Cancer-associated fibroblast inhibitor

Abstract

Provided is a cancer-associated fibroblast inhibitor, particularly a cancer-associated fibroblast inhibitor capable of augmenting the anti-cancer effects of anti-cancer agents.　The cancer-associated fibroblast inhibitor contains a PDGFR inhibitor.

Description

Cancer-associated fibroblast inhibitor

[0001] The present invention relates to an agent for inhibiting cancer-associated fibroblasts and the like.

[0002] Although molecular-targeted therapy and immunotherapy have had a significant impact on refractory cancers, many tumors ultimately acquire chemotherapy resistance. This resistance is attributed to intratumor heterogeneity, which allows some cancer cells to survive and proliferate after treatment. Notably, cancer cells acquire chemotherapy resistance by forming cellular networks with non-tumor cells, such as cancer-associated fibroblasts (CAFs) (Non-Patent Document 1). Therefore, to understand the biological basis of resistance, it is important to understand the overall picture of intratumor heterogeneity and the intercellular networks that allow resistant cancer cells to survive.

[0003] Nat Rev Clin Oncol 18, 792-804. 10.1038 / s41571-021-00546-5.

[0004] An object of the present invention is to provide a cancer-associated fibroblast inhibitor, particularly a cancer-associated fibroblast inhibitor that can enhance the anti-cancer effect of an anti-cancer agent.

[0005] In view of the above problems, the present inventors have conducted extensive research and found that PDGFR inhibitors can suppress cancer-associated fibroblasts and enhance the anticancer effects of anticancer agents. Based on this finding, the present inventors have conducted further research and completed the present invention. Specifically, the present invention encompasses the following aspects.

[0006] Item 1. A cancer-associated fibroblast inhibitor containing a PDGFR inhibitor.

[0007] Item 1A: A method for suppressing cancer-associated fibroblasts, comprising administering a PDGFR inhibitor to a subject (particularly a subject in need of suppression of cancer-associated fibroblasts).

[0008] Item 1B. A PDGFR inhibitor for use in suppressing cancer-associated fibroblasts.

[0009] Item 1C. Use of a PDGFR inhibitor for the manufacture of an agent for inhibiting cancer-associated fibroblasts.

[0010] Item 1D. Use of a PDGFR inhibitor for suppressing cancer-associated fibroblasts.

[0011] Item 2. The agent for inhibiting cancer-associated fibroblasts according to Item 1, wherein the PDGFR inhibitor is at least one selected from the group consisting of PDGFR function inhibitors and PDGFR expression inhibitors.

[0012] Item 3. The cancer-associated fibroblast inhibitor according to Item 1 or 2, wherein the PDGFR inhibitor is at least one selected from the group consisting of a low-molecular-weight compound, a polynucleotide targeting PDGFR, an expression cassette for the polynucleotide, a peptide, a protein, and an antibody.

[0013] Item 4. The cancer-associated fibroblast inhibitor according to any one of Items 1 to 3, wherein the PDGFR inhibitor is a low-molecular-weight compound, and the low-molecular-weight compound is a kinase inhibitor.

[0014] Item 5. The agent for inhibiting cancer-associated fibroblasts according to Item 4, wherein the kinase inhibitor is at least one selected from the group consisting of ripretinib, ponatinib, erdafitinib, dovitinib, lenvatinib, foretinib, ENMD-2076, PP121, and cediranib.

[0015] Item 6. The agent for inhibiting cancer-associated fibroblasts according to any one of Items 1 to 5, wherein the cancer-associated fibroblasts are cells in ovarian cancer tissue, breast cancer tissue, or colon cancer tissue.

[0016] Item 7. The agent for inhibiting cancer-associated fibroblasts according to any one of Items 1 to 6, wherein the cancer-associated fibroblasts are cells in ovarian cancer tissue.

[0017] Item 8. The cancer-associated fibroblast inhibitor according to any one of Items 1 to 7, for use in combination administration with an anticancer agent.

[0018] Item 9. The agent for inhibiting cancer-associated fibroblasts according to Item 8, wherein the anticancer drug is a platinum preparation.

[0019] Item 10. An agent for enhancing the anticancer effect of an anticancer agent, comprising a PDGFR inhibitor.

[0020] Item 10A: A method for enhancing the anti-cancer effect of an anti-cancer drug, comprising administering a PDGFR inhibitor to a subject (particularly a subject in need of an enhanced anti-cancer effect of an anti-cancer drug).

[0021] Item 10B. A PDGFR inhibitor for use in enhancing the anticancer effect of an anticancer agent.

[0022] Item 10C. Use of a PDGFR inhibitor for the manufacture of an agent for enhancing the anticancer effect of an anticancer agent.

[0023] Item 10D. Use of a PDGFR inhibitor to enhance the anti-cancer effect of an anti-cancer agent.

[0024] Item 11. A preventive or therapeutic agent for at least one cancer selected from the group consisting of ovarian cancer, breast cancer, colorectal cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, and melanoma, comprising a PDGFR inhibitor.

[0025] Section 11A. A method for preventing or treating at least one cancer selected from the group consisting of ovarian cancer, breast cancer, colon cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, endometrial cancer, gastric cancer, glioblastoma, lung cancer, and melanoma, comprising administering a PDGFR inhibitor to a subject (particularly a subject in need of prevention or treatment of at least one cancer selected from the group consisting of ovarian cancer, breast cancer, colon cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, endometrial cancer, gastric cancer, glioblastoma, lung cancer, and melanoma).

[0026] Item 11B. A PDGFR inhibitor for use in the prevention or treatment of at least one cancer selected from the group consisting of ovarian cancer, breast cancer, colorectal cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, and melanoma cancer.

[0027] Item 11C. Use of a PDGFR inhibitor for the manufacture of an agent for the prophylaxis or treatment of at least one type of cancer selected from the group consisting of ovarian cancer, breast cancer, colorectal cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, and melanoma.

[0028] Item 11D. Use of a PDGFR inhibitor for the prevention or treatment of at least one cancer selected from the group consisting of ovarian cancer, breast cancer, colorectal cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, and melanoma.

[0029] Item 12. The preventive or therapeutic agent according to Item 11, which is used for combined administration with an anticancer agent.

[0030] According to the present invention, it is possible to provide a cancer-associated fibroblast inhibitor, in particular a cancer-associated fibroblast inhibitor that can enhance the anti-cancer effect of an anti-cancer agent.

[0031] Co-culture of chemotherapy-resistant OCCC cells with CAFs demonstrates the recapitulation of the chemotherapy-resistant niche in vitro. (A) Experimental design of the in vitro co-culture system. Cancer spheroid cells and CAFs were obtained from surgical specimens of HIF-1α-positive OCCC. Established cancer cells and CAFs were labeled with GFP / Luc2 and mCherry / hRluc, respectively, and cultured alone or in combination for chemosensitivity assays, scRNA-seq, or drug screening. (B) Bright phase (top) and fluorescent (bottom) images of labeled cells cultured under organoid conditions for 7 days. Scale bar: 100 μm. (C) 7-day viability of CAFs in monoculture or co-culture with cancer cells. Cultured cells were grown in the absence or presence of the indicated concentrations of carboplatin, and cell viability was assessed by measuring hRLuc activity. P values ​​were determined by Student's t-test. (D) Western blot analysis of FACS-sorted cancer cells after 3 days of culture in monoculture or coculture conditions. (E) Representative images of HIF-1α and α-SMA immunostaining in cancer cells and CAFs cocultured for 3 days. Scale bar, 100 μm. (F) Proliferation of cancer cells in monoculture or cocultured with CAFs for 7 days. Cultured cells were grown in the absence or presence of the indicated concentrations of carboplatin, and cancer cell proliferation was assessed by measuring Luc2 activity. (G) UMAP plot of scRNA-seq data from cancer cells and CAFs cultured in monoculture and coculture conditions for 3 days. (H) Violin plot of signature scores for cancer subpopulations (Cancer #1-6) grown in monoculture and coculture conditions in G. (I) Violin plot of the indicated signature genes in CAFs grown under the monoculture and coculture conditions shown in G: ***p < 0.001. We demonstrate that CAF activation by cancer-derived PDGF mediates cancer cell chemotherapy resistance and HIF-1a activation. (A) Western blot analysis of GFP-labeled cancer cells and mCherry-labeled CAFs using the indicated antibodies. (B) Western blot analysis of CAFs grown under monoculture or coculture conditions for 3 days. Note that PDGFRB levels were reduced under coculture conditions, likely via negative feedback regulation. (C) Western blot analysis of CAFs treated with 40 nM PDGFRB for 3 days.(D) Relative proliferation of CAFs treated with different concentrations of PDGFB for 7 days. (E) Western blot analysis of CAFs with Cas9 / CRIPSR-mediated knockout. (F) Relative proliferation of CAFs transfected with the indicated sgRNAs and treated with 20 nM PDGFB for 7 days. (G) Western blot analysis of control and PDGFRB-deficient CAFs FACS-sorted for mCherry after 3 days of incubation with cancer cells. (H) Viability of control and PDGFRB-deficient CAFs incubated with cancer cells for 7 days. (I) Proliferation of cancer cells cultured with control or PDGFRB-deficient CAFs in the presence of the indicated concentrations of carboplatin for 7 days. (J) Western blot analysis of cancer cells FACS-sorted for GFP after 3 days of incubation with control or PDGFRB-deficient CAFs. P values ​​were determined by Student's t-test. Statistically significant differences are indicated: **p < 0.01, ***p < 0.001. Inhibition of CAFs by ripretinib in combination with carboplatin blocks OCCC proliferation. (A) Inhibition of ovarian cancer-derived CAFs cultured for 7 days in the presence of the indicated TKIs or carboplatin (1 μM). (B) Inhibition of CAFs by ripretinib. CAFs cocultured with cancer cells were treated with the indicated concentrations of ripretinib and carboplatin for 7 days. (C) Synergistic inhibition of cocultured cancer cell proliferation by ripretinib and carboplatin. Cancer cells cocultured with CAFs were treated with the indicated concentrations of ripretinib and carboplatin for 7 days. (D) Fluorescence images of cancer cells and CAFs cocultured for 7 days in the presence or absence of 100 μM carboplatin and / or 5 μM ripretinib. Scale bar: 100 μm. (E) Cancer cells grown in monoculture were treated with the indicated concentrations of ripretinib and carboplatin for 7 days. (F) Tumor xenograft mice were treated with the indicated combination of carboplatin and / or ripretinib, and tumor volumes (mean ± standard error of the mean) were measured weekly. The number of days after cancer cell implantation is indicated. (G) HIF-1α immunostaining of xenograft tumors (78 days after implantation) is shown in the right panel. Zoomed images are shown in the right panel. Scale bars: 500 μm (right panel), 100 μm (left panel). (H) Boxplot of the percentage of HIF-1α-positive cancer cells in the tumor tissues shown in G. Mean ± SEM is shown. P values ​​were determined by Student's t-test.Statistically significant differences are indicated: *p<0.05, **p<0.01, ***p<0.001. Figures show the inhibition of breast cancer-derived CAFs (A) and colon cancer-derived CAFs (B) cultured for 7 days in the presence of the indicated TKIs or carboplatin (1 μM). Mean values ​​± SEM are shown. P values ​​were determined by Student's t-test. Statistically significant differences are indicated: *p<0.05, **p<0.01, ***p<0.001.

[0032] In this specification, the expressions "contain" and "comprise" include the concepts of "contain," "comprise," "consist essentially of," and "consist only of."

[0033] In one aspect, the present invention relates to an agent for inhibiting cancer-associated fibroblasts, an agent for enhancing the anticancer effect of an anticancer agent, and an agent for preventing or treating ovarian cancer and / or breast cancer (these may be collectively referred to herein as the "agent of the present invention"), each of which contains a PDGFR inhibitor. This is described below.

[0034] (1) Active Ingredient (1-1) Target of Inhibition The PDGFR gene encodes the tyrosine kinase Platelet-Derived Growth Factor Receptor (PDGFR). The target of inhibition, PDGFR (PDGFR protein, PDGFR mRNA), is an expression product of the PDGFR gene and is the PDGFR protein or PDGFR mRNA expressed in an organism or its cells (particularly cancer-associated fibroblasts) to which the agent of the present invention is applied. Therefore, the target of inhibition, PDGFR protein and PDGFR mRNA, can be changed as necessary depending on the target organism species. The target organism species is not particularly limited and includes animals, such as various mammals, including humans, monkeys, mice, rats, dogs, cats, rabbits, pigs, horses, cattle, sheep, goats, and deer.

[0035] Examples of PDGFR include PDGFRα and PDGFRβ. The amino acid sequences of PDGFR proteins and the nucleotide sequences of PDGFR mRNAs derived from various biological species are known. Specifically, for example, the human PDGFRα gene is identified by NCBI gene ID 5156, and the human PDGFRβ gene is identified by NCBI gene ID 5159. The amino acid sequences and nucleotide sequences of various biological species can be obtained or estimated from this information. PDGFR proteins and PDGFR mRNAs may also include the above-mentioned splicing variants.

[0036] The PDGFR protein to be inhibited may have amino acid mutations such as substitutions, deletions, additions, and insertions, as long as it retains its inherent properties, i.e., PDGF-binding ability and tyrosine kinase activity. Mutations are preferably substitutions, more preferably conservative substitutions, from the viewpoint of being less likely to impair activity.

[0037] The PDGFR mRNA to be inhibited may also have base mutations such as substitutions, deletions, additions, and insertions, as long as the protein translated from the mRNA has its original properties, i.e., PDGF-binding ability and tyrosine kinase activity. Preferred mutations are those that do not result in amino acid substitutions in the protein translated from the mRNA or those that result in conservative amino acid substitutions.

[0038] A preferred example of the PDGFR protein to be inhibited is a protein that has PDGF-binding activity and tyrosine kinase activity and has an amino acid sequence that is 85 to 100% identical to the amino acid sequence of a wild-type PDGFR protein, with the identity being more preferably 90% or more, even more preferably 95% or more, and even more preferably 98% or more.

[0039] A preferred example of the PDGFR mRNA to be inhibited is a nucleotide sequence that has 85 to 100% identity to the nucleotide sequence of wild-type PDGFR mRNA and encodes a protein that has PDGF-binding activity and tyrosine kinase activity, with the identity being more preferably 90% or more, even more preferably 95% or more, and even more preferably 98% or more.

[0040] "Identity" of amino acid sequences refers to the degree of correspondence between the amino acid sequences of two or more comparable amino acid sequences. Thus, the greater the correspondence between two amino acid sequences, the greater the identity or similarity between those sequences. The level of identity of amino acid sequences can be determined, for example, using the sequence analysis tool FASTA with default parameters. Alternatively, it can be determined using the BLAST algorithm by Karlin and Altschul (Karlin S, Altschul SF. "Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes," Proc Natl Acad Sci USA. 87:2264-2268 (1990); Karlin S, Altschul SF. "Applications and statistics for multiple high-scoring segments in molecular sequences," Proc Natl Acad Sci USA. 90:5873-7 (1993)). A program called BLASTX has been developed based on the BLAST algorithm. Specific techniques for these analysis methods are known and can be found on the National Center of Biotechnology Information (NCBI) website (http: / / www.ncbi.nlm.nih.gov / ). The "identity" of nucleotide sequences is also defined in the same manner as above.

[0041] As used herein, the term "conservative substitution" refers to the substitution of an amino acid residue with an amino acid residue having a similar side chain. For example, substitution between amino acid residues having basic side chains such as lysine, arginine, and histidine constitutes a conservative substitution. Other examples of conservative substitutions include substitution between amino acid residues having acidic side chains such as aspartic acid and glutamic acid; amino acid residues having uncharged polar side chains such as glycine, asparagine, glutamine, serine, threonine, tyrosine, and cysteine; amino acid residues having nonpolar side chains such as alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, and tryptophan; amino acid residues having β-branched side chains such as threonine, valine, and isoleucine; and amino acid residues having aromatic side chains such as tyrosine, phenylalanine, tryptophan, and histidine.

[0042] (1-2) Inhibitors The PDGFR inhibitor is not particularly limited as long as it is a component that can inhibit the function and / or expression of PDGFR. PDGFR inhibitors preferably include low-molecular-weight compounds, polynucleotides that target PDGFR, expression cassettes for the polynucleotides, peptides, proteins, antibodies, etc. PDGFR inhibitors may be used alone or in combination of two or more.

[0043] (1-2-1) PDGFR Function Inhibitor The PDGFR function inhibitor is not particularly limited as long as it is capable of inhibiting the function of PDGFR protein and / or mRNA expressed in an organism or its cells (particularly, cancer-associated fibroblasts) to which the agent of the present invention is applied. The PDGFR function inhibitor may be used alone or in combination of two or more.

[0044] The PDGFR function inhibitor is not particularly limited as long as it can reduce tyrosine kinase activity and / or inhibit ligand (PDGF) binding, and specific examples include tyrosine kinase inhibitors and antagonists.

[0045] PDGFR function inhibitors include not only those that act specifically on PDGFR, but also those that are specific to tyrosine kinases other than PDGFR (e.g., tyrosine kinases related to PDGFR, such as KIT, ABL, VEGFR, SRC, FGFR, and FLT) but also act on PDGFR. PDGFR function inhibitors also include those that act on multiple tyrosine kinases including PDGFR (e.g., the above-mentioned tyrosine kinases related to PDGFR).

[0046] Examples of PDGFR function inhibitors include low molecular weight compounds (eg, molecular weight of 1000 or less, 800 or less, 700 or less, or 600 or less; for example, molecular weight of 100 or more, 150 or more, or 200 or more).

[0047] Various low molecular weight compounds having PDGFR function inhibitory activity are commercially available, and many have been reported in various literatures. Examples of such low molecular weight tyrosine kinase inhibitors include ripretinib, ponatinib, erdafitinib, dovitinib, lenvatinib, foretinib, ENMD-2076, PP121, cediranib, etc. Among these, ripretinib is particularly preferred.

[0048] Other PDGFR function inhibitors include, for example, PDGFR antibodies. The PDGFR antibodies are preferably antibodies that have binding affinity to the PDGF-binding domain of PDGFR. The binding site can be determined based on publicly known information and / or predicted based on publicly known information (e.g., by constructing a docking model).

[0049] The antibodies include polyclonal antibodies, monoclonal antibodies, chimeric antibodies, single-chain antibodies, and portions of the above antibodies that have antigen-binding activity, such as Fab fragments and fragments produced by an Fab expression library. The antibodies of the present invention also include antibodies that have antigen-binding activity to polypeptides consisting of at least 8 consecutive amino acids, preferably 15 amino acids, and more preferably 20 amino acids, from the amino acid sequence of PDGFR. These antibodies are commercially available, and known anti-PDGFR antibodies include ab67017 manufactured by Abcam, STJ117738 manufactured by St Johns Laboratory, and LS-C766558-60 manufactured by LifeSpan Biosciences.

[0050] In addition to the above, the PDGFR function inhibitor can also be any molecule (e.g., peptide, protein, artificial antibody, aptamer, etc.) that has binding ability (preferably specific binding ability) to PDGFR. When a protein or peptide such as an antibody is used as the PDGFR function inhibitor, its expression cassette can also be used instead.

[0051] (1-2-2) PDGFR Expression Inhibitor The PDGFR expression inhibitor is not particularly limited as long as it can suppress the expression level of PDGFR protein and / or PDGFR mRNA expressed in an organism or its cells (particularly cancer-associated fibroblasts) to which the agent of the present invention is applied. The PDGFR expression inhibitor may be used alone or in combination of two or more.

[0052] Examples of PDGFR expression inhibitors include PDGFR-specific small interfering RNA (siRNA), PDGFR-specific microRNA (miRNA), PDGFR-specific antisense nucleic acids, and expression cassettes thereof; PDGFR-specific ribozymes; and PDGFR gene editing agents using the CRISPR / Cas system.

[0053] In addition, suppression of expression means suppressing the expression level of PDGFR protein, PDGFR mRNA, etc. to, for example, 1 / 2, 1 / 3, 1 / 5, 1 / 10, 1 / 20, 1 / 30, 1 / 50, 1 / 100, 1 / 200, 1 / 300, 1 / 500, 1 / 1000, or 1 / 10,000 or less, and also includes reducing these expression levels to zero.

[0054] (1-2-2-1) siRNA, miRNA, and antisense nucleic acid PDGFR-specific siRNA is not particularly limited as long as it is a double-stranded RNA molecule that specifically suppresses the expression of a gene encoding PDGFR. In one embodiment, the siRNA is preferably, for example, 18 or more bases, 19 or more bases, 20 or more bases, or 21 or more bases in length. Furthermore, the siRNA is preferably, for example, 25 or less bases, 24 or less bases, 23 or less bases, or 22 or less bases in length. It is contemplated that the upper and lower limits of the siRNA length described herein may be arbitrarily combined.

[0055] The structure of the siRNA is not particularly limited. The siRNA may be a small hairpin RNA (shRNA). The siRNA may have additional bases at the 5' or 3' end. The siRNA may have a protruding sequence (overhang) at the 3' end, specifically, for example, dTdT (dT represents deoxythymidine) added thereto.

[0056] siRNA and / or shRNA sequences can be searched for using search software provided free of charge on various websites, including, for example, the siRNA Target Finder provided by Ambion (http: / / www.ambion.com / jp / techlib / misc / siRNA_finder.html), the insert design tool for pSilencer® Expression Vector (http: / / www.ambion.com / jp / techlib / misc / psilencer_converter.html), and GeneSeer provided by RNAi Codex (http: / / codex.cshl.edu / scripts / newsearchhairpin.cgi).

[0057] The PDGFR-specific miRNA may be any miRNA as long as it inhibits the translation of the gene encoding PDGFR. For example, instead of cleaving the target mRNA like siRNA, the miRNA may inhibit its translation by pairing with the target's 3' untranslated region (UTR). The miRNA may be any of pri-miRNA (primary miRNA), pre-miRNA (precursor miRNA), and mature miRNA. The length of the miRNA is not particularly limited; the length of the pri-miRNA is typically several hundred to several thousand bases, the length of the pre-miRNA is typically 50 to 80 bases, and the length of the mature miRNA is typically 18 to 30 bases. In one embodiment, the PDGFR-specific miRNA is preferably pre-miRNA or mature miRNA, and more preferably mature miRNA. Such PDGFR-specific miRNA may be synthesized by known techniques or purchased from a company that provides synthetic RNAs.

[0058] A PDGFR-specific antisense nucleic acid is a nucleic acid containing a base sequence complementary or substantially complementary to the base sequence of the mRNA of a gene encoding PDGFR, or a portion thereof, and functions to inhibit PDGFR protein synthesis by binding to the mRNA to form a specific and stable duplex. Antisense nucleic acids may be DNA, RNA, or DNA / RNA chimeras. When the antisense nucleic acid is DNA, the RNA:DNA hybrid formed by the target RNA and the antisense DNA is recognized by endogenous ribonuclease H (RNase H) to cause selective degradation of the target RNA. Therefore, in the case of antisense DNA directed to degradation by RNase H, the target sequence may be not only a sequence in the mRNA but also a sequence in an intron region in the initial translation product of the PDGFR gene. Intron sequences can be determined by comparing the genomic sequence with the cDNA base sequence of the PDGFR gene using homology search programs such as BLAST and FASTA. The length of the target region of a PDGFR-specific antisense nucleic acid is not limited, as long as hybridization of the antisense nucleic acid results in inhibition of translation into PDGFR protein. The PDGFR-specific antisense nucleic acid may be the entire sequence or a partial sequence of the mRNA encoding PDGFR. Considering ease of synthesis, antigenicity, intracellular internalization, and other issues, oligonucleotides consisting of about 10 to about 40 bases, particularly about 15 to about 30 bases, are preferred, but are not limited to these. More specifically, preferred target regions of the PDGFR gene include, but are not limited to, the 5'-end hairpin loop, 5'-end untranslated region, translation initiation codon, protein-coding region, ORF translation termination codon, 3'-end untranslated region, 3'-end palindrome region, and 3'-end hairpin loop.

[0059] PDGFR-specific siRNA, PDGFR-specific miRNA, and PDGFR-specific antisense nucleic acids can be prepared by determining the target sequence of mRNA or an initial transcription product based on the cDNA sequence or genomic DNA sequence of the PDGFR gene and synthesizing a sequence complementary to the mRNA using a commercially available automated DNA / RNA synthesizer. Antisense nucleic acids containing various modifications can also be chemically synthesized by known techniques.

[0060] The expression cassette for PDGFR-specific siRNA, PDGFR-specific miRNA, or PDGFR-specific antisense nucleic acid is not particularly limited, so long as it is a polynucleotide into which PDGFR-specific siRNA, PDGFR-specific miRNA, or PDGFR-specific antisense nucleic acid has been incorporated in an expressible state. Typically, the expression cassette comprises a polynucleotide comprising a promoter sequence and a coding sequence for the PDGFR-specific siRNA, PDGFR-specific miRNA, or PDGFR-specific antisense nucleic acid (and optionally a transcription termination signal sequence), and optionally other sequences.

[0061] As used herein, the terms "nucleic acid" and "polynucleotide" are not particularly limited and encompass both natural and artificial nucleic acids. Specifically, in addition to DNA, RNA, and the like, known chemical modifications may be used, as exemplified below. To prevent degradation by hydrolases such as nucleases, the phosphate residue of each nucleotide may be substituted with a chemically modified phosphate residue, such as phosphorothioate (PS), methylphosphonate, or phosphorodithioate. Furthermore, the hydroxyl group at the 2-position of the sugar (ribose) of each ribonucleotide may be substituted with -OR (where R represents, for example, CH3(2'-O-Me), CH2CHOCH3(2'-O-MOE), CH2CH2NHC(NH)NH2, CH2CONHCH3, or CH2CH2CN). Furthermore, the base moiety (pyrimidine or purine) may be chemically modified, for example, by introducing a methyl group or a cationic functional group into the 5-position of the pyrimidine base, or by substituting a thiocarbonyl group for the carbonyl group at the 2-position. Further examples include, but are not limited to, those in which the phosphate moiety or hydroxyl moiety is modified with, for example, biotin, an amino group, a lower alkylamine group, an acetyl group, etc. Also usable are BNA (LNA), in which the conformation of the sugar moiety of the nucleotide is fixed to N-type by bridging the 2' oxygen and 4' carbon of the sugar moiety.

[0062] (1-2-2-2) Gene Editing Agent The PDGFR gene editing agent is not particularly limited as long as it is capable of suppressing expression of the PDGFR gene using a target sequence-specific nuclease system (e.g., a CRISPR / Cas system). PDGFR gene expression can be suppressed, for example, by disrupting the PDGFR gene or by modifying the PDGFR gene promoter to suppress promoter activity.

[0063] For example, when the CRISPR / Cas system is employed, a vector (PDGFR gene editing vector) containing a guide RNA expression cassette targeting the PDGFR gene or its promoter and a Cas protein expression cassette can be typically used as a PDGFR gene editing agent, but is not limited to this. In addition to this typical example, a combination of a vector containing a guide RNA and / or its expression cassette targeting the PDGFR gene or its promoter, and a vector containing a Cas protein and / or its expression cassette can also be used as a PDGFR gene editing agent.

[0064] The guide RNA is not particularly limited as long as it is used in the CRISPR / Cas system. For example, various guide RNAs can be used that can bind to a target site in genomic DNA (e.g., the PDGFR gene, its promoter, etc.) and bind to a Cas protein, thereby guiding the Cas protein to the target site in genomic DNA.

[0065] As used herein, the term "target site" refers to a site on genomic DNA that consists of a DNA strand (target strand) and its complementary DNA strand (non-target strand), which consists of a PAM (Proto-spacer Adjacent Motif) sequence and a sequence adjacent to the 5' side of the PAM sequence that is approximately 17 to 30 bases long (preferably 18 to 25 bases long, more preferably 19 to 22 bases long, and particularly preferably 20 bases long).

[0066] The guide RNA has a sequence involved in binding to a target site in genomic DNA (sometimes referred to as a crRNA (CRISPR RNA) sequence), and this crRNA sequence binds complementary (preferably complementary and specific) to a sequence excluding the PAM sequence complementary sequence of the non-target strand, thereby enabling the guide RNA to bind to the target site in genomic DNA. Furthermore, the guide RNA has a sequence involved in binding to a Cas protein (sometimes referred to as a tracrRNA (trans-activating crRNA) sequence), and this tracrRNA sequence binds to the Cas protein, thereby guiding the Cas protein to the target site in genomic DNA.

[0067] The tracrRNA sequence is not particularly limited. The tracrRNA sequence is typically an RNA sequence of approximately 50 to 100 bases long that can form multiple (usually three) stem-loops, and the sequence varies depending on the type of Cas protein used. Various known sequences can be used as the tracrRNA sequence depending on the type of Cas protein used.

[0068] The guide RNA typically contains the above-mentioned crRNA sequence and tracrRNA sequence. The guide RNA may be a single-stranded RNA (sgRNA) containing the crRNA sequence and the tracrRNA sequence, or an RNA complex formed by complementary binding of an RNA containing the crRNA sequence and an RNA containing the tracrRNA sequence.

[0069] The Cas protein is not particularly limited as long as it is used in the CRISPR / Cas system, and various proteins can be used, for example, proteins that can bind to a target site in genomic DNA in a complex with a guide RNA and cleave the target site. Cas proteins derived from various organisms are known, including the Cas9 protein, and more preferably the Cas9 protein endogenously contained in bacteria belonging to the genus Streptococcus. Information on the amino acid sequences of various Cas proteins and their coding sequences can be easily obtained from various databases such as NCBI.

[0070] PDGFR gene editing agents can be easily prepared using known genetic engineering techniques, such as PCR, restriction enzyme digestion, DNA ligation, in vitro transcription / translation, and recombinant protein production techniques.

[0071] (2) Uses As will be shown in the Examples below, the PDGFR expression inhibitor has an inhibitory effect on cancer-associated fibroblasts (inhibitory effect on proliferation and activation), and therefore, the PDGFR expression inhibitor can be used as an active ingredient in an inhibitor of cancer-associated fibroblasts.

[0072] The target cancer tissue containing cancer-associated fibroblasts is not particularly limited, and examples include ovarian cancer, breast cancer, uterine cancer, colon cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, melanoma, leukemia, lung cancer, skin cancer, etc. Among these, particularly preferred are ovarian cancer, breast cancer, colon cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, kidney cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, and melanoma, particularly more preferred are ovarian cancer, breast cancer, and colon cancer, particularly still more preferred are ovarian cancer and breast cancer, and particularly preferred is ovarian cancer.

[0073] Ovarian cancer is not particularly limited, and examples include superficial, epithelial, and stromal malignant tumors (e.g., serous (cystic) adenocarcinoma, mucinous (cystic) adenocarcinoma, endometrioid adenocarcinoma, clear cell adenocarcinoma, adenocarcinoma-fibroma (each of the above types), adenosarcoma, mesodermal mixed tumor, [Müllerian mixed tumor] [carcinosarcoma], malignant Brenner tumor, transitional cell carcinoma, undifferentiated carcinoma, etc.), sex cord-stromal tumors (e.g., fibrosarcoma, Sertoli-stromal cell tumor (poorly differentiated), etc.), germ cell tumors (e.g., dysgerminoma, yolk sac tumor [endodermal sinus tumor], embryonal carcinoma [embryonic carcinoma], polyembryoma, choriocarcinoma, mature cystic teratoma with malignant transformation, immature teratoma (G3), etc.), carcinoma, sarcoma, malignant lymphoma (primary), secondary [metastatic] tumors, etc. Among these, adenocarcinoma is particularly preferred, and clear cell carcinoma is particularly preferred.

[0074] The type of cancer to be targeted is preferably chemotherapy-resistant cancer. Although the definition of chemotherapy-resistant cancer varies depending on the type of cancer, in one embodiment, chemotherapy-resistant cancer can be defined as a cancer in which first-line anticancer drug treatment (e.g., platinum drugs in the case of ovarian cancer) shows no therapeutic effect (cancer shrinkage is not observed), or a therapeutic effect (cancer shrinkage) is temporarily observed but then the cancer grows again soon after. In addition, the proportion of HIF-1α-positive cells among cancer cells in cancer tissue can be used as an indicator, and a cancer can be determined to be chemotherapy-resistant if the proportion is 10% or more.

[0075] From the viewpoint of the suppressive effect on cancer chemotherapy resistance, myofibroblastic cancer-associated fibroblasts are particularly preferred as cancer-associated fibroblasts. Cancer-associated fibroblasts can be characterized by the expression or high expression of αSMA and / or collagen I. Furthermore, the above-mentioned myofibroblastic cancer-associated fibroblasts are characterized by the expression or high expression of FAP, TPM1, THBS2 (particularly FAP-α), etc. In one embodiment, the target cancer can be a cancer containing cancer-associated fibroblasts / myofibroblastic cancer-associated fibroblasts characterized by the expression of the above-mentioned markers.

[0076] Since chemotherapy resistance is caused by cancer-associated fibroblasts, the anticancer effect of anticancer drugs against chemotherapy-resistant cancers can be enhanced by suppressing cancer-associated fibroblasts with PDGFR expression inhibitors. From this perspective, PDGFR expression inhibitors can be used as active ingredients in agents that enhance the anticancer effect of anticancer drugs. Furthermore, since chemotherapy resistance is acquired by cancer-associated fibroblasts, suppressing cancer-associated fibroblasts with PDGFR expression inhibitors can also suppress the acquisition of chemotherapy resistance in cancer. For these reasons, PDGFR expression inhibitors are suitable for administration in combination with anticancer drugs.

[0077] The active ingredient of the present invention can be used, for example, as a medicine, a reagent, a food composition, an oral composition, a health enhancer, a nutritional supplement (supplement, etc.), and further, together with an anticancer agent, as a composition for improving cancer (for example, a medicine, a reagent, a food composition, an oral composition, a health enhancer, a nutritional supplement (supplement, etc.)). The active ingredient of the present invention can be applied (for example, administered, ingested, inoculated, treated, etc.) to animals, humans, and various cells, either as is or in the form of various compositions together with conventional ingredients.

[0078] The target of application is not particularly limited, and examples of mammals include humans, monkeys, mice, rats, dogs, cats, rabbits, pigs, horses, cattle, sheep, goats, and deer.

[0079] When the active ingredient of the present invention is administered in combination with an anticancer drug, the combination includes not only simultaneous administration but also administration with an interval between them (for example, an interval between several minutes to several days (e.g., 1 minute to 10 days)).

[0080] When the active ingredient of the present invention is used as a preventive or therapeutic agent for cancer, the preventive or therapeutic agent can be one intended for use in combination with, for example, an anticancer agent. In this case, the preventive or therapeutic agent may contain the anticancer agent. Furthermore, in this case, the active ingredient of the present invention and the anticancer agent may be contained in the same container, or the active ingredient of the present invention and the anticancer agent may be contained in separate containers.

[0081] Examples of anticancer agents include platinum preparations, metabolic antagonists, alkylating agents, microtubule inhibitors, antibiotic anticancer agents, topoisomerase inhibitors, molecular targeted drugs, hormone agents, and biological agents, with platinum preparations being particularly preferred.

[0082] Examples of platinum preparations include cisplatin, carboplatin, nedaplatin, oxaliplatin, satraplatin, miriplatin, lobaplatin, spiroplatin, tetraplatin, ormaplatin, and iproplatin.

[0083] Examples of antimetabolites include enocitabine, carmofur, capecitabine, tegafur, tegafur-uracil, tegafur-gimeracil-oteracil potassium, gemcitabine, cytarabine, cytarabine ocfosfate, nelarabine, fluorouracil, fludarabine, pemetrexed, pentostatin, methotrexate, cladribine, doxifluridine, hydroxycarbamide, and mercaptopurine.

[0084] Examples of alkylating agents include cyclophosphamide, ifosfamide, nitrosourea, dacarbazine, temozolomide, nimustine, busulfan, melphalan, procarbazine, and ranimustine.

[0085] Examples of microtubule inhibitors include alkaloid anticancer drugs such as vincristine, and taxane anticancer drugs such as docetaxel and paclitaxel.

[0086] Examples of antibiotic anticancer agents include mitomycin C, doxorubicin, epirubicin, daunorubicin, bleomycin, actinomycin D, aclarubicin, idarubicin, pirarubicin, peplomycin, mitoxantrone, amrubicin, and zinostatin stimalamer.

[0087] Examples of topoisomerase inhibitors include CPT-11, irinotecan, and nogitecan, which have a topoisomerase I inhibitory effect, and etoposide and sobuzoxane, which have a topoisomerase II inhibitory effect.

[0088] Examples of hormone agents include dexamethasone, finasteride, tamoxifen, astrozole, exemestane, ethinylestradiol, chlormadinone, goserelin, bicalutamide, flutamide, prednisolone, leuprorelin, letrozole, estramustine, toremifene, fosfestrol, mitotane, methyltestosterone, medroxyprogesterone, and mepitiostane.

[0089] Examples of biological agents include interferon α, β and γ, interleukin 2, ubenimex, and dried BCG.

[0090] The agent of the present invention may further contain other components as necessary.Other components are not particularly limited as long as they can be incorporated into, for example, medicine, food composition, oral composition, health promotion agent, nutritional supplement (supplement etc.), etc., but include, for example, base, carrier, solvent, dispersant, emulsifier, buffer, stabilizer, excipient, binder, disintegrant, lubricant, thickener, moisturizer, colorant, flavoring, chelating agent etc. Pharmaceutically acceptable carriers and additives include, but are not limited to, excipients such as sucrose, starch etc.; binders such as cellulose, methylcellulose etc.; disintegrants such as starch, carboxymethylcellulose etc.; lubricants such as magnesium stearate, aerosil etc.; fragrances such as citric acid, menthol etc.; preservatives such as sodium benzoate, sodium bisulfite etc.; stabilizers such as citric acid, sodium citrate etc.; suspending agents such as methylcellulose, polyvinylpyrrolide etc.; dispersing agents such as surfactants; diluents such as water, physiological saline etc.; base wax etc. The form of the agent of the present invention is not particularly limited, and may take a form that is commonly used for each application depending on the application.

[0091] In terms of form, when the use is a pharmaceutical, any dosage form can be used, for example, oral preparation forms such as tablets (including orally disintegrating tablets, chewable tablets, effervescent tablets, troches, jelly drops, etc.), pills, granules, fine granules, powders, hard capsules, soft capsules, dry syrups, liquids (including drinks, suspensions, syrups), and jellies; and parenteral preparation forms such as injectable preparations (for example, drip injections (for example, intravenous drip preparations), intravenous injections, intramuscular injections, subcutaneous injections, and intradermal injections), topical preparations (for example, ointments, poultices, and lotions), suppositories, inhalants, eye preparations, eye ointments, nasal drops, ear drops, and liposomes.

[0092] The route of administration of the agent of the present invention is not particularly limited as long as the desired effect can be obtained, and examples thereof include enteral administration such as oral administration, tube feeding, and enema administration; and parenteral administration such as intravenous administration, intraarterial administration, intramuscular administration, intracardiac administration, subcutaneous administration, intradermal administration, and intraperitoneal administration.

[0093] In terms of form, when the application is a health promoting agent, a nutritional supplement (such as a supplement), etc., examples include formulation forms suitable for oral ingestion (oral formulation forms), such as tablets (including orally disintegrating tablets, chewable tablets, effervescent tablets, lozenges, jelly drops, etc.), pills, granules, fine granules, powders, hard capsules, soft capsules, dry syrups, liquids (including drinks, suspensions, and syrups), and jellies.

[0094] When the application is a food composition, the form may be liquid, gel or solid food, such as juice, soft drinks, tea, soup, soy milk, salad oil, dressing, yogurt, jelly, pudding, furikake, infant formula, cake mix, powdered or liquid dairy products, bread, cookies, etc.

[0095] The content of the active ingredient of the present invention in the agent of the present invention depends on the type of active ingredient, the purpose, the mode of use, the subject to which it is applied, the condition of the subject to which it is applied, etc., and is not limited thereto, but can be, for example, 0.0001 to 100% by weight, preferably 0.001 to 50% by weight.

[0096] The dosage of the agent of the present invention (e.g., administered, ingested, inoculated, etc.) is not particularly limited as long as it is an effective amount that produces the desired effect, and is generally 0.01 to 1000 mg / kg body weight per day in terms of the weight of the active ingredient. The dosage can be administered once a day or multiple times (2 to 3 times a day), and can be increased or decreased as appropriate depending on the age, pathological condition, and symptoms.

[0097] The present invention will be described in detail below based on examples, but the present invention is not limited to these examples.

[0098] 1. Test Method 1-1. Nuclei Isolation Frozen ovarian clear cell carcinoma (OCCC) samples were homogenized in 500 μl of ice-cold Nuclei EZ Lysis buffer (NUC-101, Sigma-Aldrich) using a KIMBLE Dounce tissue grinder (D8938, Sigma-Aldrich). 1 ml of lysis buffer was added and incubated on ice for 5 minutes. The homogenate was filtered through a 70-μm cell strainer (#352350, Corning) and centrifuged at 500 × g for 1 minute at 4°C. The pellet was resuspended, washed with 1 ml of lysis buffer, and incubated on ice for 5 minutes. After another cycle of washing with lysis buffer, the pellet was washed twice with 1 ml of Nuclei Suspension Buffer (1 × PBS, 1% BSA, 0.2% RNase inhibitor (2313A, Clontech / TaKaRa)). The nuclear pellet was resuspended in 1 ml of Nuclei Suspension Buffer and filtered twice through a 35-μm cell strainer (#352235, Corning).

[0099] 1-2. Single-Nucleus RNA-Seq (snRNA-Seq) For snRNA-Seq of OCCC tissues, cDNA libraries were prepared from nuclei (4,000–8,000 nuclei) isolated on a Chromium controller (10X Genomics) using the Single Cell 3′ Reagent Kit v3 (PN-1000075, 10X Genomics). Next-generation sequencing of the cDNA libraries was performed on a HiSeq 2500 (Illumina) platform with a median of 65,124 reads per cell. Fastq files of the sequencing data were processed using the cellranger pipeline (version 3.0.2, 10X Genomics) and mapped to the GRCh38 (version 3.0.0 for premRNA) reference genome to generate a matrix of unique molecular identifiers (UMIs) and cell-associated barcodes.

[0100] 1-3. Spatial Transcriptomics. Frozen OCCC samples were embedded in pre-chilled OCT compound (#25608-930, Sakura Finetech Japan Co., Ltd.), refrozen on dry ice, and stored at -80°C. cDNA libraries were prepared from tissue sections using the Visium Spatial Gene Expression kit (10X Genomics) according to the manufacturer's instructions. Optimal parameters for permeabilization of OCCC tissue were determined using the Visium Spatial Tissue Optimization Kit (PN-1000193; 10X Genomics). Subsequently, 10 mm sections cut from the OCT-embedded samples were stained with H&E and permeabilized for 20 minutes. Afterwards, cDNA libraries were prepared from the barcoded Visium spots. Next-generation sequencing was performed on a HiSeq 2500 (Illumina) platform. Fastq files of sequencing data were processed with the spaceranger pipeline (version 1.1.0., 10X Genomics) and mapped to the GRCh38 reference genome to generate a matrix of UMIs and spot-associated barcodes.

[0101] 1-4. Targeted Genomic Sequencing. Genomic DNA was extracted from frozen OCCC tissue using the DNeasy Blood & Tissue kit (#69504, Qiagen) before target sequence selection using SureSelect NCC Oncopanel (v.4.0; Agilent Technologies). Libraries were then constructed using the SureSelectXT Reagent Kit (Agilent Technologies). Paired-end sequencing (2 × 150 bp) was performed using a NextSeq 500 (Illumina). Mutations (single-nucleotide mutations, short insertions, and deletions), gene amplifications, and gene fusions were detected using the cisCall system.

[0102] 1-5. Bulk RNA-seq Analysis. Total RNA extraction and library preparation were performed as previously described. Briefly, total RNA was extracted from 30 frozen OCCC samples using TRIzol (#15596026, Invitrogen), and cDNA libraries were prepared using the TruSeq Stranded mRNA Library Prep Kit (RS-20020595, Illumina) according to the manufacturer's instructions. The cDNA libraries were then sequenced on an Illumina HiSeq 2500 platform with a 2 × 100-bp paired-end read module. Sequencing reads were mapped to the human genome reference sequence (UCSU hg19) using Basespace (Illumina).

[0103] 1-6. Establishment of tumor-derived spheroids and cancer-associated fibroblasts (CAFs) OCCC tissue obtained by surgical resection was immediately washed with PBS and cut into ~10 mm 3The cells were cut into 100-μm fragments and dissociated with collagenase / hyaluronidase (#7912, Stem Cell Technologies) for 2 hours at 37°C. Dissociated cells were filtered sequentially through 100-μm and 70-μm cell strainers (352350, BD Falcon) and isolated by density gradient centrifugation using PBS containing Histodenz (D2158, Sigma). After lysing red blood cells with ACK Lysing Buffer (A1049201, Thermo Fisher Scientific), the isolated cells were cultured in ultra-low attachment culture dishes (#3471 or #3262, Corning) to establish cancer spheroids. They were cultured in STEMPRO hESC SFM (A1000701, Thermo Fisher Scientific) supplemented with 8 ng / ml basic fibroblast growth factor (#AA10-155, Thermo Fisher Scientific) and penicillin / streptomycin at 37°C, 5% CO2. Serial passage of the formed cancer spheroids was performed every 2 weeks by dissociating them with Accumax (AM105, Innovative Cell Technologies). To establish CAF cultures, red blood cell-free Histodenz-purified cells were cultured on attachment culture dishes (#35003, Corning) in MEM-α (#12561-05, Thermo Fisher Scientific) containing 10% FBS (#10270106, Thermo Fisher Scientific) and penicillin / streptomycin at 37°C and 5% CO2. For serial passage of established CAFs, adherent cells were dissociated every two weeks using TripLE Express Enzyme (#12604013, Thermo Fisher Scientific). CAFs were also established from breast cancer tissues and colon cancer tissues, respectively, as described above. Breast cancer tissue-derived CAFs and colon cancer tissue-derived CAFs were used only in the experiments shown in Figure 4.

[0104] 1-7. Plasmid Construction To prepare the pCDH-Luc2-T2A-copGFP plasmid, a synthetic T2A sequence was ligated into Luc2 (PCR-amplified from pGL4.51[Luc2 / CMV / Neo] (Promega, E1320)) and copGFP (PCR-amplified from pCDH-CMV-MCS-EF1α-copGFP (System biosciences, CD511B-1)) to generate the Luc2-T2A-copGFP cassette. The Luc2-T2A-TagBFP sequence in pCDH-Luc2-T2A-TagBFP was then replaced with the Luc2-T2A-copGFP cassette via the EcoRI and SalI sites to generate pCDH-Luc2-T2A-copGFP. To generate the pCDH-hRluc-T2A-mCherry plasmid, the hRluc-T2A-mCherry cassette was first generated by ligating the synthesized T2A sequence with hRluc (PCR-amplified from pGL4.74[hRluc / TK] (Promega, E6921)) and mCherry (PCR-amplified from pcDNA5-MTS-TagBFP-P2AT2A-EGFP-NLS-P2AT2A-mCherry-PTS1 (Addgene, #87829)). pCDH-hRluc-T2A-mCherry was then generated from pCDH-Luc2-T2A-TagBFP using a similar construction strategy. The pCDH-Luc2-T2A-copGFP and pCDH-hRluc-T2A-mCherry plasmids were used to generate lentiviruses for gene transfer into cancer cells and CAFs, respectively.

[0105] 1-8. In vitro co-culture assay. OCCC spheroid cells and CAFs were infected with a lentivirus expressing Luc2 and GFP (pCDH-Luc2-T2A-copGFP) and a lentivirus expressing hRLuc and mCherry (pCDH-hRLuc-T2A-mCherry), respectively. For co-culture, the infected spheroid cells and CAFs were mixed at a 1:1 ratio. Subsequently, monocultured cancer cells, monocultured CAFs, or co-cultured cells were placed in a 96-well plate (1 x 10 cells) overlaid with growth factor-reduced (GFR) Matrigel (#356231, Corning). 4 Cells were plated at 1000 x 1000 cells / well and incubated in MEM-α supplemented with 10% FBS for 6 hours. After removing floating dead cells, the remaining cells were overlaid with GFR Matrigel and then cultured in E medium (DMEM / F12-GlutaMAX (#10565-042, Thermo Fisher Scientific)) supplemented with penicillin-streptomycin, 10 mM HEPES (#15630106, Thermo Fisher Scientific), N-2 supplement (#17502-001, Thermo Fisher Scientific), B-27 supplement (#17504-001, Thermo Fisher Scientific), 1 mM N-acetylcysteine ​​(A7250, Sigma-Aldrich), and 50 ng / ml human EGF (PHG0313, Thermo Fisher Scientific). For chemosensitivity assays, monocultured or cocultured cells were treated with carboplatin (S1215, Selleck Chemicals). Cell proliferation was assessed using a dual luciferase reporter kit (E1960, Promega). For Western blot analysis, cultured cells were harvested with Cell Recovery Solution (#354253, Corning) and GFP-expressing cancer cells and mCherry-expressing CAFs were selected by flow cytometry (FACS Aria III, Beckton Dickinson, Franklin Lakes, NJ).

[0106] 1-9. Single-Cell RNA-Seq (scRNA-Seq) of In Vitro-Cultured Cells. Single-cell cDNA libraries were prepared from monocultures and cocultures (after 3 days of culture) of cancer cells and CAFs. For this purpose, 3,000–6,000 cells were applied to a Chromium controller (10X Genomics). Library construction was performed using the Single Cell 3′ Reagent Kit v3 and 3′ CellPlex Kit Set A (10X Genomics) according to the manufacturer's instructions. Next-generation sequencing of the cDNA libraries was performed using a HiSeq 2500 (Illumina). Fastq files of the sequencing data were processed with the cellranger pipeline (version 6.1.2, 10X Genomics) using the "cellranger multi" command and mapped to the GRCh38 reference genome to generate a matrix of UMIs and cell-associated barcodes.

[0107] 1-10. In vitro proliferation assay of CAFs. To examine the chemosensitivity of CAFs, in vitro-cultured CAFs on days 7–10 after passage were enzymatically dissociated and used in a chemosensitivity assay. The following tyrosine kinase inhibitors (TKIs) were purchased from Selleck Chemicals and used in the assay: carboplatin (S1215), lenvatinib (S1164), cediranib (S1017), ripretinib (S8757), erdafitinib (S8401), dovitinib (S1018), PP121 (S2622), ENMD-2076 (S1181), foretinib (S1111), and ponatinib (S1490). The effect of PDGF signaling on CAFs was examined using human recombinant PDGFB (160-24033, Fujifilm Wako). The effect of TKI or PDGFB on cell proliferation was quantified by measuring luciferase activity using the CellTiter-Glo Luminescent Cell Viability Assay (G7571, Promega) according to the manufacturer's instructions.

[0108] 1-11. CRISPR / Cas9-Mediated Gene Knockout. CAFs grown for 7–10 days after passage were enzymatically dissociated and Cas9-mediated gene knockout was performed using the Neon Transfection System (Thermo Fisher Scientific) according to the manufacturer's instructions. The sgRNA / Cas9 complex formed after mixing Cas9 protein (Invitrogen) with Edit-R Human Synthetic sgRNA pool for PDGFRB (SQ-003163-01-0002, Dharmacon-Horizon Discovery) or Edit-R Synthetic sgRNA Non-targeting Control #1 (U-009501-01-001p, Dharmacon-Horizon Discovery) was used for electroporation (1600 V, 10 ms, 2 pulses).

[0109] 1-12. Animal Experiments To investigate the synergistic effect of carboplatin and ripretinib on xenograft tumors, Luc2-GFP-labeled cancer spheroid cells and HRluc-mCherry-labeled CAFs were dissociated and mixed at a 1:1 ratio. Then, 1 × 10 5 The mixed cells were suspended in 100 μl of E medium containing 50% GFR Matrigel and injected subcutaneously into the flank of NOG (NOD / Shi-scid IL-2Rγnull) mice (CLEA Japan). 49 days after implantation (tumor volume: ∼100 mm 3Mice were randomly assigned to four groups and treated with or without carboplatin (40 mg / kg / week, intraperitoneal injection) and / or ripretinib (50 mg / kg / day, oral administration) for 28 days. Tumor volume was calculated weekly using the standard formula (length × width × height × π / 6). Tumor volume was assessed by luciferase activity using an IVIS Spectrum imaging system (Caliper Life Sciences). This system measured the total light emitted (photons / second / cm² / sr) from the abdominal area of ​​each mouse 10 minutes after intraperitoneal injection of 15 mg / ml D-luciferin potassium salt (10 ml per gram of body weight, Wako). Data were analyzed using Living Image software (v. 4.2; Caliper Life Sciences).

[0110] 1-13. Western blot analysis Western blot analysis was performed as previously reported. Antibodies specific for the following markers were purchased from the indicated suppliers: PAX8 (10336-1-AP, Proteintech; dilution 1:2000), cytokeratin 7 (M7018, Dako; 1:1000), α-SMA (ab7817, abcam; 1:3000), collagen I (ab138492, abcam; 1:1000), β-actin (A5316, Sigma-Aldrich; 1:1000), HIF-1α (ab51608, abcam; 1:1000), HIF-2α (ab199, abcam; 1:1000), PDGFB (ab23914, abcam; 1:1000), fibronectin (ab268020, abcam; 1:1000), and PDGFRB (#3169, Cell Signaling Technology; 1:1000), PDGFRB (phospho Y1021; ab16868, abcam; 1:1000), FAP-α (ab53066, abcam; 1:1000).

[0111] 1-14. Immunofluorescence Analysis of Clinical Specimens. For immunostaining of OCCC clinical specimens, surgical specimens were fixed in 10% formaldehyde, embedded in paraffin, and sliced ​​into 4-mm sections. For histological examination, sections were stained with H&E. For immunofluorescence analysis, sections were subjected to antigen retrieval in 10 mM citrate buffer (pH 6.0), followed by blocking of endogenous peroxidase activity with 0.3% hydrogen peroxide. For co-staining with PAX8, HIF-1α, and α-SMA, slides were stained with rabbit anti-PAX8 antibody (1:1000; Proteintech, 10336-1-AP), biotinylated goat anti-rabbit IgG (1:500; Vector Laboratories, BA-1000), Vectastain Elite ABC Detection Kit (Vector Laboratories, PK-6100), and Alexa Fluor 1000. TM Sequential staining was performed with 488 Tyramide reagent (Invitrogen, B40953). For sequential staining with anti-HIF-1α and anti-α-SMA antibodies, slides were boiled in 10 mM citrate buffer (pH 6.0) for at least 15 minutes to remove the PAX8-secondary antibody complex. Slides were then stained with rabbit anti-HIF-1α (1:100; Abcam, ab51608) and mouse anti-α-SMA (1:600; Abcam, ab7817), followed by donkey anti-rabbit IgG AlexaFluor 750-conjugated (1:1000; Abcam, ab175728) or goat anti-mouse IgG AlexaFluor 555-conjugated (1:1000; Invitrogen, A21424) secondary antibodies. Subsequently, slides were stained with ProLong IgG containing DAPI. TMImmunostained slides were mounted using Diamond Antifade Mountant (Invitrogen, P36971). Immunostaining with anti-KRT7, anti-α-SMA, and anti-PDGFRB (phospho Y1021) antibodies was performed using the same procedure. Antibodies specific for the following markers were purchased from the listed suppliers: cytokeratin 7 (M7018, Dako, 1:100), α-SMA (ab7817, Abcam, 1:600), and PDGFRB (phospho Y1021) (ab16868, Abcam, 1:100). Immunofluorescence images were evaluated using a Vectra Polaris (Akoya Biosciences).

[0112] 1-15. Immunofluorescence Analysis of In Vitro Cultured Cells. Cancer cells, either in monoculture or coculture with CAFs, were plated on GFR Matrigel-coated glass-bottom dishes (D11140H, Matsunami Glass Industry Co., Ltd.), fixed with cold methanol, and permeabilized with 0.1% Triton X (Sigma-Aldrich). After blocking with 5% BSA, fixed cells were incubated with rabbit anti-HIF-1α (1:100; Abcam, ab51608) and mouse anti-α-SMA (1:600; Abcam, ab7817) antibodies, followed by donkey anti-rabbit IgG AlexaFluor 750 conjugate (1:1000; Abcam, ab175728) or goat anti-mouse IgG AlexaFluor 555 conjugate (1:1000; Invitrogen, A21424). Then, ProLong TM Cells were mounted with Diamond Antifade Mountant with DAPI (Invitrogen, P36971). Fluorescent images were taken with a Keyence BZ-800 Microscope (Keyence).

[0113] Clinical tumor samples and mouse xenograft tumors were fixed in neutral formalin and embedded in paraffin. Immunohistochemical staining was performed as previously described. Briefly, sections were stained with H&E or with primary anti-FAPα (ab53066, Abcam, 1:100), anti-HIF-1α (ab51608, Abcam, 1:100), or anti-α-SMA (ab7817, Abcam, 1:500) antibodies, followed by biotinylated secondary antibodies (Vector Laboratories) and incubation with The Vector stain ABC kit (PK6100, Vector Laboratories) and 3,3'-diaminobenzidine (D12384, Sigma). To evaluate HIF-1α staining, positive cells were counted in four representative areas using Hybrid Cell Count software (Keyence).

[0114] 1-17. snRNA-seq Data Processing. The gene count matrix was analyzed using Seurat software v3.2.2 running on R v3.6.0. The following cells were removed from the dataset: cells with a mitochondrial gene count greater than 1%, cells with unique feature counts greater than 6,000, and cells with unique feature counts less than 400. The gene-barcode matrix of filtered cells was normalized using 'LogNormalize'. Next, the top 2,000 variable genes were identified using the 'vst' method in the Seurat FindVariableFeatures function. All cells from the 10 OCCC samples were integrated using the Seurat FindIntegrationAnchors and IntegrateData functions. After cell filtering and data integration, a total of 62,673 cells were scaled using the Seurat ScaleData function. The scaled data were then subjected to PCA analysis using the Seurat RunPCA function with npcs = 30. UMAP plots were created with the Seurat RunUMAP function, with dims = 1:30.

[0115] 1-18. Annotation of Cell Populations in OCCC To stratify cell populations using the integrated snRNA-seq data, low-resolution clustering was performed at a resolution of 0.2 using the FindClusters function. To annotate the five classified cell populations, specific marker genes were used to identify cell populations corresponding to epithelial and non-tumor cell populations. The annotation of these cell populations was confirmed by examining the expression of various marker genes.

[0116] 1-19. Copy number estimation from sequencing data. We analyzed large-scale chromosomal copy number alterations based on single-cell sequencing data using InferCNV (https: / / github.com / broadinstitute / inferCNV). InferCNV patterns at each chromosome were examined in epithelial cells, with non-tumor cells (CAFs and endothelial cells) as the reference.

[0117] 1-20. Enrichment Analysis. To perform ssGSEA of cancer subpopulations, signature scores of the HALLMARK gene set expressed in each cancer subpopulation were determined based on ssGSEA of single-nucleus RNA-seq data. ssGSEA was performed using escape (v1.8.0, http: / / www.bioconductor.org / packages / release / bioc / vignettes / escape / inst / doc / vignette.html) running on R v4.2.1. To perform GO enrichment analysis, differentially expressed genes (DEGs) were selected using the FindAllMarkers function in Seurat. Then, clusterProfiler (v4.2.2) used the DEGs from each subpopulation to identify the top 10 most significant GO terms in the biological process (BP) category.

[0118] 1-21. Quantification of transcription factor activity. The activity of key transcription factors in each cell line was inferred using VIPER (Virtual Inference of Protein-activity by Enriched Regulon analysis) v1.30.0 running on R v4.2.1. VIPER scores were calculated using transcription factor-target interactions classified as confidence level A (DoRothEA v1.6.0). VIPER scores were visualized using violin plots and heat maps. Transcription factor-target interactions in the Cancer#2 cluster were plotted using the igraph package in R.

[0119] 1-22. Prognostic Analysis: The top 20 DEGs selected using the FindAllMarkers function in Seurat were defined as signature genes for each cancer subpopulation. Bulk RNA-seq analysis was performed on surgical specimens from 30 advanced OCCC (stages II-IV), and patients were classified into two groups based on the average expression of the signature genes. Kaplan-Meier analysis was performed using the 'Survival' package in R to assess the prognostic value of cancer cell clusters. P values ​​for overall survival and progression-free survival were evaluated using a stratified log-rank test.

[0120] Ligand-receptor interaction analysis based on snRNA-seq data was performed using NicheNet. Ligands and receptors were selected from DEGs in each cell population using the FindAllMarkers function in Seurat. The ligands selected from the Cancer #2 subpopulation were used to identify their corresponding receptors from DEGs in non-tumor cells based on the NicheNet ligand-receptor network. The average expression of the ligands and receptors in each population was visualized in a heatmap using the Seurat AverageExpression function. The interaction potential between the selected ligand-receptor pairs was then estimated using the NicheNet weighted integration network.

[0121] 1-24. Spatial Transcriptomics Data Processing. The Visium spot-gene expression matrix and spatial information from the spatial transcriptomics data were imported into Seurat v3.2.0 for downstream analysis. UMI counts for each spot were normalized using Seurat's Sctransform function. Objects were subjected to PCA with npcs = 20 parameters using the Seurat RunPCA function, and UMAP plots were generated with dims = 1:20 using the Seurat RunUMAP function. Visium spot clustering was performed using the FindClusters function at a resolution of 20.

[0122] 1-25. Integration of snRNA-seq and spatial transcriptomics data. The snRNA-seq and Visium data were integrated using the anchor-based integration method in Seurat v3.2.0. Using the combined snRNA-seq dataset as the reference and one of the Visium datasets as the query, transfer anchors were detected using the Seurat FindTransferAnchors function. After integration, the cluster labels from the snRNA-seq dataset were transferred to the spatial dataset using the Seurat TransferData function, providing predicted scores for each snRNA-seq cluster.

[0123] 1-26. Processing of scRNA-seq Data. The gene count matrix was imported into Seurat software v3.2.2 running on R v3.6.0. Cells with mitochondrial gene counts greater than 10%, cells with feature counts greater than 6,000, and cells with feature counts less than 200 were filtered. The filtered gene-barcode matrix was normalized using Seurat's 'LogNormalize' function. The top 2,000 variable genes were then identified using the 'vst' method in Seurat's FindVariableFeatures function. Data from co-cultured and mono-cultured cells were merged using Seurat's merge function. After filtering and merging, a total of 8,208 cells were processed for the following analysis: the merged objects were scaled using the Seurat ScaleData function, and PCA was performed using the Seurat RunPCA function. UMAP plots were created using the Seurat RunUMAP function with dims = 1:30.

[0124] 1-27. Multiplex Immunofluorescence Image Analysis. The immunofluorescence intensity of tumor and non-tumor cells was measured using QuPath (version 0.2.1). After loading all images, they were segmented using StarDist, and the fluorescence intensity of each cell was measured. Cancer cells and CAFs were then identified based on the expression of PAX8 and α-SMA, respectively. The same threshold intensity for immunofluorescence signals was applied to all samples. The centroid distance between α-SMA(+) cells and PAX8(+) / HIF-1α(+) cells was estimated using the "Detect centroid distance 2D" command. After annotation of each cell, the data was exported to CytoMAP (version 1.4.21).

[0125] 2. Results 2-1. Identification of cancer cell subpopulations associated with OCCC chemotherapy resistance To identify the intratumor network responsible for OCCC chemotherapy resistance, we obtained frozen samples from surgical specimens and performed an integrated analysis combining single-cell analysis and spatial transcriptomics. We then expanded the analysis by multicolor quantitative immunostaining, in vitro coculture, and mouse xenograft experiments.

[0126] To obtain single-cell transcriptome data from frozen specimens, we performed dimensionality reduction on the snRNA-seq data using Uniform Manifold Approximation and Projection (UMAP). The clustering of single-nucleus data revealed that cells were primarily stratified by clinical case, likely due to batch effects. To eliminate batch effects and integrate individual datasets, we performed an anchoring procedure to allow for comparison of cell identity across samples.

[0127] After data set consolidation, we found that the major cell types (epithelial cancer cells, CAFs, endothelial cells, and immune cells) formed distinct clusters in the UMAP presentation. Cells from chemotherapy-resistant and chemotherapy-sensitive cases were distributed within each cell type. + In the epithelial cell population, non-tumor cells were barely detectable based on copy number alterations estimated by InferCNV analysis, presumably due to careful removal of non-tumor tissue during sample preparation.

[0128] To investigate the potential relationship between chemotherapy resistance and oncogenic activation, we evaluated genomic alterations in key oncogenes and tumor suppressor genes using NCC Oncopanel. As previously reported, mutations in ARID1A and PIK3CA were identified in many samples (7 / 10 and 4 / 10 cases, respectively). However, these mutations were found in both chemotherapy-sensitive and chemotherapy-resistant cases, so no clear association with chemotherapy resistance was observed.

[0129] Next, to investigate whether chemotherapy-resistant cancer subpopulations exist, we used EpCAM + The tumor population was stratified into six subpopulations (Cancer #1-6). Surprisingly, the proportion of the Cancer #2 subpopulation was found to be higher in chemotherapy-resistant cases than in chemotherapy-sensitive cases. However, evaluation of non-tumor cell types revealed no significant differences in their numbers between chemotherapy-resistant and chemotherapy-sensitive cases.

[0130] 2-2. Chemoresistant subpopulations of OCCC are associated with HIF activation and poor prognosis. To determine the gene expression profile of each cancer subpopulation, we isolated preferentially expressed signature genes. When we examined the expression of signature genes in advanced OCCC cases (n=30), we found that the signature of the Cancer #2 subpopulation, but not the signatures of other subpopulations, was associated with shorter progression-free survival or overall survival, indicating that the chemotherapy-resistant Cancer #2 subpopulation is associated with a poor prognosis.

[0131] Next, we performed gene ontology (GO) enrichment analysis to investigate the biological characteristics of the subpopulations. The results indicated that the Cancer #2 subpopulation was associated with hypoxia response and extracellular matrix. Accordingly, single-sample gene set enrichment analysis (ssGSEA) of the Hallmark signature gene set revealed that the hypoxia pathway was specifically activated in the Cancer #2 subpopulation. Meanwhile, enrichment analysis of the other major subpopulations indicated that the Cancer #1 and #3 subpopulations were associated with the interferon response pathway and cell cycle-related pathway, respectively, suggesting that the Cancer #3 subpopulation is a circulating subpopulation.

[0132] Next, we performed VIPER (Virtual Inference of Protein-activity by Enriched Regulon) analysis to examine the transcription factors associated with each cluster. Consistent with the findings of enhanced hypoxic response, the cancer #2 subpopulation showed increased activity of HIF1A (HIF-1α) and EPAS1 (HIF-2a). Notably, the top five transcription factors activated in the cancer #2 subpopulation (HIF1A, EGR-1, ATF-2, EPAS1 (HIF-2A), and SP-1) mediate the hypoxic response, suggesting that these transcription factors cooperate to induce the hypoxic response. Taken together, these results indicate that the #2 chemotherapy-resistant subpopulation is associated with poor prognosis and a HIF-mediated hypoxic response.

[0133] 2-3. Chemoresistant cells are localized in CAF-dominated areas of OCCC. Next, we attempted to clarify the histological localization of the chemotherapy-resistant cancer subpopulation in Cancer #2 by spatial transcriptomics analysis. We performed spatial gene expression analysis using Visium on surgical specimens from a chemotherapy-resistant case (OCC-R2) and a chemotherapy-sensitive case (OCC-S3). Specific markers for epithelial cancer cells, CAFs, endothelial cells, and immune cells were used to determine the location of these cells within the tumor. Hematoxylin and eosin (H&E) staining of serial sections demonstrated that the specimens were largely separated into cancer-dominated and CAF-dominated areas. Consistent with this, the histological distribution of cancer cells and CAFs visualized by Visium analysis closely matched the cancer cell and CAF-dominated areas visualized by H&E staining. Indeed, Visium spots could be classified into three groups based on their gene expression profiles: cancer-dominated, CAF-dominated, and mixed cancer and CAF. The distribution of the three types of spots was almost identical to the distribution of cancer cells and CAFs observed in H&E images.

[0134] Next, we performed anchor-based integration of snRNA-seq and Visium data to localize the major cancer subpopulations (#1–#5) and calculated a prediction score for each subpopulation at each Visium spot. Visualization of cancer subpopulations based on prediction scores revealed that the Cancer #2 subpopulation was primarily located in mixed cancer / CAF spots in both chemotherapy-resistant and chemotherapy-sensitive cases. In contrast, Cancer #1 and #3 subpopulations were primarily located in cancer-dominated spots.

[0135] Consistent with the snRNA-seq data, the Cancer#2 signature, but not other signatures, was more highly expressed in OCC-R2 than in OCC-S3, supporting the association of cancer cells harboring the Cancer#2 signature with chemotherapy resistance.

[0136] 2-4. HIF-1α-Induced Cancer Cells Present Near CAFs in Chemoresistant OCCCs. To further investigate the location of the chemoresistant population in cancer #2 within the cancer / CAF mixed region, we next immunostained HIF-1α-positive cancer cells. Surprisingly, co-immunostaining of the chemoresistant tumor (OCC-R1-5) with antibodies specific for HIF-1α, PAX8 (a marker for ovarian cancer cells), and α-SMA (a marker for CAFs) revealed widespread distribution of PAX8-positive cancer cells co-expressing HIF-1α. In contrast, the proportion of cancer cells co-expressing detectable HIF-1α in the chemosensitive tumor (OCC-S1-5) was much lower than in the chemoresistant tumor. Indeed, quantification of stained cells using QuPath indicated that the proportion of the HIF-1α-positive population in the chemoresistant tumors was, on average, three times higher than that in the chemosensitive tumors (33.2% vs. 11.0%, respectively).

[0137] We observed that HIF-1α-positive cancer cells in chemotherapy-resistant tumors frequently localized near α-SMA-positive cells. Indeed, evaluation of the relative distances between HIF-1α-positive, HIF-1α-negative, and α-SMA-positive cancer cells by nearest neighbor analysis (CytoMAP) confirmed that HIF-1α-positive cancer cells localized near α-SMA-positive cells. These data suggest that the localization of HIF-1α-induced cancer cells near CAFs is a characteristic of chemotherapy-resistant OCCC.

[0138] 2-5. CAFs in chemotherapy-resistant tumors exhibit a myofibroblast phenotype. The close localization of CAFs in chemotherapy-resistant cells suggests that CAFs may play a functional role in enhancing chemotherapy resistance in OCCC. To investigate whether unique subpopulations of CAFs exist in chemotherapy-resistant OCCC, we stratified the CAF populations mentioned in 2-1 above using snRNA-seq data. However, contrary to the stratification of cancer populations, we did not find any subpopulations preferentially present in chemotherapy-resistant OCCC.

[0139] As an alternative approach, we used snRNA-seq data to investigate whether CAFs derived from chemosensitive cancers are associated with specific biological characteristics. CAFs consist of heterogeneous populations, including inflammatory CAFs (iCAFs), antigen-presenting CAFs (apCAFs), and myofibroblastic CAFs (myCAFs), and myofibroblastic CAFs have been reported to reside in the vicinity of cancer cells. Comparison of CAFs from chemotherapy-resistant and chemotherapy-sensitive tumors using ssGSEA and GO-term analysis demonstrated that CAFs from chemotherapy-resistant OCCC tumors are associated with epithelial-mesenchymal transition (EMT) and extracellular matrix organization, a phenotype associated with myCAFs. Surprisingly, CAFs from chemotherapy-resistant OCCC tumors displayed a myCAF gene signature and elevated expression of the myCAF-associated genes FAP, TPM1, and THBS2. Furthermore, immunostaining studies revealed higher levels of FAP-α (a protein encoded by the FAP gene) in chemotherapy-resistant tumors than in chemotherapy-sensitive tumors. Taken together, these data indicate that myCAF populations are expanded in chemotherapy-resistant cancers, and that HIF-1α-induced cancer cells and myCAFs constitute a tumor microenvironment specific to chemotherapy resistance.

[0140] 2-6. In vitro coculture of chemotherapy-resistant OCCC cells and CAFs recapitulates the chemotherapy-resistant niche. The colocalization of chemotherapy-resistant subpopulations of cancer cells and CAFs suggests reciprocal crosstalk between these cells in the chemotherapy-resistant niche. To investigate the potential crosstalk between these cells, we established an in vitro coculture system. First, cancer spheroids and CAFs were separately established from fresh surgical OCCC specimens. Next, chemotherapy-resistant cancer-derived spheroids were retrospectively selected based on widespread expression of HIF-1α in cancer cells from the original surgical specimens. The identity of the selected cancer spheroids and CAFs was confirmed by the expression of specific markers: PAX8 and KRT7 for OCCC, and αSMA and collagen I for CAFs. Subsequently, spheroids and CAFs were labeled with GFP and mCherry, respectively, and then cultured alone or together (at a 1:1 ratio) to examine the coculture-induced changes in cell proliferation and phenotype (Figures 1A and 1B). Indeed, co-culture enhanced CAF survival (Figure 1C) and induced HIF-1α and HIF-2α expression in cancer spheroid cells (Figures 1D and 1E). Surprisingly, co-culture increased chemoresistance to carboplatin (Figure 1F), indicating that the presence of CAFs contributes to cancer chemoresistance.

[0141] Next, we performed single-cell RNA-seq (scRNA-seq) of cells cultured under either monoculture or coculture conditions to examine the gene expression changes induced after coculture (Figure 1G). Using ssGSEA, we compared the gene expression profiles of cancer spheroids cultured under both coculture and monoculture conditions. Four of the five top hallmark signatures induced after coculture (EMT, NF-κB-mediated TNF-α signaling, inflammatory response, and hypoxia) were identical to those upregulated in the Cancer #2 subpopulation. Furthermore, coculture with CAFs specifically upregulated the Cancer #2 gene signature (Figure 1H), inducing the activation of all nine of the top transcription factors activated in the Cancer #2 subpopulation. Overall, the phenotypic changes of cancer spheroids induced by coculture with CAFs closely simulated the unique characteristics of the Cancer #2 subpopulation.

[0142] We also compared the gene expression profiles of CAFs under coculture and monoculture conditions using ssGSEA. The EMT pathway, which was strongly upregulated in CAFs from chemotherapy-resistant OCCC, was induced under coculture conditions. Furthermore, we found that TGF-β signaling was strongly induced after coculture. This suggests that TGF-β signaling, a well-known signaling pathway that promotes CAF generation, may be involved in the EMT phenotype of CAFs induced under coculture conditions. Furthermore, coculture upregulated the myCAF signature (Figure 1I) and genes representative of myCAFs, such as FAP, THBS2, and TPM1, whose induction was also observed in chemotherapy-resistant OCCC. Thus, when cancer spheroids and CAFs are cocultured, they undergo phenotypic changes associated with chemotherapy-resistant cancer. These data strongly suggest that interactions between cancer cells and CAFs lead to the formation of a chemotherapy-resistant niche in cancer.

[0143] 2-7. CAF activation by cancer-derived PDGF mediates chemoresistance and activates HIF-1α in cancer cells. To better understand the molecular mechanisms underlying chemoresistance mediated by cancer-CAF interactions, we used NicheNet to investigate potential ligand-receptor interactions between these cells. Examination of snRNA-seq data identified 12 ligand-encoding genes (NAMPT, EFNA5, PDGFB, C3, ANXA1, SPP1, FN1, ITGB1, LAMC2, LAMB1, LAMA1, and RELN) that were highly expressed in the cancer #2 subpopulation. We then investigated whether the genes encoding their receptors were highly expressed by CAFs. Receptor-ligand analysis revealed that the interaction between PDGFB (the β subunit of PDGF) and PDGFRB (the β subunit of the PDGF receptor) is a potential mediator of intercellular signaling between cancer cells and CAFs.

[0144] We next investigated the functional significance of PDGF-PDGFR interaction in the coculture system. As expected, PDGFB and PDGFRB were expressed at high levels by cancer spheroid cells and CAFs, respectively (Figure 2A). Coculture led to activating phosphorylation of PDGFR (p-PDGFRB) and expression of the myCAF marker FAP-α in CAFs (Figure 2B). Indeed, treatment of CAFs with purified PDGFB ligand induced PDGFRB phosphorylation and FAP-α expression (Figure 2C) and increased CAF proliferation (Figure 2D). Conversely, CRISPR-mediated knockout of PDGFRB in CAFs abolished PDGF-mediated proliferation (Figures 2E and 2F) and FAP-α expression (Figure 2G). This indicates that PDGF-induced proliferation and the development of a myCAF-like phenotype are mediated by activation of the PDGF receptor in CAFs.

[0145] Notably, immunohistochemistry of chemotherapy-resistant OCCC revealed activating phosphorylation of PDGFR in αSMA-positive CAFs located near KRT7-positive cancer cells, suggesting that PDGFR signaling in CAFs is activated by neighboring cancer cells in vivo.

[0146] Next, we used a coculture system to investigate the functional role of PDGFR signaling in cancer chemoresistance. PDGFR knockout in CAFs reduced their viability (Figure 2H). Surprisingly, PDGFR knockout in CAFs inhibited the expression of HIF-1α, HIF-2α, and PDGFB in cancer cells (Figure 2I). Furthermore, this knockout reduced cancer chemoresistance to carboplatin (Figure 2J). Taken together, these data suggest a positive feedback loop exists between cancer cells and CAFs: PDGF expressed by OCCCs induces CAF activation and survival via PDGFR, resulting in enhanced HIF activation, PDGF expression, and chemoresistance in cancer cells.

[0147] 2-8. CAF Inhibition by Combination Ripretinib and Carboplatin Suppresses Cancer Growth. The critical role of the PDGF-PDGFR signaling axis in CAF-mediated chemotherapy resistance led us to develop a novel therapeutic approach targeting PDGFR signaling in CAFs. Carboplatin had no significant effect on CAF proliferation (Figures 3A, 4A, and 4B). Meanwhile, TKIs capable of inhibiting PDGFR exhibited varying levels of growth inhibition (Figures 3A, 4A, and 4B). Ripretinib at 1 μM inhibited activating PDGFR phosphorylation and FAP-α expression within 24 hours. We then examined the inhibitory effects of ripretinib in the presence or absence of carboplatin in an in vitro coculture system. As expected, ripretinib effectively reduced CAF viability at concentrations of 1–5 μM, even in the absence of carboplatin (Figure 3B). Importantly, carboplatin-induced inhibition of cancer cell growth was significantly enhanced by ripretinib (Figures 3C and 3D). In contrast, ripretinib did not significantly enhance carboplatin-mediated inhibition in monocultured cancer cells (Figure 3E). This indicates that ripretinib inhibits cancer growth through the suppression of CAFs.

[0148] Finally, we investigated the effect of the combination of carboplatin and ripretinib. The cancer spheroids used in the coculture assay were mixed with CAFs at a 1:1 ratio and subcutaneously implanted into immunodeficient NOG mice. Notably, the combination of ripretinib and carboplatin significantly inhibited tumor growth (Figure 3F).

[0149] Thus, ripretinib suppresses the growth of chemotherapy-resistant cancers by inhibiting CAFs. Therefore, we predicted that the fraction of HIF-1α-positive cancer cells would be reduced in the presence of ripretinib. Indeed, after treatment, we observed a significant decrease in the fraction of HIF-1α-positive cancer cells (Figures 3G and 3H) and α-SMA-positive CAFs. These data indicate that CAF inhibition, when combined with standard chemotherapy agents, is an effective treatment for eliminating chemotherapy-resistant cancers.

Claims

1. A cancer-associated fibroblast inhibitor containing a PDGFR inhibitor.

2. The cancer-associated fibroblast inhibitor according to claim 1, wherein the PDGFR inhibitor is at least one selected from the group consisting of PDGFR function inhibitors and PDGFR expression inhibitors.

3. The cancer-associated fibroblast inhibitor according to claim 1, wherein the PDGFR inhibitor is at least one selected from the group consisting of a low molecular weight compound, a polynucleotide targeting PDGFR, an expression cassette for said polynucleotide, a peptide, a protein, and an antibody.

4. The cancer-associated fibroblast inhibitor according to claim 1, wherein the PDGFR inhibitor is a low molecular weight compound, and the low molecular weight compound is a kinase inhibitor.

5. The cancer-associated fibroblast inhibitor according to claim 4, wherein the kinase inhibitor is at least one selected from the group consisting of Ripretinib, Ponatinib, Erdafitinib, Dovitinib, Lenvatinib, Foretinib, ENMD-2076, PP121, and Cediranib.

6. A cancer-associated fibroblast inhibitor according to any one of claims 1 to 5, wherein the cancer-associated fibroblasts are cells in ovarian cancer tissue, breast cancer tissue, or colon cancer tissue.

7. A cancer-associated fibroblast inhibitor according to any one of claims 1 to 5, wherein the cancer-associated fibroblasts are cells in ovarian cancer tissue.

8. A cancer-associated fibroblast inhibitor according to any one of claims 1 to 5, for use in combination with an anticancer drug.

9. The cancer-associated fibroblast inhibitor according to claim 8, wherein the anticancer drug is a platinum drug.

10. An agent that enhances the anti-cancer effect of anti-cancer drugs, containing a PDGFR inhibitor.

11. A preventive or therapeutic agent for at least one type of cancer selected from the group consisting of ovarian cancer, breast cancer, colorectal cancer, pancreatic cancer, urothelial cancer, prostate cancer, esophageal cancer, liver cancer, renal cancer, uterine cancer, gastric cancer, glioblastoma, lung cancer, and melanoma, containing a PDGFR inhibitor.

12. The preventive or therapeutic agent according to claim 11, for use in combination with an anticancer agent.

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