting examples of preferred means for detecting protein and nucleic acid biomarkers are described above. Such means include immunoassay devices and methods that can utilize labeled molecules in various sandwich, competitive, or other assay formats. For example, if the biomarker contains a protein, the immunoassay may be immunophenotyping by immunohistochemistry (IHC), immunocytochemistry, immunofluorescence microscopy, or flow cytometry, as described elsewhere in this specification. If the biomarker contains a nucleic acid, the immunoassay may be fluorescence in situ hybridization (FISH).

[0115] As used herein, the term “quantity” encompasses the absolute quantity of a biomarker, the relative quantity of a biomarker, and any values ​​or parameters that correlate with or can be derived from it. Such values ​​or parameters include intensity signal values ​​from all specific physical or chemical properties obtained from the biomarker by direct measurement. Furthermore, it encompasses all values ​​or parameters obtained by indirect measurement as specified elsewhere herein. It should be understood that values ​​correlated with the aforementioned quantities or parameters can also be obtained by all standard mathematical operations.

[0116] In some embodiments, the amount or level of a biomarker (e.g., expression level) is compared to a reference level. As used herein, the term “comparing” encompasses comparing the amount of a biomarker contained in the sample being analyzed to the amount of a preferred reference source specified elsewhere herein. As used herein, “comparing” refers to a comparison of corresponding parameters or values, for example, an absolute amount being compared to an absolute reference amount, while a concentration is compared to a reference concentration, or an intensity signal obtained from a test sample is compared to an intensity signal of the same type from a reference sample. The comparison may be performed manually or with computer assistance. In the case of computer-assisted comparison, the determined amount value may be compared to a value corresponding to a preferred reference stored in a database by a computer program. The computer program may further evaluate the results of the comparison and automatically provide the desired evaluation, for example, in a preferred output format. Based on the comparison, it is possible to predict one or more of the likelihood of a patient responding to the therapies described herein, or the patient’s prognosis before or after receiving the therapies described herein. The comparison also makes it possible to select or identify candidates for specific therapies described herein.

[0117] As used herein, the term “reference level” refers to the amount of a biomarker that enables prediction of whether a patient or subject is likely to respond to the therapies described herein, whether they are a suitable candidate to receive the therapies described herein, and / or whether they will have a favorable or unfavorable prognosis before or after the therapies described herein. In some embodiments, the reference level may be derived from a group of subjects known to have the same specific disease as the patient in question (e.g., cancer, cancer type, cancer stage, etc.). For clarity, this group of subjects is “unselected” with respect to the biomarker. Preferably, the reference level is derived from a sample obtained from the aforementioned subjects (i.e., the reference level is a predetermined value). In some embodiments, the reference level may be the median expression level, or an amount that is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median expression level, derived from a sample obtained from a group of subjects known to have the same disease. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above the median expression level derived from samples obtained from a control group known to have the same disease. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less below the median expression level derived from samples obtained from a control group known to have the same disease.

[0118] In the context of the methods of this disclosure, the amounts of more than one biomarker may be determined. For clarity, the determined amounts shall be compared to various reference amounts, i.e., the reference amounts of the individual biomarkers being tested.

[0119] Furthermore, the reference level preferably defines a threshold amount or threshold. A suitable reference amount or threshold amount can be determined from a reference sample by the method of this disclosure. The reference sample can be analyzed simultaneously with the test sample, or before or after the test sample is analyzed. Once a threshold is established for a particular disease, comparison with the reference amount does not require reanalysis of the reference sample with each test sample. In some preferred embodiments, the reference level is the median expression level, or an amount that is 30%, 25%, 20%, 15%, 10%, or 5% above or below the median expression level, derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, optionally, the same disease stage, and in some embodiments, the same therapeutic environment / policy). In some embodiments, the reference level is an amount that is approximately 30% above or below the median expression level derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, optionally, the same disease stage, and in some embodiments, the same therapeutic environment / policy). In some embodiments, the reference level is approximately 25% above or below the median expression level derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, arbitrarily selected, the same disease stage, and in some embodiments, the same therapeutic environment / policy). In some embodiments, the reference level is approximately 20% above or below the median expression level derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, arbitrarily selected, the same disease stage, and in some embodiments, the same therapeutic environment / policy). In some embodiments, the reference level is approximately 15% above or below the median expression level derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, arbitrarily selected, the same disease stage, and in some embodiments, the same therapeutic environment / policy).In some embodiments, the reference level is approximately 10% above or below the median expression level derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, arbitrarily selected, the same disease stage, and in some embodiments, the same therapeutic environment / policy). In some embodiments, the reference level is approximately 5% above or below the median expression level derived from samples obtained from a control group known to have the same disease (e.g., the same cancer, arbitrarily selected, the same disease stage, and in some embodiments, the same therapeutic environment / policy). Immune checkpoint inhibitors and combination therapies

[0120] In various embodiments, this disclosure intends to involve the use of biomarkers disclosed herein that influence treatment decisions. In embodiments targeting the treatment of cancer, treatment may include administering an effective dose of an immune checkpoint inhibitor. As used herein, the terms “immune checkpoint inhibitor” and “CPI” (checkpoint inhibitor) are interchangeable and may refer to antagonists of inhibitory or co-inhibitory immune checkpoints. Immune checkpoint inhibitors may antagonize inhibitory or co-inhibitory immune checkpoints by interfering with receptor-ligand binding and / or altering receptor signaling. Examples of immune checkpoints (ligands and receptors) that may be selectively upregulated and blocked in various types of cancer cells include PD-1; PD-L1 (PD-1 ligand); BTLA (B and T lymphocyte attenuator); CTLA-4 (cytotoxic T-lymphocyte associated antigen 4); TIM-3 (T cell immunoglobulin and mucin domain containing protein 3); LAG-3 (lymphocyte activation gene 3) Examples include (lymphocyte activation gene 3); TIGIT (T cell immune receptor having Ig and ITIM domains); CD276(B7-H3); PD-L2; galectin 9; CEACAM-1; CD69; galectin-1; CD113; GPR56; VISTA; 2B4; CD48; GARP; PD1H; LAIR1; TIM-1; and TIM-4; as well as killer inhibitor receptors.

[0121] In some embodiments, the immune checkpoint inhibitor is a CTLA-4 antagonist. In further embodiments, the CTLA-4 antagonist may be an antagonist CTLA-4 antibody. Suitable antagonist CTLA-4 antibodies include, for example, monospecific antibodies such as ipilimumab or tremelimumab, and bispecific antibodies such as MEDI5752 and KN046.

[0122] In some embodiments, the immune checkpoint inhibitor is a PD-1 antagonist that blocks the interaction between PD-1 and its ligand (e.g., PD-L1). In further embodiments, the PD-1 antagonist may be an antagonist PD-1 antibody ("anti-PD-1 antibody"), a small molecule, or a peptide. Suitable antagonist PD-1 antibodies include, for example, monospecific antibodies such as valstilimab, buzigalimab, camrelizumab, cosiberimab, dostarimab, semiprimab, ezabenlimab (BI-754091), MEDI-0680 (AMP-514; International Publication No. 2012 / 145493), nivolumab, pembrolizumab, pidilizumab (CT-011), retifanlimab, sasamlimab, spartalizumab, cintilumab, tislerizumab, tripalimab, and zimbererimab, as well as bispecific antibodies such as LY3434172. In further embodiments, the PD-1 antagonist may be a recombinant protein (AMP-224) composed of the extracellular domain (B7-DC) of PD-L2 fused to the Fc portion of IgGl.

[0123] In some embodiments, the immune checkpoint inhibitor is zimberelimab. In some embodiments, zimberelimab is administered in doses of approximately 100 mg to approximately 600 mg, or approximately 200 mg to approximately 600 mg, or approximately 600 mg to approximately 800 mg. In some embodiments, zimberelimab is administered in doses of approximately 100 mg, 150 mg, 200 mg, 220 mg, 240 mg, 260 mg, 300 mg, 320 mg, 340 mg, 360 mg, 380 mg, 400 mg, 420 mg, 440 mg, or 460 mg. The dose of zimberelimab may be administered once a week or less frequently (e.g., once every 2, 3, 4, 5, 6 weeks, or more). In some embodiments, the dosing cycle includes administering dombanalimab at a dose of approximately 360 mg once every three weeks, or at a dose of approximately 480 mg once every four weeks.

[0124] In some embodiments, the immune checkpoint inhibitor is a PD-L1 antagonist that blocks the interaction between PD-L1 and PD-1. In further embodiments, the PD-L1 antagonist may be an antagonist PD-L1 antibody ("anti-PD-L1 antibody"). Suitable antagonist PD-L1 antibodies include, for example, monospecific antibodies such as avelumab, atezolizumab, durvalumab, BMS-936559, and emvafolimab, as well as bispecific antibodies such as LY3434172 and KN046.

[0125] In some embodiments, the immune checkpoint inhibitor is a TIGIT antagonist that blocks the interaction between TIGIT and CD155. In further embodiments, the TIGIT antagonist may be an antagonist TIGIT antibody ("anti-TIGIT antibody"). Suitable antagonist anti-TIGIT antibodies include, but are not limited to, monospecific antibodies such as AGEN1327, AB308 (International Publication No. 2021247591), BAT6021, COM902, domvanalimab, berresttag, etidyrimab, IBI-939, JS006, PM1021, dargisttag, osiperlimab, renvistobart, SEA-TGT, tilagolumab, and vivostrimab, as well as bispecific antibodies such as AGEN1777, AZD2936, D3L-002, HB036, HLX301, KA-1874, PM1009, SHR02992, and SIM0348. In certain embodiments, the immune checkpoint inhibitor is an antagonist TIGIT antibody disclosed in International Publication No. 2017152088 or International Publication No. 2021247591. In certain embodiments, the immune checkpoint inhibitor is domvanalimab or AB308.

[0126] In some embodiments, the immune checkpoint inhibitor is an anti-TIGIT antibody with reduced binding to one or more activated FcγR isotypes, such as FcγR isotypes I, IIA, IIB, IIIA, and IIIB, compared to a wild-type (WT) IgG1 control antibody. In some embodiments, the immune checkpoint inhibitor is an anti-TIGIT antibody that does not meaningfully bind to FcγR isotypes I, IIA, IIB, IIIA, IIIB, or any combination thereof. Binding to FcγR isotypes I, IIA, IIB, IIIA, and IIIB can be measured, for example, by the method detailed in Example 1 of International Publication No. 2023215719(A1). Alternatively, or in addition, the reduction in binding to activated FcγR can be demonstrated by showing that the anti-TIGIT antibody has reduced Fc effector function, such as reduced CDC, ADCC, and / or ADCP, compared to a wild-type IgG1 control antibody. A suitable method for evaluating CDC, ADCC, and / or ADCP can be measured, for example, by the method detailed in Example 1 of International Publication No. 2023215719(A1).

[0127] In some embodiments, the immune checkpoint inhibitor is an Fc silent anti-TIGIT antibody, i.e., an anti-TIGIT antibody that does not have meaningful binding to FcγR isotypes I, IIA, IIB, IIIA, and IIIB (in some examples, does not have binding).

[0128] Means for manipulating antibodies (e.g., known anti-TIGIT antibodies having a WT hIgG1 Fc domain) to reduce (including no binding) binding to activated FcγR isotypes I, IIA, IIB, IIIA, and IIIB are known in the art. One approach may be to use different human IgG isotypes and their variants, such as hIgG2 or hIgG4, which naturally exhibit reduced FcγR interaction. In addition, Fc mutations have also been described to achieve the same objective. Substitutions of any or all of positions 234, 235, 236, and / or 237 reduce affinity for Fcγ receptors, particularly FcγRI receptors (see, for example, U.S. Patent No. 6,624,821). Alanine is a preferred residue for substitution, and L234A / L235A is a preferred double mutation for reducing Fc effector function. Other combinations of mutations that result in reduced Fc effector function include L234A / L235A / G237A, E233P / L234V / L235A / ΔG236, A327G / A330S / P331S, K322A, L234A and L235A, and L234F / L235E / P331S. Optionally, positions 234, 236, and / or 237 in human IgG2 are substituted with alanine, and position 235 is substituted with glutamine. (See, for example, U.S. Patent No. 5,624,821.) Two amino acid substitutions at the complement Clq binding site at EU index positions 330 and 331 reduce complement binding (see Tao et al., J.Exp.Med.178:661(1993) and Canfield and Morrison, J.Exp.Med.173:1483(1991)). Substitutions of IgG2 residues at positions 233-236 with human IgG1, and IgG4 residues at positions 327, 330, and 331 significantly reduce ADCC and CDC (see, for example, Armour KL.Et al., 1999 Eur J Immunol.29(8):2613-24 and Shields R L.et al., 2001.J Biol Chem.276(9):6591-604).N297A, N297Q, or N297G (Eu-numbered) mutations reduce glycosylation, thereby reducing Fc effector function. Other substitutions may also be made in the constant region of the antibodies disclosed herein to reduce Fc effector function such as complement-mediated cytotoxicity or ADCC (see, for example, Winter et al., U.S. Patent No. 5,624,821; Tso et al., U.S. Patent No. 5,834,597; Lazar et al., Proc. Natl. Acad. Sci. USA, 103:4005, 2006; and Schlothauer et al., Protein Engineering, Design, and Selection, 29(10):457-466, 2016).

[0129] In some embodiments, the Fc silent anti-TIGIT antibody is domvanalimab. Domvanalimab has an engineered IgG1 Fc with reduced binding to one or more activated FcγRs compared to WT hIgG1. See Example 1 of International Publication No. 2023215719(A1). Domvanalimab was tested for binding to FcγR isotypes I, IIA, IIB, IIIA, and IIIB by enzyme-linked immunosorbent assay. Compared to a wild-type IgG1 antibody control, no significant binding with domvanalimab was observed for any FcγR isotype when tested up to a maximum concentration of 1 μM. Domvanalimab was also tested in an FcγR-IIIA (V158 high affinity variant) effector reporter bioassay and was found to be inactive at concentrations up to 1 μM. The CDC assay was performed using Jurkat cell lines that stably overexpress human complement and human TIGIT, in the presence of dombanalimab at gradually increasing concentrations up to 33 nM. No cytotoxicity was observed with dombanalimab at any of the concentrations tested.

[0130] In some embodiments, the Fc silent anti-TIGIT antibody is ASP8374, COM902, JS006, or renvistobart.

[0131] In some embodiments, Fc silent anti-TIGIT is a variant of a known anti-TIGIT containing a wild-type human IgG1 Fc domain or a human IgG1 Fc domain engineered to enhance Fc effector function (e.g., AGEN1327, AGEN1777, AZD2936, BAT6021, D3L-002, HB036, HLX301, IBI-939, KA-1874, PM1009, PM1021, SEA-TGT, SHR02992, SIM0348, belrest tag, etidyrimab, dargist tag, osiperlimab, ralzapastotug, tilagorumab, vivostrimab, etc.). In these embodiments, the variant includes one or more Fc mutations (such as those listed above) that reduce binding to FcγR isotypes I, IIA, IIB, IIIA, and IIIB. Typically, the variant will contain the same (or substantially the same) light and heavy chain variable regions as the anti-TIGIT antibody from which it is derived.

[0132] In certain embodiments, the immune checkpoint inhibitor is dombanalimab. In some embodiments, dombanalimab is administered in doses of approximately 500 mg to approximately 2000 mg, approximately 800 mg to approximately 1600 mg, approximately 600 mg to approximately 800 mg, approximately 900 mg to approximately 1200 mg, and approximately 1200 mg to approximately 1600 mg. Dombanalimab can be administered once a week or less frequently (e.g., once every 2, 3, 4, 5, 6 weeks, or more). In some embodiments, the dosing cycle includes administering dombanalimab at a dose of approximately 1200 mg once every 3 weeks, or at a dose of approximately 1600 mg once every 4 weeks.

[0133] In some embodiments, the immune checkpoint inhibitor is a LAG-3 antagonist. In further embodiments, the LAG-3 antagonist may be an antagonist LAG-3 antibody ("anti-LAG-3 antibody"). Suitable antagonist LAG-3 antibodies include, for example, fianlimab, BMS-986016 (International Publication Nos. 10 / 19570 and 14 / 08218), or IMP-731 or IMP-321 (International Publication Nos. 08 / 132601 and 09 / 44273).

[0134] In certain embodiments, the immune checkpoint inhibitor is a B7-H3 antagonist. In further embodiments, the B7-H3 antagonist is an antagonist B7-H3 antibody ("anti-B7-H3 antibody"). Suitable B7-H3 antibodies include, for example, enobrituzumab (MGA271, International Publication No. 11 / 109400), ombrutamab, DS-7300a, ABBV-155, and SHR-A1811.

[0135] In some embodiments, the immune checkpoint inhibitor is a TIM-3 antagonist. In further embodiments, the TIM-3 antagonist may be an antagonist TIM-3 antibody ("anti-TIM-3 antibody"). Suitable antagonist TIM-3 antibodies include, for example, dostallimab, sabatolimab, BMS-986258, and RG7769 / RO7121661.

[0136] Depending on the disease (e.g., type of cancer), immune checkpoint inhibitors may be used as monotherapy or in combination with one or more additional therapies. When used in combination, each additional therapy may be a therapeutic agent or a different mode of treatment. The selection of additional therapies may be informed by current standards of care for the specific cancer and / or the mutational status and / or stage of the disease of the target cancer. Detailed standards of care guidelines are published, for example, by the National Comprehensive Cancer Network (NCCN). For example, NCCN Colon Cancer v2.2023, NCCN Hepatobiliary Cancer v1.2023, NCCN Kidney Cancer, v4.2023, NCCN NSCLC v3.2023, NCCN Pancreatic Adenocarcinoma v1.2023, NCCN Esophageal and Esophagogastric Junction Cancers v2.2023, NCCN Gastric Cancer v1.2023, Cervical See Cancer v1.2023, Ovarian Cancer / Fallopian Tube Cancer / Primary Peritoneal Cancer v1.2023, Hepatocellular Carcinoma v1.2023.

[0137] In embodiments including one or more additional modes of treatment, immune checkpoint inhibitors may be administered before, after, or during treatment with the additional mode of treatment. Non-limiting examples of additional modes of treatment include surgical resection of tumors, bone marrow transplantation, radiotherapy, and photodynamic therapy. In embodiments including one or more additional therapeutic agents, the therapeutic agents used in such combination therapy may be formulated as a single composition or as separate compositions. If administered separately, each therapeutic agent in the combination may be administered simultaneously, nearly simultaneously, or at different times. Furthermore, the therapeutic agents are administered “in combination” even if they have different dosing forms (e.g., oral capsules and intravenous), are given at different dosing intervals, one therapeutic agent is given in a fixed dosing regimen and another is increased, decreased, or discontinued, or each therapeutic agent in the combination may be independently increased, decreased, increased or decreased in dose, or discontinued and / or restarted during the patient’s treatment course. When the combination drugs are formulated as separate compositions, in some embodiments, the separate compositions are provided together in a kit.

[0138] In some embodiments, one or more of the additional therapies are additional modes of treatment. Illustrative modes of treatment include, but are not limited to, surgical resection of tumors, bone marrow transplantation, radiotherapy, and photodynamic therapy.

[0139] In some embodiments, one or more of the additional therapies are therapeutic agents. Exemplary therapeutic agents include chemotherapeutic agents, radiopharmaceuticals, hormone therapies, epigenetic modulators, ATP-adenosine axis targeting agents, targeted therapies, signaling inhibitors, RAS signaling inhibitors, PI3K inhibitors, arginase inhibitors, HIF inhibitors, AXL inhibitors, PAK4 inhibitors, immunotherapeutic agents, cell therapies, gene therapies, immune checkpoint inhibitors, and agonists of stimulative or co-stimulative immune checkpoints.

[0140] In some embodiments, one or more of the additional therapeutic agents are chemotherapeutic agents. Examples of chemotherapeutic agents include alkylating agents, e.g., thiotepa and cyclophosphamide; alkyl sulfonates, e.g., busulfan, improsulfan, and pigosulfan; aziridines, e.g., benzodopa, carbocon, metredopa, and uredopa; ethyleneimines and methylamelamines, including altretamine, triethylenemelamine, triethylenephosphoramide, triethylenethiophosphoramide, and trimethylolmelamine; nitrogen mustards, e.g. Chlorambucil, chlornafadin, chlorophosphamide, estramustine, ifosfamide, mechloretamine, mechloretamine oxide hydrochloride, melphalan, nobenbitin, fenestrine, prednimustine, trophosphamide, uracil mustard; nitrosourea, e.g., carmustine, chlorozotocin, fotemustine, lomustine, nimustine, ranimustine; antibiotics, e.g., acrasinomycin, actinomycin, ausramycin, azacerin, bleomycin Syn, kactinomycin, calicheamicin, carabicin, carminomycin, cardinophilin, chromomycin, dactinomycin, daunorubicin, detrevicin, 6-diazo-5-oxo-L-norleucine, doxorubicin, epirubicin, esorubicin, idarubicin, marcelomycin, mitomycin, mycophenolic acid, nogaramycin, olibomycin, pomalidomide, peplomycin, porphyromycin ), puromycin, queramycin, rhodorubicin, streptonigrin, streptozocin, tubercidine, ubenimex, dinostatin, zolubicin; antimetabolites, e.g., methotrexate and 5-fluorouracil (5-fluorouracil, 5-FU); folate analogs, e.g., denopterin, methotrexate, pemetrexed, pteropterin, trimethrexate; purine analogs, e.g., fludarabine, 6-mercaptopurine, thiamiprine, thioguanine;Pyrimidine analogs, e.g., ancitabine, azacitidine, 6-azauridine, carmoflu, cytarabine, dideoxyuridine, doxifluridine, enocitabine, floxuridine, 5-FU; androgens, e.g., carsterone, dromostanolone propionate, epithiostanol, mepitiostane, testolactone; anti-adrenaline, e.g., aminoglutethimide, mitotane, trilostane; folic acid supplements, e.g., floric acid; acegraton; aldofamide glycoside; aminolevulinic acid; amsacrin; bestrabusil; bisantren ;Edatrexate;Defofamin;Demecoltin;Diaziquan;Elformitin;Erptinium acetate;Etoglucide;Gallium nitrate;Hydroxyurea;Lentinan;Lonidamin;Mitoguazone;Mitoxantrone;Mopidamol;Nitracrine;Pentostatin;Fenamet;Pirarubicin;Podophyllic acid, 2-Ethylhydrazide;Procarbazine;Lazoxane;Schizophyllan;Spirogermanium;Tenuazonic acid;Triadicone;2,2',2''-Trichlorotriethylamine;Urethane;Vindesine;Dacarbazine;Mannomustine; Mitobronitol; Mitractol; Pipobroman; Gacitosine; Arabinoside (Ara-C); Cyclophosphamide; Thiotepa; Taxoids, e.g., paclitaxel, nab-paclitaxel, and docetaxel; Chlorambucil; Gemcitabine; 6-thioguanine; Mercaptopurine; Methotrexate; Platinum and platinum-coordinate complexes such as cisplatin, carboplatin, and oxaliplatin (i.e., "platinum-containing chemotherapeutic agents"); Vinca alkaloids such as vinblastine, vincristine, vindesine, and vinorelbine; Etoposide (VP-16 ); Ifosfamide; Mitomycin C; Mitoxantrone; Vincristine; Vinorelbine; Navelbine; Novantrone; Teniposide; Daunomycin; Aminopterin; Xeroda; Ibandronate; CPT11; Proteasome inhibitors such as bortezomib, carfilzomib, and ixazomib; Topoisomerase inhibitors such as irinotecan, SN-38, topotecan, etoposide, mitoxantrone, and teniposide; Difluoromethylornithine (DMFO); Retinoic acid; Esperamycin;Examples include, but are not limited to, capecitabine; anthracyclines; and any pharmaceutically acceptable salts, acids, or derivatives of the above. In certain embodiments, the combination therapy comprises chemotherapy comprising one or more chemotherapeutic agents. In one embodiment, the combination therapy comprises chemotherapy comprising one or more of the following: FOLFOX (folic acid, fluorouracil, and oxaliplatin), FOLFIRI (e.g., folic acid, fluorouracil, and irinotecan), CAPOX (capecitabine and oxaliplatin), taxoids (e.g., docetaxel, paclitaxel, nab-paclitaxel, etc.), NALIRIFOX (fluorouracil, leucovorin, liposomal irinotecan, and oxaliplatin), fluoropyrimidine-containing chemotherapeutic agents (e.g., fluorouracil, capecitabine, phloxuridine), platinum-containing chemotherapeutic agents, topoisomerase inhibitors, and / or gemcitabine.

[0141] In some embodiments, one or more of the additional therapeutic agents are radiopharmaceuticals. A radiopharmaceutical is a form of internal radiotherapy in which a radioactive source (i.e., one or more radionuclides) is introduced into the body of a subject. The radioactive source may be in solid or liquid form. Non-limiting examples of radiopharmaceuticals include sodium iodide I-131, radium-223 dichloride, lobenguan iodine-131, radioiodized vesicles (e.g., saposin C-dioleoylphosphatidylserine (SapC-DOPS) nanovesicles), various forms of close-range irradiation therapy, and various forms of targeted radionuclides. Targeted radionuclides include radionuclides associated (e.g., by covalent bonds or ionic interactions) with molecules that specifically bind to targets on cells, typically cancer cells or immune cells ("targeting agents"). The targeting agent may be a small molecule, sugar (including oligosaccharides and polysaccharides), antibody, lipid, protein, peptide, non-natural polymer, or aptamer. In some embodiments, the targeting agent is a sugar (including oligosaccharides and polysaccharides), lipid, protein, or peptide, and the target is a tumor-associated antigen (enriched but not specific to cancer cells), a tumor-specific antigen (minimally expressed or not expressed at all in normal tissue), or a neoantigen (a cancer cell genome-specific antigen produced by non-synonymous mutations in the tumor cell genome). In some embodiments, the targeting agent is an antibody, and the target is a tumor-associated antigen (i.e., an antigen enriched but not specific to cancer cells), a tumor-specific antigen (i.e., an antigen minimally expressed or not expressed at all in normal tissue), or a neoantigen (i.e., a cancer cell genome-specific antigen produced by non-synonymous mutations in the tumor cell genome). Non-limiting examples of targeted radionuclides include somatostatin or its peptide analogues (e.g., 177Lu-Dotatate); prostate-specific membrane antigens or their peptide analogues (e.g., 177Lu-PSMA-617, 225Ac-PSMA-617, 177Lu-PSMA-I&T, 177Lu-MIP-1095); receptor homologous ligands, ligand-derived peptides, or variants thereof (e.g., 188 relabeled VEGF). 125-136or variants thereof having a higher affinity for the VEGF receptor); including radionuclides that bind to antibodies targeting tumor antigens (e.g., 131I-tositumomab, 90Y-ibritumomab tiuxetan, CAM-H2-I131 (PrecirixNV), I131-ombrutamab, etc.).

[0142] In some embodiments, one or more of the additional therapeutic agents are hormone therapies. Hormone therapies act to modulate or inhibit the hormonal effects on the tumor. Examples of hormone therapies include, but are not limited to, selective estrogen receptor degraders, e.g., fulvestrant, giredestrant, SAR439859, RG6171, AZD9833, lintodestrant, ZN-c5, LSZ102, D-0502, LY3484356, SHR9549; selective estrogen receptor modulators, e.g., tamoxifen, raloxifen, 4-hydroxytamoxifen, trioxyfen, keoxyfen, toremifene; and aromatase inhibitors, e.g., A Other aromatases that inhibit nastrozole, exemestane, letrozole, and 4(5)-imidazole, gonadotropin-releasing hormone agonists, e.g., nafarelin, triptorelin, goserelin, gonadotropin-releasing hormone antagonists, e.g., degarelix, antiandrogens, e.g., abiraterone, enzalutamide, apalutamide, dalotamide, flutamide, nilutamide, bicalutamide, leuprolide, 5α-reductase inhibitors, e.g., finasteride, dutasteride. In certain embodiments, the combination therapy includes the administration of a hormone or related hormone. In one embodiment, the combination therapy includes the administration of enzalutamide.

[0143] In some embodiments, one or more of the additional therapeutic agents are epigenetic modulators. Epigenetic modulators alter the epigenetic mechanisms that control gene expression and may, for example, be inhibitors or activators of epigenetic enzymes. Non-limiting examples of epigenetic modulators include DNA methyltransferase (DNMT) inhibitors, hypomethylating agents, and histone deacetylase (HDAC) inhibitors. In one or more embodiments, an immune checkpoint inhibitor is combined with a DNMT inhibitor or hypomethylating agent. Exemplary DNMT inhibitors include decitabine, zebralin, and azacitadine. In one or more embodiments, a combination of CPI and an HDAC inhibitor is also considered. Exemplary HDAC inhibitors include vorinostat, gibinostat, avexinostat, panobinostat, bellinostat, and trichostatin A.

[0144] In some embodiments, one or more of the additional therapeutic agents are ATP-adenosine axis targeters. ATP-adenosine axis targeters alter adenine nucleoside and nucleotide (e.g., adenosine, AMP, ADP, ATP)-mediated signaling, for example, by modulating adenosine levels or targeting adenosine receptors. In some embodiments, ATP-adenosine axis targeters are inhibitors of ectonucleotidases involved in the conversion of ATP to adenosine or antagonists of adenosine receptors (e.g., CD39 or CD73). Exemplary small molecule CD73 inhibitors include CB-708, ORIC-533, LY3475070, and quemrecrustat. Examples of anti-CD39 and anti-CD73 antibodies include ES002023, TTX-030, IPH-5201, SRF-617, CPI-006, oleculumab, NZV930, IPH5301, GS-1423, uriredlimab, AB598, and BMS-986179. In some embodiments, the ATP-adenosine axis targeting factor is A 2aR Antagonist, A 2b R antagonist, or A 2a R and A 2b It is an antagonist of R. Examples of adenosine receptor inhibitors include etramadenante, inuadenant, taminadenante, caffeine citrate, NUV-1182, TT-702, DZD-2269, INCB-106385, EVOEXS-21546, AZD-4635, imaradenant, RVU-330, sifoadenante, PBF-509, PBF-999, PBF-1129, and CS-3005. In some embodiments, this disclosure intends to combine the CPIs described herein with etramadenante, quemrecrustat, AB598, or a combination thereof.

[0145] In some embodiments, one or more of the additional therapeutic agents are targeted therapies. In one embodiment, the targeted therapy may include a targeting agent and a drug. The drug may be a chemotherapeutic agent, a radionuclide, a hormone therapy, or another small molecule drug conjugated to the targeting agent. The targeting agent may be a small molecule, a sugar (including oligosaccharides and polysaccharides), an antibody, a lipid, a protein, a peptide, a non-natural polymer, or an aptamer. In some embodiments, the targeting agent is a sugar (including oligosaccharides and polysaccharides), a lipid, a protein, or a peptide, and the target is a tumor-associated antigen (enriched but not specific to cancer cells), a tumor-specific antigen (minimally expressed or absent in normal tissue), or a neoantigen (an antigen specific to the cancer cell genome, generated by non-synonymous mutations in the tumor cell genome). In some embodiments, the targeting agent is an antibody, and the target is a tumor-associated antigen, a tumor-specific antigen, or a neoantigen. In some embodiments, the targeted therapy is an antibody-drug conjugate comprising an antibody and a drug, wherein the antibody specifically binds to HER2, HER3, nectin-4, or Trop-2. Specific examples of targeted therapies comprising antibodies and drugs include, but are not limited to, patritumab deruxtecan, sacituzumab govitecan-hziy, terisotuzumab vedotin, and trastuzumab deruxtecan. In other embodiments, the targeted therapy may inhibit or interfere with specific proteins that aid in tumor growth and / or spread. Non-exclusive examples of such targeted therapies include signaling inhibitors, RAS signaling inhibitors, oncogenic transcription factor inhibitors, oncogenic transcription factor repressor activators, angiogenesis inhibitors, immunotherapies, ATP-adenosine axis targeting agents, AXL inhibitors, PARP inhibitors, PAK4 inhibitors, PI3K inhibitors, HIF-2α inhibitors, CD39 inhibitors, CD73 inhibitors, A2R antagonists, TIGIT antagonists, and PD-(L)1 antagonists.

[0146] In some embodiments, one or more of the additional therapeutic agents are signal transduction inhibitors. Signal transduction inhibitors are agents that selectively inhibit one or more steps in a signaling pathway. Signal transduction inhibitors (STIs) intended by this disclosure include, but are not limited to, (i) BCR-ABL kinase inhibitors (e.g., imatinib), (ii) small molecule inhibitors (e.g., CLN-081, gefitinib, erlotinib, afatinib, icotinib, and osimertinib), and epidermal growth factor receptor tyrosine kinase inhibitors (EGFRs), including anti-EGFR antibodies. (iii) Inhibitors of the human epidermal growth factor (HER) family of transmembrane tyrosine kinases, e.g., HER-2 / neu receptor inhibitors (e.g., trastuzumab) and HER-3 receptor inhibitors, (iv) Small molecule inhibitors (e.g., axitinib, regorafenib, sunitinib, and sorafenib), VEGF kinase inhibitors (e.g., lenvatinib, cabozantinib, pazopanib, tivozanib, XL092, etc.), anti-VEGF antibodies (e.g., bevacizumab), and anti-VEGFR antibodies (e.g., ramucirumab), including vascular endothelial growth factor receptor inhibitors. (v) inhibitors of receptor (VEGFR), inhibitors of AKT family kinases or the AKT pathway (e.g., rapamycin), (vi) inhibitors of mTOR such as everolimus, sirolimus, and temsirolimus, (vii) inhibitors of serine / threonine-protein kinase B-Raf (BRAF) such as vemurafenib, dabrafenib, and encorafenib, (viii) inhibitors of rearrangement (RET) during transfection, including serpacatinib and pralcetonib, (ix) inhibitors of tyrosine-protein kinase Met (MET) (e.g., tepotinib, tivantinib, cabozantinib, and crizotinib), (x) anaplastic lymphoma kinase(xii) inhibitors of the kinase (ALK) (e.g., ensartinib, ceritinib, loratinib, crizotinib, and brigatinib), (xiii) inhibitors of the RAS signaling pathway as described elsewhere herein (e.g., inhibitors of KRAS, HRAS, RAF, MEK, and ERK), (xii) FLT-3 inhibitors (e.g., gilteritinib), (xiii) inhibitors of Trop-2, (xiv) inhibitors of the JAK / STAT pathway, e.g., JAK inhibitors including tofacitinib and ruxolitinib, or STAT inhibitors such as napabucasin, (xv) inhibitors of NF-κB, (xvi) inhibitors of cell cycle kinases (e.g., flavopyridol), (xvii) inhibitors of phosphatidylinositol kinase (PI3K), (xiii) inhibitors of protein kinase B (AKT) (e.g., capivacertib, mirancertib), (xx) platelet-derived growth factor receptor (PAT) Examples include (xix) insulin-like growth factor receptor (IGFR) inhibitors (e.g., imatinib, sunitinib, regorafenib, avapritinib, lenvatinib, nintedanib, famitinib, ponatinib, axitinib, lepretinib, etc.), (xix) insulin-like growth factor receptor (IGFR) inhibitors (e.g., erlotinib, afatinib, gefitinib, osimertinib, dacomitinib), (xx) fibroblast growth factor receptor (FGFR) inhibitors (e.g., futivatinib, erdafitinib, pemigatinib), and (xxi) receptor tyrosine kinase KIT inhibitors (e.g., imatinib, sorafenib, sunitinib, masitinib, lepretinib, avapritinib). In one or more embodiments, the additional therapeutic agent includes an inhibitor of EGFR, VEGFR, HER-2, HER-3, BRAF, RET, MET, ALK, RAS (e.g., KRAS, MEK, ERK), FLT-3, JAK, STAT, NF-κB, PI3K, AKT, FGFR, KIT, or any combination thereof.

[0147] In some embodiments, one or more of the additional therapeutic agents are RAS signaling inhibitors. Oncogenic mutations in RAS family genes, e.g., HRAS, KRAS, and NRAS, are associated with various cancers. For example, mutations in KRAS family genes, particularly G12C, G12D, G12V, G12A, G13D, Q61H, G13C, and G12S, have been observed in multiple tumor types. Direct and indirect inhibitory strategies have been investigated for inhibiting mutant RAS signaling. Indirect inhibitors target non-RAS effectors in the RAS signaling pathway and include, but are not limited to, inhibitors of RAF, MEK, ERK, PI3K, PTEN, SOS (e.g., SOS1), mTORC1, SHP2 (PTPN11), and AKT. Non-exclusive examples of indirect inhibitors under development include RMC-4630, RMC-5845, RMC-6291, RMC-6236, JAB-3068, JAB-3312, TNO155, RLY-1971, and BI1701963. Direct inhibitors of RAS variants are also being explored, generally targeting the KRAS-GTP or KRAS-GDP complex. Exemplary direct RAS inhibitors under development include, but are not limited to, sotrasib, adagrasib, mRNA-5671, and ARS1620. In some embodiments, one or more RAS signaling inhibitors are selected from the group consisting of RAF inhibitors, MEK inhibitors, ERK inhibitors, PI3K inhibitors, PTEN inhibitors, SOS1 inhibitors, mTORC1 inhibitors, SHP2 inhibitors, and AKT inhibitors. In other embodiments, one or more RAS signaling inhibitors directly inhibit RAS variants.

[0148] In some embodiments, one or more of the additional therapeutic agents are VEGF inhibitors or VEGFR inhibitors. In some embodiments, the VEGF or VEGFR inhibitor is a small molecule VEGFR inhibitor, a small molecule VEGF kinase inhibitor, an anti-VEGF antibody, or an anti-VEGFR antibody. In some embodiments, this disclosure intends to combine the CPI described herein with axitinib, bevacizumab, cabozantinib, lenvatinib, pazopanib, ramucirumab, regorafenib, sunitinib, sorafenib, tivozanib, or XL092. In some embodiments, this disclosure intends to combine the CPI described herein with axitinib, cabozantinib, lenvatinib, pazopanib, regorafenib, sunitinib, sorafenib, tivozanib, or XL092.

[0149] In some embodiments, one or more of the additional therapeutic agents are inhibitors of hypoxia-inducible factor (HIF) transcription factors, particularly HIF-2α. Exemplary HIF-2α inhibitors include berzutifan, ARO-HIF2, PT-2385, and those described in International Publications 2021113436, 2021188769, and 2023077046. In some embodiments, this disclosure intends to use the combination of CPI and AB521 as described herein.

[0150] In some embodiments, one or more of the additional therapeutic agents are inhibitors of Anexeselect (AXL). Exemplary multikinase AXL inhibitors include citravatinib, levastinib, gresatinib, gilteritinib, meresteinib, cabozantinib, foretinib, BMS777607, LY2801653, S49076, and RXDX-106. AXL-specific inhibitors have also been developed, including small molecule inhibitors such as DS-1205, SGI-7079, SLC-391, duvermatinib, vemcentinib, AB801, and DP3975; anti-AXL antibodies, e.g., ADCT-601; and antibody-drug conjugates (ADCs), e.g., BA3011. Another strategy for inhibiting AXL signaling involves targeting GAS6, a ligand for AXL. For example, batilactept is being developed as an Fc fusion protein that binds to a GAS6 ligand and thereby inhibits AXL signaling. In some embodiments, CPI is combined with one or more AXL inhibitors described in International Publication No. 2022246177 or 2022246179. In some embodiments, the AXL inhibitor is AB801.

[0151] In some embodiments, one or more of the additional therapeutic agents are immunotherapeutic agents. Immunotherapeutic agents treat diseases by stimulating or suppressing the immune system. Immunotherapeutic agents useful in treating cancer typically induce or amplify an immune response against cancer cells. Non-limiting examples of suitable immunotherapeutic agents include immune modulators (e.g., cytokines, chemokines, etc.); cellular immunotherapies (e.g., CAR-T cell therapy, CAR-NK cell therapy, TCR therapy, dendritic cell vaccines, etc.); vaccines; gene therapies; ATP-adenosine axis targeting agents; immune checkpoint modulators; and certain signaling inhibitors.

[0152] In some embodiments, one or more of the additional therapeutic agents are immune checkpoint inhibitors. Preferred immune checkpoint inhibitors are listed above.

[0153] In some embodiments, one or more of the additional therapeutic agents activate stimulative or co-stimulative immune checkpoints. Examples of stimulative or co-stimulative immune checkpoints (ligands and receptors) include B7-1, B7-2, CD28, 4-1BB (CD137), 4-1BBL, ICOS, ICOS-L, OX40, OX40L, GITR, GITRL, CD70, CD27, CD40, DR3, and CD2.

[0154] In some embodiments, one or more of the additional therapeutic agents are immunotherapeutic agents, more specifically intracellular signaling molecules that affect the function of immune cells. For example, one or more of the additional therapies may be inhibitors of hematopoietic progenitor kinase 1 (HPK1), a serine / threonine kinase that acts as a negative regulator of the activation signal produced by the T cell antigen receptor. Another example is that one or more of the additional therapies may be inhibitors of Cbl-b, an E3 ubiquitin ligase involved in the modulation of TCR signaling. Yet another example is that one or more of the additional therapies may be inhibitors of diacylglycerol kinase (DGK). In some embodiments, the inhibitors are small molecules. Non-exclusive examples of small molecule HPK1 inhibitors in clinical development include NDI-101150, PRJ1-3024, PF-07265028, GRC 54276, CFI-402411, and BGB-15025. Non-exclusive examples of Cbl-b inhibitors in clinical development include AP401, HST-1011, and NX-1607. Non-exclusive examples of small molecule DAG inhibitors include ASP1570 and BAY2965501.

[0155] In some embodiments, each additional therapy can independently be chemotherapy, radiopharmaceuticals, hormone therapy, epigenetic modulators, targeting agents, immunotherapeutic agents, cell therapy, or gene therapy. For example, in one embodiment, the Disclosure intends to use a CPI (e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a PD-(L)1 antagonist and a TIGIT antagonist) in combination with chemotherapy and optionally one or more additional therapeutic agents, where each additional therapeutic agent is independently a radiopharmaceutical, hormone therapy, targeting agent, immunotherapeutic agent, cell therapy, or gene therapy. In another embodiment, the Disclosure intends to use a CPI (e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a PD-(L)1 antagonist and a TIGIT antagonist) in combination with chemotherapy and optionally one or more additional therapeutic agents, where each additional therapeutic agent is independently a targeting agent, an immunotherapeutic agent, or cell therapy. In another embodiment, the disclosure envisions the use of a CPI (e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a PD-(L)1 antagonist and a TIGIT antagonist) in combination with one or more immunotherapeutic agents and optionally one or more additional therapeutic agents or therapies, where each additional therapeutic agent is independently a radiopharmaceutical, hormone therapy, targeted agent, chemotherapy, cell therapy, or gene therapy. In another embodiment, the disclosure envisions the use of a CPI (e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a PD-(L)1 antagonist and a TIGIT antagonist) in combination with one or more immunotherapeutic agents and optionally one or more additional therapies, where each additional therapy is independently chemotherapy, targeted agent, or cell therapy. In another embodiment, the Disclosure envisions the use of a CPI (e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a PD-(L)1 antagonist and a TIGIT antagonist) in combination with one or more immune checkpoint inhibitors and / or one or more ATP-adenosine axis targeting agents, and optionally one or more additional therapies, where each additional therapeutic agent is independently a chemotherapy agent, a targeting agent, an immunotherapy agent, or a cell therapy.In the further embodiments described above, (a) the targeting agent is a VEGF or VEGFR inhibitor (e.g., axitinib, bevacizumab, cabozantinib, lenvatinib, pazopanib, ramucirumab, regorafenib, sunitinib, sorafenib, tivozanib, or XL092), a PI3K inhibitor, an arginase inhibitor, a HIF2α inhibitor, an AXL inhibitor, or a PAK4 inhibitor; (b) the immunotherapy agent is an ATP-adenosine axis targeting agent or an immune checkpoint inhibitor; and (c) the ATP-adenosine axis targeting agent is A. 2a R and / or A 2b(d) The ATP-adenosine axis targeting agent is an R antagonist, CD73 inhibitor, or CD39 inhibitor; (e) The chemotherapeutic agent is an immune checkpoint inhibitor, optionally an anti-TIGIT antagonist antibody, optionally an Fc silent antibody, optionally domvanarimab; (f) The chemotherapy is platinum-containing chemotherapy, platinum doublets, platinum and fluoropyrimidine-based chemotherapy, pemetrexed and platinum chemotherapy, taxane or taxane-containing chemotherapy, topoisomerase inhibitors (e.g., irinotecan, SN-38, doxorubicin, etc.), carboplatin and either paclitaxel or protein-bound paclitaxel, FOLFOX, FOLFIRI, or CAPOX; or (g) any combination thereof. In the further embodiments described above, the disclosure intends to describe the use of a CPI (e.g., a PD-(L)1 antagonist) in combination with an anti-TIGIT antibody (e.g., an Fc-silent anti-TIGIT antibody, optionally, domvanalimab, etc.). In the further embodiments described above, the disclosure intends to describe the use of a CPI (e.g., a PD-(L)1 antagonist) in combination with an anti-TIGIT antibody (e.g., domvanalimab, etc.) and chemotherapy. In the further embodiments described above, the disclosure intends to describe the use of a CPI (e.g., a PD-(L)1 antagonist) in combination with an anti-TIGIT antibody (e.g., an Fc-silent anti-TIGIT antibody, optionally, domvanalimab, etc.) and a VEGF or VEGFR inhibitor. In further embodiments described above, the disclosure intends to describe the use of a CPI (e.g., a PD-(L)1 antagonist) in combination with dombanalimab, etrumadenant, quemriculstat, AB308, AB521, AB801, or any combination thereof. In some embodiments, the PD-(L)1 antagonist is atezolizumab, avelumab, semiprimab, dostallimab, durvalumab, nivolumab, pembrolizumab, retifanlimab, tislerizumab, tripalimab, or zimbererimab. In certain embodiments, the PD-(L)1 antagonist is zimbererimab. Patient identification method for treatment

[0156] In one embodiment, the present disclosure provides a method for identifying a patient for treatment with a therapy, such as a therapy comprising an immune checkpoint inhibitor. In some embodiments, a method is provided for identifying a candidate suitable for a particular therapy described herein. In some embodiments, a method is provided for selecting a patient for a particular therapy described herein. In some embodiments, the patient is a patient with cancer, such as a solid tumor. Biomarkers of the following embodiments are further described elsewhere in this specification, and their disclosures are incorporated by reference in this section. Suitable samples are also described elsewhere in this specification, and are incorporated by reference in this section.

[0157] In one embodiment, the present disclosure provides a biomarker useful for identifying a patient for treatment with a therapy (e.g., an immune checkpoint inhibitor, e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a therapy comprising a PD-(L)1 antagonist and a TIGIT antagonist). In some embodiments, the biomarker is selected from PD-L1 (PD-L1 expression level), CD155 (CD155 expression level), CD226 (CD226 expression level), CD73 (CD73 expression level), adenosine pathway biomarkers, and any combination thereof. In some embodiments, the adenosine pathway biomarker is CD73 (CD73 expression level). Patients may be identified for treatment with an immune checkpoint inhibitor if the sample obtained from the patient contains (a) a PD-L1 expression level above or below the PD-L1 reference level, (b) a CD155 expression level above or below the CD155 reference level, (c) a CD226 expression level above or below the CD226 reference level, (d) an adenosine pathway biomarker expression level above or below the adenosine pathway biomarker reference level, (e) a CD73 expression level above or below the CD73 reference level, or (f) any combination of (a) to (e). In other words, the sample is obtained and determined to contain (a) to (f) by the method described herein. In some embodiments, a patient is identified for treatment with a therapy including an immune checkpoint inhibitor if (a) the PD-L1 expression level is equal to or greater than the PD-L1 reference level, (b) the CD155 expression level is lower than the CD155 reference level, (c) the CD226 expression level is equal to or greater than the CD226 reference level, (d) the adenosine pathway biomarker expression level is lower than the adenosine pathway biomarker reference level, (e) the CD73 expression level is lower than the reference level, or (f) any combination of (a) to (e).The sample may be a sample containing tumor cells, a sample containing immune cells (e.g., lymphocytes, monocytes, myeloid cells, dendritic cells, plasma cells, or a combination thereof), or a sample containing both tumor cells and immune cells. The sample may also further contain one or more additional cell types in the tumor microenvironment, e.g., another cell type.

[0158] In some embodiments, the therapy identified for a patient's treatment is a monotherapy. The monotherapy may include, but is not limited to, an anti-PD-L1 antagonist or an anti-PD-1 antagonist (referred to herein as “anti-PD-(L)1 antagonist”). The monotherapy may also include, but is not limited to, an anti-PD-L1 antibody or an anti-PD-1 antibody (referred to herein as “anti-PD-(L)1 antibody”). In some embodiments, treatment with anti-PD-(L)1 as a monotherapy may be indicated when the CD155 expression level is lower than the CD155 reference level and / or the CD73 expression level is greater than or equal to the CD73 reference level.

[0159] In some embodiments, the therapy identified for treatment of a patient is the combination therapy described herein. In some embodiments, the combination therapy comprises at least two therapies (i.e., 2, 3, 4, 5, or more therapies). In some embodiments, the combination therapy comprises at least three therapies (i.e., 3, 4, 5, 6, or more therapies). In some embodiments, the combination may include an anti-PD-1 antibody. In some embodiments, the combination may include an anti-PD-L1 antibody. In some embodiments, the combination may include an anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-1 antibody and an anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-L1 antibody and an anti-TIGIT antibody. In embodiments including an anti-TIGIT antibody, the anti-TIGIT antibody may be an Fc silent anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-(L)1 antibody and one or more additional therapies, but the combination may not include an anti-TIGIT antibody. Treatment with combination therapy including an anti-TIGIT antibody may provide greater clinical benefit when CD73 expression levels are below the CD73 reference level and / or CD155 expression levels are above the CD155 reference level, while treatment with combination therapy that does not include an anti-TIGIT antibody but includes a different CPI (e.g., an anti-PD-(L)1 antibody) may provide greater clinical benefit when CD73 expression levels are above the CD73 reference level and / or CD155 expression levels are below the CD155 reference level.

[0160] In some embodiments, the combination may include an ATP-adenosine axis targeting agent. In some embodiments, the combination may not include an ATP-adenosine axis targeting agent. In some embodiments, the combination may include an antagonist anti-PD-1 antibody, an antagonist anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the combination may include an antagonist anti-PD-L1 antibody, an antagonist anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the ATP-adenosine axis targeting agent is an adenosine receptor antagonist. In some embodiments, the ATP-adenosine axis targeting agent is A 2a R and / or A 2b The R antagonist, CD73 inhibitor, or CD39 inhibitor is used. In some embodiments, the ATP-adenosine axis targeting agent is A 2a R and / or A 2b He is an R antagonist.

[0161] In some embodiments, the combination therapy includes chemotherapy, such as a chemotherapeutic agent or chemotherapy regimen described herein. In some embodiments, the chemotherapy includes a platinum-containing agent. In some embodiments, the combination therapy includes a VEGF or VEGFR inhibitor. In some embodiments, the combination therapy includes one or more additional therapies described elsewhere in this specification.

[0162] In some embodiments, the patient identified for the therapy described herein has cancer, including solid tumors. In some embodiments, the patient has solid tumors selected from the group consisting of ovarian cancer, endometrial cancer, breast cancer, lung cancer, colon cancer, prostate cancer, cervical cancer, bile duct cancer, pancreatic cancer, stomach cancer, esophageal cancer, liver cancer, kidney cancer, head and neck tumors, mesothelioma, melanoma, sarcoma, central nervous system (CNS) hemangioblastoma, and brain tumors. In some embodiments, the patient has cancer selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, and lung cancer. In some embodiments, the patient has lung cancer, including, but not limited to, squamous cell lung cancer or non-squamous cell lung cancer (NSCLC). In some embodiments, the patient has upper gastrointestinal (GI) cancer, including, but not limited to, stomach cancer, gastroesophageal junction (GEJ) cancer, or esophageal adenocarcinoma (EAC). The cancer may be an early stage cancer (e.g., stage I or stage II). The cancer may be locally advanced and unresectable. The cancer may be recurrent or metastatic.

[0163] In some embodiments, the biomarker expression level in a sample is determined by immunohistochemistry (IHC). The expression level can be measured or determined based on the IHC staining intensity and / or the percentage of stain-positive cells (e.g., tumor cells and / or immune cells and / or stromal cells or other cells in the tumor microenvironment). In some embodiments, the reference level is determined by IHC. In some embodiments, the IHC staining intensity and / or the percentage of stain-positive cells is determined based on cytoplasmic staining, membrane staining, or both cytoplasmic and membrane staining. Methods for determining the level of a biomarker in a sample using IHC are known in the art and are further described herein.

[0164] In some embodiments, the reference level is the median expression level derived from samples obtained from a control group known to have the same disease, or an amount approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median expression level. For example, in some embodiments, the PD-L1 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level derived from samples obtained from a patient group known to have the same disease. In some embodiments, the CD155 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level derived from samples obtained from patients in a patient group known to have the same disease. In some embodiments, the CD226 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the adenosine pathway biomarker reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level derived from samples obtained from a control group known to have the same disease. In some embodiments, the CD73 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease.

[0165] In some embodiments, the patient has a sample obtained from the patient in which (a) the PD-L1 expression level is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level, or (b) the CD155 expression level is greater than or equal to the CD155 expression level derived from samples obtained from a group of patients known to have the same disease. (c) CD155 expression levels are above the median level, or are 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median level of CD155 expression levels; (c) CD226 expression levels are above the median level of CD226 expression levels derived from samples obtained from a group of patients known to have the same disease, or are 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above the median level of CD226 expression levels. (d) The adenosine pathway biomarker expression level is lower than the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease, or is lower than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level, or (e) The CD73 expression level is in a group of patients known to have the same disease. If the CD73 expression level derived from the samples obtained from the group is lower than the median CD73 expression level, or lower than 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level, or in any combination of (f)(a) to (e), then it is identified for treatment with a therapy including an immune checkpoint inhibitor (e.g., a TIGIT antagonist, or a TIGIT antagonist in combination with a PD-(L)1 antagonist).

[0166] In some embodiments, the patient has a sample obtained from the patient in which (a) the PD-L1 expression level is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level; (b) the CD155 expression level is greater than or equal to the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level; or (c) the CD226 expression level is obtained from a sample obtained from a group of patients known to have the same disease. (d) The CD226 expression level derived from the sample is greater than or equal to the median CD226 expression level, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD226 expression level; (d) The CD73 expression level is lower than the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease, or less than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level; or (e) In any combination of (a) to (d), the patient is identified for treatment with a therapy including an immune checkpoint inhibitor (e.g., a TIGIT antagonist, or a TIGIT antagonist in combination with a PD-(L)1 antagonist).

[0167] In some embodiments, the patient has either (a) high PD-L1 levels (e.g., 50% or more TC in the case of NSCLC, or 5% or more TAP in the case of EAC, GEJ, gastric cancer, or other cancers) or PD-L1 positivity (e.g., 1% or more TC in the case of NSCLC, or 1% or more TAP in the case of EAC, GEJ, gastric cancer, or other cancers), (b) CD155 expression levels that are above the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or above or below 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level, or (c) CD226 expression levels obtained from a group of patients known to have the same disease. (d) The CD226 expression level derived from the sample is greater than or equal to the median CD226 expression level, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD226 expression level, or (d) the CD73 expression level is lower than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level, or (e) any combination of (a) to (d) is identified for treatment with a therapy comprising an immune checkpoint inhibitor (e.g., a TIGIT antagonist, or a TIGIT antagonist in combination with a PD-(L)1 antagonist). In some embodiments, the therapy comprises an anti-TIGIT antibody. In some embodiments, the therapy comprises an anti-PD(L)1 antibody and an anti-TIGIT antibody. In some embodiments, the anti-TIGIT antibody is an Fc silent anti-TIGIT antibody.

[0168] In some embodiments, expression levels can be represented in a number of ways, including, but not limited to, the percentage of biomarker-positive tumor cells ("TC%"), the percentage of biomarker-positive tumor cells stained at a moderate or high intensity ("2+ or 3+TC%"), the percentage of biomarker-positive immune cells ("IC%"), characterization by tumor H score, and characterization of expression relative to tumor area (e.g., the number of biomarker-positive tumor cells showing positive staining at any intensity and / or the number of biomarker-positive tumor-associated immune cells showing positive staining at any intensity relative to tumor area), as described elsewhere in this specification. Treatment method

[0169] This disclosure provides a method for treating a disease (e.g., cancer) in a patient known to have the disease, the method comprising administering an effective dose of therapy to the patient when it is determined that the patient has a specific expression pattern of one or more biomarkers. The biomarkers of the following embodiments are further described elsewhere in this specification, and their disclosures are incorporated by reference in this section. Preferred samples are also described elsewhere in this specification, and are incorporated by reference in this section.

[0170] In one embodiment, the present disclosure provides a method for treating a patient with an effective dose of therapy (e.g., an immune checkpoint inhibitor, e.g., a PD-(L)1 antagonist, a TIGIT antagonist, or a therapy comprising a PD-(L)1 antagonist and a TIGIT antagonist). In some embodiments, the therapy is administered to a patient if a sample obtained from the patient contains a specific expression pattern of one or more biomarkers described herein. In some embodiments, the biomarkers are selected from PD-L1 (PD-L1 expression level), CD155 (CD155 expression level), CD226 (CD226 expression level), an adenosine pathway biomarker, CD73 (CD73 expression level), and any combination thereof. In some embodiments, the adenosine pathway biomarker is CD73 (CD73 expression level). Patients may be treated with a therapy comprising an immune checkpoint inhibitor as described herein if the sample obtained from the patient contains (a) a PD-L1 expression level above or below the PD-L1 reference level, (b) a CD155 expression level above or below the CD155 reference level, (c) a CD226 expression level above or below the CD226 reference level, (d) an adenosine pathway biomarker expression level above or below the adenosine pathway biomarker reference level, (e) a CD73 expression level above or below the CD73 reference level, or (f) any combination of (a) to (e). In other words, the sample is obtained and determined to contain (a) to (f) by the method described herein. In some embodiments, a patient is identified for treatment with a therapy including an immune checkpoint inhibitor if (a) the PD-L1 expression level is equal to or greater than the PD-L1 reference level, (b) the CD155 expression level is lower than the CD155 reference level, (c) the CD226 expression level is equal to or greater than the CD226 reference level, (d) the adenosine pathway biomarker expression level is lower than the adenosine pathway biomarker reference level, (e) the CD73 expression level is lower than the CD73 reference level, or (f) any combination of (a) to (e).In some embodiments, a patient is identified for treatment with a therapy including an immune checkpoint inhibitor (e.g., a TIGIT antagonist, or a TIGIT antagonist in combination with a PD-(L)1 antagonist) if their CD155 expression level is ≥ the CD155 reference level and optionally, (a) their PD-L1 expression level is ≥ the PD-L1 reference level, (b) their CD226 expression level is ≥ the CD226 reference level, (c) their adenosine pathway biomarker expression level is below the adenosine pathway biomarker reference level, (d) their CD73 expression level is below the CD73 reference level, or (f) any combination of (a) to (d). The sample may be a sample containing tumor cells, a sample containing immune cells (e.g., lymphocytes, monocytes, myeloid cells, dendritic cells, plasma cells, or any combination thereof), or a sample containing both tumor cells and immune cells.

[0171] In some embodiments, the therapy administered to the patient is monotherapy. Monotherapy may include, but is not limited to, an anti-PD-L1 antagonist or an anti-PD-1 antagonist. Monotherapy may include, but is not limited to, an anti-PD-L1 antibody or an anti-PD-1 antibody. In some embodiments, treatment with anti-PD-(L)1 as monotherapy may be indicated when the CD155 expression level is lower than the CD155 reference level and / or the CD73 expression level is greater than or equal to the CD73 reference level.

[0172] In some embodiments, the therapy administered to the patient is the combination therapy described herein. In some embodiments, the combination therapy comprises at least two therapies (i.e., 2, 3, 4, 5, or more therapies). In some embodiments, the combination therapy comprises at least three therapies (i.e., 3, 4, 5, 6, or more therapies). In some embodiments, the combination may include an anti-PD-1 antibody. In some embodiments, the combination may include an anti-PD-L1 antibody. In some embodiments, the combination may include an anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-1 antibody and an anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-L1 antibody and an anti-TIGIT antibody. In embodiments including an anti-TIGIT antibody, the anti-TIGIT antibody may be an Fc-silent anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-(L)1 antibody and one or more additional therapies, but the combination may not include an anti-TIGIT antibody. Treatment with combination therapy including an anti-TIGIT antibody may provide greater clinical benefit when CD73 expression levels are below the CD73 reference level and / or CD155 expression levels are above the CD155 reference level, while treatment with combination therapy that does not include an anti-TIGIT antibody but includes a different CPI (e.g., an anti-PD-(L)1 antibody) may provide greater clinical benefit when CD73 expression levels are above the CD73 reference level and / or CD155 expression levels are below the CD155 reference level.

[0173] In some embodiments, the combination can include an ATP-adenosine axis targeting agent. In some embodiments, the combination can include an anti-PD-1 antibody, an anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the combination can include an anti-PD-L1 antibody, an anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the combination can include an anti-PD-(L)1 antibody, an anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the ATP-adenosine axis targeting agent is an adenosine receptor antagonist. In some embodiments, the ATP-adenosine axis targeting agent is 2a an AR and / or 2b an AR antagonist, a CD73 inhibitor, or a CD39 inhibitor. In some embodiments, the ATP-adenosine axis targeting agent is 2a an AR and / or 2b an AR antagonist.

[0174] In some embodiments, the combination therapy includes chemotherapy such as a chemotherapeutic agent or chemotherapeutic regimen described herein. In some embodiments, the chemotherapy includes a platinum-containing agent. In some embodiments, the combination therapy includes a VEGF or VEGFR inhibitor. In some embodiments, the combination therapy includes one or more additional therapies described elsewhere herein.

[0175] In some embodiments, the patient to whom the therapies described herein are administered has cancer, including solid tumors. In some embodiments, the patient has a solid tumor selected from the group consisting of ovarian cancer, endometrial cancer, breast cancer, lung cancer, colon cancer, prostate cancer, cervical cancer, bile duct cancer, pancreatic cancer, gastric cancer, esophageal cancer, liver cancer, kidney cancer, head and neck tumors, mesothelioma, melanoma, sarcoma, central nervous system (CNS) hemangioblastoma, and brain tumors. In some embodiments, the patient has cancer selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, and lung cancer. In some embodiments, the patient has lung cancer, including but not limited to squamous cell lung cancer or non-squamous cell lung cancer (NSCLC). In some embodiments, the patient has upper gastrointestinal (GI) cancer, including but not limited to gastric cancer, gastroesophageal junction (GEJ) cancer, or esophageal adenocarcinoma (EAC). The cancer can be locally advanced unresectable cancer. The cancer can be recurrent or metastatic cancer.

[0176] In some embodiments, the biomarker expression level in a sample is determined by immunohistochemistry (IHC). The expression level can be measured or determined based on the IHC staining intensity and / or the percentage of stained positive cells (e.g., cells and / or immune cells). In some embodiments, the reference level is determined by IHC. In some embodiments, the IHC staining intensity and / or the percentage of stained positive cells is determined based on cytoplasmic staining, membrane staining, or both cytoplasmic and membrane staining. Methods for determining the level of a biomarker in a sample using IHC are known in the art and are further described herein.

[0177] In some embodiments, the reference level is the median expression level derived from samples obtained from a group of patients known to have the same disease, or an amount that is approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median expression level. For example, in some embodiments, the PD-L1 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the CD155 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the CD226 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the adenosine pathway biomarker reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the CD73 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease.

[0178] In some embodiments, the patient has a sample obtained from the patient in which (a) the PD-L1 expression level is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level, or (b) the CD155 expression level is obtained from a sample obtained from a group of patients known to have the same disease. (c) CD226 expression levels are greater than or equal to the median CD155 expression level, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level, or (c) CD226 expression levels are greater than or equal to the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above the median CD226 expression level. (d) The adenosine pathway biomarker expression level is lower than the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease, or is lower than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level, or the ICD73 expression level is lower than or equal to the amount obtained from samples obtained from a group of patients known to have the same disease. If the CD73 expression level derived from samples obtained from the patient group is lower than the median CD73 expression level, or lower than 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level, or any combination of (f)(a)I(e), then the patient is administered a therapy including an immune checkpoint inhibitor (e.g., a TIGIT antagonist, or a TIGIT antagonist in combination with a PD-(L)1 antagonist).

[0179] In some embodiments, the patient has a sample obtained from the patient in which (a) the PD-L1 expression level is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level; (b) the CD155 expression level is greater than or equal to the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level; or (c) the CD226 expression level is obtained from a group of patients known to have the same disease (d) If the CD226 expression level derived from the obtained sample is above the median CD226 expression level, or is above or below 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD226 expression level, or (e) if the CD73 expression level is below the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease, or is below 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level, or (e) if any combination of (a) to (d) is found, the patient is administered a therapy including an immune checkpoint inhibitor (e.g., a TIGIT antagonist, or a TIGIT antagonist in combination with a PD-(L)1 antagonist).

[0180] In some embodiments, expression levels can be represented in a number of ways, including, but not limited to, the percentage of biomarker-positive tumor cells ("TC%"), the percentage of biomarker-positive tumor cells stained at a moderate or high intensity ("2+ or 3+TC%"), the percentage of biomarker-positive immune cells ("IC%"), characterization by tumor H score, and characterization of expression relative to tumor area (e.g., the number of biomarker-positive tumor cells showing positive staining at any intensity and / or the number of biomarker-positive tumor-associated immune cells showing positive staining at any intensity relative to tumor area), as described elsewhere in this specification.

[0181] In one embodiment, the present disclosure is a method for treating a disease (e.g., cancer) in a patient known to have said disease, comprising: (a) measuring the level of one or more of PD-L1, CD155, CD226, adenosine pathway biomarkers, and CD73 in a sample obtained from the patient; (b) comparing the level measured in (a) to the respective reference level; and (c) (i) whether the measured PD-L1 level is equal to or lower than the PD-L1 reference level, and / or (ii) whether the measured CD155 level is equal to or higher than the CD155 reference level, or The present invention provides a method comprising administering an effective dose of a therapy including an immune checkpoint inhibitor to a patient if (iii) the measured CD226 level is lower than the CD155 reference level and / or (iv) the measured adenosine pathway biomarker level is higher than or equal to the adenosine pathway biomarker reference level and / or (v) the measured CD73 level is higher than or equal to the CD73 reference level and / or lower than the CD73 reference level. In some embodiments, a patient is administered an effective dose of therapy if (i) the measured PD-L1 level is greater than or equal to the PD-L1 reference level and / or (ii) the measured CD155 level is greater than or equal to the CD155 reference level and / or (iii) the measured CD226 level is greater than or equal to the CD226 reference level and / or (iv) the measured adenosine pathway biomarker level is lower than the adenosine pathway biomarker reference level and / or (v) the measured CD73 level is lower than the CD73 reference level. In some embodiments, the adenosine pathway biomarker is CD73 (CD73 expression level). In some of the aforementioned embodiments where the measured CD73 level is lower than the CD73 reference level, the therapy comprises a first immune checkpoint inhibitor that is not an anti-TIGIT antagonist and a second immune checkpoint inhibitor that is an anti-TIGIT antagonist.In further embodiments, the therapy comprises a PD-(L)1 antagonist, optionally an anti-PD-(L)1 antibody, and an anti-TIGIT antagonist, optionally an anti-TIGIT antibody. In some embodiments, the anti-TIGIT antagonist is an Fc silent anti-TIGIT antibody.

[0182] In one embodiment, the present disclosure provides a method for treating CD73 low cancer in a patient, comprising administering to the patient an effective dose of a therapy comprising an immune checkpoint inhibitor. In some embodiments, the therapy is a combination therapy comprising a first immune checkpoint inhibitor that is not an anti-TIGIT antagonist and a second immune checkpoint inhibitor that is an anti-TIGIT antagonist. In further embodiments, the combination comprises a PD-(L)1 antagonist, optionally an anti-PD-(L)1 antibody, and an anti-TIGIT antagonist, optionally an anti-TIGIT antibody. In some embodiments, the anti-TIGIT antagonist is an Fc silent anti-TIGIT antibody. In each of these embodiments, the combination therapy may further comprise one or more additional therapies. Preferred additional therapies are described elsewhere in this specification.

[0183] In some embodiments, CD73 low cancer is cancer in which the CD73 expression level is below a threshold, which is either the median CD73 expression level derived from samples obtained from a group of patients known to have the same cancer (e.g., NSCLC, gastric cancer, GEJ, EAC, etc.), or about 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level. In some embodiments, an effective dose of therapy is administered to a patient if the patient is determined to have CD73 low cancer. In other words, the sample is obtained from a patient and is determined to be CD73 via the method described herein. In some embodiments, the sample further includes (a) a PD-L1 expression level above the PD-L1 reference level, (b) a CD155 expression level above the CD155 reference level, (c) a CD226 expression level above the CD226 reference level, and (d) any combination of (a) to (c). In some embodiments, an effective dose of therapy is defined as a sample obtained from a patient having (a) a PD-L1 expression level that is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or a level that is 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level, or (b) a CD155 expression level that is greater than or equal to the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or a CD155 expression level (c) The amount is greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median of Bell's expression level, or (d) any combination of (a) to (c) is administered to patients with low CD73 cancer.

[0184] In one embodiment, the present disclosure provides a method for treating CD155 hypercancer in a patient, comprising administering to the patient an effective dose of a therapy comprising an immune checkpoint inhibitor. In some embodiments, the therapy is a combination therapy comprising a first immune checkpoint inhibitor that is not an anti-TIGIT antagonist and a second immune checkpoint inhibitor that is an anti-TIGIT antagonist. In further embodiments, the combination comprises a PD-(L)1 antagonist, optionally an anti-PD-(L)1 antibody, and an anti-TIGIT antagonist, optionally an anti-TIGIT antibody. In some embodiments, the anti-TIGIT antagonist is an Fc silent anti-TIGIT antibody. In each of these embodiments, the combination therapy may further comprise one or more additional therapies. Preferred additional therapies are described elsewhere in this specification.

[0185] In some embodiments, CD155-high cancer is cancer in which the CD155 expression level is above a threshold, which is either the median CD155 expression level derived from samples obtained from a group of patients known to have the same cancer (e.g., NSCLC, gastric cancer, GEJ, EAC, etc.) or about 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level. In some embodiments, an effective dose of therapy is administered to a patient when the patient is determined to have CD155-high cancer. In other words, the sample is obtained from a patient and is determined to be CD155-high via the method described herein. In some embodiments, the sample further includes (a) a PD-L1 expression level above the PD-L1 reference level, (b) a CD73 expression level below the CD155 reference level, (c) a CD226 expression level above the CD226 reference level, and (d) any combination of (a) to (c). In some embodiments, an effective dose of therapy is defined as a sample obtained from a patient having (a) a PD-L1 expression level greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or a level greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level, or (b) a CD73 expression level less than or equal to the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease, or a CD73 expression level (c) The amount is greater than or equal to 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median of (a) the CD226 expression level is greater than or equal to the median of CD226 expression level derived from samples obtained from a group known to have the same disease, or is greater than or equal to 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median of CD226 expression level, or (d) any combination of (a) to (c) is administered to patients with high CD155 levels.

[0186] In some embodiments, the CD155 expression level of a sample is characterized by the percentage of CD155-positive cells (TC%). When the CD155 expression level is characterized by CD155 TC%, the reference level may be the median CD155 TC% in a control group having the same disease (e.g., cancer), or may be a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median level. In various embodiments, the reference level may be 1% TC, 5% TC, 10% TC, 15% TC, 20% TC, 25% TC, 30% TC, 35% TC, 40% TC, 45% TC, 50% TC, 55% TC, 60% TC, 65% TC, 70% TC, 75% TC, 80% TC, 85% TC, or 90% TC.

[0187] In some embodiments, the CD155 expression level of a sample is characterized by CD155 2+ or 3+TC%. When the CD155 expression level is characterized by CD155 2+ or 3+TC%, the reference level may be the median CD155 2+ or 3+TC% in a control group having the same disease (e.g., cancer), or a value above or below the median. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median level. In some embodiments, the reference level may be 30% 2+ or 3+TC, 35% 2+ or 3+TC, 40% 2+ or 3+TC, 45% 2+ or 3+TC, 50% 2+ or 3+TC, 55% 2+ or 3+TC, 60% 2+ or 3+TC, or 65% 2+ or 3+TC. In some embodiments, the reference level may be 30% 2+ or 3+TC, 35% 2+ or 3+TC, 40% 2+ or 3+TC, 45% 2+ or 3+TC, or 50% 2+ or 3+TC. In some embodiments, the reference level may be 40% 2+ or 3+TC, 45% 2+ or 3+TC, 50% 2+ or 3+TC, 55% 2+ or 3+TC, or 60% 2+ or 3+TC. In some embodiments, the reference level may be 50% 2+ or 3+TC. In some embodiments, the reference level may be 7% 2+ or 3+TC, 8% 2+ or 3+TC, 9% 2+ or 3+TC, 10% 2+ or 3+TC, 11% 2+ or 3+TC, 12% 2+ or 3+TC, or 13% 2+ or 3+TC. In some embodiments, the reference level may be 40% 2+ or 3+TC. In some embodiments, the reference level may be 35% 2+ or 3+TC. In some embodiments, the reference level may be 45% 2+ or 3+TC.

[0188] In some embodiments, the CD155 expression level of a sample is characterized by a tumor H score. In some embodiments, the reference level may be ≤30%, ≤25%, ≤20%, ≤15%, ≤10%, or ≤5% above or below the median. In various embodiments, the reference level may be a tumor H score of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, or 300. In some embodiments, the reference level may be a tumor H score of 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, or 175. In some embodiments, the reference level may be a tumor H score of 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, or 160. In some embodiments, the reference level may be a tumor H score of 110, 115, 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, or 135. In some embodiments, the reference level may be a tumor H score of 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 95, 100, 105, 110, 115, 120, 125, or 130. In some embodiments, the reference level may be a tumor H score of 120, 125, 130, 135, 140, 145, or 150. In some embodiments, the reference level may be a tumor H score of 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, or 135. In some embodiments, the reference level may be a tumor H score of 25, 30, 35, 40, 45, 50, or 55.In some embodiments, the reference level may be a tumor H score of 95, 100, 105, 110, 115, 120, 125, or 130.

[0189] In some embodiments, the CD155 expression level of a sample is characterized by cell membrane 2+ or 3+ TC% and is combined with positive staining in the membrane and cytoplasm. In some embodiments, the reference level may be 30%, 25%, 20%, 15%, 10%, or 5% above or below the median (e.g., 10% for gastrointestinal cancer). In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, or 18% cell membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, or 16% cell membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, or 15% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, or 14% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 9%, 10%, 11%, 12%, or 13% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 9%, 10%, 11%, or 12% of cell membrane 2+ or 3+TC%. In various embodiments, the reference level may be 9%, 10%, or 11% of cell membrane 2+ or 3+TC%.

[0190] In some embodiments, the CD155 expression level of a sample is characterized by membrane 2+ or 3+ TC%. In some embodiments, the reference level may be 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median (e.g., 10% for gastrointestinal cancer). In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, 14%, or 15% membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 8%, 9%, 10%, 11%, 12%, 13%, or 14% membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 9%, 10%, 11%, 12%, or 13% membrane 2+ or 3+ TC%. In various embodiments, the reference level may be 9%, 10%, 11%, or 12% of the film 2+ or 3+TC%.

[0191] In some embodiments, the CD155 expression level of a sample is characterized by a cell membrane H score, combined with positive staining in the membrane and cytoplasm. In some embodiments, the reference level may be ≤30%, ≤25%, ≤20%, ≤15%, ≤10%, or ≤5% above or below the median (e.g., 105 for gastrointestinal cancer). In various embodiments, the reference level may be a cell membrane H score of 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, or 115. In various embodiments, the reference level may be a cell membrane H score of 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, or 113. In various embodiments, the reference level may be a cell membrane H score of 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, or 112. In various embodiments, the reference level may be a cell membrane H score of 102, 103, 104, 105, 106, 107, 108, 109, or 110. In various embodiments, the reference level may be a cell membrane H score of 103, 104, 105, 106, 107, or 108. In various embodiments, the reference level may be a cell membrane H score of 104, 105, or 106.

[0192] In some embodiments, the CD155 expression level of a sample is characterized by a membrane H score. In some embodiments, the reference level may be 30%, 25%, 20%, 15%, 10%, or 5% above or below the median (e.g., 39 for gastrointestinal cancer). In various embodiments, the reference level may be a membrane H score of 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, or 50. In various embodiments, the reference level may be a membrane H score of 24, 26, 28, 30, 32, 34, 36, 38, 39, 40, 42, 44, 46, or 48. In various embodiments, the reference level may be a membrane H score of 26, 28, 30, 32, 34, 36, 38, 39, 40, 42, 44, or 46. In various embodiments, the reference level may be a membrane H score of 28, 30, 32, 34, 36, 38, 39, 40, 42, or 44. In various embodiments, the reference level may be a membrane H score of 32, 34, 36, 38, 39, 40, 42, or 44. In various embodiments, the reference level may be a membrane H score of 34, 36, 38, 39, 40, or 42. In various embodiments, the reference level may be a membrane H score of 38, 39, or 40. Prognosis methods

[0193] In one embodiment, the present disclosure provides a method for determining the prognosis of a patient having a disease. In some embodiments, the present disclosure provides a method for determining the prognosis of a patient having a specific disease, the patient being treated for the disease. Biomarkers of the following embodiments are further described elsewhere in this specification, and their disclosures are incorporated by reference in this section. Preferred samples are also described elsewhere in this specification, and are incorporated by reference in this section.

[0194] As used herein, the phrase "determining prognosis" refers to a process by which one of ordinary skill in the art can predict the course or outcome of a condition in a patient. The term "prognosis" does not refer to the ability to predict the course or outcome of a condition with 100% accuracy. Instead, one of ordinary skill in the art will understand that the term "prognosis" refers to an increased probability that a particular course or outcome will occur, i.e., the course or outcome is more likely to occur in a patient presenting a given condition (e.g., biomarker) as compared to an individual not presenting that condition. Prognosis can be expressed as the amount of time that a patient can be expected to survive. Alternatively, prognosis can refer to the likelihood that a disease will enter remission or the amount of time that a disease can be expected to remain in remission. Prognosis can be expressed in a variety of ways. For example, prognosis can be expressed as the percentage chance that a patient will survive after 1 year, 5 years, 10 years, etc. Alternatively, prognosis can be expressed as the number of years that, on average, a patient can be expected to survive as a result of a condition or disease. The prognosis of a patient can be considered a relativistic expression in which many factors influence the final outcome. For example, for a patient having a particular condition, prognosis can be appropriately expressed as the likelihood that the condition can be treatable or curable, or the likelihood that the disease will enter remission, while for a patient having a more severe condition, prognosis can be more appropriately expressed as the likelihood of survival for a particular period of time.

[0195] In the context of a patient having cancer, as used herein, the term "poor prognosis" refers to an increased likelihood that a patient has a reduced remission period, a reduced progression-free survival period, a reduced survival, or a reduced life span as compared to that of a patient not sharing the same biomarker expression profile described herein.

[0196] In the context of a patient having cancer, as used herein, the term "good prognosis" refers to an increased likelihood that a patient has an increased remission period, an increased progression-free survival period, an increased survival, or an increased life span as compared to that of a patient not sharing the same biomarker expression profile described herein.

[0197] In one embodiment, the disclosure provides a biomarker useful for determining the prognosis of a patient, such as a patient identified as having cancer. The biomarker is useful for determining the prognosis of a patient who has received or will receive cancer therapy, such as a therapy containing an immune checkpoint inhibitor. In some embodiments, the biomarker is selected from PD-L1 (PD-L1 expression level), CD155 (CD155 expression level), CD226 (CD226 expression level), an adenosine pathway biomarker, CD73 (CD73 expression level), and any combination thereof. In some embodiments, the adenosine pathway biomarker is CD73 (CD73 expression level). The prognosis of patients who have received or will receive therapy including immune checkpoint inhibitors may be determined if the sample obtained from the patient contains (a) a PD-L1 expression level above or below the PD-L1 reference level, (b) a CD155 expression level above or below the CD155 reference level, (c) a CD226 expression level above or below the CD226 reference level, (d) an adenosine pathway biomarker expression level above or below the adenosine pathway biomarker reference level, (e) a CD73 expression level above or below the CD73 reference level, or (f) any combination of (a) to (e).

[0198] In some embodiments, patients who have received or will receive therapy including an immune checkpoint inhibitor may be determined to have a favorable prognosis if the sample obtained from the patient includes (a) a PD-L1 expression level above the PD-L1 reference level, (b) a CD155 expression level below the CD155 reference level, (c) a CD226 expression level above the CD226 reference level, (d) an adenosine pathway biomarker expression level above the adenosine pathway biomarker reference level, (e) a CD73 expression level above the CD73 reference level, or (f) any combination of (a) to (e). In some embodiments, a patient who has received or will receive a therapy including an immune checkpoint inhibitor may be determined to have a poor prognosis if a sample obtained from the patient includes (a) a PD-L1 expression level lower than the PD-L1 reference level, (b) a CD155 expression level equal to or greater than the CD155 reference level, (c) a CD226 expression level lower than the CD226 reference level, (d) an adenosine pathway biomarker expression level lower than the adenosine pathway biomarker reference level, (e) a CD73 expression level lower than the reference level, or (f) any combination of (a) to (e). In some embodiments described above, the therapy the patient has received or will receive includes or consists of a single immune checkpoint inhibitor. In some embodiments, the therapy is a monotherapy (e.g., a single immune checkpoint inhibitor). In some embodiments, the therapy is a combination therapy comprising a single immune checkpoint inhibitor and one or more additional non-immune checkpoint inhibitor therapies (e.g., chemotherapy (optionally, platinum-containing chemotherapy), VEGF or VEGFR inhibitors, ATP-adenosine axis targeting agents, etc.). In certain embodiments, the single immune checkpoint inhibitor is a PD-L1 antagonist or a PD-1 antagonist (designated herein as “PD-(L)1 antagonist”), optionally, an anti-PD-L1 antibody or an anti-PD-1 antibody (designated herein as “anti-PD-(L)1 antibody”).

[0199] In some embodiments, patients who have received or will receive therapy including an immune checkpoint inhibitor may be determined to have a favorable prognosis if the sample obtained from the patient includes (a) a PD-L1 expression level above the PD-L1 reference level, (b) a CD155 expression level below the CD155 reference level, (c) a CD226 expression level above the CD226 reference level, (d) an adenosine pathway biomarker expression level below the adenosine pathway biomarker reference level, (e) a CD73 expression level below the CD73 reference level, or (f) any combination of (a) to (e). In some embodiments, a patient who has received or will receive therapy including an immune checkpoint inhibitor (e.g., a PD-(L)1 antagonist) may be determined to have a poor prognosis if a sample obtained from the patient includes (a) a PD-L1 expression level lower than the PD-L1 reference level, (b) a CD155 expression level greater than or equal to the CD155 reference level, (c) a CD226 expression level lower than the CD226 reference level, (d) an adenosine pathway biomarker expression level greater than or equal to the adenosine pathway biomarker reference level, (e) a CD73 expression level greater than or equal to the CD73 reference level, or (f) any combination of (a) to (e). In some embodiments described above, the therapy the patient has received or will receive includes or is a combination therapy consisting of the first and second immune checkpoint inhibitors. In embodiments including the first and second immune checkpoint inhibitors, the therapy may further include one or more additional therapies (e.g., chemotherapy, VEGF or VEGFR inhibitors, ATP-adenosine axis targeting agents, etc.). In certain embodiments, either the first or second checkpoint inhibitor is a PD-L1 antagonist or a PD-1 antagonist (referred to herein as "PD-(L)1 antagonist"), optionally, an anti-PD-L1 antibody or an anti-PD-1 antibody (referred to herein as "anti-PD-(L)1 antibody"). In certain embodiments, either the first or second checkpoint inhibitor is a TIGIT antagonist, optionally, an anti-TIGIT antibody.In some embodiments, the first immune checkpoint inhibitor is a PD-(L)1 antagonist, and the second immune checkpoint inhibitor is a TIGIT antagonist.

[0200] In the embodiments described above, the sample may include tumor cells, immune cells (e.g., lymphocytes, monocytes, bone marrow cells, dendritic cells, plasma cells, etc.), other cell types of the tumor microenvironment, or any combination thereof.

[0201] In embodiments including combination therapy, the combination therapy may comprise at least two therapies (i.e., 2, 3, 4, 5, or more therapies). In some embodiments, the combination therapy comprises at least three therapies (i.e., 3, 4, 5, 6, or more therapies). In some embodiments, the combination may include an anti-PD-1 antibody. In some embodiments, the combination may include an anti-PD-L1 antibody. In some embodiments, the combination may include an anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-1 antibody and an anti-TIGIT antibody. In some embodiments, the combination may include an anti-PD-L1 antibody and an anti-TIGIT antibody. In embodiments including an anti-TIGIT antibody, the anti-TIGIT antibody may be an Fc silent anti-TIGIT antibody.

[0202] In some embodiments, the combination may include an ATP-adenosine axis targeting agent. In some embodiments, the combination may include an anti-PD-1 antibody, an anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the combination may include an anti-PD-L1 antibody, an anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the combination may include an anti-PD-(L)1 antibody, an anti-TIGIT antibody, and an ATP-adenosine axis targeting agent. In some embodiments, the ATP-adenosine axis targeting agent is an adenosine receptor antagonist. In some embodiments, the ATP-adenosine axis targeting agent is A 2a R and / or A2b The R antagonist, CD73 inhibitor, or CD39 inhibitor is used. In some embodiments, the ATP-adenosine axis targeting agent is A 2a R and / or A 2b He is an R antagonist.

[0203] In some embodiments, the combination therapy includes chemotherapy such as the chemotherapeutic agents or chemotherapy regimens described herein. In some embodiments, the chemotherapy includes a platinum-containing agent.

[0204] In some embodiments, as described herein, the patient whose prognosis is being determined has cancer, including solid tumors. In some embodiments, the patient has solid tumors selected from the group consisting of ovarian cancer, endometrial cancer, breast cancer, lung cancer, colon cancer, prostate cancer, cervical cancer, bile duct cancer, pancreatic cancer, stomach cancer, esophageal cancer, liver cancer, kidney cancer, head and neck tumors, mesothelioma, melanoma, sarcoma, central nervous system (CNS) hemangioblastoma, and brain tumors. In some embodiments, the patient has cancer selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, and lung cancer. In some embodiments, the patient has lung cancer, including, but not limited to, squamous cell lung cancer or non-squamous cell lung cancer (NSCLC). In some embodiments, the patient has upper gastrointestinal (GI) cancer, including, but not limited to, stomach cancer, gastroesophageal junction (GEJ) cancer, or esophageal adenocarcinoma (EAC). The cancer may be locally advanced and unresectable. The cancer may be recurrent or metastatic.

[0205] In some embodiments, the biomarker expression level in a sample is determined by immunohistochemistry (IHC). The expression level can be measured or determined based on the IHC staining intensity and / or the percentage of stain-positive cells (e.g., cells and / or immune cells). In some embodiments, the reference level is determined by IHC. In some embodiments, the IHC staining intensity and / or the percentage of stain-positive cells is determined based on cytoplasmic staining, membrane staining, or both cytoplasmic and membrane staining. Methods for determining the level of a biomarker in a sample using IHC are known in the art and are further described herein.

[0206] In some embodiments, the reference level is the median expression level derived from samples obtained from a group of patients known to have the same disease, or an amount that is approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median expression level. For example, in some embodiments, the PD-L1 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the CD155 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the CD226 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the adenosine pathway biomarker reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease. In some embodiments, the CD73 reference level may be approximately 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease.

[0207] In some embodiments, the patient has a sample obtained from the patient in which (a) the PD-L1 expression level is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level; (b) the CD155 expression level is lower than the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or less than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level; (c) the CD226 expression level is greater than or equal to the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease, or less than or equal to 30% above or below the median CD226 expression level. (d) The adenosine pathway biomarker expression level is greater than or equal to the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median adenosine pathway biomarker expression level, or (e) The CD73 expression level is greater than or equal to the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD73 expression level, or (f) Any combination of (a) to (e) is judged to have a good prognosis. In some embodiments described above, the therapy that the patient has received or will receive includes or consists of a single immune checkpoint inhibitor. In some embodiments, the therapy is monotherapy (e.g., a single immune checkpoint inhibitor).In some embodiments, the therapy is a combination therapy comprising a single immune checkpoint inhibitor and one or more additional therapies that are not immune checkpoint inhibitors (e.g., chemotherapy, VEGF or VEGFR inhibitors, ATP-adenosine axis targeting agents, etc.). In certain embodiments, the single immune checkpoint inhibitor is a PD-L1 antagonist or a PD-1 antagonist (designated herein as “PD-(L)1 antagonist”), optionally, an anti-PD-L1 antibody or an anti-PD-1 antibody (designated herein as “anti-PD-(L)1 antibody”).

[0208] In some embodiments, the patient has the following characteristics in a sample obtained from the patient: (a) PD-L1 expression level is greater than or equal to the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or greater than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median PD-L1 expression level; (b) CD155 expression level is lower than the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or less than or equal to 30%, 25%, 20%, 15%, 10%, or 5% above or below the median CD155 expression level; (c) CD226 expression level is greater than or equal to the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease, or less than or equal to 30% above or below the median CD226 expression level. (d) The adenosine pathway biomarker expression level is lower than the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease, or is lower than 30%, 25%, 20%, 15%, 10%, or is higher than or lower than 5% of the median adenosine pathway biomarker expression level, or is lower than 30%, 25%, 20%, 15%, 10%, or is lower than or lower than 5% of the median adenosine pathway biomarker expression level, or (f) Any combination of (a) to (e) is judged to have a good prognosis. In some of the embodiments described above, the therapy that the patient has received or will receive includes or is a combination therapy comprising the first and second immune checkpoint inhibitors. In embodiments comprising the first and second immune checkpoint inhibitors, the therapy may further include one or more additional therapies (e.g., chemotherapy, VEGF or VEGFR inhibitors, ATP-adenosine axis targeting agents, etc.).In certain embodiments, either the first or second checkpoint inhibitor is a PD-L1 antagonist or a PD-1 antagonist (referred to herein as "PD-(L)1 antagonist"), optionally, an anti-PD-L1 antibody or an anti-PD-1 antibody (referred to herein as "anti-PD-(L)1 antibody"). In certain embodiments, either the first or second checkpoint inhibitor is a TIGIT antagonist, optionally, an anti-TIGIT antibody. In some embodiments, the first immune checkpoint inhibitor is a PD-(L)1 antagonist, and the second immune checkpoint inhibitor is a TIGIT antagonist.

[0209] In some embodiments, patients, in samples obtained from patients, (a) have a PD-L1 expression level that is lower than the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median PD-L1 expression level; (b) have a CD155 expression level that is greater than or equal to the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median CD155 expression level; or (c) have a CD226 expression level that is lower than the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease, or is 30% or less above or below the median CD226 expression level. (d) The adenosine pathway biomarker expression level is lower than the median adenosine pathway biomarker expression level derived from samples obtained from a group of patients known to have the same disease, or is lower than 30%, 25%, 20%, 15%, 10%, or is higher or lower than 5% above or below the median adenosine pathway biomarker expression level, or (e) The CD73 expression level is lower than the median CD73 expression level derived from samples obtained from a group of patients known to have the same disease, or is lower than 30%, 25%, 20%, 15%, 10%, or is higher or lower than 5% above or below the median CD73 expression level, or (f) Any combination of (a) to (e) is judged to have a poor prognosis. In some embodiments described above, the therapy that the patient has received or will receive includes or consists of a single immune checkpoint inhibitor. In some embodiments, the therapy is monotherapy (e.g., a single immune checkpoint inhibitor).In some embodiments, the therapy is a combination therapy comprising a single immune checkpoint inhibitor and one or more additional therapies that are not immune checkpoint inhibitors (e.g., chemotherapy, VEGF or VEGFR inhibitors, ATP-adenosine axis targeting agents, etc.). In certain embodiments, the single immune checkpoint inhibitor is a PD-L1 antagonist or a PD-1 antagonist (designated herein as “PD-(L)1 antagonist”), optionally, an anti-PD-L1 antibody or an anti-PD-1 antibody (designated herein as “anti-PD-(L)1 antibody”).

[0210] In some embodiments, the patient has a sample obtained from the patient in which (a) the PD-L1 expression level is lower than the median PD-L1 expression level derived from samples obtained from a group of patients known to have the same disease, or is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median PD-L1 expression level; (b) the CD155 expression level is greater than or equal to the median CD155 expression level derived from samples obtained from a group of patients known to have the same disease, or is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median CD155 expression level; or (c) the CD226 expression level is lower than the median CD226 expression level derived from samples obtained from a group of patients known to have the same disease. (d) The adenosine pathway biomarker expression level is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below that amount; (e) The CD73 expression level is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below that amount; or (f) Any combination of (a) to (e) is judged to have a poor prognosis. In some of the embodiments described above, the therapy that the patient has received or will receive includes or is a combination therapy comprising the first and second immune checkpoint inhibitors. In embodiments comprising the first and second immune checkpoint inhibitors, the therapy may further include one or more additional therapies (e.g., chemotherapy, VEGF or VEGFR inhibitors, ATP-adenosine axis targeting agents, etc.).In certain embodiments, either the first or second checkpoint inhibitor is a PD-L1 antagonist or a PD-1 antagonist (referred to herein as "PD-(L)1 antagonist"), optionally, an anti-PD-L1 antibody or an anti-PD-1 antibody (referred to herein as "anti-PD-(L)1 antibody"). In certain embodiments, either the first or second checkpoint inhibitor is a TIGIT antagonist, optionally, an anti-TIGIT antibody. In some embodiments, the first immune checkpoint inhibitor is a PD-(L)1 antagonist, and the second immune checkpoint inhibitor is a TIGIT antagonist.

[0211] In some embodiments, expression levels can be represented in a number of ways, including, but not limited to, the percentage of biomarker-positive tumor cells ("TC%"), the percentage of biomarker-positive tumor cells stained at a moderate or high intensity ("2+ or 3+TC%"), the percentage of biomarker-positive immune cells ("IC%"), characterization by tumor H score, and characterization of expression relative to tumor area (e.g., the number of biomarker-positive tumor cells showing positive staining at any intensity and / or the number of biomarker-positive tumor-associated immune cells showing positive staining at any intensity relative to tumor area), as described elsewhere in this specification. Oncology and oncology-related disorders

[0212] In one or more embodiments of this disclosure, the biomarkers described herein are useful in the treatment or prognosis of a disease, such as cancer. In certain embodiments, the cancer may be an early-stage cancer, for example, stage I or stage II. In other embodiments, the cancer may be locally advanced and / or unresectable, metastatic, or at risk of becoming metastatic. Alternatively, or in addition, the cancer may be recurrent or no longer respond to treatments such as standard treatments known to those skilled in the art. Exemplary types of cancers intended by this disclosure include cancers of the urogenital tract (e.g., bladder, kidney, renal cells, penis, prostate, testes, etc.), uterus, cervix, ovaries, breast, gastrointestinal tract (e.g., esophagus, oropharynx, stomach, small or large intestine, colon, or rectum), bone, bone marrow, skin (e.g., melanoma), head and neck, liver, gallbladder, bile duct, heart, lung, pancreas, salivary glands, adrenal glands, thyroid, brain (e.g., glioma), ganglia, central nervous system (CNS), peripheral nervous system (PNS), hematopoietic system (i.e., hematological malignancies), and immune system (e.g., spleen or thymus).

[0213] In some embodiments, the biomarkers provided herein may be useful for the treatment or prognosis of hematological malignancies. Exemplary types affecting the hematopoietic system include acute myeloid leukemia, adult T-cell leukemia, T-cell macrogranular lymphocytic leukemia, acute lymphoblastic leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, acute monocytic leukemia, Hodgkin and non-Hodgkin lymphomas, diffuse large B-cell lymphoma, and multiple myeloma.

[0214] In another embodiment, the biomarkers according to this disclosure may be useful for the treatment or prognosis of solid tumors. Solid tumors may include, for example, ovarian cancer, endometrial cancer, breast cancer, lung cancer (small cell or non-small cell), colorectal cancer, prostate cancer, cervical cancer, biliary tract cancer, pancreatic cancer, gastric cancer, esophageal cancer, liver cancer (e.g., hepatocellular carcinoma), kidney cancer (e.g., renal cell carcinoma), head and neck tumors, mesothelioma, melanoma, sarcoma, central nervous system (CNS) hemangioblastoma, and brain tumors (e.g., gliomas such as astrocytoma, oligodendroglioma, and glioblastoma).

[0215] In some embodiments, the biomarkers according to this disclosure may be useful for the treatment or prognosis of gastrointestinal cancer, genitourinary cancer, gynecological cancer, lung cancer, or combination thereof.

[0216] In some embodiments, the biomarkers provided herein are useful for the treatment or prognosis of gastrointestinal (GI) cancer. In some embodiments, the GI cancer is colorectal cancer, pancreatic cancer, or liver cancer. In some embodiments, the GI cancer is an upper GI cancer such as esophageal cancer or gastric cancer. In further embodiments, the upper GI cancer is adenocarcinoma, squamous cell carcinoma, or any combination thereof. In further embodiments, the upper GI cancer is esophageal adenocarcinoma (EAC), esophageal squamous cell carcinoma (ESCC), gastroesophageal junction adenocarcinoma (GEJ), gastric adenocarcinoma (also referred to herein as “gastric cancer”), or any combination thereof.

[0217] In some embodiments, subjects requiring the treatment or method described herein may be gastrointestinal cancers, optionally, (i) upper GI cancers, (ii) GI cancers selected from the group consisting of GA, GEJ, ESCC, EAC, and any combination thereof, or (iii) GI cancers selected from the group consisting of GA, GEJ, EAC, and any combination thereof; in certain embodiments, patients with early disease (stage I or stage II); in other embodiments, patients with locally advanced, unresectable, or metastatic disease. Subjects may or may not have received prior systemic treatment, and may or may not have had prior immune checkpoint inhibitor (CPI) treatment. Furthermore, subjects may or may not have been screened for biomarkers such as microsatellite instability (MSI) by PCR or NGS, mismatch repair (MMR) by IHC, and / or HER2 expression by IHC or HER2 copy number by ISH or FISH. In some embodiments, cancers may be MSI stable or low MSI, as determined by clinically validated or FDA-approved tests. In some embodiments, the cancer may have a high MSI, as determined by clinically validated or FDA-approved tests. In some embodiments, the cancer may be HER-2 positive, as determined by clinically validated or FDA-approved tests. In some embodiments, the cancer may be HER-2 negative, as determined by clinically validated or FDA-approved tests. In some embodiments, the cancer may be PD-L1 positive, for example, with a TAP (tumor area positive) of ≥1%, ≥5%, ≥10%, 1% to <5%, 5% to <10%, or ≥10% as measured by the Ventana SP263 IHC assay, or an equivalent value as measured by another clinically validated PD-L1 IHC assay. In some embodiments, the cancer may be PD-L1 negative, for example, with a TAP of less than 1%.

[0218] In some embodiments, the biomarkers according to this disclosure are useful for the treatment or prognosis of pancreatic cancer. In further embodiments, pancreatic cancer is a pancreatic neuroendocrine tumor or a pancreatic adenocarcinoma.

[0219] In some embodiments, the biomarkers according to this disclosure are useful for the treatment or prognosis of liver cancer. In further embodiments, liver cancer is hepatocellular carcinoma. In other embodiments, liver cancer is liver metastasis.

[0220] In some embodiments, the biomarkers provided herein are useful for the treatment or prognosis of genitourinary cancers. In some embodiments, genitourinary cancers are bladder cancer, kidney cancer, or prostate cancer.

[0221] In some embodiments, the biomarkers according to this disclosure are useful for the treatment or prognosis of renal cancer. In further embodiments, renal cancer is renal cell carcinoma. In further embodiments, renal cell carcinoma is clear cell renal cell carcinoma.

[0222] In some embodiments, the present disclosure is useful for the treatment or prognosis of gynecological cancers. In some embodiments, the gynecological cancer is breast cancer, endometrial cancer, or ovarian cancer. In some embodiments, the gynecological cancer is hormone receptor-positive (e.g., ERα-positive cancer, PR-positive cancer, ERα-positive and PR-positive cancer), HER2-positive cancer, HER2-overexpressing cancer, or any combination thereof. In further embodiments, the cancer is triple-negative (e.g., ER, PR, and HER2-negative).

[0223] In some embodiments, the biomarkers according to this disclosure are useful for the treatment or prognosis of lung cancer. In further embodiments, the lung cancer is mesothelioma, small cell lung cancer (SCLC), or non-small cell lung cancer (NSCLC). In even further embodiments, the lung cancer is NSCLC, optionally squamous cell carcinoma of the lung, or adenocarcinoma of the lung.

[0224] In some embodiments, the subjects requiring the treatment or method described herein may be human subjects having NSCLC (squamous or non-squamous cell disease), which in certain embodiments may be patients with early disease (stage I or II) or resectable stage II or stage III NSCLC, ...

Claims

1. Use of a biomarker for identifying a patient for treatment with a combination therapy comprising an anti-TIGIT antibody and an anti-PD-(L)1 antibody, wherein the patient has cancer and a sample obtained from the patient contains a biomarker comprising a CD155 expression level of CD155 or higher than the CD155 reference level, the biomarker is identified for treatment with the combination therapy, and optionally further comprises (a) a PD-L1 expression level of PD-L1 or higher than the PD-L1 reference level, (b) a CD226 expression level of CD226 or higher than the CD226 reference level, (c) an adenosine pathway biomarker expression level lower than the adenosine pathway biomarker reference level, (d) a CD73 expression level lower than the CD73 reference level, or (e) any combination of (a), (b), (c), and (d).

2. The use according to claim 1, wherein the anti-TIGIT antibody is (i) Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

3. The use according to claim 1 or 2, wherein the combination therapy further comprises chemotherapy.

4. The use according to any one of claims 1 to 3, wherein the cancer is (i) stage I, stage II, or stage III and optionally resectable, or (ii) locally advanced or metastatic.

5. The use according to any one of claims 1 to 4, wherein the cancer is a solid tumor.

6. The use according to claim 5, wherein the cancer is selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, head and neck cancer, and lung cancer.

7. A method for treating cancer in a patient, wherein if a sample obtained from the patient contains a biomarker having a CD155 expression level at or above the CD155 reference level, the method further comprises administering to the patient a combination therapy comprising a therapeutically effective amount of anti-TIGIT antibody and a therapeutically effective amount of anti-PD-(L)1 antibody, wherein the biomarker optionally comprises (a) a PD-L1 expression level at or above the PD-L1 reference level, (b) a CD226 expression level at or above the CD226 reference level, (c) an adenosine pathway biomarker expression level lower than the adenosine pathway biomarker reference level, (d) a CD73 expression level lower than the CD73 reference level, or (e) any combination of (a), (b), (c), and (d).

8. The method according to claim 7, wherein the anti-TIGIT antibody is (i) Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

9. The method according to claim 7 or 8, wherein the combination therapy further comprises chemotherapy.

10. The method according to any one of claims 7 to 9, wherein the cancer is (i) stage I, stage II, or stage III and optionally resectable, or (ii) locally advanced or metastatic.

11. The method according to any one of claims 7 to 10, wherein the cancer is a solid tumor.

12. The method according to claim 11, wherein the cancer is selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, head and neck cancer, and lung cancer.

13. A method for identifying patients with cancer for treatment with a combination therapy comprising a therapeutically effective dose of anti-TIGIT antibody and a therapeutically effective dose of anti-PD-(L)1 antibody, (a) Measuring the levels of CD155 in a sample obtained from a patient, and optionally, one or more levels of PD-L1, CD226, adenosine pathway biomarkers, and CD73, (b) Compare the levels measured in (a) with their respective reference levels, (c) A method comprising identifying a patient for treatment in therapy if the measured CD155 level is equal to or greater than the CD155 reference level, and optionally, the measured PD-L1 level is equal to or greater than the PD-L1 reference level.

14. The method according to claim 13, wherein the anti-TIGIT antibody is (i) Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

15. The method according to claim 13 or 14, wherein the combination therapy further comprises chemotherapy.

16. The method according to any one of claims 13 to 15, wherein the cancer is stage I, stage II, or stage III, and optionally the cancer is resectable, or (ii) locally advanced or metastatic.

17. The method according to any one of claims 13 to 16, wherein the cancer includes a solid tumor.

18. The method according to claim 17, wherein the cancer is selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, head and neck cancer, and lung cancer.

19. A method for treating patients, (a) In a sample obtained from a patient, measure the levels of PD-L1, CD155, and optionally, one or more of the following biomarkers: (i) CD226 expression level above the CD226 reference level, (ii) adenosine pathway biomarker expression level below the adenosine pathway biomarker reference level, (iii) CD73 expression level below the CD73 reference level, or (v) any combination of (i), (ii), and (iii). (b) Compare the levels of each biomarker measured in (a) with their respective reference levels, (c) A method comprising administering to the patient a combination therapy comprising a therapeutically effective dose of anti-TIGIT antibody and a therapeutically effective dose of anti-PD-(L)1 antibody if the measured CD155 level is equal to or greater than the CD155 reference level, and optionally, if measured, the measured PD-L1 level is equal to or greater than the PD-L1 reference level.

20. The method according to claim 19, wherein the anti-TIGIT antibody is (i) an Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

21. The method according to claim 19 or 20, wherein the combination therapy includes chemotherapy.

22. The method according to any one of claims 19 to 21, wherein the patient has cancer.

23. The method according to any one of claims 22, wherein the patient has a solid tumor.

24. The method according to claim 23, wherein the solid tumor is selected from the group consisting of ovarian cancer, endometrial cancer, breast cancer, lung cancer, colon cancer, prostate cancer, cervical cancer, bile duct cancer, pancreatic cancer, stomach cancer, esophageal cancer, liver cancer, kidney cancer, head and neck cancer, mesothelioma, melanoma, sarcoma, central nervous system (CNS) hemangioblastoma, and brain tumor.

25. The method according to claim 22, wherein the patient has a cancer selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, head and neck cancer, and lung cancer.

26. The use or method according to any one of claims 1 to 25, wherein the sample is a sample containing tumor cells.

27. The use or method according to any one of claims 1 to 26, wherein the sample is a sample containing immune cells.

28. The use or method according to any one of claims 1 to 27, wherein the sample is a tumor biopsy.

29. The use or method according to any one of claims 1 to 28, wherein the CD155 expression level is measured by immunohistochemistry (IHC).

30. The use or method according to any one of claims 1 to 29, wherein the reference level is (i) the median expression level derived from samples obtained from a group of patients having the same cancer, or (ii) an amount that is 30% or less, 25% or less, 20% or less, 15% or less, 10% or less, or 5% or less above or below the median expression level.

31. The use or method according to claim 29 or 30, wherein the expression level is measured based on IHC staining intensity and / or the percentage of stain-positive cells.

32. The use or method according to claim 31, wherein the stain-positive cells are tumor cells.

33. The use or method according to claim 31, wherein the stain-positive cells are immune cells.

34. The use or method according to claim 31, wherein the stain-positive cells are cells of the tumor microenvironment and are not immune cells or tumor cells.

35. The use or method according to claim 31, wherein the stain-positive cells are (i) tumor cells and immune cells, or (i) tumor cells, immune cells and other cells of the tumor microenvironment.

36. The use or method according to any one of claims 31 to 35, wherein the IHC staining intensity and / or the percentage of stain-positive cells are determined based on cytoplasmic staining.

37. The use or method according to any one of claims 31 to 35, wherein the IHC staining intensity and / or the percentage of stain-positive cells are determined based on membrane staining.

38. The use or method according to any one of claims 31 to 35, wherein the IHC staining intensity and / or the percentage of stain-positive cells are determined based on cytoplasmic staining and membrane staining.

39. The use or method according to any one of claims 1 to 38, wherein the CD155 expression level is measured as TC%.

40. The use or method according to any one of claims 1 to 38, wherein the CD155 expression level is measured as IC%.

41. The use or method according to any one of claims 1 to 38, wherein the CD155 expression level is measured as an H score.

42. The method according to any one of claims 19 to 41, wherein the sample is high in PD-L1 or positive for PD-L1.

43. The method according to claim 42, wherein the sample is high in PD-L1 when the percentage of PD-L1-positive tumor cells (PD-L1 TC%) of the sample is 50% or more.

44. The method according to claim 42, wherein the sample has a high PD-L1 level when the tumor area ratio (TAP) of the sample is 5% or more.

45. The method according to claim 42, wherein the sample is PD-L1 positive if the percentage of PD-L1 positive tumor cells (PD-L1 TC%) of the sample is 1% or more.

46. The method according to claim 42, wherein the sample is PD-L1 positive if the tumor area ratio (TAP) of the sample is 1% or more.

47. A method for treating cancer in a patient with CD155 hypertumor, the method comprising administering to the patient a combination therapy comprising a therapeutically effective amount of a TIGIT antagonist and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the CD155 hypertumor has a CD155 expression level that is (i) the median tumor H score derived from a sample obtained from a group of patients known to have the same cancer, or (ii) approximately 30%, approximately 25%, approximately 20%, approximately 15%, approximately 10%, or approximately 5% above or below the median tumor H score.

48. The method according to claim 47, wherein the CD155 hypertumor has a CD155 expression level that is (i) above or below the median tumor H score derived from samples obtained from a group of patients known to have the same cancer, or (ii) above or below the median tumor H score by approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20%.

49. A method for treating cancer in a patient with CD155 hypertumor, the method comprising administering to the patient a combination therapy comprising a therapeutically effective amount of a TIGIT antagonist and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the CD155 hypertumor has a CD155 expression level that is (i) greater than or equal to the median 2+ or 3+ TC% derived from a sample obtained from a group of patients known to have the same cancer, or (ii) greater than or equal to about 30%, about 25%, about 20%, about 15%, about 10%, or about 5% above or below the median 2+ or 3+ TC%.

50. The method according to claim 49, wherein the CD155 hypertumor has a CD155 expression level that is (i) above or below the median 2+ or 3+ TC% derived from samples obtained from a group of patients known to have the same cancer, or (ii) above or below the median 2+ or 3+ TC% by approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20%.

51. A method for treating cancer in a patient with high CD155 tumors, the method comprising administering to the patient a combination therapy comprising a therapeutically effective amount of a TIGIT antagonist and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the high CD155 tumors have a CD155 tumor H score of 95 or higher, 100 or higher, 105 or higher, 110 or higher, 115 or higher, 120 or higher, 125 or higher, 130 or higher, 135 or higher, 140 or higher, 145 or higher, 150 or higher, 155 or higher, 160 or higher, 165 or higher, 170 or higher, or 175 or higher.

52. The method according to claim 51, wherein the CD155 high tumor has a CD155 tumor H score of 110 or higher, 115 or higher, 120 or higher, 125 or higher, 130 or higher, 135 or higher, 140 or higher, 145 or higher, 150 or higher, 155 or higher, or 160 or higher.

53. A method for treating cancer in a patient with CD155 hypertumor, the method comprising administering to the patient a combination therapy comprising a therapeutically effective amount of a TIGIT antagonist and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the CD155 hypertumor has 30% or more, 35% or more, 40% or more, 45% or more, 50% or more, 55% or more, 60% or more, or 65% or more of CD155 2+ or 3+ TC%.

54. The method according to claim 53, wherein the CD155 hypertumor has 30% or more, 35% or more, 40% or more, 45% or more, or 50% or more of CD155 2+ or 3+ TC%.

55. The method according to any one of claims 47 to 54, wherein the TIGIT antagonist is an anti-TIGIT antibody, the PD-(L) antagonist is an anti-PD-(L)1 antibody, or the TIGIT antagonist is an anti-TIGIT antibody and the PD-(L) antagonist is an anti-PD-(L)1 antibody.

56. The method according to claim 55, wherein the anti-TIGIT antibody is (i) Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

57. A method for treating cancer in a patient with CD155 hypertumor, the method comprising administering to the patient a combination therapy comprising a therapeutically effective amount of an anti-TIGIT antibody that is FcSilent and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the CD155 hypertumor has a CD155 expression level equal to or greater than the CD155 reference level.

58. The aforementioned CD155 reference level is (a) the median tumor H score derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 30%, approximately 25%, approximately 20%, approximately 15%, approximately 10%, or approximately 5% above or below the median tumor H score, (b) the median 2+ or 3+ TC% derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 30%, approximately 25%, approximately 20%, approximately 15%, approximately 10%, or approximately 5% above or below the median 2+ or 3+ TC%; (c) Tumor H score of 95 or higher, 100 or higher, 105 or higher, 110 or higher, 115 or higher, 120 or higher, 125 or higher, 130 or higher, 135 or higher, 140 or higher, 145 or higher, 150 or higher, 155 or higher, 160 or higher, 165 or higher, 170 or higher, or 175 or higher, or (d) The method according to claim 57, wherein the 2+ or 3+TC% is 30% or more, 35% or more, 40% or more, 45% or more, 50% or more, 55% or more, 60% or more, or 65% or more.

59. The aforementioned CD155 reference level is (a) the median tumor H score derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20% above or below the median tumor H score, (b) The median 2+ or 3+ TC% derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20% above or below the median 2+ or 3+ TC%. (c) Tumor H score of 110 or higher, 115 or higher, 120 or higher, 125 or higher, 130 or higher, 135 or higher, 140 or higher, 145 or higher, 150 or higher, 155 or higher, or 160 or higher, (d) The method according to claim 57, wherein the 2+ or 3+TC% is 30% or more, 35% or more, 40% or more, 45% or more, or 50% or more.

60. The method according to any one of claims 47 to 59, wherein the PD-(L) antagonist is an anti-PD-(L)1 antibody, and optionally the anti-PD-(L)1 antibody is atezolizumab, avelumab, semiprimab, dostallimab, durvalumab, nivolumab, pembrolizumab, retifanlimab, tislerizumab, tripalimab, or zimbererimab.

61. The method according to any one of claims 47 to 60, wherein the CD155 hypertumor is PD-L1 positive, and optionally, PD-L1 positivity is defined as a percentage of PD-L1 positive tumor cells of 1% or more (PD-L1 TC%), a PD-L1 tumor area ratio of 1% or more (TAP), or a PD-L1 CPS score of 1 or more.

62. The method according to any one of claims 47 to 60, wherein the PD-L1 expression level in the CD155 hypertumor is 10% or more.

63. The method according to any one of claims 62, wherein the PD-L1 expression level in the CD155 hypertumor is greater than 10% TC.

64. The method according to any one of claims 62, wherein the PD-L1 expression level in the CD155 hypertumor is 50% or more of a TC.

65. The method according to any one of claims 47 to 60, wherein the PD-L1 expression level in the CD155 hypertumor is 5% or higher (TAP) or 5% or higher (CPS).

66. The method according to any one of claims 65, wherein the PD-L1 expression level in the CD155 hypertumor is 10% or more TAP or 10 or more CPS.

67. A method for treating cancer in a patient with CD155 hypertumor, the method comprising administering to the patient a combination therapy comprising a therapeutically effective amount of an anti-TIGIT antagonist and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the CD155 hypertumor has a CD155 expression level equal to or greater than the CD155 reference level, and the PD-L1 expression level in the CD155 hypertumor is 10% or more of TC, 5% or more of TAP, or 5% or more of CPS.

68. The method according to claim 67, wherein the PD-L1 expression level in the CD155 hypertumor is 10% or more TAP or 10 or more CPS.

69. The method according to claim 67, wherein the PD-L1 expression level in the CD155 hypertumor is 50% or higher in the TC.

70. The aforementioned CD155 reference level is (a) the median tumor H score derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 30%, approximately 25%, approximately 20%, approximately 15%, approximately 10%, or approximately 5% above or below the median tumor H score, (b) the median 2+ or 3+ TC% derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 30%, approximately 25%, approximately 20%, approximately 15%, approximately 10%, or approximately 5% above or below the median 2+ or 3+ TC%; (c) Tumor H score of 95 or higher, 100 or higher, 105 or higher, 110 or higher, 115 or higher, 120 or higher, 125 or higher, 130 or higher, 135 or higher, 140 or higher, 145 or higher, 150 or higher, 155 or higher, 160 or higher, 165 or higher, 170 or higher, or 175 or higher, or (d) The method according to any one of claims 67 to 69, wherein the 2+ or 3+TC% is 30% or more, 35% or more, 40% or more, 45% or more, 50% or more, 55% or more, 60% or more, or 65% or more.

71. The aforementioned CD155 reference level is (a) the median tumor H score derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20% above or below the median tumor H score, (b) The median 2+ or 3+ TC% derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, or 20% above or below the median 2+ or 3+ TC%. (c) Tumor H score of 110 or higher, 115 or higher, 120 or higher, 125 or higher, 130 or higher, 135 or higher, 140 or higher, 145 or higher, 150 or higher, 155 or higher, or 160 or higher, (d) The method according to any one of claims 67 to 69, wherein the 2+ or 3+TC% is 30% or more, 35% or more, 40% or more, 45% or more, or 50% or more.

72. The method according to any one of claims 67 to 71, wherein the TIGIT antagonist is an anti-TIGIT antibody, the PD-(L) antagonist is an anti-PD-(L)1 antibody, or the TIGIT antagonist is an anti-TIGIT antibody and the PD-(L) antagonist is an anti-PD-(L)1 antibody.

73. The method according to claim 72, wherein the anti-TIGIT antibody is (i) Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

74. The method according to claim 72, wherein the anti-PD-(L)1 antibody is atezolizumab, avelumab, semiprimab, dostallimab, durvalumab, nivolumab, pembrolizumab, retifanlimab, tislerizumab, tripalimab, or zimberelimab.

75. The method according to any one of claims 47 to 54, 58, 59, 70, or 71, wherein the CD155 staining intensity and the percentage of stain-positive cells are determined based on cytoplasmic staining and membrane staining.

76. The method according to any one of claims 47 to 54, 58, 59, 70, or 71, wherein the CD155 staining intensity and the percentage of stain-positive cells are determined based on membrane staining.

77. A method for treating cancer in a patient having high expression levels of CXCL9, CXCL10, IL-6, or IFNγ prior to treatment, wherein the method comprises administering to the patient a combination therapy comprising a therapeutically effective amount of a TIGIT antagonist and a therapeutically effective amount of a PD-(L)1 antagonist, wherein the high expression level of CXCL9, CXCL10, IL-6, or IFNγ is greater than or equal to a reference value.

78. The method according to claim 77, wherein the reference value is a CD155 reference level that is the median derived from samples obtained from a group of patients known to have the same cancer, or a value that is approximately 30%, approximately 25%, approximately 20%, approximately 15%, approximately 10%, or approximately 5% above or below the median.

79. The method according to claim 77 or 78, wherein the TIGIT antagonist is an anti-TIGIT antibody, or the PD-(L) antagonist is an anti-PD-(L)1 antibody, or the TIGIT antagonist is an anti-TIGIT antibody and the PD-(L) antagonist is an anti-PD-(L)1 antibody.

80. The method according to claim 79, wherein the anti-TIGIT antibody is (i) Fc silent anti-TIGIT antibody, or (ii) domvanalimab.

81. The method according to claim 79, wherein the anti-PD-(L)1 antibody is atezolizumab, avelumab, semiprimab, dostallimab, durvalumab, nivolumab, pembrolizumab, retifanlimab, tislerizumab, tripalimab, or zimberelimab.

82. The method according to any one of claims 47 to 81, wherein the combination therapy further comprises chemotherapy.

83. The method according to any one of claims 47 to 82, wherein the cancer is (i) stage I, stage II, or stage III.

84. The method according to claim 78, wherein the cancer is resectable, and the combination therapy is administered before surgery (neoadjuvant therapy), after surgery (adjuvant therapy), or before and after surgery (neoadjuvant + adjuvant therapy).

85. The method according to any one of claims 47 to 81, wherein the cancer is locally advanced or metastatic.

86. The method according to claim 85, wherein the cancer is resectable, and the combination therapy is administered before surgery (neoadjuvant therapy), after surgery (adjuvant therapy), or before and after surgery (neoadjuvant + adjuvant therapy).

87. The method according to claim 85, provided that locally advanced or metastatic cancer is previously untreated but previous surgery is acceptable.

88. The method according to claim 85, wherein locally advanced or metastatic cancer has not been previously treated with chemotherapy, optionally with chemotherapy comprising a platinum agent.

89. The method according to claim 85, wherein locally advanced or metastatic cancer has been previously treated with chemotherapy, optionally, with a platinum-containing chemotherapy agent.

90. The method according to any one of claims 85, 87, 88, or 89, wherein the locally advanced or metastatic cancer has not been previously treated with a PD-(L)1 antagonist, optionally, with an anti-PD-(L)1 antibody.

91. The method according to any one of claims 86, 87, 88, or 89, wherein the locally advanced or metastatic cancer has been previously treated with a PD-(L)1 antagonist, or optionally with an anti-PD-(L)1 antibody.

92. The method according to any one of claims 47 to 91, wherein the cancer is a solid tumor.

93. The method according to claim 92, wherein the cancer is selected from the group consisting of gastrointestinal cancer, genitourinary cancer, gynecological cancer, head and neck cancer, and lung cancer.

94. The method according to claim 93, wherein the cancer is lung cancer or upper gastrointestinal (GI) cancer.

95. The method according to claim 94, wherein the cancer is squamous cell lung cancer, non-squamous cell lung cancer, gastric cancer, gastroesophageal junction (GEJ) cancer, esophageal adenocarcinoma (EAC), or esophageal squamous cell carcinoma (ESCC).

96. The method according to claim 94, wherein the cancer is non-squamous cell lung cancer (NSCLC), gastric cancer, gastroesophageal junction (GEJ) cancer, or esophageal adenocarcinoma (EAC).

97. The method according to claim 92, wherein the cancer is selected from the group consisting of bladder cancer, breast cancer, endometrial cancer, head and neck squamous cell carcinoma, melanoma, ovarian cancer, and renal cell carcinoma.

98. The method according to claim 92, wherein the cancer is selected from the group consisting of melanoma, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), squamous cell carcinoma of the head and neck (HNSCC), classical Hodgkin lymphoma (cHL), primary mediastinal large B-cell lymphoma (PMBCL), urothelial carcinoma, cancer with high microsatellite instability or deficiency in mismatch repair, colorectal cancer with high microsatellite instability or deficiency in mismatch repair (CRC), gastric cancer, esophageal cancer, cervical cancer, hepatocellular carcinoma (HCC), Merkel cell carcinoma (MCC), renal cell carcinoma (RCC), endometrial cancer, cancer with high tumor mutation burden (TMB-H), cutaneous squamous cell carcinoma (cSCC), and triple-negative breast cancer (TNBC).

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