Composition for predicting prognosis of treatment response to cancer immunotherapeutic agent in gastric cancer and use thereof

Abstract

The present invention relates to: a composition for predicting the prognosis of a treatment response to a cancer immunotherapeutic agent in cancer; a kit for predicting the prognosis, comprising same; a method for providing information for predicting the prognosis of a treatment response to a cancer immunotherapeutic agent in cancer, using same; a composition for screening for a cancer immunotherapeutic agent; and a method for screening for a cancer immunotherapeutic agent. The composition of the present invention can be effectively used for predicting and diagnosing the prognosis of a treatment response to a cancer immunotherapeutic agent in cancer, and in particular, can be used to develop a drug for personalized treatment of stem-like type gastric cancer patients.

Description

Composition for predicting prognosis of immunotherapy response in gastric cancer and use thereof

[0001] The present invention relates to a composition for predicting the prognosis of a response to immunotherapy in cancer, a kit for predicting the prognosis including the same, a method for predicting the prognosis of a response to immunotherapy in cancer using the same, a composition for screening immunotherapy, and a method for screening immunotherapy.

[0002] Precision medicine has enabled a paradigm shift in cancer treatment by enabling personalized treatment through precise drug and timing predictions. Precision immunology integrates cutting-edge scientific understanding with evidence-based clinical practice to provide a holistic view of each individual patient's condition. Predicting cancer patient response to immunotherapy remains a critical challenge, but currently no standard method exists. The tumor microenvironment, characterized by diverse cell types, tumor signatures, and metabolic reprogramming, offers valuable insights into predicting immunotherapy response. Furthermore, distinct metabolic profiles have been identified between tumors with high epithelial-mesenchymal transition (EMT) activity and those with low EMT activity.

[0003] Cancer-associated fibroblasts (CAFs) are essential for the tumor microenvironment, matrix degradation and remodeling, signaling with cancer cells, and communication with infiltrating leukocytes. CAFs promote tumor phenotypes, particularly cancer cell proliferation and invasion, angiogenesis, inflammation, and extracellular matrix (ECM) remodeling. While the role of CAFs remains controversial, it is generally accepted that CAFs activate tumor promotion.

[0004] The present inventors analyzed the tumor microenvironment at the single-cell level in immunotherapy drug-resistant groups, which are immunotherapy drug-resistant groups, characterized CAF subtype signature genes, investigated the mechanism of stem-like molecular subtype formation through CAF, and completed the present invention by developing a new biomarker that can be used to develop tumor heterogeneity and new treatments through transcriptomic analysis.

[0005] The purpose of the present invention is to provide a composition for predicting the prognosis of immunotherapy response in cancer, comprising a preparation for measuring the expression level of the SDC2 (SYNDECAN 2) gene.

[0006] Another object of the present invention is to provide a kit for predicting the prognosis of a response to immunotherapy in cancer, comprising the composition.

[0007] Another object of the present invention is to provide a method for predicting the prognosis of a response to immunotherapy, comprising the steps of: measuring the mRNA or protein expression level of the SDC2 (Syndecan 2) gene from a biological sample obtained from a patient; and predicting the prognosis of a response to immunotherapy in cancer based on the measured mRNA or protein expression level.

[0008] Another object of the present invention is to provide a composition for screening immunotherapy drugs in cancer, comprising a preparation for measuring the expression level of the SDC2 (Syndecan 2) gene.

[0009] Another object of the present invention is to provide a method for screening an immunotherapy agent in cancer, comprising a step of measuring the expression level of the SDC2 (Syndecan 2) gene.

[0010] Other objects and advantages of the present invention will become more apparent from the detailed description, claims and drawings below.

[0011] Using single-cell data from gastric cancer, we classified gastric cancer cells into three CAF subtypes and defined gene signatures for each type. Among these gene signatures, the immune-regulatory CAF gene signature was highly correlated with the stem-like phenotype, and we confirmed that these genes primarily utilize the PTN-SDC2 signaling pathway. We evaluated the CAF subtype signature genes in relation to the prognosis of pan-cancer patients and confirmed that prognosis was differentiated in BLCA and LGG, similar to the CAF signature of gastric cancer. Furthermore, we characterized the CAF subtypes of five molecular subtypes of gastric cancer to determine which cell types were enriched in the tumor microenvironment. We also confirmed that distinct tumor microenvironments were formed according to CAF subtypes within the same molecular subtype. Specifically, among patients with the stem-like molecular subtype, irCAF patients had relatively high M2 and Treg counts. From a precision medicine perspective, this suggests the possibility of more accurately classifying patients and enabling personalized treatment. We confirmed that fibroblasts from patients with stem-like gastric cancer are associated with the PTN-SDC2 signaling pathway. As a result, SDC2 activity was particularly high in patients who did not respond to immune checkpoint blockade (ICB), with the highest expression observed in patients with stem-like gastric cancer.

[0012]

[0013] Hereinafter, the present invention will be described in detail.

[0014]

[0015] The present invention provides a composition for predicting the prognosis of a response to immunotherapy in cancer, comprising a preparation for measuring the expression level of the SDC2 (SYNDECAN 2) gene.

[0016] In the present invention, the gene may refer to any nucleic acid sequence or a portion thereof that has a functional role in protein coding or transcription or in the regulation of other gene expression. The gene may be comprised of all nucleic acids encoding a functional protein or only a portion of a nucleic acid encoding or expressing a protein. The nucleic acid sequence may include genetic abnormalities within exons, introns, start or end regions, promoter sequences, other regulatory sequences, or unique sequences adjacent to the gene.

[0017] In the present invention, the SDC2 (Syndecan 2) gene may bind to peiotrophin (PTN).

[0018] In the present invention, the immunotherapy agent may suppress one or more genes selected from the group consisting of PD-1, PD-L1, TIM-3, LAG-3, and BTLA.

[0019] In the present invention, the immuno-oncology agent may be, for example, at least one immuno-oncology agent selected from the group consisting of regorafenib (trade name: Stivarga), sorafenib (trade name: Nexavar), nivolumab (trade name: Opdivo), pembrolizumab (trade name: Keytruda), and atezolizumab (trade name: Tecentriq), and more specifically, at least one immuno-oncology agent selected from the group consisting of regorafenib (trade name: Stivarga), sorafenib (trade name: Nexavar), and nivolumab (trade name: Opdivo).

[0020] In the present invention, the cancer may be gastric cancer. According to one embodiment of the present invention, a composition for predicting the prognosis of an immunotherapy response, comprising a preparation capable of measuring the expression level of the SDC2 (SYNDECAN 2) gene of the present invention, can predict the prognosis of an immunotherapy response in a gastric cancer patient.

[0021] In the present invention, the gastric cancer may be derived from at least one selected from the group consisting of myofibroblastic CAF, immune-regulatory CAF, and inflammatory CAF.

[0022] In the present invention, the gastric cancer may be of the stem-like type. According to one embodiment of the present invention, it was confirmed that the activity of the three types of cancer-associated fibroblasts (CAFs) was high in gastric cancer patients of the stem-like type.

[0023] In the present invention, the composition can accurately and quickly predict the prognosis of immunotherapy treatment response in gastric cancer, which is difficult to diagnose, by targeting the tumor microenvironment.

[0024] In the present invention, "protein" is used interchangeably with "polypeptide" or "peptide," and refers to a polymer of amino acid residues, such as those commonly found in proteins in their natural state. "mRNA" refers to RNA that transmits genetic information (gene-specific base sequence) from a specific gene to a ribosome, which specifies the amino acid sequence during protein synthesis.

[0025] In the present invention, expression means the production of a protein or nucleic acid in a cell.

[0026] In the present invention, the agent capable of measuring the expression level of a gene may refer to an agent that directly or indirectly measures the expression of the gene or the protein encoded by the gene in a sample of a cancer patient to determine the level of expression in order to predict the therapeutic response to an immunotherapy agent. The expression level of the gene may be confirmed by measuring the expression level of the mRNA of the gene or the expression level of the protein encoded by the gene. The expression level of the gene according to one aspect may be utilized as a marker, and specifically, the therapeutic response of a cancer patient to an immunotherapy agent may be determined differently depending on the expression level of the gene.

[0027] In the present invention, measuring the mRNA expression level is a process of confirming the presence and expression level of mRNA of the gene in a target sample, and may be measuring the amount of mRNA. In one specific example of the present invention, measuring the mRNA expression level may be performed by one or more techniques selected from the group consisting of reverse transcriptase polymerase reaction (RT-PCR), competitive reverse transcriptase polymerase reaction (Competitive RT-PCR), real-time reverse transcriptase polymerase reaction (Realtime RT-PCR), RNase protection assay (RPA), Northern blotting, and DNA chip.

[0028] In the present invention, the agent capable of measuring the expression level of the mRNA may be a primer or probe that specifically binds to the gene.

[0029] In the present invention, a primer may mean a short nucleic acid sequence having a short free 3-terminal hydroxyl group, which can form base pairs with a complementary template, and which functions as a starting point for copying the template strand.

[0030] In the present invention, the probe refers to a nucleic acid fragment such as RNA or DNA, which is short, a few bases or long, several hundred bases, and can specifically bind to mRNA, and may be labeled to confirm the presence or absence of a specific mRNA. The probe can be produced in the form of an oligonucleotide probe, a single-stranded DNA probe, a double-stranded DNA probe, an RNA probe, etc. In one aspect, hybridization is performed using a probe complementary to a polynucleotide of a gene, and the reactivity of allulose can be predicted or tested based on the presence or absence of hybridization. The selection of an appropriate probe and hybridization conditions can be modified based on those known in the art.

[0031] In the present invention, the primer or probe can be chemically synthesized using a phosphoramidite solid support method or other well-known methods. Such nucleic acid sequences can also be modified using many means known in the art. Non-limiting examples of such modifications include methylation, capping, substitution with one or more homologs of a natural nucleotide, and modification between nucleotides, such as modification with uncharged linkers such as methyl phosphonate, phosphotriester, phosphoramidate, carbamate, etc., or with charged linkers such as phosphorothioate, phosphorodithioate, etc.

[0032] In the present invention, the measurement of the protein expression level is a process of confirming the presence and expression level of the protein encoded by the gene in the target sample, and may be a process of measuring the amount of the protein. In one specific example of the present invention, the measurement of the protein expression level may be performed by one or more techniques selected from the group consisting of Western blot, enzyme linked immunosorbent assay (ELISA), radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, flow cytometry (Fluorescence Activated Cell Sorter, FACS), and protein chip.

[0033] In the present invention, the agent capable of measuring the expression level of the protein may be an antibody or aptamer that specifically binds to the protein of the gene.

[0034] In the present invention, the antibody may refer to a specific protein molecule directed against an antigenic site as a term known in the art. The form of the antibody according to one aspect is not particularly limited, and may include a polyclonal antibody, a monoclonal antibody, or a part thereof as long as it has antigen binding property, and all immunoglobulin antibodies may be included, and further, special antibodies such as humanized antibodies may also be included. The antibody according to one aspect may include a complete form having two full-length light chains and two full-length heavy chains, as well as a functional fragment of an antibody molecule. A functional fragment of an antibody molecule means a fragment that has at least an antigen binding function, and may be, for example, Fab, F(ab'), F(ab')2, Fv, etc.

[0035] In the present invention, an aptamer refers to a single-stranded nucleic acid (DNA, RNA, or modified nucleic acid) that has a stable tertiary structure in itself and can specifically bind to an analyte to be detected in a sample, and can specifically confirm the presence of a target protein in a sample. The aptamer can be manufactured by determining and synthesizing the sequence of an oligonucleotide that has selective and high binding affinity for the target protein to be confirmed according to a general aptamer manufacturing method, and then modifying the 5' end or 3' end of the oligonucleotide with -SH, -COOH, -OH, or NH2 so that it can bind to a functional group of an aptamer chip, but is not limited thereto.

[0036] In addition, the present invention provides a kit for predicting the prognosis of a response to immunotherapy in cancer comprising the composition.

[0037] In the above kit, the composition, cancer, immuno-oncology agent, and prediction are as described above.

[0038] In the present invention, the kit can detect a marker by determining the mRNA expression level or protein expression level of the gene. According to one aspect, the kit may include primers, probes, or optionally, antibodies recognizing the marker for measuring the expression level of the gene, the expression of which increases or decreases depending on the therapeutic response to an immunotherapy agent, as well as one or more other component compositions, solutions, or devices suitable for the analytical method.

[0039] In the present invention, a kit for measuring the mRNA expression level of the gene may be a kit containing essential elements for performing RT-PCR. In addition to each primer specific for the gene, the RT-PCR kit may include a test tube or other appropriate container, a reaction buffer, deoxynucleotides (dNTPs), enzymes such as Taq polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC water, sterile water, and the like.

[0040] In the present invention, a kit for measuring the expression level of the protein may include a substrate, an appropriate buffer solution, a secondary antibody labeled with a chromogenic enzyme or fluorescent substance, and a chromogenic substrate for immunological detection of an antibody. The substrate may be a nitrocellulose membrane, a 96-well plate synthesized with a polyvinyl resin, a 96-well plate synthesized with a polystyrene resin, and a glass slide glass. The chromogenic enzyme may be peroxidase, alkaline phosphatase, etc., the fluorescent substance may be FITC, RITC, etc., and the chromogenic substrate solution may be ABTS (2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid)), OPD (o-phenylenediamine), or TMB (tetramethyl benzidine).

[0041] In addition, the present invention comprises a step of measuring the mRNA or protein expression level of the SDC2 (Syndecan 2) gene from a biological sample obtained from a patient; and

[0042] A method for predicting the prognosis of a response to immunotherapy is provided, including a step of predicting the prognosis of a response to immunotherapy in cancer based on the measured mRNA or protein expression level thereof.

[0043] In the above method, the measurement of cancer, gene, mRNA expression level, protein expression level, immunotherapy, and prediction are as described above.

[0044] In the present invention, a biological sample means a sample obtained from a subject. The biological sample may include whole blood, plasma, serum, red blood cells, white blood cells (e.g., peripheral blood monocytes), ductal fluid, ascites, pleural effusion, nipple aspirate, lymph (e.g., disseminated tumor cells in a lymph node), bone marrow aspirate, saliva, urine, feces (i.e., excretions), sputum, bronchial washings, tears, fine needle aspirates (e.g., harvested by random mammary fine needle aspiration), any other body fluid, a tissue sample (e.g., tumor tissue) such as a tumor biopsy (e.g., a puncture biopsy) or a lymph node (e.g., a sentinel lymph node biopsy), a tissue sample (e.g., tumor tissue) such as a surgical resection of a tumor, and cell extracts thereof. In one embodiment of the present invention, the sample may be whole blood or a component thereof, such as plasma, serum, or a cell pellet. In one embodiment of the present invention, the sample may be obtained by isolating circulating cells of a solid tumor from whole blood or a cell fraction thereof using any technique known in the art. In one embodiment of the present invention, the sample may be, for example, a formalin-fixed, paraffin-embedded (FFPE) tumor tissue sample from a solid tumor. In one embodiment of the present invention, the sample may be a tumor lysate or extract prepared from frozen tissue obtained from a subject having cancer.

[0045] In the present invention, the obtaining may refer to obtaining a nucleic acid sample or a polypeptide sample from a biological sample. The obtaining of the nucleic acid sample may be performed using a conventional nucleic acid isolation method. For example, the target nucleic acid may be obtained by amplifying and purifying the target nucleic acid through polymerase chain reaction (PCR), ligase chain reaction (LCR), transcription-mediated amplification, or real-time nucleic acid sequence-based amplification (NASBA). Alternatively, the target nucleic acid may be obtained as a crudely isolated nucleic acid from a lysate of the biological sample. The obtaining of the polypeptide sample may be performed using a conventional protein extraction or isolation method.

[0046] In the present invention, the control group may be used interchangeably with the term negative control.

[0047] In one specific embodiment of the present invention, the step of predicting the prognosis for response to immunotherapy in the cancer may be such that if the measured mRNA or protein expression level of the SDC2 (Syndecan 2) gene is increased compared to other cancer patients, the patient is judged to have a poor prognosis for response to immunotherapy in the cancer.

[0048] In the present invention, the patient may be a tumor patient, and the tumor may be benign or malignant. Preferably, the patient may be a stem-like type gastric cancer patient.

[0049] In the present invention, the patient may be a mammal. Specifically, the patient may be a human, dog, cat, ferret, hamster, mouse, horse, cow, monkey, chimpanzee, etc.

[0050] In addition, the present invention provides a composition for screening an immunotherapy agent in cancer, comprising a preparation for measuring the expression level of the SDC2 (Syndecan 2) gene.

[0051] In the above composition, the cancer, gene, expression level measurement, and immuno-oncology agent are as described above.

[0052] In addition, the present invention provides a method for screening an immunotherapy agent in cancer, comprising a step of measuring the expression level of the SDC2 (Syndecan 2) gene.

[0053] In the above method, the measurement of cancer, genes, expression levels, and immunotherapy are as described above.

[0054] The present invention relates to a composition for predicting the prognosis of a response to immunotherapy in cancer, and has the advantage that the composition of the present invention can be used to predict and diagnose the prognosis of a response to immunotherapy in cancer and can be usefully utilized as a treatment target, and can be used for drug development for customized treatment of patients with stem-like type gastric cancer.

[0055] Figure 1 shows that cancer-associated fibroblast subtypes exhibit distinct gene signatures. (a) UMAP of three CAF subtypes (irCAF, myoCAF, and infCAF) in Cohort 1. (b) Gene ontology network and protein-protein interactions for inflammatory CAF, along with a bar graph of transcription factors. (c) Heatmap of marker genes for three CAF subtypes (irCAF, myoCAF, and infCAF). (d) Gene ontology network for myofibroblast CAF. (e) MCODE results for protein-protein interactions in immune-regulatory CAF. (f) t-SNE plot for high-entropy and high-stemness activated fibroblasts in Cohort 2. (g) Bar graph of stemness clusters in Cohort 2. (h) Gene ontology network of high-stemness fibroblasts in Cohort 2. (i) Box plot for inflammatory signature scores in the fibroblast clusters of Cohort 2. (j) Box plot for immune-regulatory signature scores in the fibroblast clusters of Cohort 2. (k) Box plot for myofibroblast signature scores in the fibroblast clusters of Cohort 2. (l) Box plot for stemness with signature scores in the fibroblast clusters of Cohort 2.

[0056] Figure 2 illustrates the clinical relevance of the three CAF signatures. (a) Kaplan-Meier survival plots showing overall survival (OS) for patients classified by CAF signature (infCAF, irCAF, and myoCAF) in TCGA STAD (p-values ​​were calculated using the log-rank test). (b) Kaplan-Meier survival plots for the combined CAF signature in TCGA STAD. (c) Box plots for each CAF signature in five molecular subtypes (mixed stromal, stem-like, intestinal, inflammatory, and gastric; abbreviated as MS, SL, IN, IF, and GA, respectively). (d) Kaplan-Meier survival plots for each CAF signature in the Y497 cohort. (e) Kaplan-Meier survival plots for nine CAF subtypes in the Y497 cohort. (f) Heatmap of p-values ​​for survival analysis in the TCGA pan-cancer population. (g) Heatmap of tumor microenvironment deconvolution analysis in three CAF subtypes of five molecular subtypes.

[0057] Figure 3 shows activated high-stemness cells enriched in endothelial cells and fibroblasts at the single-cell level in non-responders in immunotherapy response. (a) t-SNE plot for high-entropy and stemness clusters (blue: high stemness, red: low stemness). (b) Histogram for the stemness cluster. (c) Histogram of cell type fractions in the high-stemness cluster (left) and low-stemness cluster (right). (d) Gene ontology network of highly enriched stem-like cells in the non-responder group. (e) Kaplan-Meier survival plot for the high-entropy endothelial signature from TCGA STAD. (f) Box plot for 149 endothelial signature scores across five molecular subtypes. (g) Box plot for the endothelial signature and CAF subtype signature between non-responders and responders in the SMC data and Yonsei University Hospital cohort. (h) Box plots of the endothelial signature and CAF subtype signatures between other types and stem-like types in Yonsei gastric cancer PDO. (i) Scatter plots of the correlations between each CAF signature and the stem-like signature. (j) Box plots of the stem-like PDO signature in the CAF subtype.

[0058] Figure 4 shows that intercellular communication for CAF subtypes is linked to PTN-SDC2 signaling in stem-like gastric cancer. (a) Heatmap of outgoing and incoming signaling patterns in Cohort 2. (b) Cellular and communication patterns in Cohort 2. (c) Heatmap of the PTN signaling network in Cohort 2. (d) PTN signaling pathway network for transmitters, receivers, mediators, and influencers in Cohort 2. (e) PTN signaling networks for the three CAF subtypes in Cohort 2. (f) Bar graph of the contribution of each ligand-receptor pair in CAF subtypes. (g) Network for protein-protein interactions for SDC2. (h) Box plot of SDC2 expression in CAF subtypes. (i) Kaplan-Meier survival plot for SDC2 expression in TCGA STAD. (j) Box plot of SDC2 expression between non-responders and responders in Samsung Medical Center data. (k) Box plot of SDC2 expression between non-responders and responders in the Yonsei Medical Center cohort. (l) Box plot of SDC2 expression in five molecular subtypes in the Yonsei Medical Center cohort. (m) Kaplan-Meier survival plot for SDC2 expression in the Yonsei Medical Center cohort.

[0059] Hereinafter, to aid understanding of the present invention, examples will be given in detail. However, the following examples are intended only to illustrate the scope of the present invention and are not intended to limit its scope. These examples are provided to more fully explain the present invention to those of average skill in the art.

[0060]

[0061] Example 1. Experimental materials and methods

[0062]

[0063] 1.1. Single-cell RNA-seq analysis

[0064]

[0065] Two gastric cancer single-cell cohorts were used, and CAF subtypes were classified in the first cohort (NPJ Precis Oncol, 2022, Kim, J., et al.,) and validated in the second cohort (Cancer Res, 2020, Sathe, A., et al.,). The default parameter values ​​of the “Seurat” R package were used as the basic parameters (Cell, 2021, Hao, Y., et al.,). Gene ontology analysis was performed using Metascape (Nat Commun, 2019, Zhou, Y., et al.,), and stemID (Cell Stem Cell, 2016, Grun, D., et al.,) was used to analyze stemness at the single-cell level. The R package “GSVA” (BMC Bioinformatics, 2013, Hanzelmann, S., R. Castelo, and J. Guinney,) was used to calculate the signature score, and cellchat (Nat Commun, 2021, Jin, S., et al.,) was used to find cell-to-cell interaction signaling pathways.

[0066]

[0067] 1.2. Bulk RNA-seq Analysis

[0068]

[0069] Survival analysis using TCGA STAD data was performed using gepia2 (Nucleic Acids Res, 2019, Tang, Z., et al.,), and survival analysis using the 497 Yonsei Medical Center cohort (gastric cancer cohort) was performed using the R package "survival." Gepia2 was also used for survival analysis of the TCGA pan-cancer dataset. xCell (Genome Biol, 2017, Aran, D., Z. Hu, and AJ Butte) was used for deconvolution analysis. Immune checkpoint blockade response data were downloaded from the Samsung Medical Center cohort data (Nat Med, 2018, Kim, ST, et al.,), and the ICB response of the Y497 cohort was analyzed using TIDE (Nat Med, 2018, Jiang, P., et al.,). Correlation analysis was performed using the R package.

[0070]

[0071] 1.3. Production and culture of normal and malignant gastric organoids

[0072]

[0073] After receiving approval from the Institutional Review Board (IRB No. 4-2017-0106), clinical samples used for organoid development were obtained from patients at Yonsei University Cancer Hospital who provided informed consent. Healthy and malignant tissue samples were obtained through surgical resection, endoscopic biopsy, or ascites drainage. With minor modifications, organoids were generated and maintained as previously described (Gastroenterology, 2015; Bartfeld, S., et al.). Surgical specimens were rinsed vigorously with phosphate-buffered saline (PBS) and dissected using surgical instruments to a 3 mm diameter. 3 Tumor fragments were chopped into pieces. Tumor fragments were further enzymatically digested with 1.5% collagenase for 60 minutes at 37°C. Normal fragments were treated with 10 mM EDTA for 10 minutes at room temperature.

[0074] Before plating, the collected epithelium was washed with PBS containing 10% fetal bovine serum (FBS) to inactivate digestive enzymes. For organoid culture, ascites samples were centrifuged, rinsed three times with ice-cold PBS, and the precipitated cells were used. The cells were encapsulated in Matrigel vesicles and covered with culture medium. Culture conditions were as follows: Advanced Dulbecco's modified Eagle medium / F12 medium (Invitrogen, Carlsbad, CA, USA), R-spondin-conditioned medium, Wnt-conditioned medium containing bone morphogenetic protein inhibitor, noggin (PeproTech, Cranbury, NJ, USA), GlutaMAX-I (Invitrogen), B27 (Invitrogen), TGF beta I A83-01 (TOCRIS, Minneapolis, MN, USA), ROCK inhibitor, nicotinamide (Sigma-Aldrich, St. Louis, MO, USA), N-acetylcysteine ​​(Sigma-Aldrich), gastrin (Sigma-Aldrich), epidermal growth factor (PeproTech), and fibroblast growth factor 10 (R&D systems, Minneapolis, MN, USA). The medium was changed every 3–4 days. Afterwards, the organoids were passaged every 6–8 days, depending on the size of the organoids. Organoid size was determined by averaging the shortest and longest diameters across the center of the organoid (Gastroenterology, 2015, Bartfeld, S., et al.,).

[0075]

[0076] Example 2. Experimental Results

[0077]

[0078] 2.1. Cancer-associated fibroblasts (CAF) subtypes have distinct gene signatures at the single-cell level.

[0079]

[0080] Advances in single-cell technology have enabled differentiation of CAF heterogeneity based on molecular characteristics. However, little research has been conducted on the molecular characteristics of CAF subtypes in gastric cancer.

[0081] Using single-cell fibroblast data, we classified CAFs into three subtypes (myofibroblastic CAFs, immune-regulatory CAFs, and inflammatory CAFs, abbreviated as myoCAFs, irCAFs, and infCAFs, respectively). Each subtype has a unique gene signature, and the marker genes for each are listed below (myoCAF: HBB, NDUFA4L2, RGS16; irCAF: CXCL14, PDPN, AGT; infCAF: SFRP2, C7, IGF1) (Figures 1A and 1C). We performed gene ontology analysis using the signature genes of each subtype. Inflammatory CAFs were enriched in NABA ECM glycoproteins, matrix-related pathways, and molecules associated with elastic fibers via protein-protein interactions, and the transcription factors NFKB1, RELA, HDAC2, SP1, and JUN were predicted (Fig. 1b). Protein-protein interaction analysis using a novel graph-theoretic clustering algorithm, “Molecular Complex Detection” (MCODE) (BMC Bioinformatics, 2003; Bader, GD, and CW Hogue), revealed that myoCAFs were primarily enriched for vascular development, while immune-regulatory CAFs were enriched for peptide ligand-binding receptors and chemokine receptor-binding chemokines (Fig. 1d, 1e). Using different single-cell cohorts and the StemID tool, we calculated the stemness of fibroblasts. Clusters of high-entropy activated fibroblasts could be distinguished, with clusters 17 and 8 corresponding to high stem-like fibroblasts (Fig. 1f, 1g). Predominantly high-like fibroblasts were enriched in extracellular matrix composition, forming navacore matrisomes and elastic fibers (Fig. 1h).We investigated how CAF subtype signatures are distributed according to CAF clusters based on stemness, and found that the immune-regulatory CAF signatures and stem-like signatures observed in bulk gastric cancer samples shared similar trends (Figures 1i–1l). These analyses helped to understand and define CAF diversity at the single-cell level.

[0082]

[0083] 2.2. Clinical Relevance of the CAF Subtype Gene Signature

[0084]

[0085] We evaluated patient prognosis in the cancer genome atlas (TCGA) stomach adenocarcinoma (STAD) dataset using the CAF subtype signature.

[0086] High-expression groups with inflammatory CAF signatures, immune-regulatory CAF signatures, and myofibroblast CAF signatures all had poor prognosis (Fig. 2a). Furthermore, prognosis analysis using the combined signatures of all three CAF types revealed that the high-expression group had a poor prognosis (Fig. 2b). We investigated the molecular subtypes of gastric cancer associated with the three CAF signatures and found that the three CAF subtypes were enriched in the stem-like phenotype in the Y497 data set (Fig. 2c), which included 497 gastric cancer patients. We examined how each signature was associated with prognosis in the Y497 cohort. Inflammatory CAF signature did not significantly correlate with patient prognosis, whereas irCAF and myoCAF showed poor prognosis in the high-expression group (irCAF: p = 0.0022, myoCAF: p = 0.0053) (Fig. 2d). In the Y497 cohort, CAF subtype signature vis gene set enrichment test classified patients into nine groups (noCAF: CAF related gene down, IIM: inflammatory CAF and immune regulatory CAF and myofibroblastic CAF, INF: inflammatory CAF, IR: immune regulatory CAF, RM: immune regulatory CAF and myofibroblastic CAF, II: immune regulatory CAF and inflammatory CAF, IM: inflammatory CAF and myofibroblastic CAF, INM: inflammatory CAF and myofibroblastic CAF, MYO: myofibroblastic CAF), but the myoCAF group had the worst prognosis (Fig. 2e).We also examined how the CAF subtype signatures discovered in the TCGA pan-cancer dataset functioned differently across cancer types, and all three CAF signatures across BLCA, LGG, and STAD cancer types showed significant patient prognostic significance (Fig. 2f). To investigate how different CAF subtypes shape the immune tumor microenvironment, we performed deconvolution analysis on Y497 transcriptome profiling. InfCAFs and irCAFs showed similar trends in stem-like-type samples, primarily positively correlated with macrophage-2 and Tregs. CD8+ T cells were primarily enriched in the gastric molecular subtype (Fig. 2g).

[0087]

[0088] 2.3. Prediction of immune checkpoint blockade responses to endothelial and CAF subtype signatures

[0089]

[0090] At the single-cell level, stemID analysis was used to determine which cell types were high-entropy stem-like activated cells in the tumor microenvironment of a group of non-responder patients. The blue circle group represents the cluster with the highest entropy and stemness (Figure 3a).

[0091] Clusters 1 and 7 exhibited the highest stemness (Figure 3b). Conversely, clusters 8 and 10 possessed the lowest entropy and stemness. Cluster 1 consisted of over 90% endothelial cells, cluster 7 comprised fibroblasts, T cells, macrophages, and other cells. Clusters 8 and 9, which exhibited the lowest stemness, comprised over 90% B cells associated with innate immunity (Figure 3c). This indicates that the entropy of non-responsive B cells is relatively low compared to that of endothelial cells and fibroblasts.

[0092] Gene ontology analysis of 149 genes highly expressed in high-stemness endothelial cells but not in fibroblasts revealed that they were primarily enriched in vascular development, positive regulation of cell migration, and VEGFA-VEGFA2 signaling (Fig. 3d). In the TCGA STAD dataset, the group with high expression of these 149 genes had a poor prognosis (Fig. 3e). In a cohort of 497 gastric cancer patients from Yonsei Medical Center, these 149 genes were enriched for stem-like phenotypes (Fig. 3f). Bulk RNA-seq data were used to evaluate the signature genes associated with drug resistance at the single-cell level in non-responders and responders of the ICB response. All were significantly elevated in the non-responder group (Fig. 3g). Similarly, SMC data showed significantly higher expression in the non-responder group among the 497 Yonsei Medical Center cohort. These results were reaffirmed in the gastric cancer PDO dataset, where stem-like PDO samples had significantly higher expression levels (Fig. 3h). To determine which CAF subtype patients predominantly harbor, we examined the correlation between the stem-like signature and each CAF subtype signature. The immune-regulatory signature had the highest correlation with the stem-like signature (Fig. 3i). To further confirm this, we compared the expression of genes highly expressed in PDO stem-like samples from CAF at the single-cell level. Immune-regulatory CAF had the highest expression levels of stem-like PDO signature genes (Fig. 3h). This suggests a potential therapeutic response in a non-responsive patient group by identifying cell types and signature genes that drive drug resistance in the ICB response.

[0093]

[0094] 2.4. PTN-SDC2 ligand receptor signaling is associated with CAF in intercellular communication.

[0095]

[0096] Cellchat (Nat Commun, 2021; Jin, S., et al.) was used to determine which signals are involved in each cell-cell interaction at the single-cell level. By analyzing the various patterns of outgoing and incoming signals, we identified signaling pathways used by fibroblasts (Fig. 4a). Eight cell types were classified into three communication patterns, and fibroblast ligands for VEGF, pleiotrophin (PTN), and ANGPT were predicted (Figs. 4b, 4c). We confirmed that fibroblasts are involved in the PTN signaling network, where they act as senders, receivers, and influencers. Specifically, for PTN signaling, fibroblasts, as senders, are associated with four cell types that provide high signals: mesenchymal stem cells, proliferating cells, PMCs, and tumor cells (Fig. 4d). The PTN signaling network communicates with irCAFs and infCAFs within the CAF subtype (Fig. 4e). Within the CAF subtype, ligand-receptor prediction confirmed the highest predictive power of the PTN ligand and SDC2 receptor (Fig. 4f). SDC2 has been implicated in various biological processes, including chondroitin sulfate / dermatan sulfate metabolism and glycosaminoglycan metabolism, and is particularly enriched in exostoses caused by EXT2 defects (Fig. 4g). At the single-cell level, SDC2 was relatively highly expressed in myofibroblast CAF (Fig. 4h). SDC2 showed poor prognosis in the high-expression group in the TCGA STAD dataset (Fig. 4i), and SDC2 expression was significantly higher in the non-responder group in the ICB response results of the SMC cohort data (Fig. 4j). Furthermore, in the data cohort 497 of the Yonsei Medical Center cohort, we confirmed that SCD2 expression was high in the non-responder group (Fig. 4k), and significantly higher activity was observed in the stem-like type among the five molecular subtypes (Fig. 4l). Through binding to extracellular matrix protein receptors, syndecan-2 protein functions as an integral membrane protein and is involved in cell proliferation, migration, and cell-matrix interactions.Additionally, SDC2, a cell surface heparan sulfate proteoglycan, has attracted attention for its unique properties and roles in many cellular functions, including carcinogenesis (IUBMB Life, 2017, Mytilinaiou, M., et al.,).

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[0098] While specific aspects of the present invention have been described in detail above, it will be apparent to those skilled in the art that these specific descriptions merely represent preferred embodiments and are not intended to limit the scope of the present invention. Therefore, the substantial scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A composition for predicting the prognosis of immunotherapy response in cancer, comprising a preparation for measuring the expression level of the SDC2 (Syndecan 2) gene.

2. In paragraph 1, A composition wherein the above SDC2 (Syndecan 2) gene binds to peiotrophin (PTN).

3. In paragraph 1, A composition wherein the above-mentioned immunotherapy agent inhibits at least one gene selected from the group consisting of PD-1, PD-L1, TIM-3, LAG-3, and BTLA.

4. In paragraph 1, A composition wherein the cancer is gastric cancer.

5. In paragraph 4, A composition wherein the above gastric cancer originates from at least one selected from the group consisting of myofibroblastic CAF, immune-regulatory CAF, and inflammatory CAF.

6. In paragraph 4, A composition wherein the above gastric cancer is of the stem-like type.

7. In paragraph 1, The above composition is a composition that targets the tumor microenvironment.

8. In paragraph 1, A composition wherein the measurement of the expression level of the gene is performed by measuring mRNA expressed by the gene or protein expressed by the gene or a fragment thereof.

9. In paragraph 1, A composition wherein the agent capable of measuring the expression level of the mRNA is a primer or probe that specifically binds to the gene.

10. In paragraph 1, A composition wherein the agent capable of measuring the expression level of the above protein is an antibody that specifically binds to the protein of the above gene.

11. A biomarker for predicting prognosis of response to immunotherapy in cancer, comprising a composition according to any one of claims 1 to 10.

12. A kit for predicting the prognosis of a response to immunotherapy in cancer, comprising a composition of any one of claims 1 to 10.

13. A step of measuring the mRNA or protein expression level of the SDC2 (Syndecan 2) gene from a biological sample obtained from a patient; and A method for predicting the prognosis of an immunotherapy response, comprising: a step of predicting the prognosis of an immunotherapy response in cancer based on the measured mRNA or protein expression level thereof.

14. In paragraph 13, A method for predicting the prognosis for the response to immunotherapy in the cancer, wherein the step of predicting the prognosis for the response to immunotherapy in the cancer is such that if the measured mRNA or protein expression level of the gene is increased compared to other control patients, the patient is judged to have a poor prognosis for the response to immunotherapy in the cancer.

15. In paragraph 13, The above method is for stomach cancer.

16. In paragraph 15, A method wherein the above gastric cancer originates from at least one selected from the group consisting of myofibroblastic CAF, immune-regulatory CAF, and inflammatory CAF.

17. In paragraph 13, A method wherein the measurement of the mRNA expression level is performed by one or more techniques selected from the group consisting of reverse transcriptase polymerase reaction (RT-PCR), competitive reverse transcriptase polymerase reaction (Competitive RT-PCR), real-time reverse transcriptase polymerase reaction (Realtime RT-PCR), RNase protection assay (RPA), Northern blotting, and DNA chip.

18. In paragraph 13, A method wherein the measurement of the protein expression level is performed by one or more techniques selected from the group consisting of Western blot, enzyme linked immunosorbent assay (ELISA), radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, flow cytometry (Fluorescence Activated Cell Sorter, FACS), and protein chip.

19. A composition for screening an immuno-oncology agent, comprising a preparation for measuring the expression level of the SDC2 (Syndecan 2) gene.

20. A method for screening an immunotherapy drug, comprising a step of measuring the expression level of the SDC2 (Syndecan 2) gene.

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