Method for predicting sensitivity of cancer to glutathione metabolism-related enzyme inhibitor

Abstract

The present invention addresses the problem of providing a novel index (marker) for predicting the sensitivity of a cancer with respect to a glutathione metabolism-related enzyme inhibitor.　The present invention provides a method for predicting the sensitivity of a target cancer to a glutathione metabolism-related enzyme inhibitor, said method comprising measuring the expression level of cystathionine γ lyase (CSE) in a cancer cell derived from the target, wherein CSE overexpression in the cancer cell indicates that the cancer has high sensitivity to the glutathione metabolism-related enzyme inhibitor.

Description

Method for predicting cancer sensitivity to glutathione metabolism-related enzyme inhibitors

[0001] The present invention relates to a method for predicting the sensitivity of a subject's cancer to an inhibitor of a glutathione metabolism-related enzyme. The present invention also relates to a pharmaceutical composition for treating a subject's cancer predicted to be highly sensitive to an inhibitor of a glutathione metabolism-related enzyme. The present invention also relates to a composition or kit for use in the method for predicting the sensitivity of a subject's cancer to an inhibitor of a glutathione metabolism-related enzyme.

[0002] In the treatment of ovarian cancer, initial tumor debulking surgery is often followed by chemotherapy with platinum-based drugs (such as cisplatin), but some patients exhibit resistance to such chemotherapy, and such patients are known to have a poor prognosis.

[0003] The present inventors previously performed comprehensive protein expression analysis to search for biomarkers that predict the efficacy of platinum-based chemotherapy (Non-Patent Document 1, Patent Document 1). As a result, they found that among ovarian cancer patients who underwent platinum-based chemotherapy after tumor-reductive surgery, those with overexpression of cystathionine γ-lyase (CSE) had a poor prognosis.

[0004] CSE is an enzyme that synthesizes cysteine ​​from cystathionine. Cysteine ​​is not only synthesized intracellularly from cystathionine by CSE, but also produced by the uptake and reduction of cystine into cells via the cystine transporter xCT. In another study, the present inventors further demonstrated that cysteine-depleting therapy, which involves the simultaneous administration of a CSE inhibitor and an xCT inhibitor, can be an effective treatment for CSE-overexpressing cancers (Patent Document 2).

[0005] Recently, a new mechanism of cell death, ferroptosis, has been reported (Non-Patent Document 2). Ferroptosis is a cell death induced by the iron-dependent generation of reactive oxygen species and the subsequent generation of lipid peroxides.

[0006] Ferroptosis is suppressed in cells by glutathione peroxidase 4 (GPX4), which converts reduced glutathione to oxidized glutathione, and suppresses ferroptosis by reducing peroxidized phospholipids to alcohols using the resulting reducing power.

[0007] Induction of ferroptosis in cancer cells by inhibiting glutathione metabolism-related enzymes, such as GPX4, which converts reduced glutathione to oxidized glutathione, and glutamate-cysteine ​​ligase (GCL) and glutathione synthetase (GS), which are involved in glutathione synthesis, is expected to be a new cancer treatment. For example, Patent Document 3 describes the use of GPX4 inhibitors as ferroptosis inducers and anticancer agents. Patent Document 4 describes that inhibition of GPX4 in cancer cells in which the function of SWI / SNF complex factors is suppressed can suppress the proliferation of the cancer cells, and that based on this finding, the sensitivity of cancer cells to GPX4 inhibitors can be predicted using the suppression of SWI / SNF complex factors as an indicator.

[0008] US Patent Application Publication No. 2012 / 0058204 JP 2019-144152 A JP 2023-518027 A International Publication No. 2021 / 132592

[0009] Kazufumi Honda et al., 2021, Redox Biology, 41, 101926Scott J. Dixon et al., 2012, Cell, 149, 1060-1072

[0010] An objective of the present invention is to provide a new indicator (marker) for predicting the sensitivity of cancer to glutathione metabolism-related enzyme inhibitors.

[0011] As a result of extensive research to solve the above-mentioned problems, the inventors discovered that cancer cells that overexpress CSE are more sensitive to inhibitors of glutathione metabolism-related enzymes than cancer cells that do not overexpress CSE, and thus completed the present invention.

[0012] That is, the present invention encompasses the following: [1] A method for predicting the sensitivity of a subject's cancer to a glutathione metabolism-related enzyme inhibitor, comprising measuring the expression level of cystathionine gamma-lyase (CSE) in cancer cells derived from the subject, wherein overexpression of CSE in the cancer cells indicates that the cancer is highly sensitive to a glutathione metabolism-related enzyme inhibitor. [2] The method according to [1], wherein the glutathione metabolism-related enzyme inhibitor is a glutathione peroxidase 4 (GPX4) inhibitor, a glutamate-cysteine ​​ligase (GCL) inhibitor, or a glutathione synthetase (GS) inhibitor. [3] The method according to [2], wherein the glutathione metabolism-related enzyme inhibitor is RSL3, ML162, or buthionine sulfoximine (BSO). [4] A pharmaceutical composition comprising a glutathione metabolism-related enzyme inhibitor for treating a subject's cancer predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor by the method according to any one of [1] to [3]. [5] A composition or kit for use in the method of any one of [1] to [3], comprising a means for measuring CSE expression levels. [6] The composition or kit of [5], wherein the means for measuring CSE expression levels is an antibody that specifically binds to the CSE protein. [7] A method for determining the dosage of a glutathione metabolism-related enzyme inhibitor for a subject with cancer, comprising measuring the CSE expression level in cancer cells derived from the subject, wherein overexpression of CSE in the cancer cells indicates a first dose, and non-overexpression of CSE in the cancer cells indicates a second dose, the first dose being lower than the second dose. This specification incorporates the disclosure of Japanese Patent Application No. 2024-099309, from which the present application claims priority.

[0013] According to the present invention, it is possible to efficiently predict the sensitivity of cancer to glutathione metabolism-related enzyme inhibitors using CSE expression levels as an indicator. According to the present invention, cancer can be effectively treated by administering a glutathione metabolism-related enzyme inhibitor to a subject whose cancer is predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor. According to the present invention, it is possible to provide a new treatment option for CSE-overexpressing cancers.

[0014] 7 shows the expression levels of CSE, GCLC, GS, and GPX4 in ovarian cancer cell lines. (A) An image showing the results of Western blot analysis. (B) Relative CSE expression levels quantified from the image in (A). Cell survival curves showing the cell viability of ovarian cancer cell lines in the presence of RSL3. Error bars indicate standard error. Cell survival curves showing the cell viability of ovarian cancer cell lines in the presence of ML162. Error bars indicate standard error. Figure 7 shows the expression levels of CSE, GCLC, GS, and GPX4 in melanoma cell lines. (A) An image showing the results of Western blot analysis. (B) Relative CSE expression levels quantified from the image in (A). Cell survival curves showing the cell viability of melanoma cell lines in the presence of RSL3. Error bars indicate standard error. Cell survival curves showing the cell viability of ovarian cancer cell lines in the presence of BSO. Error bars indicate standard error. Figure 7 shows the schedule of the animal experiment performed in Example 7. 1 shows the change in relative tumor volume when the ovarian cancer cell line OVISE was subcutaneously implanted into immunodeficient mice and then a DMSO solution of RSL3 (0 or 10 mg / kg / day) was administered. 2 shows the change in relative tumor volume when the ovarian cancer cell line KURAMOCHI was subcutaneously implanted into immunodeficient mice and then a DMSO solution of RSL3 (0 or 10 mg / kg / day) was administered.

[0015] The present invention will be described in detail below.

[0016] <Sensitivity Prediction Method, etc.> The present invention relates to a method for predicting the sensitivity of a subject's cancer to a glutathione metabolism-related enzyme inhibitor (hereinafter, sometimes referred to as the "sensitivity prediction method of the present invention").

[0017] Glutathione is a tripeptide (γ-Glu-Cys-Gly) consisting of glutamic acid (Glu), cysteine ​​(Cys), and glycine (Gly). Glutathione itself has the ability to reduce reactive oxygen species, and as a coenzyme for glutathione peroxidase 4 (GPX4), it also has the ability to reduce hydrogen peroxide and lipid peroxides.

[0018] Glutathione is produced from glutamic acid, cysteine, and glycine through a two-step reaction. Specifically, glutamic acid (Glu) and cysteine ​​(Cys) are first linked by glutamic acid-cysteine ​​ligase (GCL) to produce γ-Glu-Cys. Next, γ-Glu-Cys and glycine (Gly) are linked by glutathione synthetase (GS) to produce glutathione.

[0019] Glutathione contains a thiol group (-SH) in the molecule, and when it undergoes oxidation, it forms a disulfide bond (-SS-) and dimerizes. Monomeric glutathione that has not undergone oxidation is called reduced glutathione (GSH), and dimerized glutathione that has undergone oxidation is called oxidized glutathione (GSSG).

[0020] Glutathione peroxidase 4 (GPX4) converts reduced glutathione (GSH) to oxidized glutathione (GSSG), and the resulting reducing power reduces peroxidized phospholipids to alcohols.

[0021] Oxidized glutathione (GSSG) is reduced to reduced glutathione (GSH) by glutathione reductase (GR).

[0022] As used herein, "glutathione metabolism" refers to a series of chemical reactions related to the synthesis and conversion of glutathione in vivo, particularly the synthesis of glutathione from glutamic acid, cysteine, and glycine, the conversion of reduced glutathione to oxidized glutathione, and the conversion of oxidized glutathione to reduced glutathione.

[0023] As used herein, "glutathione metabolism-related enzyme" refers to an enzyme that catalyzes any reaction in glutathione metabolism, and includes, for example, GPX4, GCL, or GS.

[0024] As used herein, the term "glutathione metabolism-related enzyme inhibitor" refers to a drug that inhibits the activity and / or expression of a glutathione metabolism-related enzyme. The glutathione metabolism-related enzyme inhibitor may be, but is not limited to, a compound such as a low molecular weight compound, a medium molecular weight compound, a polypeptide, or a polynucleotide. The glutathione metabolism-related enzyme inhibitor preferably consists of one type of compound.

[0025] In this specification, the term "low molecular weight compound" refers to a compound having a molecular weight of less than 500, and the term "medium molecular weight compound" refers to a compound having a molecular weight of 500 or more and less than 2000.

[0026] As used herein, "polypeptide" may be a natural or synthetic polypeptide, and includes, for example, a full-length protein or a fragment thereof. Polypeptides that can be used as glutathione metabolism-related enzyme inhibitors include, for example, antibodies and antigenic peptides, such as antibodies that specifically bind to glutathione metabolism-related enzymes. As used herein, "antibody" includes full-length antibodies and antigen-binding fragments thereof (e.g., Fab, Fab', F(ab')2, Fv, scFv, sc(Fv)2, dsFv, and diabodies). An antibody may be a polyclonal antibody or a monoclonal antibody. An antibody may also be a human antibody, a non-human animal antibody, or a recombinant antibody (e.g., a humanized antibody or a chimeric antibody).

[0027] As used herein, the term "polynucleotide" may refer to a natural or synthetic polynucleotide, including, for example, DNA and RNA. Polynucleotides that can be used as glutathione metabolism-related enzyme inhibitors include, for example, antisense nucleic acids, siRNAs (small interfering RNAs), and shRNAs (short hairpin RNAs), such as antisense nucleic acids, siRNAs, and shRNAs that inhibit the expression of glutathione metabolism-related enzymes.

[0028] In one embodiment, the glutathione metabolism-related enzyme inhibitor is a glutathione peroxidase 4 (GPX4) inhibitor.

[0029] As mentioned above, glutathione peroxidase 4 (GPX4) is an enzyme that converts reduced glutathione (GSH) to oxidized glutathione (GSSG) and reduces phospholipid peroxides to alcohol, and is also called phospholipid hydroperoxide glutathione peroxidase. The nucleotide sequence of cDNA encoding human GPX4 protein is shown, for example, in NCBI reference number NM_002085.5. The amino acid sequence of human GPX4 protein is shown, for example, in NCBI reference number NP_002076.2.

[0030] A GPX4 inhibitor can be, for example, a drug that inhibits the activity of GPX4. Whether a test substance inhibits the activity of GPX4 can be evaluated, for example, as described in Wan Seok Yang et al., Cell, 2014, 156(1-2):317-331, using the reduction of 7α-cholesterol hydroperoxide, a GPX4-specific substrate, as an indicator. Specifically, for example, a lysate of cells treated with the test substance is incubated with 7α-cholesterol hydroperoxide, and the reduction rate of 7α-cholesterol hydroperoxide is measured. If the reduction rate of 7α-cholesterol hydroperoxide is slower in the lysate of cells treated with the test substance than in the lysate of cells not treated with the test substance, the test substance can be determined to have an inhibitory effect on GPX4 activity.

[0031] Examples of agents that inhibit GPX4 activity include RSL3, ML162, ML210, FIN56, FINO2, and Withaferin A, with RSL3, ML162, and ML210 being particularly preferred. RSL3 and ML162 are compounds that bind to the selenocysteine ​​active site of GPX4 and inhibit its enzymatic activity. RSL3 is, in particular, (1S,3R)-RSL3. The IUPAC name of (1S,3R)-RSL3 is methyl (1S,3R)-2-(2-chloroacetyl)-1-(4-methoxycarbonylphenyl)-1,3,4,9-tetrahydropyrido[3,4-b]indole-3-carboxylate, and its CAS number is 1219810-16-8. The IUPAC name of ML162 is 2-(3-chloro-N-(2-chloroacetyl)-4-methoxyanilino)-N-(2-phenylethyl)-2-thiophen-2-ylacetamide, and its CAS number is 1035072-16-2. ML210 is a prodrug molecule that is activated after uptake into living cells and inhibits GPX4. The IUPAC name of ML210 is [4-[bis(4-chlorophenyl)methyl]piperazin-1-yl]-(5-methyl-4-nitro-1,2-oxazol-3-yl)methanone, and its CAS number is 1360705-96-9. Drugs that inhibit GPX4 activity also include antibodies that specifically bind to the GPX4 protein. Japanese Patent Publication No. 2023-518027 describes drugs that inhibit GPX4 activity, and these drugs can also be used in the present invention.

[0032] A GPX4 inhibitor may also be a drug that inhibits GPX4 expression. Whether a test substance inhibits GPX4 expression can be evaluated, for example, using the expression level of GPX4 protein or mRNA as an indicator. For example, if the expression level of GPX4 protein or mRNA in cells treated with the test substance is lower than the expression level of GPX4 protein or mRNA in cells not treated with the test substance, the test substance can be determined to have the effect of inhibiting GPX4 expression. The expression level of protein or mRNA can be measured by known means. The expression level of protein can be measured, for example, by Western blotting, ELISA, flow cytometry, or the like. The expression level of mRNA can be measured, for example, by RT-PCR, Northern blotting, DNA array, in situ hybridization, or the like.

[0033] Agents that inhibit the expression of GPX4 include, for example, antisense nucleic acids, siRNAs, and shRNAs that target GPX4 mRNA.

[0034] In another embodiment, the glutathione metabolism-related enzyme inhibitor is a glutamate-cysteine ​​ligase (GCL) inhibitor.

[0035] As described above, glutamate-cysteine ​​ligase (GCL) is an enzyme that links glutamate (Glu) and cysteine ​​(Cys) to produce γ-Glu-Cys, and is composed of two subunits: a modifying subunit (GCLM) and a catalytic subunit (GCLC). The nucleotide sequence of cDNA encoding human GCLC protein is shown, for example, in NCBI reference number NM_001498.4. The amino acid sequence of human GCLC protein is shown, for example, in NCBI reference number NP_001489.1. The nucleotide sequence of cDNA encoding human GCLM protein is shown, for example, in NCBI reference number NM_002061.4. The amino acid sequence of human GCLM protein is shown, for example, in NCBI reference number NP_002052.1.

[0036] The GCL inhibitor may be, for example, a drug that inhibits the activity of GCL (particularly GCLC). Examples of drugs that inhibit GCL activity include buthionine sulfoximine (BSO) (CAS No.: 83730-53-4), EN25 (CAS No.: 1647534-29-9, N-{4-[(3,4-dimethylphenyl)sulfanyl]phenyl}-4-[(prop-2-enamido)methyl]benzamide), and antibodies that specifically bind to GCLC or GCLM proteins. Furthermore, WO 2023 / 085367 discloses (2S)-2-amino-4-[S-(4,4,4-trifluorobutyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclopentylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclobutylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclobutylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclopentyl ...pentylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclopentylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclopentylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(2-cyclo 2-amino-4-[S-(2-cyclopropylethyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-[S-(4,4,4-trifluoro-3-methylbutyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-{S-[2-(3,3-difluorocyclobutyl)ethyl]sulfonimidoyl}butanoic acid, (2S)-2-amino-4-[S-(4,4-dimethylpentyl)sulfonimidoyl]butanoic acid carboxylic acid, (2S)-2-amino-4-{S-[2-(1-hydroxycyclobutyl)ethyl]sulfonimidoyl}butanoic acid, (2S)-2-amino-4-[S-(4,4,4-trifluoro-3-hydroxybutyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-{S-[2-(1-fluorocyclobutyl)ethyl]sulfonimidoyl}butanoic acid, (2S)-2-amino-4-[S-(4,4,4 -trifluoro-3-hydroxy-3-methylbutyl)sulfonimidoyl]butanoic acid, (2S)-2-amino-4-{S-[4,4,4-trifluoro-3-hydroxy-3-(trifluoromethyl)butyl]sulfonimidoyl}butanoic acid, (2S)-2-amino-4-[S-(3,3,4,4,4-pentafluorobutyl)sulfonimidoyl]butanoic acid, (S)-2-amino-4-((R,3R)-4,4,4-trifluoro-3-hydroxybutylsulfonimidoyl)butanoic acid, (S)-2-amino-4-((R,3S)-4,4,4-trifluoro-3-hydroxybutylsulfonimidoyl)butanoic acid, (S)-2-amino-4-((R)-2-(1-hydroxycyclobutyl)ethylsulfonimidoyl)butanoic acid, (S)-2-amino-4-((S)-4,4,4-trifluorobutylsulfonimidoyl)butanoic acid, (S)-2-amino-4-((R)-4,4,4-trifluoro-3-hydroxy-3-(trifluoromethyl)butylsulfonimidoyl)butanoic acid, ethyl(2S (2S)-2-amino-4-[S-(4,4,4-trifluorobutyl)sulfonimidoyl]butanoate, isopropyl (2S)-2-amino-4-[S-(4,4,4-trifluorobutyl)sulfonimidoyl]butanoate, ethyl (2S)-2-amino-4-[S-(4,4,4-trifluoro-3-hydroxybutyl)sulfonimidoyl]butanoate, and isopropyl (2S)-2-amino-4-[S-(4,4,4-trifluoro-3-hydroxybutyl)sulfonimidoyl]butanoate are described, and these drugs can also be used in the present invention.

[0037] GCL inhibitor can also be, for example, a drug that inhibits the expression of GCLC or GCLM. Drugs that inhibit the expression of GCLC or GCLM include, for example, antisense nucleic acid, siRNA, and shRNA that target GCLC or GCLM mRNA. Drugs that inhibit the expression of GCLC or GCLM also include NaAsO2.

[0038] In another embodiment, the glutathione metabolism-related enzyme inhibitor is a glutathione synthetase (GS) inhibitor.

[0039] As mentioned above, glutathione synthetase (GS) is an enzyme that links γ-Glu-Cys and glycine (Gly) to produce glutathione (γ-Glu-Cys-Gly). The nucleotide sequence of cDNA encoding human GS protein is shown, for example, in NCBI reference number NM_001322495.1. The amino acid sequence of human GS protein is shown, for example, in NCBI reference number NP_001309424.1.

[0040] A GS inhibitor can be, for example, a drug that inhibits GS activity. Examples of drugs that inhibit GS activity include antibodies that specifically bind to GS protein.

[0041] The GS inhibitor may also be, for example, a drug that inhibits the expression of GS. Examples of drugs that inhibit the expression of GS include antisense nucleic acids, siRNAs, and shRNAs that target GS mRNA.

[0042] In the susceptibility prediction method of the present invention, the subject may be any mammal, including, for example, humans, livestock (horses, cows, sheep, goats, pigs, etc.), pets (dogs, cats, rabbits, etc.), laboratory animals (mice, rats, monkeys, etc.), etc., but is preferably a human. The subject may have or be suspected of having cancer.

[0043] As used herein, "cancer" refers to all malignant tumors. Examples of cancers to which the susceptibility prediction method of the present invention can be applied include cancers that may overexpress CSE, such as epithelial cell cancer, sarcoma, and blood cancer. Specific examples include lung cancer (e.g., non-small cell lung cancer, small cell lung cancer), bronchial adenoma / carcinoid, mesothelioma, malignant mesothelioma, thymoma, thymic carcinoma, pleuropulmonary blastoma, salivary gland cancer, oral cancer, pharyngeal cancer, hypopharyngeal cancer, nasopharyngeal cancer, laryngeal cancer, throat cancer, thyroid cancer, parathyroid cancer, paranasal sinus cancer, nasal cavity cancer, tongue cancer, esophageal cancer, gastric cancer, gastrointestinal carcinoid tumor, gastrointestinal stromal tumor (GIST), pancreatic cancer, islet cell tumor, liver cancer, hepatocellular carcinoma, gallbladder cancer, biliary tract cancer, extrahepatic bile duct cancer, intrahepatic bile duct cancer, and small intestine cancer. Intestinal cancer, colon cancer, colorectal cancer, rectal cancer, anorectal cancer, anal cancer, appendix cancer, kidney cancer, adrenocortical cancer, pheochromocytoma, Wilms' tumor, urinary tract cancer (e.g., bladder cancer, urethral cancer, transitional cell carcinoma of the renal pelvis and ureter), germ cell tumors (e.g., extracranial germ cell tumors, extragonadal germ cell tumors), penile cancer, testicular cancer, prostate cancer, ovarian cancer, ovarian epithelial cancer, ovarian low malignant potential tumor, ovarian germ cell tumor, gestational trophoblastic tumor, breast cancer, uterine cancer, cervical cancer, endometrial cancer, uterine cancer, vaginal cancer, vulvar cancer, and cancer of the central nervous system Cancer of the head and neck, brain cancer, brain tumor, glioma, malignant glioma, brain stem glioma, visual pathway and hypothalamic glioma, neuroblastoma, astrocytoma (e.g., cerebellar astrocytoma, cerebral astrocytoma), ependymoma, medulloblastoma, supratentorial primitive neuroectodermal tumor, pineoblastoma, pituitary tumor, metastatic squamous cell carcinoma of the neck, eye cancer (e.g., intraocular melanoma, retinoblastoma), skin cancer (e.g., non-melanoma skin cancer, melanoma, basal cell carcinoma, squamous cell carcinoma, Merkel cell skin cancer), multiple endocrine neoplasia syndrome, AIDS-related cancer, childhood cancer, carcinoid tumor, lymphoma (e.g., nervous system lymphoma, central nervous system lymphoma, primary central nervous system lymphoma, Hodgkin's lymphoma, non-Hodgkin's lymphoma, Seziary syndrome, cutaneous T-cell lymphoma, and AIDS-related lymphoma), leukemia (e.g., acute lymphoblastic leukemia, acute myeloid leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, hairy cell leukemia), myeloma (e.g., multiple myeloma), chronic myeloproliferative disorders, Waldenstrom's macroglobulinemia, plasmacytoma,Examples of cancers include myelodysplastic syndromes, myelodysplastic / myeloproliferative disorders, bone and joint cancers, and sarcomas (e.g., rhabdomyosarcoma, Ewing's sarcoma, soft tissue sarcoma, mycosis fungoides, Kaposi's sarcoma, osteosarcoma, malignant fibrous histiocytoma, and uterine sarcoma), with ovarian cancer and melanoma being preferred. The cancer may be primary, metastatic, recurrent, or postoperative.

[0044] The cancer to which the susceptibility prediction method of the present invention is applied may or may not have a BRAF V600 mutation (e.g., a BRAF V600E mutation). As used herein, "BRAF V600 mutation" refers to a mutation in the BRAF gene that results in a mutation in valine (V), the 600th amino acid of the BRAF protein. As used herein, "BRAF V600E mutation" refers to a mutation in the BRAF gene that results in a substitution of glutamic acid (E) for valine (V), the 600th amino acid of the BRAF protein.

[0045] As used herein, the term "sensitivity" refers to the degree of effect (for example, antitumor effect or therapeutic effect) of a drug.

[0046] The method for predicting susceptibility of the present invention is characterized by using the expression level of cystathionine γ-lyase (CSE) as an index.

[0047] Cystathionine γ-lyase (CSE) is an enzyme that synthesizes cysteine ​​from cystathionine. The nucleotide sequence of cDNA encoding human CSE protein is shown, for example, in NCBI Reference No. NM_001902.6. The amino acid sequence of human CSE protein is shown, for example, in NCBI Reference No. NP_001893.2. As used herein, "CSE expression level" refers to the expression level of CSE protein and / or CSE mRNA, and includes the expression amount of CSE protein, the expression amount of CSE mRNA, and the proportion of cells expressing a certain amount of CSE protein or mRNA. The CSE expression level may be, for example, the expression amount of CSE protein or mRNA per cell. The CSE expression level may also be the expression amount of CSE protein or mRNA normalized with an endogenous control, i.e., the expression amount of CSE protein or mRNA divided by the expression amount of an endogenous control protein or mRNA. Examples of endogenous control proteins or mRNAs that can be used include ubiquitously expressed housekeeping gene products, such as α-tubulin, β-tubulin, β-actin, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and heat shock protein 90 (HSP90) proteins or mRNAs.

[0048] In a previous study, the present inventors found that cysteine ​​depletion therapy could be an effective treatment for CSE-overexpressing cancers (JP 2019-144152 A).

[0049] Cysteine ​​is involved in many metabolic pathways, including glutathione synthesis, protein synthesis, and taurine synthesis. Surprisingly, we have found that CSE-overexpressing cancers can be effectively treated by inhibiting only the glutathione metabolic pathway, which is one of the cysteine ​​metabolic pathways (see Examples 2, 3, and 5 below). The present invention was made based on this new finding.

[0050] Without being bound by theory, it is thought that cancer cells that overexpress CSE protect themselves from ferroptosis by overexpressing CSE and promoting the production of cysteine ​​by CSE, the synthesis of glutathione from cysteine, etc., and the reduction of phospholipid peroxides by glutathione and GPX4. However, when these cells are given an inhibitor of glutathione metabolism-related enzymes, the reduction of phospholipid peroxides is suppressed, causing ferroptosis.

[0051] The method for predicting susceptibility of the present invention includes, for example, measuring the expression level of cystathionine γ-lyase (CSE) in cancer cells derived from a subject. The measurement of the CSE expression level may be carried out in vitro.

[0052] The cancer cells for which CSE expression levels are measured may be cancer cells contained in a biological sample derived from a subject. Examples of biological samples include, but are not limited to, cancer tissues and cancer biopsy specimens. The cancer biopsy specimen may be a fixed and embedded (e.g., formalin-fixed, paraffin-embedded) cancer biopsy specimen. The cancer cells may also be cultured cancer cells.

[0053] The CSE expression level can be measured by known means. The CSE protein expression level can be measured by, for example, Western blotting, ELISA, flow cytometry, or immunohistochemical staining. The CSE mRNA expression level can be measured by, for example, RT-PCR, Northern blotting, DNA array, or in situ hybridization.

[0054] CSE is an enzyme that converts cystathionine to cysteine, and it is known that increased expression of CSE significantly reduces cystathionine (JP 2019-144152 A). Therefore, the CSE expression level can also be measured using the amount of cystathionine in a biological sample as an indicator.

[0055] In the sensitivity prediction method of the present invention, overexpression of CSE in the above-mentioned cancer cells indicates that the cancer is highly sensitive to an inhibitor of glutathione metabolism-related enzymes.

[0056] As used herein, "CSE overexpression" means that the CSE expression level is higher than the reference level.

[0057] The reference value can be, for example, the CSE expression level in a negative control, or 1.5-fold or 3-fold the CSE expression level in the negative control. The reference value can also be the CSE expression level in a positive control, or a CSE expression level comparable to the CSE expression level in the positive control (e.g., 0.8-fold or 0.9-fold the CSE expression level in the positive control). The negative control can be, for example, cancer cells derived from a cancer patient in which glutathione metabolism-related enzyme inhibitors are ineffective, normal cells not expressing CSE derived from a healthy individual or subject, or a cancer cell line such as OVCAR-3, KURAMOCHI, OVSHAO, TKY-nu Cpr, TKY-nu, ES-2, A2058, A375, CoLo673, G361, MeWo, SK-MEL-1, or VMM39. The positive control may be, for example, cancer cells derived from a cancer patient in which glutathione metabolism-related enzyme inhibitors are effective, vascular smooth muscle cells that are highly CSE-expressing cells derived from a healthy individual or subject, or a cancer cell line such as OVISE, OVTOKO, RMUG-S, HMCB, or CJM.

[0058] The reference value may also be a cutoff value set based on the difference in CSE expression levels in cancer cells between cancer patients in whom glutathione metabolism-related enzyme inhibitors are ineffective and cancer patients in whom glutathione metabolism-related enzyme inhibitors are effective. For example, a cutoff value obtained statistically from the CSE expression levels in cancer cells of cancer patients in whom glutathione metabolism-related enzyme inhibitors are ineffective and cancer patients in whom glutathione metabolism-related enzyme inhibitors are effective, using, for example, multivariate analysis, logistic regression analysis, receiver operating characteristic (ROC) curves, or the like, can be used as the reference value. The reference value may be set in advance.

[0059] As shown in Examples 1 to 3 and 6 below, ovarian cancer cell lines with higher CSE expression levels than the ovarian cancer cell line OVTOKO were more sensitive to glutathione metabolism-related enzyme inhibitors than ovarian cancer cell lines with CSE expression levels equal to or lower than the OVTOKO. Therefore, the reference value is not limited to, but can be set as, for example, the CSE expression level in OVTOKO. Furthermore, as shown in Examples 4 and 5 below, melanoma cell lines with higher CSE expression levels than the melanoma cell line CJM were more sensitive to glutathione metabolism-related enzyme inhibitors than melanoma cell lines with CSE expression levels equal to or lower than the CSE expression level in CJM. Therefore, the reference value can also be the CSE expression level in CJM.

[0060] In one embodiment, the cancer cells for which the CSE expression level is measured are cancer cell cultures derived from a subject. A higher CSE expression level in the cancer cell culture than in a positive control may indicate that the subject's cancer is highly sensitive to a glutathione metabolism-related enzyme inhibitor. In this case, the CSE expression level can be measured, for example, using Western blotting as described below. Cancer cells are cultured, and proteins are extracted from the cancer cell culture. The proteins are fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to a membrane. The CSE protein is detected on the membrane using an anti-CSE antibody and a labeled secondary antibody that detects it, and the endogenous control protein is detected using an antibody against an endogenous control protein and a labeled secondary antibody that detects it. The same procedure is performed on positive control cells. The detected CSE protein expression level is normalized to that of the endogenous control.

[0061] In another embodiment, the cancer cells whose CSE expression levels are measured are those contained in a cancer biopsy specimen derived from a subject. Higher CSE expression in the cancer cells compared to non-CSE-expressing normal cells contained in the cancer specimen may indicate that the subject's cancer is highly sensitive to a glutathione metabolism-related enzyme inhibitor. In this case, the CSE expression levels in the cancer cells and non-CSE-expressing normal cells contained in the cancer biopsy specimen can be measured, for example, by the method described in Honda et al. Redox Biology (2021) as described below. The cancer biopsy specimen is immunostained using an anti-CSE antibody and a fluorescent red-labeled secondary antibody that detects it, and an anti-tumor marker antibody and a fluorescent green-labeled secondary antibody that detects it. The red fluorescence intensity in the green-stained portion (cancer cells) represents the CSE expression level in the cancer cells, and the red fluorescence intensity in the unstained portion (normal cells) represents the CSE expression level in the normal cells.

[0062] In yet another embodiment, the cancer cells whose CSE expression level is to be measured are cancer cells contained in a cancer biopsy specimen derived from a subject, and CSE expression in the cancer cells is equal to or greater than the CSE expression level in vascular smooth muscle cells contained in the cancer specimen, which may indicate that the subject's cancer is highly sensitive to a glutathione metabolism-related enzyme inhibitor. In this case, the CSE expression levels in the cancer cells and vascular smooth muscle cells contained in the cancer biopsy specimen can be measured, for example, by immunostaining with an anti-CSE antibody.

[0063] As used herein, "high sensitivity" of a cancer to a drug may mean that treatment of the cancer with the drug is effective or likely to be effective.

[0064] The method for predicting susceptibility of the present invention may include measuring the CSE expression level of a positive control and / or a negative control.

[0065] According to the sensitivity prediction method of the present invention, cancer can be effectively treated by administering a glutathione metabolism-related enzyme inhibitor to a subject whose cancer is predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor.The sensitivity prediction method of the present invention can provide a new treatment option for CSE-overexpressing cancers.

[0066] As shown in the Examples below, the CSE expression level and sensitivity to glutathione metabolism-related enzyme inhibitors in cancer cells do not depend on the BRAF V600 mutation. Therefore, the method of predicting sensitivity of the present invention does not need to include assessing the presence or absence of the BRAF V600 mutation in cancer cells derived from a subject.

[0067] On the other hand, to further improve the efficiency of cancer treatment, the sensitivity prediction method of the present invention can be performed together with other anticancer drug sensitivity predictions, such as sensitivity predictions to anticancer drugs such as dabrafenib and trametinib based on the presence or absence of the BRAF V600E mutation.

[0068] The present invention also provides methods for assessing the sensitivity of a subject's cancer to a glutathione metabolism-related enzyme inhibitor, methods for assisting in predicting or assessing the sensitivity of a subject's cancer to a glutathione metabolism-related enzyme inhibitor, methods for obtaining auxiliary data for predicting or assessing the sensitivity of a subject's cancer to a glutathione metabolism-related enzyme inhibitor, and methods for selecting a subject having a cancer highly sensitive to a glutathione metabolism-related enzyme inhibitor. The steps of these methods and the criteria for predicting or assessing sensitivity are the same as those of the above-mentioned sensitivity prediction method of the present invention.

[0069] The present invention also provides a method for predicting the sensitivity of cancer cells to glutathione metabolism-related enzyme inhibitors, comprising measuring the expression level of cystathionine γ-lyase (CSE) in cancer cells. A higher CSE expression level in the cancer cells than in the control cells indicates a higher sensitivity of the cancer cells to the glutathione metabolism-related enzyme inhibitor than the control cells, and a lower CSE expression level in the cancer cells than in the control cells indicates a lower sensitivity of the cancer cells to the glutathione metabolism-related enzyme inhibitor than the control cells. Glutathione metabolism-related enzyme inhibitors that can be used in this method are similar to those described in the sensitivity prediction method of the present invention, such as GPX4 inhibitors, GCL inhibitors, or GS inhibitors, preferably GPX4 inhibitors or GCL inhibitors, more preferably RSL3, ML162, or buthionine sulfoximine (BSO). In this method, the CSE expression level may be measured in vitro.

[0070] <Pharmaceutical composition> The present invention also provides a pharmaceutical composition containing a glutathione metabolism-related enzyme inhibitor for treating cancer in a subject predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor by the above-mentioned sensitivity prediction method of the present invention (hereinafter also referred to as the "pharmaceutical composition of the present invention").

[0071] In the pharmaceutical composition of the present invention, the "glutathione metabolism-related enzyme inhibitor" is as described above in the description of the sensitivity prediction method of the present invention. Examples of the glutathione metabolism-related enzyme inhibitor include a GPX4 inhibitor, a GCL inhibitor, or a GS inhibitor, preferably a GPX4 inhibitor or a GCL inhibitor, more preferably RSL3, ML162, or buthionine sulfoximine (BSO).

[0072] The pharmaceutical composition of the present invention may contain one glutathione metabolism-related enzyme inhibitor or two or more glutathione metabolism-related enzyme inhibitors, and may further contain other anticancer drugs as long as they do not inhibit the action of the glutathione metabolism-related enzyme inhibitor.

[0073] The pharmaceutical composition of the present invention may further contain pharmaceutically acceptable additives, such as carriers (such as solid or liquid carriers), excipients, diluents, disintegrants, binders, coating agents, lubricants, glidants, gliding agents, flavoring agents, sweeteners, colorants, emulsifiers, surfactants, solubilizers, suspending agents, preservatives, buffers, pH adjusters, etc. In this case, the additives etc. can be appropriately selected depending on the dosage form of the preparation.

[0074] The pharmaceutical composition of the present invention may be formulated into any dosage form, such as solid preparations such as tablets, granules, powders, pills, capsules, etc., liquid preparations such as solutions, suspensions, syrups, etc., gels, aerosols, etc. When the pharmaceutical composition is used as a liquid preparation, it can also be formulated as a dry product intended to be reconstituted with, for example, physiological saline immediately before use.

[0075] Furthermore, the amount of the glutathione metabolism-related enzyme inhibitor in the pharmaceutical composition of the present invention can be appropriately determined, and the amount can be changed depending on the dosage form, additives, the severity of the disease in the subject, the CSE expression level, etc. The pharmaceutical composition of the present invention may contain, for example, a therapeutically effective amount of the glutathione metabolism-related enzyme inhibitor. The pharmaceutical composition of the present invention may contain, for example, but is not limited to, 0.001 to 100,000 mg, preferably 0.01 to 5,000 mg, of the glutathione metabolism-related enzyme inhibitor.

[0076] The administration route of the pharmaceutical composition of the present invention includes, but is not limited to, oral administration and parenteral administration (e.g., intravenous administration, intraarterial administration, intramuscular administration, subcutaneous administration, transdermal administration, intraperitoneal administration, intratumoral administration, etc.). The dosage of the pharmaceutical composition of the present invention is not limited to, but may be, for example, 0.1 mg / kg / day to 1000 mg / kg / day, 1 mg / kg / day to 100 mg / kg / day, or 1 mg / kg / day to 50 mg / kg / day in terms of the amount of the active ingredient. The pharmaceutical composition of the present invention may be administered once, or multiple times at intervals of several hours to several months. The pharmaceutical composition of the present invention may be administered, for example, once every several hours to several months, for example, once every 8 hours, once every 12 hours, once a day, once a week, or once a month.

[0077] As mentioned above, in our previous study, we demonstrated that co-administration of a CSE inhibitor and an xCT inhibitor could treat CSE-overexpressing cancers. However, when using two types of drugs, it was necessary to determine the optimal dose and administration method for each drug, which was a major obstacle to clinical development.

[0078] In contrast, the pharmaceutical composition of the present invention can use only one type of glutathione metabolism-related enzyme inhibitor as the active ingredient, making clinical development easier than in the prior art, which uses two types of drugs.

[0079] <Composition for Measuring CSE Expression Levels> The present invention also provides a composition for use in the susceptibility prediction method of the present invention, which comprises a means for measuring CSE expression levels (hereinafter, sometimes referred to as the "composition for measuring CSE expression levels of the present invention"). Examples of the means for measuring CSE expression levels include antibodies that specifically bind to CSE protein. Examples of the means for measuring CSE expression levels also include nucleic acid probes and / or primer sets. As used herein, the term "nucleic acid probe" refers to a single-stranded nucleic acid that can hybridize to a specific nucleic acid and be used to detect or quantify the nucleic acid. The nucleic acid probe may, for example, hybridize to CSE mRNA or cDNA. As used herein, the term "primer set" refers to a combination of a forward primer and a reverse primer that can be used to amplify a specific sequence in a nucleic acid amplification reaction such as polymerase chain reaction (PCR). Primers are typically short-chain oligonucleotides with a length of 20 to 30 mers. The primer set may, for example, target CSE cDNA. The composition for measuring CSE expression levels of the present invention may further comprise a carrier such as water, a preservative, a buffer, a pH adjuster, etc.

[0080] <Kit for Measuring CSE Expression Level> The present invention also provides a kit for use in the susceptibility prediction method of the present invention described above, which includes a means for measuring CSE expression level (hereinafter, this may be referred to as the "kit for measuring CSE expression level of the present invention"). Examples of the means for measuring CSE expression level include antibodies that specifically bind to CSE protein. Examples of the means for measuring CSE expression level also include nucleic acid probes and / or primer sets. The nucleic acid probe may, for example, be one that hybridizes to CSE mRNA or cDNA. The primer set may, for example, be one that targets CSE cDNA.

[0081] The kit may include instructions for determining the level of CSE expression in cancer cells.

[0082] <Therapeutic Method> The present invention also provides a method for treating cancer (hereinafter, sometimes referred to as the "therapeutic method of the present invention"), which comprises administering a glutathione metabolism-related enzyme inhibitor to a subject. In the therapeutic method of the present invention, the cancer may be cancer of a subject predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor by the sensitivity prediction method of the present invention. In the therapeutic method of the present invention, the subject is preferably a subject having a cancer predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor by the sensitivity prediction method of the present invention. Administering a glutathione metabolism-related enzyme inhibitor to such a subject enables effective and efficient cancer treatment. The therapeutic method of the present invention may, for example, comprise: (a) using the sensitivity prediction method of the present invention to select a subject having a cancer predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor; and (b) administering a glutathione metabolism-related enzyme inhibitor to the subject selected in (a).

[0083] In the treatment method of the present invention, the "glutathione metabolism-related enzyme inhibitor" is as described above in the description of the sensitivity prediction method of the present invention. Examples of the glutathione metabolism-related enzyme inhibitor include a GPX4 inhibitor, a GCL inhibitor, or a GS inhibitor, preferably a GPX4 inhibitor or a GCL inhibitor, more preferably RSL3, ML162, ML210, or buthionine sulfoximine (BSO).

[0084] <Dosage Determination Method> The present invention also provides a method for determining the dosage of a glutathione metabolism-related enzyme inhibitor for a subject with cancer (hereinafter, sometimes referred to as the "dosage determination method of the present invention").

[0085] The dosage determination method of the present invention is characterized in that the dosage of a glutathione metabolism-related enzyme inhibitor is determined based on the CSE expression level.

[0086] The dosage determination method of the present invention includes, for example, measuring the CSE expression level in cancer cells derived from a subject. The measurement of the CSE expression level may be carried out in vitro.

[0087] In the dosage determination method of the present invention, overexpression of CSE in cancer cells indicates that the dosage is the first dose, and no overexpression of CSE in cancer cells indicates that the dosage is the second dose.

[0088] Therefore, the dosage determination method of the present invention may include determining the dosage of the glutathione metabolism-related enzyme inhibitor as a first dose when CSE is overexpressed in cancer cells, and determining the dosage of the glutathione metabolism-related enzyme inhibitor as a second dose when CSE is not overexpressed in cancer cells.

[0089] In the dosage determination method of the present invention, the "first dose" may be a therapeutically effective amount in a patient with a cancer that overexpresses CSE, and the "second dose" may be a therapeutically effective amount in a patient with a cancer that does not overexpress CSE. The first dose may be lower than the second dose, for example, by 1.2-fold or more, 1.5-fold or more, 2-fold or more, 4-fold or more, 6-fold or more, 8-fold or more, 10-fold or more, 20-fold or more, 40-fold or more, 60-fold or more, or 80-fold or more lower than the second dose.

[0090] In the dosage determination method of the present invention, the determined dosage may be a recommended dosage.

[0091] <Marker> The present invention also provides a marker (sometimes referred to as "the marker of the present invention") for predicting or assessing the sensitivity of a subject's cancer to an inhibitor of a glutathione metabolism-related enzyme, which comprises a CSE protein or mRNA. The present invention also provides use of the CSE protein or mRNA (sometimes referred to as "the use of the present invention") as a marker or indicator for predicting or assessing the sensitivity of a subject's cancer to an inhibitor of a glutathione metabolism-related enzyme.

[0092] The present invention will be described in more detail below using examples, although the technical scope of the present invention is not limited to these examples.

[0093] (Example 1) Expression levels of CSE, GCLC, GS, and GPX4 in ovarian cancer cell lines The expression levels of CSE, GCLC, GS, and GPX4 in the following ovarian cancer cell lines were analyzed by Western blotting: OVSAHO (Human Science Research Resources Bank), OVTOKO (Human Science Research Resources Bank), OVISE (Human Science Research Resources Bank), KURAMOCHI (Human Science Research Resources Bank), RMUG-S (Human Science Research Resources Bank), TYK-nu CP-r (Human Science Research Resources Bank), TYK-nu (Human Science Research Resources Bank), ES-2 (American Type Culture Collection), and OVCAR-3 (American Type Culture Collection).

[0094] Specifically, each ovarian cancer cell line was lysed in RIPA (Radio-Immunoprecipitation Assay) buffer to obtain a protein-containing lysate. This was fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and blotted onto an Immobilon-P membrane (Millipore). This was then incubated overnight at 4°C with primary antibodies: anti-CSE mouse monoclonal antibody (M03) (Abnova), anti-GCLC rabbit monoclonal antibody (ab125066) (Abcam), anti-GS mouse monoclonal antibody (sc-166882) (Santa Cruz Biotechnology), anti-GPX4 rabbit monoclonal antibody (ab125066) (Abcam), or anti-β-actin antibody (ab6276) (Abcam). The blots were then detected using horseradish peroxidase (HRP)-conjugated anti-mouse or anti-rabbit IgG antibodies as secondary antibodies and SuperSignal® West Dura Extended Duration Substrate (Thermo Fisher Scientific) as the HRP substrate.

[0095] Western blotting images were acquired using Fusion Capt Advance software (Vilber Lourmat, France), and the band areas were measured. The CSE expression level was normalized by dividing the CSE protein band area by the band area of ​​the endogenous control, β-actin. The CSE expression level of each cell line was calculated as a relative CSE expression level, with the CSE expression level of the OVISE cell line set at 1.

[0096] The results are shown in Figure 1A and B. CSE expression levels were highest in the OVISE cell line, approximately 0.5-fold higher in the OVTOKO and RMUG-S cell lines, and approximately 0.3-fold lower in the other ovarian cancer cell lines. GCLC, GS, and GPX4 were expressed in all ovarian cancer cell lines.

[0097] (Example 2) Sensitivity of ovarian cancer cell lines to the GPX4 inhibitor RSL3 The sensitivities of the ovarian cancer cell lines OVISE, OVTOKO, OVCAR-3, and KURAMOCHI (obtained from the same source as in Example 1) to the GPX4 inhibitor RSL3 were compared.

[0098] Specifically, 1 × 10 cells were placed in each well of an opaque-walled 96-well plate (Corning Inc.). 4 or 5 x 10 3 Ovarian cancer cell lines were seeded, and various concentrations of (1S,3R)-RSL3 (A15865) (AdooQ BioScience or Selleck (product number: S8155)) were added 6 hours after seeding. Cell viability was measured 96 hours later using the Cell Titer-Glo® Luminescent Cell Viability Assay (Promega). Luminescence activity was measured using a GloMAX Discover Microplate Reader (Promega). Cell viability was calculated as the ratio of the number of cells in wells containing various concentrations of RSL3 to the number of cells in wells without RSL3.

[0099] The cell viability as a function of RSL3 concentration in the cell culture medium is shown in Figure 2. The 50% inhibitory concentration (IC50) of RSL3 (the drug concentration at which cell viability is 50%) calculated from the cell viability curve in Figure 2 is shown in Table 1 below.

[0100]

[0101] The IC50 value of RSL3 was low in OVISE, which has a high CSE expression level, high in OVCAR-3 and KURAMOCHI, which have low CSE expression levels, and moderate in OVTOKO, which has a moderate CSE expression level. The IC50 value for OVISE was more than eight times lower than the IC50 values ​​for OVCAR-3 and KURAMOCHI. Therefore, it was shown that the higher the CSE expression level of cancer cells, the more sensitive the cancer cells are to GPX4 inhibitors.

[0102] (Example 3) Sensitivity of ovarian cancer cell lines to the GPX4 inhibitor ML162 An experiment similar to that in Example 2 was conducted, except that ML162 was used as the GPX4 inhibitor, to compare the sensitivity of the ovarian cancer cell lines OVISE, OVTOKO, OVCAR-3, and KURAMOCHI to the GPX4 inhibitor ML162.

[0103] The relationship between cell viability and the concentration of ML162 (Merck) in the cell culture medium is shown in Figure 3. The 50% inhibitory concentration (IC50) of ML162 (the drug concentration at which cell viability is 50%) calculated from the cell viability curve in Figure 3 is shown in Table 2 below.

[0104]

[0105] The IC50 value of ML162 was low in OVISE, which has a high CSE expression level, high in OVCAR-3 and KURAMOCHI, which have low CSE expression levels, and moderate in OVTOKO, which has a moderate CSE protein expression level. These results were consistent with the results of Example 2 obtained using RSL3 as a GPX4 inhibitor. Therefore, regardless of the type of GPX4 inhibitor, it was shown that the higher the CSE expression level of cancer cells, the more sensitive the cancer cells are to GPX4 inhibitors.

[0106] (Example 4) Expression levels of CSE, GCLC, GS, and GPX4 in melanoma cell lines Using the same method as in Example 1, the expression levels of CSE, GCLC, GS, and GPX4 in the following melanoma cell lines were analyzed by Western blotting: A2058 (Human Science Research Resources Bank), A375 (American Type Culture Collection), CJM (RIKEN BioResource Research Center), COLO679 (RIKEN BioResource Research Center), G-361 (American Type Culture Collection), HMCB (American Type Culture Collection), MeWo (Human Science Research Resources Bank), SK-MEL-1 (American Type Culture Collection), and VMM39 (American Type Culture Collection).

[0107] However, tubulin was used as an endogenous control instead of β-actin. The primary antibody used to detect tubulin was anti-α / β-tubulin rabbit polyclonal antibody (2148) (Cell Signaling). The CSE expression level of each cell line was calculated as a relative CSE expression level, with the CSE expression level of HMCB set at 1.

[0108] The results are shown in Figures 4A and 4B. The CSE expression level was highest in the HMCB cell line, approximately 0.2-fold higher in the CJM cell line than in the HMCB cell line, and approximately 0.1-fold higher or lower in the other melanoma cell lines than in the HMCB cell line. GCLC, GS, and GPX4 were expressed in all melanoma cell lines.

[0109] (Example 5) Sensitivity of melanoma cell lines to GPX4 inhibitors The sensitivity of melanoma cell lines HMCB, CJM, VMM39, and A2058 (obtained from the same source as in Example 4) to the GPX4 inhibitor RSL3 was compared.

[0110] Specifically, the cell viability of each melanoma cell line in the presence of RSL3 was measured in the same manner as in Example 2.

[0111] The cell viability as a function of RSL3 concentration in the cell culture medium is shown in Figure 5. The 50% inhibitory concentration (IC50) of RSL3 (the drug concentration at which cell viability is 50%) calculated from the cell viability curve in Figure 5 is shown in Table 3 below.

[0112]

[0113] The IC50 value of RSL3 was low in HMCB, which has a high CSE expression level, high in VMM39 and A2058, which have a low CSE expression level, and moderate in CJM, which has a moderate CSE expression level. The IC50 value for HMCB was more than 59-fold lower than the IC50 values ​​for VMM39 and A2058. Therefore, regardless of the type of cancer cell, the higher the CSE expression level of the cancer cell, the more sensitive the cancer cell is to the GPX4 inhibitor.

[0114] HMCB, CJM, and VMM39 did not have a BRAF V600 mutation, whereas A2058 had a BRAF V600E mutation. Therefore, the CSE expression level and sensitivity to GPX4 inhibitors in cancer cells were independent of the BRAF V600 mutation.

[0115] (Example 6) Sensitivity of ovarian cancer cell lines to GCL inhibitors The sensitivities of the ovarian cancer cell lines OVISE, OVTOKO, OVCAR-3, and KURAMOCHI to the GCL inhibitor buthionine sulfoximine (BSO) were compared.

[0116] 1 x 10 cells per well of a 96-well plate 4 pieces, 1.5×10 4 or 2 x 10 4 Ovarian cancer cell lines were seeded, and various concentrations of BSO were added 6 hours after seeding. Cell viability was measured 48 hours later using CellTiter-Glo® 2.0. Cell viability was calculated as the ratio of the number of cells in the wells containing various concentrations of BSO to the number of cells in the wells without BSO.

[0117] The cell viability as a function of BSO concentration in the cell culture medium is shown in Figure 6. The 50% inhibitory concentration (IC50) of BSO (the drug concentration at which cell viability is 50%) calculated from the cell viability curve in Figure 6 is shown in Table 4 below.

[0118]

[0119] For OVCAR-3 and KURAMOCHI, which have low CSE expression levels, the cell viability was above 0.5 at all BSO concentrations tested, so IC50 values ​​could not be determined. In contrast, IC50 values ​​could be determined for OVISE, which has high CSE expression levels, and OVTOKO, which has intermediate CSE expression levels.

[0120] The IC50 value of OVISE, which has a high CSE expression level, was approximately 2730-fold lower than that of OVTOKO, which has a moderate CSE expression level.

[0121] Therefore, it was shown that the higher the CSE expression level in cancer cells, the more sensitive the cancer cells are to GCL inhibitors.

[0122] (Example 7) In vivo sensitivity of ovarian cancer cell lines to the GPX4 inhibitor RSL3 The in vivo sensitivity of the ovarian cancer cell lines OVISE and KURAMOCHI (obtained from the same source as in Example 1) to the GPX4 inhibitor RSL3 was compared.

[0123] Specifically, 1.5 x 10 7 OVISE cultured cells or 1 x 10 7KURAMOCHI cells were implanted subcutaneously on the dorsal surface of immunodeficient nude mice (BALB / c-nu / nu, Jackson Laboratory Japan) to form tumors. Hereafter, the day the ovarian cancer cell line was implanted into the mice is designated as Day 1. After tumor formation, mice were intraperitoneally administered RSL3 in DMSO (0 or 10 mg / kg / day) once daily on Days 8-12, 15-19, and 22-26 (Figure 7). The RSL3 DMSO solution was prepared to a final concentration of 5% DMSO (dimethyl sulfoxide), 40% polyethylene glycol 300, 5% Tween 80, and 50% sterile ultrapure water.

[0124] The major and minor axes of the tumor were measured using calipers from day 8 to day 29, and the tumor volume was calculated using the following formula: tumor volume = major axis × major axis × minor axis ÷ 2. The tumor volume on day 8 was defined as 1, and the tumor volume was calculated as the relative tumor volume.

[0125] The results of an experiment in which OVISE was subcutaneously implanted into mice are shown in Figure 8. In an experiment in which OVISE, an ovarian cancer cell line with high CSE expression levels, was implanted subcutaneously, the group that did not receive RSL3 showed an increase in tumor volume during the experimental period, but the group that received RSL3 (10 mg / kg / day) showed a suppressed increase in tumor volume.

[0126] The results of an experiment in which KURAMOCHI was subcutaneously transplanted into mice are shown in Figure 9. In an experiment in which KURAMOCHI, an ovarian cancer cell line with low CSE expression levels, was subcutaneously transplanted, the tumor volume increased during the experimental period regardless of the presence or absence of RSL3.

[0127] These results indicated that, even in vivo, the higher the CSE expression level in cancer cells, the more sensitive the cancer cells were to GPX4 inhibitors.

[0128] All publications, patents, and patent applications cited herein are hereby incorporated by reference in their entirety.

Claims

1. A method for predicting the sensitivity of a subject's cancer to a glutathione metabolism-related enzyme inhibitor, comprising measuring the expression level of cystathionine gamma-lyase (CSE) in cancer cells derived from the subject, wherein overexpression of CSE in the cancer cells indicates that the cancer is highly sensitive to the glutathione metabolism-related enzyme inhibitor.

2. The method according to claim 1, wherein the glutathione metabolism-related enzyme inhibitor is a glutathione peroxidase 4 (GPX4) inhibitor, a glutamate-cysteine ​​ligase (GCL) inhibitor, or a glutathione synthetase (GS) inhibitor.

3. The method according to claim 2, wherein the glutathione metabolism-related enzyme inhibitor is RSL3, ML162, or buthionine sulfoximine (BSO).

4. A pharmaceutical composition comprising an inhibitor of glutathione metabolism-related enzymes for treating cancer in a subject predicted to be highly sensitive to a glutathione metabolism-related enzyme inhibitor by the method according to any one of claims 1 to 3.

5. A composition or kit for use in the method according to any one of claims 1 to 3, comprising a means for measuring the CSE expression level.

6. The composition or kit according to claim 5, wherein the means for measuring the CSE expression level is an antibody that specifically binds to the CSE protein.

7. A method for determining the dosage of a glutathione metabolism-related enzyme inhibitor for a subject having cancer, comprising measuring the CSE expression level in cancer cells derived from the subject, wherein overexpression of CSE in the cancer cells indicates a first dose, and non-overexpression of CSE in the cancer cells indicates a second dose, the first dose being lower than the second dose.

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