Marker for predicting therapeutic response to immune checkpoint inhibitor in renal cancer, and method for predicting therapeutic response by using same

Abstract

The present invention relates to a marker for predicting a therapeutic response to an immune checkpoint inhibitor in renal cancer, and a method for predicting a therapeutic response by using same. Specifically, IL-6 and / or IL-10, which are biomarkers that can predict a therapeutic response to an immune checkpoint inhibitor in renal cancer, and cut-off values of the biomarkers are established, and thus data for guiding treatment decisions and establishing appropriate treatment plans for patients can be provided through non-invasive measurement of the concentrations of the markers.

Description

Predictive markers for treatment response to immune checkpoint inhibitors in renal cell carcinoma and methods for predicting treatment response using the markers.

[0001] The present invention relates to IL-6 and / or IL-10, which are biomarkers capable of predicting the treatment response and initial resistance to an immune checkpoint inhibitor in renal cancer, and to a method for predicting the treatment response to an immune checkpoint inhibitor using the biomarkers.

[0002] Renal cell carcinoma (RCC) is the most common kidney malignancy worldwide. Approximately 30% of patients initially diagnosed with RCC have metastatic disease, and one-third of patients who receive curative treatment such as surgery will develop recurrence and metastasis. Furthermore, clear cell carcinoma, the most common type of RCC, is characterized by mutations in the Von Hippel-Lindau (VHL) gene, which activate angiogenic signaling pathways such as vascular endothelial growth factor (VEGF) and hypoxia-inducible factor (HIF). Based on these characteristics, therapies targeting tumor angiogenesis have been emerging since 2006. Sunitinib, an orally available multi-targeted receptor tyrosine kinase inhibitor, demonstrated a clear survival advantage over interferon alpha in patients with advanced renal cell carcinoma. Subsequently, various angiogenesis inhibitors, including pazopanib, bevacizumab, axitinib, cabozantinib, and lenvatinib, have been approved for the treatment of advanced renal cell carcinoma.

[0003]

[0004] The advent of immune checkpoint inhibitors (ICIs) is changing the paradigm of cancer treatment. Renal cell carcinoma (RCC) is well known as an immune-driven tumor with high immune cell infiltration and is relatively sensitive to cytokine immunotherapy. Therefore, immune checkpoint inhibitor treatment is currently considered a desirable approach for patients with advanced RCC. The combination of nivolumab and ipilimumab (CheckMate-214 study) demonstrated a clear survival advantage over sunitinib in patients with advanced RCC. Furthermore, combination therapy of anti-angiogenic agents and immune checkpoint inhibitors is being studied. In the KEYNOTE-426 study, the combination of pembrolizumab and axitinib demonstrated superior survival outcomes compared to sunitinib. Since then, various combinations of immune checkpoint inhibitors and anti-angiogenic agents have been approved as first-line treatments for advanced RCC.

[0005]

[0006] However, various studies have shown that patients develop resistance to immune checkpoint inhibitor therapy, and 10.9% of patients receiving the combination therapy with pembrolizumab and axitinib showed disease progression at the first response assessment, and 44.1% of patients had disease progression within 1 year of starting treatment. Therefore, reliable and clinically actionable biomarkers that can predict treatment response and initial resistance in renal cell carcinoma to immunotherapy are needed. Meanwhile, intratumoral PD-L1 (programmed death-ligand 1) expression is used to predict the clinical benefit of anti-PD-1 (programmed cell death protein-1) or PD-L1 immunotherapy in various malignancies, but it cannot play such a role in patients with advanced renal cell carcinoma who have received first-line immunotherapy. Additionally, tissue-based biomarkers such as microsatellite instability-high / deficient mismatch repair (MSI-H / MMR) and high tumor mutational burden (TMB-H) cannot predict the efficacy of immunotherapy in renal cell carcinoma.

[0007]

[0008] Interleukin-6 (IL-6) is a proinflammatory cytokine involved in chronic inflammation and carcinogenesis, and acts as a poor prognostic factor in various cancer types, including melanoma and renal cell carcinoma. Furthermore, high serum IL-6 levels predict poor progression-free survival (PFS) in patients with metastatic renal cell carcinoma treated with pazopanib. Meanwhile, IL-6, which regulates immune cell function, weakens antitumor immunity, and myeloid-derived suppressor cells (MDSCs) activated by IL-6 suppress T cell responses and promote cancer cell persistence through the JAK / STAT3 signaling pathway. Moreover, in vitro in non-small cell lung cancer, IL-6 increases PD-L1 expression through the JAK / STAT3 signaling pathway, and increases the recruitment of MDSCs, M2 macrophages, and regulatory T cells (Tregs) in tumor samples, while decreasing the infiltration of CD8+ T cells. In bladder cancer, IL-6 enhances the immunosuppressive activity of MDSCs through activation of the mitogen-activated protein kinase (MAPK) signaling pathway. In addition, a recent in vivo study using an acute lymphoblastic leukemia mouse model revealed that IL-6 can suppress chemotherapy-induced antitumor immunity through the tumor microenvironment (TME), but the immunological effects of IL-6 during immunotherapy have not yet been elucidated.

[0009]

[0010] In addition, interleukin-10 (IL-10) is an immunosuppressive cytokine that suppresses the expression of major histocompatibility complex (MHC) class II molecules and proinflammatory cytokines. Although the immunological role of IL-10 is relatively well known, the clinical role of IL-10 in the tumor microenvironment is still poorly studied. Several studies, including those in patients with melanoma and lung cancer, have reported that high IL-10 levels are associated with poor prognosis, and in renal cell carcinoma, IL-10 is known to act as a prognostic factor in patients who received surgical resection of early-stage renal cell carcinoma or cytokine or targeted therapy in advanced disease. However, the effect of IL-10 as a treatment predictive marker in patients with advanced renal cell carcinoma treated with first-line immune checkpoint inhibitors is unknown.

[0011]

[0012] Accordingly, the present inventors intend to provide a biomarker capable of predicting treatment response and initial resistance in patients with advanced renal cell carcinoma, and a method for predicting treatment response to an immune checkpoint inhibitor using the biomarker.

[0013] [Prior Art Literature]

[0014] [Patent Document]

[0015] (Patent Document 1) Registered Patent No. 10-2524548

[0016] [Non-patent literature]

[0017] (Non-patent Document 1) Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma, Rini, BI et al. N. Engl. J. Med. 2019

[0018] One aspect is to provide a biomarker for predicting immune checkpoint inhibitor responsiveness in renal cell carcinoma comprising the IL-6 (Interleukin-6) or IL-10 (Interleukin-10) gene, or the protein encoded by said gene.

[0019] Another aspect provides a composition or kit for predicting responsiveness to an immune checkpoint inhibitor in renal cancer, comprising an agent for measuring the expression level of an IL-6 or IL-10 gene, or a protein encoded by said gene.

[0020] Another aspect provides a method for predicting therapeutic responsiveness to an immune checkpoint inhibitor, comprising the step of measuring the concentration of IL-6 or IL-10 from a biological sample isolated from a patient with renal cell carcinoma.

[0021] One aspect provides a biomarker for predicting immune checkpoint inhibitor responsiveness in renal cell carcinoma comprising the IL-6 (Interleukin-6) or IL-10 (Interleukin-10) gene, or the protein encoded by said gene.

[0022] The above biomarkers can be used as IL-6, IL-10 and combinations thereof, and can also be used as IL-6, IL-10 and combinations thereof in the 'composition for predicting response' and the 'method for predicting treatment response' of the present invention.

[0023] In addition, the renal cancer is preferably, but not limited to, advanced renal cell carcinoma.

[0024] The above immune checkpoint inhibitor may refer to a drug that activates immune cells to attack cancer cells by blocking the activity of target immune checkpoint proteins involved in immune cell suppression. Immune checkpoints that can be targets of immune checkpoint inhibitors include PD-1, PD-L1, CD80, CD86, CTLA4, B7-H3, -H4, -H5, BTLA, 4-1BB, Tim-3, TIGIT, CD94 / NKG2A, KIR2DL-1, -2, -3, etc., and the targets of immune checkpoint inhibitors currently used clinically are PD-1, PD-L1, and CTLA4. More specifically, immune checkpoint inhibitors currently used clinically include, but are not limited to, CTLA-4 monoclonal antibodies such as ipilimumab and tremelimumab; PD-1 monoclonal antibodies such as nivolumab, pembrolizumab, and cemiplimab; and PD-L1 monoclonal antibodies such as atezolizumab, durvalumab, and avelumab.

[0025] In one specific example, the immune checkpoint inhibitor may be administered in combination with another type of immune checkpoint inhibitor or may be administered in combination with an angiogenesis inhibitor, and the angiogenesis inhibitor is preferably, but is not limited to, one selected from the group consisting of sunitinib, pazopanib, bevacizumab, axitinib, cabozantinib, lenvatinib, or a combination thereof.

[0026] In another specific example, the immune checkpoint inhibitor may be, but is not limited to, a combination of pembrolizumab + axitinib; a combination of ipilimumab + nivolumab; and a combination of pembrolizumab + lenvatinib.

[0027] In one specific example, the biomarker of the present invention can be determined to have low therapeutic responsiveness to an immune checkpoint inhibitor when the concentration of the biomarker is measured before treatment with an immune checkpoint inhibitor in renal cancer, and the IL-6 concentration is 5 to 10 pg / mL, preferably 5.5 to 8 pg / mL, more preferably 6 to 7 pg / mL or higher, or the IL-10 concentration is 3 to 8 ng / mL, preferably 3.5 to 7 ng / mL, more preferably 4 to 5 ng / mL or higher.

[0028] Meanwhile, since the biomarker can predict immune checkpoint inhibitor responsiveness in patients who have already received first-line immunotherapy, i.e., those who have already received first-line immunotherapy, the immune checkpoint inhibitor responsiveness can be confirmed by measuring the concentration of the biomarker of the present invention in the same manner before new immune checkpoint inhibitor treatment or additional immune checkpoint inhibitor treatment in patients who have already received first-line immunotherapy.

[0029] In another specific example, the prediction of responsiveness means predicting whether a patient will respond favorably or unfavorably to an immune checkpoint inhibitor, predicting the risk of resistance to an immune checkpoint inhibitor, or predicting the prognosis of a patient after treatment with an immune checkpoint inhibitor, i.e., relapse, metastasis, survival, or disease-free survival, which can be preferably confirmed through measurements of objective response, progression-free survival (PFS), and overall survival (OS), but is not limited thereto.

[0030] Additionally, the above "PFS (Progression-free survival)" or "Progression-free survival" refers to the period of time a patient survives before the disease progresses or before it worsens or dies, and can be a method for observing the effectiveness of a new treatment. The above "progression" can refer to a tumor size increase of 20% or more. Additionally, "OS (Overall survival)" or "Overall survival" refers to the time from randomization to death, and can refer to a value that tracks the period from the start of treatment to the moment of death.

[0031] In addition, objective response is the proportion of patients who can confirm objective responses such as tumor size reduction compared to all patients, and can be divided into complete response where the tumor completely disappeared, partial response where the tumor size decreased by 30% or more, progressive disease where the tumor size increased by 20% or more, and stable disease which is not a partial response or progressive lesion.

[0032]

[0033] Another aspect provides a composition or kit for predicting responsiveness to an immune checkpoint inhibitor in renal cancer, comprising a preparation measuring the expression level of an IL-6 or IL-10 gene, or a protein encoded by said gene.

[0034] In the present invention, the agent for measuring the level of mRNA of the gene may be, but is not limited to, sense and antisense primers or probes that complementarily bind to the mRNA of the gene.

[0035] The above "primer" refers to a short genetic sequence that serves as the starting point of DNA synthesis, and an oligonucleotide synthesized for the purpose of diagnosis, DNA sequencing, etc. The primers can be synthesized and used with a length of typically 15 to 30 base pairs, but this may vary depending on the intended use, and can be modified by methylation, capping, etc. using a known method. In addition, the above "probe" refers to a nucleic acid that can specifically bind to mRNA of several bases to several hundred bases in length, produced through an enzymatic chemical separation and purification or synthesis process. The presence or absence of mRNA can be confirmed by labeling with a radioactive isotope or enzyme, and can be designed and modified using a known method.

[0036] In the present invention, the agent for measuring the level of the protein may be, but is not limited to, an antibody that specifically binds to the protein. The term "antibody" includes an immunoglobulin molecule that immunologically reactives with a specific antigen, and includes both monoclonal and polyclonal antibodies. Furthermore, the antibody includes forms produced through genetic engineering, such as chimeric antibodies (e.g., humanized murine antibodies) and heterologous antibodies (e.g., bispecific antibodies).

[0037] The composition for predicting reactivity of the present invention may be composed of one or more other component compositions, solutions or devices suitable for the analysis method.

[0038] In one specific example, the composition of the present invention may be a composition comprising genomic DNA derived from a sample to be analyzed, a primer set specific for the biomarker of the present invention, an appropriate amount of DNA polymerase, a dNTP mixture, a PCR buffer solution, and water for performing PCR. The PCR buffer solution may contain KCl, Tris-HCl, and MgCl2. In addition, components necessary for performing electrophoresis to confirm whether a PCR product has been amplified may be additionally included in the composition of the present invention.

[0039] Additionally, the composition of the present invention may be a kit comprising essential elements necessary for performing RT-PCR. In addition to each primer pair specific for a marker gene, the RT-PCR kit may include a test tube or other suitable container, a reaction buffer, deoxynucleotides (dNTPs), enzymes such as Taq polymerase and reverse transcriptase, DNase and RNase inhibitors, DEPC water, sterile water, and the like. In addition, the kit may include a primer pair specific for a gene used as a quantitative control.

[0040] Additionally, the composition of the present invention may be a kit comprising essential elements necessary for performing a DNA chip. The DNA chip kit may include a substrate to which a cDNA corresponding to a gene or a fragment thereof is attached as a probe, and the substrate may include a cDNA corresponding to a quantitative structural gene or a fragment thereof. Furthermore, the kit of the present invention may be in the form of a microarray having a substrate to which the marker gene of the present invention is immobilized.

[0041]

[0042] Another aspect provides a method for predicting therapeutic responsiveness to an immune checkpoint inhibitor, comprising the step of measuring the concentration of IL-6 or IL-10 from a biological sample isolated from a patient with renal cell carcinoma.

[0043] The above renal cancer and immune checkpoint inhibitors are as described in the above 'biomarkers'.

[0044] In one embodiment, the biological sample may be at least one selected from the group consisting of blood cells, blood, serum, plasma, bone marrow, lymph, urine, sputum, saliva, sputum, feces, semen, spinal fluid or CSF; external secretions of the skin, respiratory tract, intestines and genitourinary tracts; tears, milk, any human organ or tissue, any sample obtained by lavage, optionally a breast ductal system, a pleural effusion, in vitro or ex vivo cell cultures and cell culture components.

[0045] In addition, the biological sample is isolated before the start of treatment, after the start of treatment for the patient, 14 to 28 days, 14 to 27 days, 14 to 26 days, 14 to 25 days, 14 to 24 days, 14 to 23 days, 14 to 22 days, 14 to 21 days, 14 to 20 days, 14 to 19 days, 14 to 18 days, 15 to 28 days, 15 to 27 days, 15 to 26 days, 15 to 25 days, 15 to 24 days, 15 to 23 days, 15 to 22 days, 15 to 21 days, 15 to 20 days, 15 to 19 days, 15 to 18 days, 16 to 28 days, 16 to 27 days, 16 to 26 days, 16 16 to 25, 16 to 24, 16 to 23, 16 to 22, 16 to 21, 16 to 20, 16 to 19, 16 to 18, 17 to 28, 17 to 27, 17 to 26, 17 to 25, 17 to 24, 17 to 23, 17 to 22, 17 to 21, 17 to 20, 17 to 19, 17 to 18, 18 to 28, 18 to 27, 18 to 26, 18 to 25, 18 to 24, 18 to 23, 18 to 22, 18 to 21, 18 to 20, It may be separated after 18 to 19 days, 19 to 28 days, 19 to 27 days, 19 to 26 days, 19 to 25 days, 19 to 24 days, 19 to 23 days, 19 to 22 days, 19 to 21 days, 19 to 20 days, 20 to 28 days, 20 to 27 days, 20 to 26 days, 20 to 25 days, 20 to 24 days, 20 to 23 days, 20 to 22 days, 20 to 21 days, 21 to 28 days, 21 to 27 days, 21 to 26 days, 21 to 25 days, 21 to 24 days, 21 to 23 days, 21 to 22 days or 21 days.

[0046] In one specific example, the concentration of IL-6, IL-10 or a combination thereof may be measured by at least one method selected from the group consisting of western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip, preferably an enzyme-linked immunosorbent assay (ELISA) or a cytometric bead array, but is not limited thereto and may be measured by a conventional method known in the art.

[0047] In another specific example, when the concentration of the biomarker is measured before treatment with an immune checkpoint inhibitor in renal cancer, and the IL-6 concentration is 5 to 10 pg / mL, preferably 5.5 to 8 pg / mL, more preferably 6 to 7 pg / mL or higher, or the IL-10 concentration is 3 to 8 ng / mL, preferably 3.5 to 7 ng / mL, more preferably 4 to 5 ng / mL or higher, the therapeutic responsiveness to the immune checkpoint inhibitor may be judged to be low.

[0048] Meanwhile, the "cutoff value" of the present invention refers to a numerical value used for mediating the classification between two or more states (e.g., high treatment responsiveness to immune checkpoint inhibitors in renal cancer patients and low treatment responsiveness to immune checkpoint inhibitors) for a biological sample. For example, if a parameter is below the cutoff value, a first classification of quantitative data (e.g., high treatment responsiveness to immune checkpoint inhibitors in renal cancer patients) is made, or if the parameter exceeds the cutoff value, another classification of quantitative data (e.g., low treatment responsiveness to immune checkpoint inhibitors in renal cancer patients) is made.

[0049] The present invention establishes IL-6 and / or IL-10, which are biomarkers capable of predicting the treatment response of an immune checkpoint inhibitor in renal cancer, and a cutoff value of the biomarker, thereby providing data for guiding treatment decisions for patients and establishing an appropriate treatment plan through non-invasive measurement of the concentration of the marker.

[0050] Figure 1 is a diagram showing the enrollment and trial progress procedures for patients with advanced or metastatic renal cell carcinoma (RCC) who received pembrolizumab (Pembro) and axitinib (Axi).

[0051] Figure 2 illustrates the correlation between IL-6 levels and tumor immunity in clear cell renal cell carcinoma: Figure 2a is a correlation plot between IL-6 levels and antitumor immune cells (CD8+ T cells, CD4+ T cells, dendritic cells, and natural killer cells); and Figure 2b is a correlation plot between IL-6 levels and regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), monocytes, and cancer-associated fibroblasts. The correlation plots were generated using Pearson correlation. The blue solid line represents the regression curve, the shaded area represents the 95% confidence interval range of the best fit, and TIDE stands for tumor immune dysfunction and exclusion.

[0052] Figure 3 shows the baseline serum IL-6 levels and survival outcome after pembrolizumab / axitinib treatment: Figure 3a is a graph comparing IL-6 levels according to best response, and the values ​​were compared using ANOVA and Tukey's post hoc test, and the corresponding p value is indicated in each plot; Figure 3b is a graph showing the time-dependent receiver operating characteristic curve of serum IL-6 levels; and Figure 3c is a bar chart showing the best response to treatment according to IL-6 levels.

[0053] Figure 4 is a diagram showing the IL-10 cutoff value confirmed using Maxstat in advanced renal cell carcinoma.

[0054] Figure 5 shows the relationship between baseline serum IL-6 levels and survival outcomes after pembrolizumab / axitinib treatment, where IL-6 > 6.5 pg / mL was defined as 'high IL-6': Figure 5a is a Kaplan-Meier curve showing PFS according to IL-6 levels; Figure 5b is a Kaplan-Meier curve showing OS according to IL-6 levels; Figure 5c is a forest plot showing PFS according to nephrectomy, metastasis, pathology, ECOG performance status, IMDC risk criteria, and IL-6 status; and Figure 5d is a forest plot showing OS according to nephrectomy, metastasis, pathology, ECOG performance status, IMDC risk criteria, and IL-6 status. Hazard ratios and 95% confidence intervals were displayed on survival curves and forest plots, and multivariate analysis was performed using Cox proportional hazards regression. PFS refers to progression-free survival, and OS refers to overall survival.

[0055] Figure 6 confirms that high serum IL-6 levels are associated with impaired CD8+ T cell function. Representative plots using flow cytometry analysis according to IL-6 status are shown, along with comparisons of intracellular IFN-γ and TNF-α levels in CD8+ T cells. T cells were stimulated with anti-CD3 antibody for 24 hours, and values ​​were compared using a t-test, with the corresponding p-value indicated for each plot.

[0056] Figure 7 illustrates that patients with high IL-10 levels exhibited adverse survival outcomes in first-line immune checkpoint inhibitor (ICI) treatment: Figure 7a shows progression-free survival (PFS) in patients with advanced renal cell carcinoma (n=69); and Figure 7b shows overall survival (OS). High IL-10 levels were defined as baseline serum IL-10 levels ≥4.3 ng / mL, and P values ​​were calculated using the log-rank test.

[0057] Figure 8 is a forest plot showing multivariate Cox regression analysis data of OS (Figure 8a) and PFS (Figure 8b) according to serum IL-10 levels, confirming that high serum IL-10 levels are an independent predictor of adverse clinical outcomes in first-line immune checkpoint inhibitor treatment.

[0058] Figure 9 is a diagram showing survival outcomes according to changes in IL-10 levels, and PFS (Figure 9a) and OS (Figure 9b) of patients with advanced renal cell carcinoma in three groups classified according to the C2D1 / basal IL-10 ratio. P-values ​​were calculated using the log-rank test.

[0059] Figure 10 shows T cell dysfunction in patients with high IL-10 levels: Figures 10a and 10b show flow cytometric analysis of intracellular IFN-γ and TNF-α in CD8+ T cells according to IL-10 levels; and Figures 10c and 10d show flow cytometric analysis of Ki-67+ proliferating CD8+ T cells between basal and C2D1. Values ​​were compared using an independent t-test, and P-values ​​are reported for each plot.

[0060] Figure 11 shows that patients with high IL-10 levels had a shorter duration of response to immune checkpoint inhibitor treatment, and depicts a Kaplan-Meier curve showing the duration of response according to IL-10 level. P values ​​were calculated using the log-rank test.

[0061] The present invention will be described in more detail through the following examples. However, these examples are provided for illustrative purposes only and the scope of the present invention is not limited to these examples.

[0062]

[0063] Example 1. Patient recruitment and treatment

[0064] From November 2019 to December 2021, 58 patients with advanced or metastatic renal cell carcinoma (RCC) who received pembrolizumab (Pembro) and axitinib (Axi) as first-line treatment at Bundang CHA Medical Center (Seongnam, Korea) were enrolled (Fig. 1). Patients were eligible for the study if they were 19 years of age or older, had histologically confirmed recurrent or metastatic clear cell or non-clear cell RCC, had no prior systemic therapy, and had an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2. Furthermore, patients with autoimmune diseases, immunocompromised states, or active infections were excluded.

[0065] All patients received pembrolizumab 200 mg intravenously every 3 weeks and axitinib 5 mg orally twice daily. Dose reduction or interruption was determined according to the KEYNOTE-426 clinical trial protocol (Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma, Rini, BI et al. N. Engl. J. Med. 2019). Pembrolizumab and axitinib combination (Pembro / Axi) treatment continued until intolerable toxicity, disease progression, or withdrawal of consent. Response assessments were performed every 6 or 9 weeks using computed tomography (CT), magnetic resonance imaging (MRI), or bone scans according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. This invention was approved by the Institutional Review Board (CHA Bundang Medical Center, 201711054), and all patients signed written informed consent.

[0066] Additionally, patients who received various first-line immune checkpoint inhibitors, including pembrolizumab, were recruited together using the same method as above, and are shown in [Table 3].

[0067]

[0068] Example 2. Sample collection and measurement of serum IL-6 or IL-10

[0069] Venous blood sampling was performed immediately before the first dose of Pembro / Axi. All serum samples were collected in the morning after an overnight fast. To obtain serum, blood was centrifuged at 1000 x g for 5 minutes and stored in a deep freezer at -80°C.

[0070] Additionally, in patients receiving various first-line immune checkpoint inhibitors including pembrolizumab, blood samples were collected before the first combination dose (baseline) and immediately before the second combination dose (day 1 of cycle 2, hereinafter C2D1), and serum was diluted 1:2 and stored in a deep freezer at -80°C.

[0071] Serum IL-6 or IL-10 was quantified using a cytometric bead array (560484, BD Biosciences, Franklin Lakes, NJ, USA) according to the manufacturer's instructions.

[0072] Specifically, human IL-6 or IL-10 capture beads were incubated with serum samples and detection reagents at room temperature for 3 hours. After washing, IL-6 or IL-10 bead complexes were measured using a flow cytometer (Beckman Coulter, Brea, CA, USA), and the data were analyzed using FlowJo software version 10.8.1 (Tree Star Inc., San Francisco, CA, USA).

[0073]

[0074] Example 3. Cytokine secretion test and flow cytometry

[0075] Peripheral blood mononuclear cells (PBMCs) were obtained by density gradient centrifugation using Ficoll-Paque PLUS (GE Healthcare). To assess cytokine production, PBMCs were activated with plate-bound anti-CD3 antibody (1 μg / mL). After 4 h, brefeldin A (eBioscience) (San Diego, CA, USA) and monensin (eBioscience) were added to inhibit cytokine secretion, and the stimulated cells were harvested after 20 h. Before antibody staining, the cells were stained with Fixable Viability Dye eFluorTM 780 (eBioscience) on ice for 30 min to exclude dead cells, and then treated with human Fc receptor-binding inhibitor (eBioscience) for 15 min at room temperature. Surface proteins were stained with fluorophore-conjugated antibodies anti-human CD3 (clone SK7, eBioscience), anti-human CD4 (clone RPA-T4, BioLegend) (San Diego, CA, USA), and anti-human CD8 (clone RPA-T8, eBioscience) for 30 min on ice. In addition, for intracellular staining, cells were fixed, permeabilized with a FoxP3 staining buffer kit (Thermo Fisher Scientific) (Waltham, MA, USA), and stained with fluorophore-conjugated antibodies anti-human interferon-γ (clone B27, BD Bioscience) (San Jose, CA, USA), anti-human tumor necrosis factor (TNF)-α (clone Mab11, BD Bioscience), and Ki-67 (clone Ki-67, BioLegend).Flow cytometry was performed using a CytoFLEX flow cytometer (Beckman Coulter) (Brea, CA, USA), and the results were analyzed using FlowJo software version 10.8.1 (Tree Star Inc.) (San Francisco, CA, USA). In addition, T cell activation was performed according to the method described in High serum IL-6 correlates with reduced clinical benefit of atezolizumab and bevacizumab in unresectable hepatocellular carcinoma. Yang H et al. JHEP Reports, 2023.

[0076]

[0077] Example 4. Public database analysis

[0078] Intratumoral immune cell profiles of clear cell renal cell carcinomas from The Cancer Genome Atlas (TCGA) were analyzed using TIMER version 2.0, a comprehensive resource for immune cell analysis in various cancer types (http: / timer.cistrome.org; accessed May 10, 2022).

[0079]

[0080] Example 5. Statistical Analysis

[0081] Between-group comparisons were performed using the chi-square test and the independent sample t-test for categorical and continuous data, respectively. Survival plots were estimated using Kaplan-Meier analysis and compared using the log-rank test. The Cox proportional hazards model was used to predict progression-free survival (PFS) and overall survival (OS) after adjusting for other variables. Time-dependent receiver operating characteristic curve (ROC) analysis was performed using R 4.2.0 (https: / / www.r-project.org / ) (accessed April 29, 2022) to determine the IL-6 cutoff value at maximum sensitivity and specificity. In all statistical analyses, a p value < 0.05 was considered statistically significant, and statistical analyses were performed using SPSS statistical software (Release 18.0).

[0082] Statistical analysis for IL-10 evaluation was performed using the same method as above, except that between-group comparisons were performed using Fisher's exact test and chi-square test, and IL-10 cutoff values ​​were determined by performing cytokine screening using the Maxstat (maximally selected rank statistics) package in R software (version 4.2.2).

[0083]

[0084] Experimental Example 1. Confirming the Effect of IL-6 on Tumor Immunity

[0085] To investigate the immunological impact of IL-6 on the tumor microenvironment, we analyzed IL-6 levels in immune and stromal cells in a clear cell renal cell carcinoma (RCC) dataset (n = 533) from the TCGA database. Antitumor immune cells, including CD8+ T cells, CD4+ T cells, and dendritic cells, did not correlate with IL-6 levels, while only a weak negative correlation was found between IL-6 and natural killer (NK) cells (Fig. 2a).

[0086] In addition, we confirmed that IL-6 levels were positively correlated with immunosuppressive cells such as Tregs (regulatory T cells), MDSCs (myeloid-derived suppressor cells), and cancer-associated fibroblasts (Fig. 2b).

[0087] Therefore, because high IL-6 levels may be associated with increased intratumoral immunosuppression in patients with renal cell carcinoma, we investigated whether treatment outcomes differed according to IL-6 levels in patients with renal cell carcinoma receiving pembrolizumab and axitinib as first-line treatment.

[0088]

[0089] Experimental Example 2. Analysis of patient demographics and disease outcomes in combination with pembrolizumab and axitinib.

[0090] Fifty-nine patients receiving combination therapy with pembrolizumab and axitinib were enrolled, and baseline blood samples suitable for IL-6 measurement were obtained from 58 of these patients. No written consent was withdrawn, and three patients discontinued Pembro / Axi treatment due to immune-related adverse events. Baseline demographics are presented in Table 1.

[0091] Specifically, the median age of the patient cohort was 60 years (range: 39-83 years), and the male-to-female ratio was 2.6:1. In addition, clear cell histology was observed in 41 patients (70.7%). The IMDC risk was classified as favorable in 19.0% of patients, intermediate in 50.0%, and poor in 31.0%. The most common metastatic site was the lung (81.0%), followed by bone (36.2%), lymph nodes (29.3%), and liver (10.3%). In addition, half of the patients (51.7%) had previously undergone nephrectomy. All patients were followed until February 20, 2022, with a median follow-up period of 12.1 months (IQR: 8.0-17.4). The median PFS and OS for all patients were 12.4 months (95% confidence interval [CI]: 8.2-16.6) and 21.9 months (95% CI: 18.5-25.3), respectively.

[0092] CharacteristicsNumber of patients (% of total)Age≥6523 (39.7)Male42 (72.4)ECOG performance status022 (37.9)129 (50.0)27 (12.1)IMDC riskGood11 (19.0)Intermediate29 (50.0)Poor18 (31.0)PathologyClear cell41 (70.7)Non-clear cell17 (29.3)Number of tissues with metastases120 (34.5)≥238 (65.5)Metastatic siteLung47 (81.0)Lymph node17 (29.3)Bone21 (36.2)Liver6 (10.3)Previous nephrectomy30 (51.7)

[0093] Experimental Example 3. Confirmation of Baseline Serum IL-6 Levels and Clinical Response to Pembrolizumab / Axitinib

[0094] The mean baseline plasma IL-6 concentrations in patients with objective response (complete response [CR] / partial response [PR]; n = 29) were 8.6 pg / mL, in patients with stable disease (SD, n = 21) 9.9 pg / mL, and in patients with progressive disease (PD, n = 8) 84.1 pg / mL (Fig. 3a). Next, the cutoff value of serum IL-6 was determined to define patients with high and low IL-6 levels. Using time-dependent receiver operating characteristic (ROC) curve analysis, the cutoff value of 6.5 pg / mL was found to have a sensitivity of 71.3% and a specificity of 87.5% for predicting the 6-month OS rate in patients treated with Pembro / Axi. In addition, the area under the curve was 88.5% (Fig. 3b). Using the above cutoff values, we confirmed that 37.9% (n = 22) and 62.1% (n = 36) of patients had high and low serum IL-6 levels, respectively, at baseline. In addition, after Pembro / Axi treatment, patients in the high IL-6 group (high IL-6 group) using the above cutoff values ​​had a significantly higher progressive disease (PD) rate of 31.8% and 2.8% than patients in the low IL-6 group (low IL-6 group), indicating a significantly higher PD rate in the high IL-6 group. In addition, we confirmed that the objective response rates were 36.4% and 58.3% in the high and low IL-6 groups, respectively (Fig. 3c).

[0095] Patients with higher baseline IL-6 levels were more likely to have a 'bad' IMDC risk and more likely to develop lymph node and bone metastases than patients with lower IL-6 levels (Table 2).

[0096] CharacteristicsLow IL-6High IL-6p-ValueAge (range), y61 (39-82)59 (47-83)0.572≥65, number (%)13 (36.1)10 (45.5)0.480Male, number (%)28 (77.8)14 (63.6)0.242ECOG performance status 0.316016 (44.4)6 (27.3)117 (47.2)12 (54.5)23 (8.3)4 (18.2)IMDC risk, number (%)0.009Good9 (25.0)2 (9.1)Intermediate21 (58.3)8 (36.4)Poor6 (16.7)12 (54.5)Pathology, number (%)0.356Clear cell type27 (75.0)14 (63.6)Non-clear cell type9 (25.0)8 (36.4)Number of tissues with metastases, number (%) 0.366114 (38.9)6 (27.3)≥222 (61.1)16 (72.7)Site of metastases, number (%) Lung28 (77.8)19 (86.4)0.418Lymph nodes7 (19.4)10 (45.5)0.035Bone9 (25.0)12 (54.5)0.023Liver4 (11.1)2 (9.1)0.806Number of nephrectomy experiences (%)28 (53.8)2 (33.3)0.018

[0097] Experimental Example 4. Characteristics of patients receiving various first-line immune checkpoint inhibitors, including pembrolizumab, and clinical responses.

[0098] Baseline serum IL-10 levels were analyzed in 69 patients diagnosed with advanced renal cell carcinoma (RCC) using the method of Example 1 above (Table 3).

[0099] The median age at treatment initiation was 59 years (range, 19-83 years), and 71% of patients (n = 49) were male. Most patients had clear cell histology (n = 47, 68.1%). According to the IMDC risk group, patients were classified into good (n = 15, 21.7%), intermediate (n = 34, 49.3%), and poor (n = 20, 29.0%). More than half of the patients (n = 39, 56.6%) had a history of prior nephrectomy. The objective response rate of the patient cohort was 47.8%, the 1-year overall survival (OS) rate was 77.9%, and the median follow-up period was 12.1 months. The cutoff value for serum IL-10 was set at 4.3 ng / mL using Maxstat (Fig. 4). Based on this cutoff value, patients were classified into two groups: low IL-10 group (n=60, 87.0%) and high IL-10 group (n=9, 13.0%). There were no statistically significant differences in baseline characteristics between the low and high IL-10 groups (Table 3). The objective response rates were similar between the two groups (46.6% vs. 55.6%, P = 0.862).

[0100] Total (Number = 69) IL-10 low level group (Number = 60) IL-10 high level group (Number = 9) p-ValueRegimenpembrolizumab + axitinib58 (84.1%)49 (81.7%)9 (100.0%)0.505ipilimumab + nivolumab9 (13.0%)9 (15.0%)0 (0.0%)pembrolizumab + lenvatinib2 (2.9%)2 (3.3%)0 (0.0%)Age59 (19-83)59 (19-82)59 (47-83)0.260SexFemale20 (29.0%)17 (28.3%)3 (33.3%)0.712Male49 (71.0%)43 (71.7%)6 (66.7%)PathologyClear cell type47 (68.1%)40 (66.7%)7 (77.8%)0.708Non-clear cell type22 (31.9%)20 (33.3%)2 (22.2%)IMDCGood15 (21.7%)15 (25.0%)0 (0.0%)0.094Intermediate34 (49.3%)30 (50.0%)4 (44.4%)Poor20 (29.0%)15 (25.0%)5 (55.6%)ECOG027 (39.1%)24 (40.0%)3 (33.3%)0.546134 (49.3%)30 (50.0%)4 (44.4%)28 (11.6%)6 (10.0%)2 (22.2%)No prior nephrectomy30 (43.5%)24 (40.0%)6 (66.7%)0.163Yes39 (56.5%)36 (60.0%)3 (33.3%)Optimal response

[0101] Experimental Example 5. Confirmation of survival outcomes according to serum IL-6 levels and Pembro / Axi treatment.

[0102] We compared different survival outcomes according to serum IL-6 levels. According to the cutoff value set above, patients with high IL-6 levels were confirmed to have a significantly shorter PFS than patients with low IL-6 levels (hazard ratio (HR): 3.51, 95% CI: 1.54–7.98, p = 0.003; Fig. 5a). In addition, most patients with low IL-6 levels (72.2%) remained progression-free for 12 months, whereas only 40.9% of patients with high IL-6 levels remained progression-free for 12 months. Patients in the high IL-6 group were confirmed to have worse OS than those in the low IL-6 group (HR: 7.18, 95% CI: 2.26–22.82, p = 0.001; Fig. 5b).

[0103] Therefore, we confirmed that measurement of baseline IL-6 levels in response to Pembro / Axi treatment can be used as a marker of Pembro / Axi treatment response, including survival outcome.

[0104] In addition, a multivariate analysis was performed using the Cox proportional hazards model, considering clinicopathologic variables such as IMDC risk group and pathologic type that could act as confounding variables for survival outcomes (Figs. 5c and 5d). High baseline IL-6 levels were confirmed to be an independent predictor of PFS and OS, regardless of previous nephrectomy, number of metastatic sites, pathologic type, ECOG performance status, and IMDC risk group (HR: 2.454, 95% CI: 1.035–5.818, p = 0.041, and HR: 5.511, 95% CI: 1.656–18.342, p = 0.005, respectively).

[0105]

[0106] Experimental Example 6. Confirmation of the association between high serum IL-6 levels and reduced T cell responses.

[0107] To assess the effect of serum IL-6 on T cell function, we compared cytokine production between the high and low IL-6 groups at baseline, based on the cutoff values ​​established above. Specifically, the high IL-6 group showed a 43.6% decrease in interferon-γ and TNF-α secretion compared to the low IL-6 group (Fig. 6). Furthermore, the average percentage of activated CD8+ T cells was 4.1% and 7.3% in the high and low IL-6 groups, respectively (p = 0.009).

[0108] Therefore, we confirmed that high basal IL-6 concentrations were associated with reduced CD8+ T cell activation.

[0109]

[0110] Experimental Example 7. Confirmation of the association between high baseline serum IL-10 levels and decreased survival after immune checkpoint inhibitor treatment in patients with advanced renal cell carcinoma.

[0111] We examined the relationship between serum IL-10 levels and clinical outcomes (Fig. 7). Specifically, patients with high IL-10 levels, based on the IL-10 cutoff value, had significantly shorter median progression-free survival (PFS) than those with low IL-10 levels (5.2 months vs. not reached, P = 0.007). Median overall survival (OS) was also significantly worse in the high IL-10 group than in the low IL-10 group (13.9 months vs. not reached, P < 0.001).

[0112] In addition, multivariate Cox regression analysis was performed to exclude other factors that may affect survival outcomes. Specifically, potential confounders such as tumor pathology, IMDC risk group, ECOG performance status, and history of nephrectomy were adjusted to identify serum IL-10 levels. Multivariate analysis results showed that the IL-10-high group had worse OS (hazard ratio [HR] 4.466, 95% confidence interval [CI], 1.513–13.183, P = 0.007) and PFS (HR 2.422, 95% CI 1.043–5.622, P = 0.040) than the IL-10-low group (Fig. 8). These results confirmed that baseline serum IL-10 levels were an independent predictor of poor clinical outcomes in patients with advanced renal cell carcinoma receiving first-line immune checkpoint inhibitor therapy.

[0113] Additionally, we analyzed baseline and C2D1 levels and baseline IL-10 levels in patients with paired data (n=52). Specifically, to determine the impact of changes in IL-10 between baseline and C2D1, patients were divided into three groups according to the C2D1 / baseline IL-10 ratio: no change or <1.5 (n=26), 1.5-2.0 (n=11), and ≥2.0 (n=15). The objective response rates did not differ significantly between the three groups (57.6% vs. 63.6% vs. 46.7%, respectively, P=0.673) (Table 4). Additionally, we confirmed that there was no statistically significant difference in PFS (median: not reached vs. 10.7 months vs. 7.8 months, respectively, P = 0.133) and OS (median: not reached vs. 19.3 months vs. not reached, respectively, P = 0.229) according to the C2D1 / basal IL-10 ratio (Fig. 9).

[0114] Total (Number = 52) No change or < 1.5 (n = 26) 1.5-2.0 (n = 11) ≥ 2.0 (n = 15) p-Value CR 3 (5.8%) 1 (3.8%) 1 (9.1%) 1 (6.7%) 0.67 3 PR 26 (50.0%) 14 (53.8%) 6 (54.5%) 6 (40.0%) SD 19 (36.5%) 10 (38.5%) 3 (27.3%) 6 (40.0%) PD 4 (7.7%) 1 (3.8%) 1 (9.1%) 2 (13.3%)

[0115] Experimental Example 8. Decreased CD8+ T cell function was confirmed in the high IL-10 group.

[0116] To determine how serum IL-10 levels affect immune checkpoint inhibitor responses, cytokine production and T cell proliferation were assessed between the high-IL-10 and low-IL-10 groups. In the high-IL-10 group, IFN-γ and TNF-α production in CD8+ T cells was significantly reduced compared to the low-IL-10 group (Figures 10a and 10b). Furthermore, the proportion of Ki-67+ proliferating CD8+ T cells before and after treatment was compared. In the low-IL-10 group, CD8+ T cells proliferating in C2D1 significantly increased, whereas no significant change was observed in the high-IL-10 group (Figures 10c and 10d).

[0117] Therefore, we confirmed that high serum IL-10 levels were associated with decreased cytokine production and decreased CD8+ T cell proliferation.

[0118]

[0119] Experimental Example 9. Determination of the Duration of Response to First-Line Immune Checkpoint Inhibitor Treatment in the IL-10 High-Level Group

[0120] During follow-up, continuous response assessments were performed in all patients except those with progressive disease (Fig. 11). After an initial objective partial or complete response, most patients in the low IL-10 group (n = 24, 85.7%) maintained a sustained response, whereas all patients in the high IL-10 group, except one, experienced rapid disease progression.

[0121] Therefore, the median duration of response in the IL-10-high group was significantly shorter than in the IL-10-low group (4.6 months vs. not reached, P < 0.001).

Claims

1. A composition for predicting the responsiveness of an immune checkpoint inhibitor in renal cancer, comprising a preparation for measuring the expression level of an IL-6 or IL-10 gene, or a protein encoded by the gene.

2. In claim 1 A composition characterized in that the agent for measuring the level of mRNA of the gene is a sense and antisense primer or probe that complementarily binds to the mRNA of the gene.

3. In claim 1 A composition characterized in that the agent for measuring the level of the protein is an antibody that specifically binds to the protein.

4. In claim 1, A composition characterized by being a combination of IL-6 and IL-10.

5. In claim 1, A composition characterized in that the above renal cancer is advanced renal cell carcinoma.

6. In claim 1, A composition characterized in that the above immune checkpoint inhibitor is any one selected from the group consisting of Ipilimumab, Tremelimumab, Pembrolizumab, Cemiplimab, Nivolumab, Durvalumab, Atezolizumab, Avelumab, and combinations thereof.

7. In claim 1, A composition characterized in that the above immune checkpoint inhibitor is treated in combination with an angiogenesis inhibitor.

8. In claim 7, A composition characterized in that the angiogenesis inhibitor is any one selected from the group consisting of sunitinib, pazopanib, bevacizumab, axitinib, cabozantinib, lenvatinib, or a combination thereof.

9. A biomarker for predicting immune checkpoint inhibitor responsiveness in renal cell carcinoma comprising the IL-6 (Interleukin-6) or IL-10 (Interleukin-10) gene, or the protein encoded by the gene.

10. A method for predicting therapeutic responsiveness to an immune checkpoint inhibitor, comprising the step of measuring the concentration of IL-6 or IL-10 from a biological sample isolated from a patient with renal cancer.

11. In claim 10, A method, characterized in that the biological sample is at least one selected from the group consisting of blood, plasma, serum, bone marrow, tissue, cells, saliva, sputum, and urine.

12. In claim 10, A method, characterized in that the biological sample is isolated before initiation of treatment for the patient.

13. In claim 10, A method wherein the above concentration is measured by an enzyme-linked immunosorbent assay or a cytometric bead array.

14. In claim 10, A method further comprising a step of determining that the therapeutic responsiveness of an immune checkpoint inhibitor is low when the IL-6 concentration of the biological sample is 5 to 10 pg / mL or higher or the IL-10 concentration is 3 to 8 ng / mL or higher.

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