Method for providing information pertaining to cancer, system for providing information pertaining to cancer, and method for treating cancer

Abstract

There are many options in cancer evaluation and treatment, and it is desired to ascertain the characteristics and conditions of individual patients and improve treatment efficacy and cost performance.　Provided is a method for providing information pertaining to a cancer in a subject using an indicator based on the amount of D-amino acid in a biological sample from the subject, wherein the information is selected from the group consisting of: a verification result of the validity of a test or diagnosis result of the cancer in the subject; a classification of the degree of progression of the cancer in the subject; a result of a prognosis prediction for the cancer in the subject; and information for selecting a treatment means for the cancer in the subject. Also provided is a system for providing information pertaining to a cancer in a subject. Further provided is a cancer treatment method for treating a subject via a cancer treatment means selected on the basis of the information provided by the method or the system.

Description

Method for providing information about cancer, system for providing information about cancer, and method for treating cancer

[0001] The present invention relates to a method for providing information about cancer and a system for providing information about cancer. The present invention also relates to a method for treating cancer.

[0002] Tumors are cells that grow autonomously without normal control due to some abnormality in the genes of cells, while cancer (malignant tumors) is a type of invasive cell growth and metastasis. Cancer treatments include surgery, radiation therapy, chemotherapy, drug therapy, and immunotherapy, and are performed individually or in combination with several selected modalities. Advances in cancer research since the late 1990s have revealed that drug responses, such as efficacy and side effects, vary depending on the nature of the cancer. Biomarkers for selecting optimal drugs have been developed. Biomarkers include those that identify individual characteristics and types by examining changes in proteins and genes contained in blood, urine, saliva, cells, tissues, etc., as well as tumor markers used in health checkups and medical examinations. Drugs targeting molecules involved in cancer growth (molecular targeted drugs) have used biomarkers, such as EGFR gene mutations in lung cancer, ALK fusion genes, and HER2 protein overexpression in breast and gastric cancer, in relation to their mechanism of action. For example, mutation markers of the EGFR gene are used to predict the therapeutic effect of EGFR tyrosine kinase inhibitors (EGFR inhibitors). For immune checkpoint inhibitors, microsatellite instability, tumor mutation burden, PD-L1 positivity rate, and Epstein-Berr virus are being studied as candidate markers.

[0003] In recent years, advances in the technology for identifying and analyzing chiral amino acids have led to progress in quantitative research that has distinguished between trace amounts of D-amino acids and L-amino acids in living organisms, including mammals. This progress has shed light on the existence and functions of some D-amino acids, which, due to previous technological limitations, were treated as total amino acids (D-amino acids + L-amino acids) or simply as L-amino acids. It has been reported that the amounts of D-amino acids in living organisms, tissues, cells, and body fluids vary depending on their ingestion, symbiotic bacteria, metabolism (degradation, synthesis), transport, excretion, etc. (Non-Patent Documents 1 to 5), and that characteristic chiral amino acid profiles are exhibited depending on physical condition and disease, such as kidney disease (Patent Document 1). Furthermore, it has been reported that D-amino acids are involved in intestinal immunity (Non-Patent Document 6), protect kidney-derived cells (Non-Patent Document 2), and that carbohydrate metabolism is involved in the biosynthesis of D-serine in neurons (Non-Patent Document 7). It has been disclosed that the blood of cancer patients varies in D-serine, D-threonine, D-alanine, D-asparagine, D-allo-threonine, D-glutamine, D-proline, and D-phenylalanine in kidney cancer, D-histidine and D-asparagine in prostate cancer, and D-alanine in lung cancer (Patent Document 1). However, no stratification or evaluation of individual cancer patients has been performed based on the amount of D-amino acids.

[0004] International Publication No. 2013 / 140785 Japanese Patent Application Laid-Open No. 2008-96313 International Publication No. 2020 / 196436

[0005] Y. Miyoshi, R. Konno, J. Sasabe, K. Ueno, Y. Tojo, M. Mita, S. Aiso and K. Hamase, Alteration of intrinsic amounts of D-serine in mice lacking serine racemase and D-amino acid oxidase, Amino Acids, 43, 1919-1931 (2012). DOI: 10.1007 / s00726-012-1398-4Y. Nakade, Y. Iwata, K. Furuichi, M. Mita, K. Hamase, R. Konno, T. Miyake, N. Sakai, S. Kitajima, T. Toyama, Y. Shinozaki, A. Sagara, T. Miyagawa, A. Hara, M. Shimizu, Y. Kamikawa, K. Sato, M. Oshima, S. Yoneda-Nakagawa, Y. Yamamura, S. Kaneko, T. Miyamoto, M. Katane, H. Homma, H. Morita, W. Suda, M. Hattori and T. Wada, Gut microbiota-derived D-serine protects against acute kidney injury, JCI Insight, 3 (20) (2018). DOI: 10.1172 / jci.insight.97957M. Ariyoshi, M. Katane, K. Hamase, Y. Miyoshi, M. Nakane, A. Hoshino, Y. Okawa, Y. Mita, S. Kaimoto, M. Uchihashi, K. Fukai, K. Ono, S. Tateishi, D. Hato, R. Yamanaka, S. Honda, Y. Fushimura, E. Iwai-Kanai, N. Ishihara, M. Mita, H. Homma and S.Matoba, D-Glutamate is metabolized in the heart mitochondria, Scientific Reports, 7, 43911 (2017). DOI: 10.1038 / srep43911P. Wiriyasermkul, S. Moriyama, Y. Tanaka, P. Kongpracha, N. Nakamae, M. Suzuki, T. Kimura, M. Mita, J. Sasabe and S. Nagamori, bioRxiv preprint. DOI: 10.1101 / 2020.08.10.244822A. Hesaka, S. Sakai, K. Hamase, T. Ikeda, R. Matsui, M. Mita, M. Horio, Y. Isaka and T. Kimura, D-Serine reflects kidney function and diseases, Scientific Reports, 9, 5104 (2019). DOI: 10.1038 / s41598-019-41608-0J. Sasabe, Y. Miyoshi, S. Rakoff-Nahoum, T. Zhang, M. Mita, BM Davis, K. Hamase and MK Waldor, Interplay between microbial D-amino acids and host D-amino acid oxidase modifies murine mucosal defense and gut microbiota, Nature Microbiology, 1, 16125 (2016). DOI: 10.1038 / microbiol.2016.125M. Suzuki , Sasabe J , Miyoshi Y , Kuwasako K , Muto Y , Hamase K , M .Matsuoka, N. Imanishi and S. Aiso, Glycolytic flux controls D-serine synthesis through glyceraldehyde-3-phosphate dehydrogenase in astrocytes, Proceedings of the National Academy of Sciences of the United States of America, 112 (17), E2217-E2224 (2015). DOI: 10.1073 / pnas.1416117112N. Okamoto, Y. Miyagi, A. Chiba, M. Akaike, M. Shiozawa, A. Imaizumi, H. Yamamoto, T. Ando, ​​M. Yamakado and O. Tochikubo, Diagnostic modeling with differences in plasma amino acid profiles between non-cachectic colorectal / breast cancer patients and healthy individuals, International Journal of Medicine and Medical Sciences, 1 (1), 001-008 (2009). DOI: 10.5897 / IJMMS.9000074 Naoyuki Okamoto, Cancer screening using "Amino Index Technology", Ningendock, 26 (3), 454-466 (2011). DOI:10.11320 / ningendock.26.454.

[0006] Cancer is the leading cause of death, and there are many treatment options available, including surgery, radiation therapy, chemotherapy, drug therapy, and immunotherapy. However, there is a strong need for methods to improve treatment effectiveness and cost-effectiveness by identifying the characteristics and conditions of individual patients.

[0007] The inventors comprehensively quantified and analyzed chiral amino acids (D-amino acids and L-amino acids) in the blood of cancer patients and discovered that the amount of chiral amino acids in the blood is related to the pathology, stage, prognosis, and treatment effect. As a result of intensive research into this relationship, they developed an indicator based on D-amino acids, which they found to be clinically useful in diagnosis, stage classification, prognosis prediction, and treatment selection, and they arrived at the present invention, which provides a solution to the problems. That is, the present invention encompasses the following inventions.

[0008] [1] A method for providing information about cancer in a subject using an index based on the amount of a D-amino acid in a biological sample (e.g., blood, urine, or feces) from the subject, wherein the information is selected from the group consisting of: results of verifying the validity of a cancer test or diagnosis result in the subject; a classification of the stage of cancer in the subject; results of predicting the prognosis of cancer in the subject; and information for selecting a treatment for cancer in the subject. [2] The method of item 1, wherein the index is a formula or value obtained by correcting the amount of the D-amino acid by the amount of a substance in the body of the subject. [3] The method of item 2, wherein the substance in the body is an L-amino acid. [4] The method of item 1, wherein the index is a formula or value obtained by correcting the amount of the D-amino acid by an index of renal function of the subject. [5] The method according to item 4, wherein the indicator of renal function is the amount of one or more factors selected from the group consisting of creatinine, cystatin C, inulin clearance, creatinine clearance, urinary protein, urinary albumin, β2-MG, α1-MG, NAG, L-FABP, and NGAL. [6] The method according to any one of items 1 to 5, wherein the D-amino acid is one or more selected from the group consisting of D-proline, D-serine, D-alanine, D-asparagine, and D-leucine. [7] The method according to any one of items 1 to 6, wherein the cancer is a gastrointestinal cancer. [8] The method according to item 7, wherein the gastrointestinal cancer is gastric cancer, esophageal cancer, or colorectal cancer. [9] The method according to any one of items 1 to 8, wherein the cancer treatment is an anti-cancer drug.

[10] The method according to item 9, wherein the anti-cancer drug is an immune checkpoint inhibitor and / or an NMDA receptor antagonist.

[11] The method of Aspect 10, wherein the immune checkpoint inhibitor is an inhibitor of an immune checkpoint molecule selected from the group consisting of CTLA-4, PD-1, PD-L1, PD-L2, LAG-3, TIM3, BTLA, B7H3, B7H4, 2B4, CD160, A2aR, KIR, VISTA, and TIGIT.

[0009]

[12] The method of any one of items 1 to 11, wherein the index is compared with a determination value determined from the amount of D-amino acids in a biological sample from a subject with cancer, thereby providing a result verifying the validity of a cancer test or diagnosis result in the subject.

[13] The method of any one of items 1 to 11, wherein the index is compared with a determination value determined from the amount of D-amino acids in a biological sample from a patient with cancer who is responsive and / or not responsive to cancer treatment, thereby providing information for selecting a cancer treatment for the subject.

[14] The method of any one of items 1 to 11, wherein the index is compared with a determination value determined from the amount of D-amino acids in a biological sample from a patient with cancer whose stage of cancer has been classified, thereby providing information on the classification of the stage of cancer in the subject.

[15] The method of any one of items 1 to 11, wherein the index is compared with a determination value determined from the amount of D-amino acids in a biological sample from a patient with cancer, which provides information on the prognosis of cancer in the subject.

[0010]

[16] A method for treating cancer, wherein the subject is treated with a cancer therapeutic selected based on information provided by the method according to any one of items 1 to 15.

[17] The method according to item 16, wherein the cancer is a gastrointestinal cancer.

[18] The method according to item 17, wherein the gastrointestinal cancer is gastric cancer, esophageal cancer, or colorectal cancer.

[19] The method according to any one of items 16 to 18, wherein the cancer therapeutic is an anti-cancer drug.

[20] The method according to item 19, wherein the anti-cancer drug is an immune checkpoint inhibitor.

[21] The method according to item 20, wherein the immune checkpoint inhibitor is an inhibitor of an immune checkpoint molecule selected from the group consisting of CTLA-4, PD-1, PD-L1, PD-L2, LAG-3, TIM3, BTLA, B7H3, B7H4, 2B4, CD160, A2aR, KIR, VISTA, and TIGIT.

[22] The method of any one of items 16 to 21, wherein the cancer treatment is or includes a means for adjusting the amount of a D-amino acid in the subject's biological sample so that the value of an index based on the amount of the D-amino acid in the subject's biological sample falls within or approaches a predetermined range.

[23] The method of item 22, wherein the means for adjusting the amount of a D-amino acid is administration of a D-amino acid or a pharmaceutically acceptable salt thereof, or administration of a composition from which a D-amino acid or a pharmaceutically acceptable salt thereof has been removed.

[24] The method of any one of items 16 to 23, wherein the cancer treatment is an NMDA receptor antagonist.

[25] The method of item 24, wherein the NMDA receptor antagonist is memantine or a pharmaceutically acceptable salt thereof.

[0011]

[26] A system for providing information about cancer in a subject, comprising a memory unit, an input unit, an analysis and measurement unit, a data processing unit, and an output unit, wherein the memory unit stores the amount of D-amino acids in a biological sample (e.g., blood, urine, or feces) and a judgment value related to cancer, wherein the judgment value is selected from the group consisting of: a judgment value related to the validity of a cancer test or diagnosis result determined from the amount of D-amino acids in the biological sample of a patient with cancer; a judgment value related to the progression of cancer determined from the amount of D-amino acids in the biological sample of a patient with cancer; a judgment value related to the prognosis of cancer determined from the amount of D-amino acids in the biological sample of a patient with cancer; and a judgment value related to the selection of a cancer treatment method determined from the amount of D-amino acids in the biological sample of a patient with cancer; the analysis and measurement unit separates and quantifies D-amino acids in the biological sample of the subject; the data processing unit selects information about the cancer in the subject by comparing an index based on the amount of D-amino acid of the subject with the judgment value stored in the memory unit; and the output unit outputs the information.

[27] The system of Item 26, wherein the index is a formula or value obtained by correcting the amount of the D-amino acid by the amount of a substance in the body of the subject.

[28] The system of Item 27, wherein the substance in the body is an L-amino acid.

[29] The system of Item 26, wherein the index is a formula or value obtained by correcting the amount of the D-amino acid by an index of renal function of the subject.

[30] The system of Item 29, wherein the index of renal function is the amount of one or more factors selected from the group consisting of creatinine, cystatin C, inulin clearance, creatinine clearance, urinary protein, urinary albumin, β2-MG, α1-MG, NAG, L-FABP, and NGAL.

[31] The system of any one of Items 26 to 30, wherein the D-amino acid is one or more selected from the group consisting of D-proline, D-serine, D-alanine, D-asparagine, and D-leucine.

[32] The system according to any one of items 26 to 31, wherein the cancer is a digestive cancer.

[33] The system according to item 32, wherein the digestive cancer is gastric cancer, esophageal cancer, or colorectal cancer.

[34] The system according to any one of items 26 to 33, wherein the cancer treatment is an anti-cancer drug.

[35] The system of item 34, wherein the anti-cancer drug is an immune checkpoint inhibitor.

[36] The system of item 35, wherein the immune checkpoint inhibitor is an inhibitor of an immune checkpoint molecule selected from the group consisting of CTLA-4, PD-1, PD-L1, PD-L2, LAG-3, TIM3, BTLA, B7H3, B7H4, 2B4, CD160, A2aR, KIR, VISTA, and TIGIT.

[37] The system of any one of items 26 to 36, wherein the system provides a result of verifying the validity of a cancer test or diagnosis result in a subject by comparing the index with a determination value determined from the amount of D-amino acids in a biological sample from a subject with cancer.

[38] The system of any one of items 26 to 36, wherein the system provides information for selecting a cancer treatment for the subject by comparing the index with a determination value determined from the amount of D-amino acids in a biological sample from a patient with cancer who is responsive and / or not responsive to a cancer treatment.

[39] The system of any one of items 26 to 36, which provides information on the classification of the stage of cancer in the subject by comparing the index with a determination value determined from the amount of D-amino acids in a biological sample from a patient with cancer whose stage of cancer has been classified.

[40] The system of any one of items 26 to 36, which provides information on the prognosis of cancer in the subject by comparing the index with a determination value determined from the amount of D-amino acids in a biological sample from a patient with cancer who has information on prognosis.

[0012] According to the present invention, by using an index based on the amount of D-amino acids in a subject with cancer, it is possible to analyze, extract, consider, select, and provide the optimal treatment at an individual level, thereby making it possible to control the effects and side effects of the treatment, thereby realizing precision medicine that contributes to improving patients' quality of life and reducing medical costs.

[0013] Amount of D-amino acids in plasma collected from healthy subjects and subjects with gastric or esophageal cancer. ROC curve using the amount of D-serine or D-alanine in plasma as the explanatory variable and the presence or absence of cancer in the subject as the outcome. ROC curve using an equation consisting of the amount of D-serine and D-alanine in plasma as the explanatory variable and the presence or absence of cancer in the subject as the outcome. Proportion of D-amino acids (% D) in the total amount of each amino acid in plasma collected from healthy subjects and subjects with gastric or esophageal cancer. ROC curve using the % D-alanine in plasma as the explanatory variable and the presence or absence of cancer in the subject as the outcome. % D-serine and % D in plasma. -asparagine as explanatory variables and ROC curve with the presence or absence of cancer as the outcome. Value of the amount of D-amino acids in plasma collected from healthy subjects and subjects with gastric cancer, corrected for creatinine (D-AA / Cre). ROC curve with D-serine / Cre or D-alanine / Cre in plasma as explanatory variables and the presence or absence of cancer as the outcome. ROC curve with D-serine / Cre and D-alanine / Cre in plasma as explanatory variables and the presence or absence of cancer as the outcome. D-amino acids in plasma collected from healthy subjects and subjects with gastric cancer at different stages of progression as explanatory variables. The proportion of D-amino acids (% D) in the total amount of each amino acid in plasma collected from healthy subjects and subjects with gastric cancer at various stages of progression. ROC curve using the amount of D-serine in plasma as the explanatory variable and the response to nivolumab administration in subjects with gastric cancer as the outcome. ROC curve using an equation consisting of the amounts of D-serine, D-asparagine, D-proline, and L-alanine in plasma as explanatory variables and the response to nivolumab administration in subjects with gastric cancer as the outcome. ROC curve using an equation consisting of the amounts of D-serine and D-alanine in plasma as explanatory variables and the response to nivolumab administration in subjects with gastric cancer as the outcome. ROC curve with progression-free survival or overall survival in subjects with gastric cancer who were administered nivolumab, with an explanatory variable consisting of the amount of D-serine and D-alanine in plasma. Tumor volume and weight in mice transplanted with cancer, depending on the amount of D-amino acids in the body. Configuration diagram of the system of the present invention. Tumor volume in mice transplanted with cancer, depending on the amount of D-amino acids in the body (with or without the addition of memantine). Amounts of D-amino acids (corrected for creatinine (Cr)) (upper row) and excretion rates (FE) in urine collected from healthy subjects and subjects with gastric cancer at different stages of progression. Ｄ－Ｓｅｒ) (lower row) The amount of D-Leu or L-Leu in urine collected from healthy subjects and subjects with gastric cancer at various stages (corrected for creatinine (Cr)). The amount of L-amino acids in urine collected from healthy subjects and subjects with gastric cancer at various stages (corrected for creatinine (Cr)) (corrected for Cr) (upper row), and excretion rate (FE Ｄ－Ｓｅｒ ) (Lower) % D-amino acids, D-amino acid amounts (nmol / g), and L-amino acid amounts (nmol / g) in feces. (Upper) D-amino acid amounts in plasma collected from healthy subjects and subjects with gastric cancer at different stages, and the percentage of D-amino acids in the total amount of each amino acid (% D). (Lower) Correlation diagram plotting D-amino acid amounts and eGFR values ​​in plasma collected from healthy subjects and subjects with gastric cancer at different stages.

[0014] Hereinafter, embodiments for carrying out the present invention will be described, but the technical scope of the present invention is not limited to the following embodiments. Note that the prior art documents cited in this specification are incorporated herein by reference.

[0015] The present invention provides a new approach to cancer evaluation, which uses an index based on the amount of D-amino acids in a biological sample, thereby improving the accuracy of diagnosis and assisting in the selection of appropriate treatment methods.

[0016] In one embodiment, the present invention provides a method for providing information about cancer in a subject using an index based on the amount of D-amino acids in the subject's biological sample (e.g., blood, urine, or stool), wherein the information is selected from the group consisting of: a result of verifying the validity of a test or diagnosis result for cancer in the subject; a classification of the stage of cancer in the subject; a result of predicting the prognosis of cancer in the subject; and information for selecting a treatment for cancer in the subject.

[0017] In the present specification, the term "cancer" is not particularly limited, and examples thereof include leukemia (e.g., acute myeloid leukemia, chronic myeloid leukemia, acute lymphocytic leukemia, chronic lymphocytic leukemia), malignant lymphoma (Hodgkin's lymphoma, non-Hodgkin's lymphoma (e.g., adult T-cell leukemia, follicular lymphoma, diffuse large B-cell lymphoma)), multiple myeloma, myelodysplastic syndrome, head and neck cancer, digestive cancer (e.g., esophageal cancer, esophageal adenocarcinoma, gastric cancer, colorectal cancer, colon cancer, rectal cancer), liver cancer (e.g., hepatocellular carcinoma), gallbladder / bile duct cancer, biliary tract cancer, pancreatic cancer, thyroid cancer, and the like. Cancers include lung cancer (e.g., non-small cell lung cancer (e.g., squamous non-small cell lung cancer, non-squamous non-small cell lung cancer), small cell lung cancer), breast cancer, ovarian cancer (e.g., serous ovarian cancer), cervical cancer, uterine cancer, endometrial cancer, vaginal cancer, vulvar cancer, kidney cancer (e.g., renal cell carcinoma), urothelial cancer (e.g., bladder cancer, upper urinary tract cancer), prostate cancer, testicular tumors (e.g., germ cell tumors), bone and soft tissue sarcoma, skin cancer (e.g., uveal melanoma, malignant melanoma, Merkel cell carcinoma), glioma, brain tumor (e.g., glioblastoma), pleural mesothelioma, and cancer of unknown primary origin). Cancers to which the present invention can be applied include, for example, digestive cancer, preferably gastric cancer, esophageal cancer, or colon cancer.

[0018] As used herein, the term "D-amino acid" refers to a proteinogenic amino acid in the "D-form," which is a stereoisomer of an "L-form" proteinogenic amino acid, as well as glycine, which does not have a stereoisomer. Specifically, the term refers to glycine, D-alanine, D-histidine, D-isoleucine, D-allo-isoleucine, D-leucine, D-lysine, D-methionine, D-phenylalanine, D-threonine, D-allo-threonine, D-tryptophan, D-valine, D-arginine, D-cysteine, D-glutamine, D-proline, D-tyrosine, D-aspartic acid, D-asparagine, D-glutamic acid, and D-serine. Since D-cysteine ​​contained in a biological sample is oxidized to D-cystine outside the body, in one embodiment of the present invention, the amount of D-cysteine ​​contained in a biological sample can be calculated by measuring D-cystine instead of D-cysteine.

[0019] As used herein, the "amount of a D-amino acid in a biological sample" refers to the amount of a D-amino acid in a specific amount of biological sample (e.g., blood, urine, or feces), and may be expressed as a concentration. The amount of a D-amino acid in a biological sample is measured as the amount in a sample obtained by centrifugation, sedimentation, or other pretreatment for analysis. Therefore, the amount of a D-amino acid in a biological sample can be measured as the amount in the obtained biological sample (e.g., blood-derived blood samples such as whole blood, serum, and plasma; urine; feces). For example, in the case of analysis using HPLC, the amount of a D-amino acid contained in a given amount of biological sample is represented by a chromatogram, and can be quantified by comparison of peak height, area, and shape with standards or by analysis using calibration.

[0020] The amount of D-amino acids and / or L-amino acids can be measured by any method, such as chiral column chromatography, enzymatic methods, or immunological methods using monoclonal antibodies that distinguish optical isomers of amino acids. The amount of D-amino acids and / or L-amino acids in a sample in the present invention can be measured by any method known to those skilled in the art. For example, the following chromatographic and enzymatic methods (Y. Nagata et al., Clinical Science, 73 (1987), 105. Analytical Biochemistry, 150 (1985), 238., A. D'Aniello et al., Comparative Biochemistry and Physiology Part B, 66 (1980), 319. Journal of Neurochemistry, 29 (1977), 1053., A. Berneman et al., Journal of Microbial & Biochemical Technology, 2 (2010), 139., W. G. Gutheil et al., Analytical Biochemistry, 287 (2000), 196., G. Molla et al., Methods in Molecular Biology, 794 (2012), 273., T. Ito et al., Analytical Biochemistry, 371 (2007), 167.) etc.), antibody methods (T. Ohgusu et al., Analytical Biochemistry, 357 (2006), 15., etc.), gas chromatography (GC) (H. Hasegawa et al., Journal of Mass Spectrometry, 46 (2011), 502., MC Waldhier et al., Analytical and Bioanalytical Chemistry, 394 (2009), 695., A. Hashimoto, T. Nishikawa et al., FEBS Letters, 296 (1992), 33., H. Bruckner and A. Schieber, Biomedical Chromatography, 15 (2001), 166., M. Junge et al., Chirality, 19 (2007), 228., M. C. Waldhier et al., Journal of Chromatography A, 1218 (2011), 4537., etc.), capillary electrophoresis (CE) (H. Miao et al., Analytical Chemistry, 77 (2005), 7190., D. L. Kirschner et al., Analytical Chemistry, 79 (2007), 736., F. Kitagawa, K. Otsuka, Journal of Chromatography B, 879 (2011), 3078., G. Thorsen and J. Bergquist, Journal of Chromatography B, 745 (2000), 389., etc.), high performance liquid chromatography (HPLC) (N. Nimura and T. Kinoshita, Journal of Chromatography, 352 (1986), 169., A. Hashimoto et al., Journal of Chromatography, 582 (1992),Gogami et al., Journal of Chromatography B, 879 (2011), 3259., Y. Nagata et al., Journal of Chromatography, 575 (1992), 147., S. A. Fuchs et al., Clinical Chemistry, 54 (2008), 1443., D. Gordes et al., Amino Acids, 40 (2011), 553., D. Jin et al., Analytical Biochemistry, 269 (1999), 124., J. Z. Min et al., Journal of Chromatography B, 879 (2011), 3220., T. Sakamoto et al., Analytical and Bioanalytical Chemistry, 408 (2016), 517., W. F. Visser et al., Journal of Chromatography A, 1218 (2011), 7130., Y. Xing et al., Analytical and Bioanalytical Chemistry, 408 (2016), 141., K. Imai et al., Biomedical Chromatography, 9 (1995), 106., T. Fukushima et al., Biomedical Chromatography, 9 (1995), 10., R. J. Reischl et al., Journal of Chromatography A, 1218 (2011), 8379., R. J. Reischl and W. Lindner, Journal of Chromatography A, 1269 (2012), 262., S. Karakawa et al., Journal of Pharmaceutical and Biomedical Analysis, 115 (2015), 123., Hamase K, et al., Chromatography 39 (2018) 147-152, etc.).

[0021] The optical isomer separation and analysis system of the present invention may combine multiple separation and analysis methods. Specifically, the amount of D-amino acids and / or L-amino acids in a sample can be measured by using a method for analyzing optical isomers, which includes the steps of: passing a sample containing components having optical isomers, together with a first liquid as a mobile phase, through a first column packing material as a stationary phase to separate the components of the sample; individually retaining each of the components of the sample in a multi-loop unit; supplying each of the components of the sample individually retained in the multi-loop unit, together with a second liquid as a mobile phase, through a flow path to a second column packing material having an optically active center as a stationary phase to resolve the optical isomers contained in each of the components of the sample; and detecting the optical isomers contained in each of the components of the sample (Japanese Patent No. 4291628). In HPLC analysis, D- and L-amino acids may be derivatized in advance with fluorescent reagents such as o-phthalaldehyde (OPA) or 4-fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F), or diastereomerized using N-tert-butyloxycarbonyl-L-cysteine ​​(Boc-L-Cys) or the like (Kenji Hamase and Kiyoshi Zaitsu, Analytical Chemistry, Vol. 53, pp. 677-690 (2004)). Alternatively, D- and / or L-amino acids can be measured by immunological techniques using monoclonal antibodies that distinguish optical isomers of amino acids, for example, monoclonal antibodies that specifically bind to D- or L-amino acids. Furthermore, when the total amount of D- and L-amino acids is used as an indicator, it is not necessary to separate and analyze D- and L-amino acids; amino acids can also be analyzed without distinguishing between D- and L-amino acids. In this case, separation and quantification can be performed using enzymatic methods, antibody methods, GC, CE, or HPLC.

[0022] In the present invention, the amount of a biomolecule or drug, such as D-amino acids, L-amino acids, creatinine, or protein, is expressed not only in terms of simple mass, weight, or amount of substance (mol), but also in terms of any measurable physical quantity, such as the mass, weight, or amount of substance (mol) per tissue, cell, organ, or molecular unit, or per volume or weight, or the mass, weight, amount of substance (mol), concentration, specific gravity, or density in a biological sample, such as feces, blood, or urine.

[0023] As used herein, an "indicator based on the amount of D-amino acid" refers to a measured value of the amount of D-amino acid, D-amino acid clearance, D-amino acid excretion rate (Non-Patent Document 5), a formula or value corrected according to the purpose using the amount of D-amino acid as an explanatory variable, or a value calculated from a preset formula, and the value measured in a subject is referred to as a test value of an indicator based on the amount of D-amino acid. In one embodiment of the present invention, the amount of D-amino acid in a biological sample may be corrected for physiological variables such as age, sex, BMI, etc. Furthermore, when the dynamics of D-amino acids are affected by renal function, a value corrected by an indicator of renal function may be used. Although not intended to be limiting, the renal function indicator can be one or more selected from creatinine, cystatin C, inulin clearance, creatinine clearance, urinary protein, urinary albumin, β2-MG, α1-MG, NAG, L-FABP, NGAL, glomerular filtration rate, estimated glomerular filtration rate (eGFR), etc., and a specific example is the ratio of the amount of D-amino acid to the amount of creatinine. Furthermore, since it is known that D-amino acids in the body fluctuate in neurodegenerative diseases (ALS, etc.), autoimmune diseases (multiple sclerosis, etc.), etc. (Patent Documents 1 and 2), correction can also be made using fluctuation factors or markers of each disease.

[0024] As used herein, "verifying the validity of test or diagnostic results" refers to verifying the validity of diagnostic results for subjects diagnosed by clinical tests that may result in false positives, such as interviews or tests of samples collected from subjects (biochemical tests, serological tests, endocrine tests, tumor marker tests, microbiological tests, virological tests, genetic and chromosomal tests, cellular immune tests, pathological tests, etc.), imaging tests (endoscopy, contrast agent tests, ultrasound tests, CT scans, MRI scans, etc.), gene panel tests, nematode tests, microRNA tests, AminoIndex®, 5-ALA fluorescent risk tests, and companion diagnostic tests that investigate the effects and side effects of specific drugs in advance. Specifically, for subjects determined to be positive by a specific tumor marker, if the test value based on an index based on the amount of D-amino acids in a biological sample is determined to be positive, it can be determined to be a true positive, and if the test value is determined to be negative, it can be determined to be a false positive (type I error).

[0025] The validity of test or diagnostic results using an index based on the amount of D-amino acids can be verified using the judgment value of the index (also referred to herein as the "reference range" or "clinical judgment value"). The judgment value (reference range or clinical judgment value) that can be used in the present invention is generally set as the central 95% interval of the test value distribution of healthy individuals (reference individuals) or subjects with cancer who meet certain criteria, but any interval can also be set depending on the purpose. The judgment value is a standard for determining the diagnosis, prevention, treatment, and prognosis of a specific pathology, and includes a diagnostic threshold, a treatment threshold, and a preventive medicine threshold. These thresholds (cutoff values) can be set using analytical data or results regarding predictive and diagnostic capabilities using ROC curves (Receiver Operating Characteristic curves), multivariate logistic regression models, Cox proportional hazards models, etc., and can be set based on case-control studies, clinical empirical rules, case-series studies, cohort studies, expert consensus, etc. In one embodiment, for example, by comparing the indicator with a determination value determined from the amount of D-amino acids in a biological sample from a subject with cancer, it is possible to provide a verification result of the validity of the test or diagnosis result for cancer in the subject.

[0026] As used herein, "classification of the stage of cancer" refers to classifying the severity of cancer as a stage. Stages are determined primarily based on TNM factors, such as wall invasion depth (T), lymph node metastasis (N), and the presence or absence and location of other metastases (M), and include clinical and pathological classifications. Clinical classification is performed based on physical findings, diagnostic imaging, biopsy, cytology, etc., and serves as the basis for determining treatment methods. Pathological classification, on the other hand, is performed based on surgical specimens, peritoneal lavage cytology, etc., and serves as the basis for prognostic evaluation. Generally, various cancer treatment guidelines established by academic societies and the TNM classification established by the Union for International Cancer Control are used; for example, gastric cancer is classified into stages I to IV. In one embodiment, for example, by comparing the index with a value determined from the amount of D-amino acids in a biological sample from a subject with a cancer whose stage has been classified, information on the classification of the stage of cancer in the subject can be provided.

[0027] As used herein, "prediction of prognosis" refers to predicting or estimating the subsequent course and outlook for a disease or treatment. When expressing prognosis prediction, units such as hours, days, weeks, months, or years may be used. Kaplan-Meier analysis and the PaP score (Palliative Prognosis Score) and PPI (Palliative Prognostic Index) for cancer patients can be used as representative prognosis prediction tools. Prognosis includes organ function prognosis, estimated mortality prognosis, tumor shrinkage, growth, metastasis, recurrence, etc., and can be expressed in terms of variables (parameters) and units of each evaluation item. Prognosis prediction provides important information for selecting a treatment option. In one embodiment, for example, information about the prognosis prediction of cancer in a subject can be provided by comparing the index with a determination value determined from the amount of D-amino acids in a biological sample from a cancer-bearing subject that provides prognostic information.

[0028] As used herein, "selection of a therapeutic measure" refers to selecting the most appropriate therapeutic measure from among surgery, radiation therapy, chemotherapy, drug therapy, immunotherapy, dietary therapy, exercise therapy, etc., and each of these techniques (e.g., surgical procedure, administration method, etc.), or determining the priority of the appropriate therapeutic measure, or administering treatment to the subject so that a predetermined therapeutic measure is optimal. Criteria and objectives for selection include curing the disease, alleviating or eliminating symptoms, halting or slowing disease progression, preventing the disease or symptoms, suppressing the worsening of the underlying disease, avoiding or minimizing side effects, cost-effectiveness, and improving or maintaining quality of life. In one embodiment, for example, by comparing the index with a value determined from the amount of D-amino acids in a biological sample from a subject with cancer who is responsive and / or unresponsive to a cancer therapeutic measure, information for selecting a cancer therapeutic measure for the subject can be provided.

[0029] The present invention utilizes an index based on the amount of D-amino acids in a biological sample from a subject suspected of or diagnosed with cancer through a predetermined clinical test, enabling the validity of test and diagnostic results to be verified. Taking advantage of the differences in D-amino acid and L-amino acid profiles in the biological samples of subjects with and without cancer, in one embodiment, true positives and false positives can be determined by comparing the subject's test value for an index based on the amount of D-amino acids with a predetermined judgment value (reference range or clinical judgment value) of the index based on the amount of D-amino acids. Tumor markers (e.g., for gastrointestinal cancers, SCC, CEA, CA19-9, AFP, PIVKA-II, Span-1, anti-p53 antibody, etc.) are substances produced by cancer cells or by patient cells in response to tumors, and their detection is used to diagnose tumors, assess recurrence, metastasis, and therapeutic efficacy. However, there has been a problem in that they can also test positive in healthy individuals and those with benign diseases. The amount of D-amino acids in a biological sample fluctuates due to the influence of cancer on their uptake, absorption, transport, distribution, metabolism (synthesis and degradation), excretion, and activity. Therefore, the fluctuations in test values ​​of indicators based on the amount of D-amino acids in a biological sample are fundamentally different from the fluctuations of conventional tumor markers, making them highly useful for determining true positives and false positives. If a subject's symptoms suggest cancer, but a specific test yields a negative result, an indicator based on the amount of D-amino acids can be used to determine whether the result is a false negative (type II error) or true negative. The AminoIndex® test (Non-Patent Documents 8-9) is a test based on amino acid amount that does not distinguish between stereoisomers, while genetic tests are based on genotype. Therefore, an indicator based on the amount of D-amino acids that can distinguish between D- and L-amino acids and determine the phenotype of a disease state has unique characteristics and is effective in determining the authenticity of test results.

[0030] In another aspect, the verification results of the test and diagnostic results provided by the present invention may be used for screening for cancer or diagnosing its pathology. In yet another aspect, the results of verifying the validity of the test and diagnostic results can be used for screening for efficacy, side effects, and adverse reactions in drug development, for determining clinical trials, as alternative endpoints, and the like. When verifying test and diagnostic results, one or more D-amino acid species, L-amino acid species, correction factors, and indicators can be used, and multiple indicator sets can be simultaneously used in panel testing. The subject sample used may be the same as that used in a specified test, or may be collected at a different time in relation to the response or characteristics to cancer. Furthermore, the subject may be a mammal, including a human, or an animal in which cancer has been induced by cancer cell transplantation, genetic modification, or drug, or may be an individual, cell, tissue, organoid, or the like that serves as a specified cancer model.

[0031] In the present invention, an index based on the amount of D-amino acids in a subject's biological sample can be used to classify the stage of cancer. Taking advantage of the fact that the profiles of D-amino acids and L-amino acids in a biological sample from a subject with cancer vary depending on the stage of cancer, in one embodiment, the stage of cancer can be classified by comparing the subject's test value for an index based on the amount of D-amino acids with a predetermined judgment value (reference range or clinical judgment value) based on the amount of D-amino acids, thereby providing information regarding the subject's prognosis and treatment. For example, information regarding the classification of the stage of cancer in the subject can be provided by comparing the index with a judgment value determined from the amount of D-amino acids in a biological sample from a patient with cancer whose stage of cancer has been classified.

[0032] The present invention is a preliminary or auxiliary method for diagnosis, which is carried out by comparing a test value in a subject with a predetermined judgment value (reference range or clinical judgment value), and does not involve judgment by a physician, but aims to improve the diagnostic accuracy of a physician based on the verification results. This method can be carried out by persons other than physicians, such as clinical testing / health checkup / data processing companies, analysis systems, and analysis programs.

[0033] In one embodiment, the present invention provides information to assist in the selection of cancer treatment methods using an index based on the amount of D-amino acids in a subject's biological sample. The differences in D-amino acid and L-amino acid profiles in a subject's biological sample, related to cancer response and prognosis during treatment, are utilized to select the optimal treatment from among surgery, radiation therapy, chemotherapy, drug therapy, immunotherapy, dietary therapy, exercise therapy, etc., or to assist in determining the priority of treatments by comparing a predetermined judgment value (reference range or clinical judgment value) for an index based on the amount of D-amino acids with the subject's test values. Chemotherapy is the treatment of cancer using anticancer drugs, and compared with the local effects of surgery and radiation therapy, it is effective over a wider area, such as the whole body. For early-stage and advanced cancer, surgical treatment (reduced surgery, standard surgery, expanded surgery, etc.) and endoscopic treatment are often selected, but chemotherapy may also be performed in combination with surgery. The purpose of pre-operative chemotherapy is to reduce bleeding and physical burden by shrinking the cancer, and the purpose of post-operative chemotherapy is to suppress the recurrence, metastasis, and proliferation of residual cancer. In unresectable cases, chemotherapy is selected. In another aspect, an index based on the amount of D-amino acids can be used to select the most appropriate drug or to provide information to assist in determining the priority of the drug. As a specific example, for an index based on the amount of D-amino acids, judgment values ​​(reference ranges or clinical diagnostic values) regarding the efficacy, side effects, and adverse reactions of a given drug can be set in advance, and the appropriateness of drug administration can be determined by comparing them with the test values ​​of the subject. Furthermore, in another aspect, an index based on the amount of D-amino acids can be used to predict and assess the efficacy, side effects, and adverse reactions after drug administration, or to provide information to assist in determining whether to continue or discontinue administration, or the dosage and timing of administration.The drugs used herein include, but are not limited to, anti-cancer drugs, such as metabolic antagonists (fluorouracil (5-FU), tegafur / gimeracil / oteracil potassium combination (S-1), gemcitabine hydrochloride (GEM), levofolinate calcium (1-LV), folinate calcium (LV), tegafur / uracil combination, capecitabine, trifluridine / tipiracil hydrochloride combination), platinum Drugs (cisplatin (CDDP), oxaliplatin, miriplatin hydrate), anthracyclines (epirubicin hydrochloride), topoisomerase inhibitors (irinotecan hydrochloride hydrate), microtubule inhibitors (paclitaxel, docetaxel hydrate), alkylating agents (streptozocin), molecular targeted drugs (anti-VEGF antibody preparations: bevacizumab, anti-EGFR antibody preparations: cetuximab, panitumumab, anti-HER2 antibody preparations: trametinib, Stuzumab, anti-VEGFR antibody preparation: ramucirumab, BCR / ABL inhibitor: imatinib mesylate, multikinase inhibitor: sunitinib malate, regorafenib hydrate, sorafenib tosylate, lenvatinib mesylate, EGFR inhibitor: erlotinib hydrochloride, VEGF inhibitor: aflibercept beta, mTOR inhibitor: everolimus), immune checkpoint inhibitor (e.g., CTLA-4, PD- Inhibitors of immune checkpoint molecules selected from the group consisting of PD-1, PD-L1, PD-L2, LAG-3, TIM3, BTLA, B7H3, B7H4, 2B4, CD160, A2aR, KIR, VISTA, and TIGIT, such as anti-PD-1 antibodies (nivolumab, pembrolizumab), antitumor antibiotics (mitomycin C), corticosteroids (prednisolone, budesonide), herbal medicines, etc. Representative regimens for gastric cancer include SP therapy, XP therapy, SOX therapy, CapeOX (XELOX), etc., in which molecular targeted drugs are used depending on the results of genetic testing and protein testing (e.g., HER2, etc.) of the subject, and microtubule inhibitors, topoisomerase inhibitors, and immune checkpoint inhibitors are used in combination depending on the therapeutic effect, and the present invention can provide the information necessary for such selection.For example, if the test value of an index based on the amount of D-amino acids falls within a range in which the application of an immune checkpoint inhibitor is deemed appropriate, it can provide information necessary for selecting an immune checkpoint inhibitor, changing its priority, and changing the administration timing, etc., in a treatment plan aimed at improving the therapeutic effect.

[0034] In the present invention, adjusting the amount of D-amino acids in the body based on the test value of an index based on the amount of D-amino acids in the subject's biological sample (e.g., blood) (e.g., adjusting the amount of D-amino acids in the subject's biological sample (e.g., blood) so that the value of an index based on the amount of D-amino acids in the subject's biological sample (e.g., blood) falls within or approaches a predetermined range) can control the progression of cancer, change the therapeutic response of a subject diagnosed with cancer, and assist in the selection of a treatment option. Taking advantage of the differences in the profiles of D-amino acids and L-amino acids in a subject's biological sample in relation to the prognosis of cancer following drug administration, one embodiment involves pre-setting a range or judgment value (clinical diagnostic value) within which the therapeutic effect is expected for an index based on the amount of D-amino acids, and then adjusting the subject's test value to fit within that range (adjustment of test value). Specifically, by controlling the amount of D-amino acids in the subject's body, the test value is adjusted to maintain the value if it is within a set range, to decrease the value if it exceeds the set range, or to increase the value if it is below the set range. In another embodiment, if a range or judgment value (clinical diagnostic value) for the occurrence of side effects or adverse reactions is set for an indicator based on the amount of D-amino acids, treatment is performed so that the test value of the subject falls outside that range. To adjust the test value of an indicator based on the amount of D-amino acids in a biological sample that can be used in the present invention, drugs or foods that can increase or decrease the amount of D-amino acids in tissues, cells, organs, or body fluids by administering D-amino acids from an external source or by adding or removing D-amino acids from foods (compositions) can be used. For example, drinking an aqueous solution containing D-amino acids can increase D-amino acid concentrations in blood and tissues (Non-Patent Document 1), and ingesting foods from which D-amino acids have been removed can decrease D-amino acid concentrations in blood. The D-amino acids used here may contain modified or derivative D-amino acids, or pharmaceutically acceptable salts thereof, as long as they increase or decrease the amount of D-amino acids in the body and allow the adjustment of test values. They may also contain pharmacologically acceptable carriers, diluents, or excipients, or may take the form of prodrugs. When a drug is used to adjust a test value of a subject, a dosage form suitable for any administration route can be selected and formulated.For oral administration, dosage forms such as tablets, capsules, liquids, powders, granules, and chewable preparations can be designed; for parenteral administration, dosage forms such as injections, powders, and infusions can be designed. These preparations may also contain various pharmaceutical adjuvants, i.e., carriers and other auxiliary agents, such as stabilizers, preservatives, soothing agents, flavorings, corrigents, fragrances, emulsifiers, fillers, and pH adjusters, and can be incorporated within a range that does not impair the effects of the present invention. The optical purity of the D-amino acid used as a drug or raw material is preferably 50% or higher, more preferably 90% or higher; however, any optical purity can be selected within the effective range, and is not limited thereto. Furthermore, test values ​​based on the amount of D-amino acid can be adjusted using any physiological mechanism. Specifically, the amount of D-amino acids can be controlled by acting on the mechanisms of expression (promotion, inhibition, etc.) and / or activity (agonism, inhibition, stimulation, etc.) of proteins involved in the absorption, transport, distribution, metabolism (synthesis and / or degradation), excretion, or action of D-amino acids, or of D-amino acid transporters or receptors. Therefore, D-amino acid amount regulators that can be used in the present invention may directly or indirectly promote the gene expression of proteins involved in the absorption, transport, distribution, metabolism, or excretion of D-amino acids, such as the protein or a vector that expresses it, or a factor that regulates the activity upstream of the cascade that promotes the expression of the protein, or a vector that expresses it. D-amino acid amount regulators that can be used in the present invention may directly or indirectly suppress the gene expression of proteins involved in the absorption, transport, distribution, metabolism, or excretion of D-amino acids, such as small molecules, aptamers, antibodies, antibody fragments, as well as antisense RNA or DNA molecules, RNAi-inducing nucleic acids, microRNAs (miRNAs), ribozymes, genome-editing nucleic acids, and their expression vectors. The protein may be an enzyme such as a protein involved in the absorption, transport, distribution, metabolism (synthesis and / or degradation), excretion, or action of D-amino acids, for example, D-amino acid oxidase (DAO), D-aspartate oxidase (DDO), serine isomerase (SRR), or DPP-4.As a specific example, DAO inhibitors (e.g., risperidone, etc.) can increase the amount of D-amino acids by suppressing the oxidation of D-amino acids, and therefore can be used as agents for controlling the amount of D-amino acids. Furthermore, because D-amino acid transporters increase or decrease the amount of D-amino acids at the source and destination, agents that act directly or indirectly on D-amino acid transporters can also be applied to the present invention. Non-Patent Document 4 discloses that D-amino acid transporter proteins, such as the SMCT family and ASCT family, expressed in the brain, kidney, and intestinal tract, can change the localized amount of D-amino acids by agonists / inhibitors. These transporters are affected by cooperation / competition via cotransporters (e.g., sodium ions) and scaffolds, and the transport activity of D-amino acids can be controlled, for example, by sodium / glucose cotransporter (SGLT2) inhibitors. Therefore, agents that act on such transporters can also be used as agents for controlling the amount of D-amino acids. Patent Document 3 discloses that angiotensin 2 receptor antagonists (ARBs) change the amount of D-amino acids in the blood, and agents acting on such receptors can also be used as D-amino acid amount regulators. Furthermore, since D-serine, D-alanine, and glycine are coagonists of the NMDA-type glutamate receptor (NMDA receptor: N-methyl-D-aspartate receptor), NMDA receptor antagonists (e.g., memantine, ketamine, dextromethorphan, dextrorphan, amantadine, eliprodil, ifenprodil, phencyclidine, MK-801, dizocilpine, CCPene, flupirtine, or pharmaceutically acceptable salts thereof) can also change the amount and activity of D-amino acids in the body and can be used as D-amino acid amount regulators. As the NMDA receptor antagonist, memantine or a pharmaceutically acceptable salt thereof can be preferably used in the present invention. Similarly, drugs that exert their effects via delta-type glutamate receptors or AMPA-type glutamate receptors can also be applied to the present invention.

[0035] As used herein, the term "D-amino acid amount regulator" refers to an agent that, when applied (e.g., administered), can increase or decrease the amount of a D-amino acid in a subject's living body (e.g., in a cell, tissue, organ, or body fluid), or in isolated cells, tissues, or organoids, and may act on any mechanism, such as absorption, transport, distribution, metabolism (synthesis and / or degradation), or excretion. When the amount or concentration of a desired D-amino acid is known, the amount of the D-amino acid in a sample can be evaluated by appropriate testing or monitoring.

[0036] As used herein, the term "aptamer" refers to a synthetic DNA or RNA molecule or a peptide molecule that has the ability to specifically bind to a target substance, and can be chemically synthesized in a test tube in a short period of time. The aptamer used in the present invention can bind to, for example, a protein involved in the absorption, transport, distribution, metabolism, or excretion of D-amino acids, and inhibit their activity. The aptamers used in the present invention can be obtained, for example, by using the SELEX method to repeatedly select in vitro the binding to various molecular targets such as small molecules, proteins, and nucleic acids (see Tuerk C., Gold L., Science, 1990, 249(4968), 505-510; Ellington AD, Szostak JW., Nature, 1990, 346(6287):818-822; U.S. Patent No. 6,867,289; U.S. Patent No. 5,567,588; and U.S. Patent No. 6,699,843).

[0037] As used herein, the term "antibody fragment" refers to a portion of a full-length antibody that retains its antigen-binding activity, and generally includes the antigen-binding domain or variable domain. Examples of antibody fragments include F(ab')2, Fab', Fab, or Fv antibody fragments (including scFv antibody fragments). Fragments obtained by treating an antibody with a protease enzyme and optionally reducing it are also included in the antibody fragment category. The antibody or antibody fragment used in the present invention may be any of human-derived antibodies, mouse-derived antibodies, rat-derived antibodies, rabbit-derived antibodies, antibodies from camelids such as llamas, and goat-derived antibodies. Furthermore, these antibodies or antibody fragments may be polyclonal or monoclonal antibodies, complete or truncated antibodies (e.g., F(ab')2, Fab', Fab, or Fv fragments), chimeric antibodies, humanized antibodies, or fully human antibodies.

[0038] As used herein, the term "antisense RNA or DNA molecule" refers to a molecule that has a base sequence complementary to a functional RNA (sense RNA), such as messenger RNA (mRNA), and that, by forming a duplex with the sense RNA, inhibits the synthesis of the protein that the sense RNA is intended to control. In the present invention, antisense oligonucleotides containing antisense RNA or DNA molecules bind to the mRNA of proteins involved in the absorption, transport, distribution, metabolism, or excretion of D-amino acids, thereby inhibiting their translation into protein. This reduces the expression level of proteins involved in the absorption, transport, distribution, metabolism, or excretion of D-amino acids, thereby inhibiting their activity. Methods for synthesizing antisense RNA or DNA molecules are well known in the art and can be used in the present invention.

[0039] As used herein, the term "RNAi-inducing nucleic acid" refers to a polynucleotide capable of inducing RNA interference (RNAi) when introduced into a cell. The polynucleotide is typically an RNA, DNA, or chimeric molecule of RNA and DNA containing 19 to 30 nucleotides, preferably 19 to 25 nucleotides, and more preferably 19 to 23 nucleotides, and is optionally modified. RNAi may occur in mRNA, or in RNA immediately after transcription before processing, i.e., RNA with a nucleotide sequence containing exons, introns, a 3' untranslated region, and a 5' untranslated region. RNAi methods that can be used in the present invention include (1) directly introducing short double-stranded RNA (siRNA) into cells, (2) incorporating small hairpin RNA (shRNA) into various expression vectors and introducing the vector into cells, or (3) creating a vector that expresses siRNA by inserting a short double-stranded DNA corresponding to the siRNA between two promoters arranged in opposing directions, and then introducing the vector into cells. The RNAi-inducing nucleic acid may include siRNA, shRNA, or miRNA that enables cleavage of the RNA of the D-serine transporter protein or inhibition of its function, and these RNAi nucleic acids may be directly introduced using liposomes or the like, or may be introduced using an expression vector that induces these RNAi nucleic acids.

[0040] The RNAi-inducing nucleic acid used in the present invention for a protein associated with the absorption, transport, distribution, metabolism, or excretion of D-amino acids may be any nucleic acid that exhibits a biological effect of inhibiting or significantly suppressing the expression of a protein associated with the absorption, transport, distribution, metabolism, or excretion of D-amino acids, and those skilled in the art can synthesize such nucleic acids by referring to the base sequence of the protein. For example, such nucleic acids can be chemically synthesized using an automated DNA ( / RNA) synthesizer utilizing DNA synthesis techniques such as the solid-phase phosphoramidite method, or can be synthesized by an siRNA-related contract synthesis company (e.g., Life Technologies, Inc.). In one embodiment, the siRNA used in the present invention may be derived from its precursor, short-hairpin double-stranded RNA (shRNA), via processing by the intracellular RNase Dicer.

[0041] As used herein, "microRNA (miRNA)" refers to a single-stranded RNA molecule 21 to 25 bases long that is involved in post-transcriptional regulation of gene expression in eukaryotes. miRNAs generally recognize the 3'UTR of mRNA to suppress translation of target mRNA and inhibit protein production. Therefore, miRNAs that can directly and / or indirectly reduce the expression level of D-serine transporter proteins are also included within the scope of the present invention.

[0042] As used herein, the term "ribozyme" refers to a general term for an enzymatic RNA molecule capable of catalyzing the specific cleavage of RNA. Ribozymes include those with a size of 400 nucleotides or more, such as group I intron-type ribozymes and M1 RNA contained in RNase P. Other ribozymes have active domains of approximately 40 nucleotides, known as hammerhead or hairpin-type ribozymes (see, for example, Koizumi, M., and Otsuka, Eiko, Protein, Nucleic Acid, Enzymes, 1990, 35, 2191). For example, the self-cleaving domain of a hammerhead ribozyme cleaves the 3' side of C15 in the sequence G13U14C15. It has been shown that base pairing between U14 and A9 is important for its activity, and that cleavage can also be achieved with A15 or U15 instead of C15 (see, for example, Koizumi, M. et al., FEBS Lett, 1988, 228, 228). By designing a ribozyme whose substrate binding site is complementary to an RNA sequence near the target site, it is possible to obtain an RNA-cleaving ribozyme that recognizes the UC, UU, or UA sequence in the target RNA, similar to a restriction enzyme. Those skilled in the art can prepare such ribozymes by referring to the following literature: Koizumi, M. et al., FEBS Lett, 1988, 239, 285; Koizumi, M. and Otsuka, Eiko, Protein, Nucleic Acid, and Enzymes, 1990, 35, 2191; Koizumi, M. et al., Nucl. Acids Res., 1989, 17, 7059. Hairpin ribozymes can also be used in the present invention. This ribozyme is found, for example, in the minus strand of satellite RNA of tobacco ringspot virus (Buzayan, J.M., Nature, 1986, 323, 349). It has been shown that target-specific RNA-cleaving ribozymes can also be produced from hairpin ribozymes (see, for example, Kikuchi, Y. & Sasaki, N., Nucl. Acids. Res., 1991, 19, 6751; Kikuchi, Hiroshi, Chemistry and Biology, 1992, 30, 112). By using a ribozyme to specifically cleave the transcription product of a gene encoding a D-serine transporter protein, the expression of the D-serine transporter protein can be inhibited.

[0043] As used herein, the term "genome editing nucleic acid" refers to a nucleic acid used to edit a desired gene in a system utilizing a nuclease used in gene targeting. Nucleases used in gene targeting include not only known nucleases but also new nucleases that will be used for gene targeting in the future. For example, known nucleases include CRISPR / Cas9 (Ran, F.A., et al., Cell, 2013, 154, 1380-1389), TALEN (Mahfouz, M., et al., PNAS, 2011, 108, 2623-2628), ZFN (Urnov, F., et al., Nature, 2005, 435, 646-651), and the like.

[0044] Utilizing the fact that commensal bacteria, including enterobacteria, are one of the living body's resources of D-amino acids, the microflora and growth environment can be altered by administering antibiotics, intestinal regulators, oligosaccharides, probiotics, microbial transplantation, fecal transplantation, amelioration of dysbiosis, etc., thereby increasing or decreasing the amount of D-amino acids in the living body. While not intended to be limiting, it is known that ingestion of yogurt containing 1073R-1 lactic acid bacteria, as an example of probiotics, increases D-serine and decreases D-lysine in feces, and such lactic acid bacteria may be used as a D-amino acid amount regulator in the present invention.

[0045] Regardless of the above-mentioned mechanism, any medicine or food that can adjust test values ​​based on the amount of D-amino acids can be used as a means of controlling the amount of D-amino acids in the body in the present invention.

[0046] In this specification, the term "drug" is used to include pharmaceutical products and quasi-drugs.

[0047] In this specification, "food" refers to food in general, but also includes general foods including so-called health foods, as well as health functional foods such as foods for specified health uses and foods with nutrient functions, and further includes dietary supplements (supplements, nutritional supplements), feed, food additives, etc., in the food of the present invention.

[0048] In another aspect, the present invention provides a system or program for carrying out the above-mentioned method for providing information about cancer in a subject. For example, the present invention provides a system for providing information about cancer in a subject, comprising a memory unit, an input unit, an analysis and measurement unit, a data processing unit, and an output unit, wherein the memory unit stores the amount of D-amino acids in a biological sample and a judgment value related to cancer, wherein the judgment value is selected from the group consisting of: a judgment value related to the validity of a cancer test or diagnosis result determined from the amount of D-amino acids in the biological sample of a patient with cancer; a judgment value related to the stage of cancer determined from the amount of D-amino acids in the biological sample of a patient with cancer; a judgment value related to the prognosis of cancer determined from the amount of D-amino acids in the biological sample of a patient with cancer; and a judgment value related to the selection of a cancer treatment method determined from the amount of D-amino acids in the biological sample of a patient with cancer; the analysis and measurement unit separates and quantifies the D-amino acids in the biological sample of the subject; the data processing unit selects information about the cancer in the subject by comparing an index based on the amount of D-amino acid of the subject with the judgment value stored in the memory unit; and the output unit outputs the information.

[0049] Figure 17 is a diagram showing the configuration of a system of the present invention. The sample analysis system 10 shown in Figure 17 is configured to be able to carry out the method of the present invention. This sample analysis system 10 includes a memory unit 11, an input unit 12, an analysis and measurement unit 13, a data processing unit 14, and an output unit 15, and is able to analyze a biological sample and output information about cancer in a subject.

[0050] More specifically, in the sample analysis system 10 of the present invention, the memory unit 11 stores the amount of D-amino acid in a biological sample input from the input unit 12 and a judgment value related to cancer, the analysis measurement unit 13 separates and quantifies the biological sample, the data processing unit 14 compares an index based on the amount of D-amino acid in the subject with the judgment value stored in the memory unit to select information about cancer in the subject, and the output unit 15 outputs the information.

[0051] The storage unit 11 includes a memory device such as RAM, ROM, or flash memory, a fixed disk device such as a hard disk drive, or a portable storage device such as a flexible disk or optical disk. The storage unit stores data measured by the analysis and measurement unit, data and instructions input from the input unit, calculation results performed by the data processing unit, computer programs used for various processes of the information processing device, databases, etc. The computer program may be installed from a computer-readable recording medium such as a CD-ROM or DVD-ROM, or via the Internet. The computer program is installed in the storage unit using a known setup program, etc. The storage unit stores data on cancer-related determination values ​​input in advance from the input unit 12.

[0052] The input unit 12 is an interface or the like, and also includes an operation unit such as a keyboard, mouse, etc. This allows the input unit to input data measured by the analysis and measurement unit 13, instructions for the calculation processing to be performed by the data processing unit 14, etc. Furthermore, if the analysis and measurement unit 13 is external, for example, the input unit 12 may include an interface unit, separate from the operation unit, that can input measured data, etc. via a network or storage medium.

[0053] The analytical measurement unit 13 measures the amount of at least D-amino acids in a biological sample. Therefore, the analytical measurement unit 13 may have a configuration that enables separation and measurement of D- and L-amino acids. Amino acids may be analyzed one by one, or some or all types of amino acids may be analyzed together. The analytical measurement unit 13 is not intended to be limited to the following, but may be, for example, a chiral chromatography system, preferably a high-performance liquid chromatography system, equipped with a sample introduction unit, an optical resolution column, and a detection unit. To detect only the amount of a specific amino acid, quantification may be performed using an enzymatic method or an immunological method. The analytical measurement unit 13 may be configured separately from the renal pathology evaluation system, and measured data, etc., may be input via the input unit 12 using a network or a storage medium.

[0054] The data processing unit 14 can select information about cancer in a subject by comparing the index based on the measured amount of D-amino acid with the determination value stored in the storage unit. The index based on the amount of D-amino acid may be a formula or value corrected for the amount of a substance in the subject's body (e.g., the amount of L-amino acid or an index of renal function), or may be a formula or value corrected for physiological variables such as age, sex, and BMI.

[0055] The data processing unit 14 performs various arithmetic operations on the data measured by the analysis and measurement unit 13 and stored in the memory unit 11 in accordance with the programs stored in the memory unit. The arithmetic operations are performed by a CPU included in the data processing unit. This CPU includes functional modules that control the analysis and measurement unit 13, input unit 12, memory unit 11, and output unit 15, and is capable of performing various controls. Each of these units may be composed of an independent integrated circuit, microprocessor, firmware, etc.

[0056] The output unit 15 is configured to output information about the target cancer, which is the result of the arithmetic processing performed by the data processing unit. The output unit 15 may be an output means such as a display device such as a liquid crystal display that directly displays the results of the arithmetic processing, or a printer, or may be an interface unit for outputting to an external storage device or via a network.

[0057] In another aspect, the present invention may be a program that causes an information processing device to execute the method for providing information about cancer in a subject.

[0058] In one embodiment, the present invention may be a method for treating cancer, in which a subject is treated with a cancer treatment selected based on information about the cancer provided by an information device in which the above-described method, system, or program is implemented. By referring to the cancer information provided by the above-described invention, it becomes possible to select the optimal treatment for the subject.

[0059] The contents of all patent and non-patent literature or references explicitly cited in this specification are hereby incorporated by reference in their entirety.

[0060] The present invention will be described in detail below with reference to examples, but the present invention is not limited to these examples. Those skilled in the art can easily modify and alter the present invention based on the description in this specification, and such modifications and alterations are within the technical scope of the present invention.

[0061] In the examples, the meanings of the symbols are as follows:

[0062] D-AA: D-amino acid L-AA: L-amino acid Asn: asparagine Ser: serine Ala: alanine Pro: proline Leu: leucine PD-AA: D-amino acid concentration in plasma (nmol / mL) PL-AA: L-amino acid concentration in plasma (nmol / mL) PCre: creatinine concentration in plasma UD-AA / Cre: D-amino acid amount in urine / creatinine amount in urine (nmol / mg) UL-AA / Cre: L-amino acid amount in urine / creatinine amount in urine (nmol / mg) FD-AA: D-amino acid amount in feces (nmol / g) FL-AA: L-amino acid amount in feces (nmol / g) P%D: PD-AA / PD-AA + PL-AA x 100 (%)

[0063] The subjects included cancer patients who visited Keio University Hospital, as well as those who had not been diagnosed with cancer, kidney disease, or other diseases during a health checkup (healthy subjects: see M. Suzuki, et al., Amino Acids, 54, 421-432 (2022)). Blood samples were collected from subjects who had fasted for at least two hours, and the separated plasma was subjected to chiral amino acid analysis by 2D-HPLC. The data obtained were compared and analyzed. Both studies were approved by the Keio University Hospital Ethics Committee, and written informed consent was obtained from all subjects. The cancer patients received standard treatment at Keio University Hospital in accordance with the academic guidelines.

[0064] [Example 1] Determination using an index based on the amount of D-amino acids in blood

[0065] The test samples were collected from 25 subjects with gastric cancer who were not receiving immune checkpoint inhibitors, an anti-cancer drug, 6 subjects with esophageal cancer, and 81 healthy individuals. D-amino acids in plasma were analyzed for indicators to be used for verifying test or diagnostic results and / or classifying the stage of cancer. The decision value (cutoff value) or candidate decision value in the ROC curve was derived from the point where the distance from the curve to the point where the positive rate (sensitivity) was 1.00 (100%) and the specificity was 1.00 (100%) was minimal.

[0066] (1) Assessment using "PD-AA" as an index The amounts of D-Asn, D-Ser, D-Ala, D-Pro, and D-Leu detected in the plasma of a group of subjects with cancer and a group of healthy individuals are shown in Figure 1 as PD-AA (nmol / mL).

[0067] D-Leu is not observed in plasma from healthy individuals and is detected only in subjects with cancer, so it can be used in qualitative tests, with a positive rate (sensitivity) of 100% and a specificity of 48.4%.

[0068] The results of the t-test between the cancer subject group and the healthy control group for PD-Asn, PD-Ser, PD-Ala, and PD-Pro are shown in the table below. Since the PD-AA detected in the plasma from cancer patients was significantly elevated, the "amount of D-amino acids in the blood" represented by PD-AA can be used as an index using D-amino acids in the blood to verify test and diagnostic results.

[0069] ROC curve analysis showed that when the PD-Ser determination value for gastric cancer was set to 1.49, the positive rate was 96.0% and the specificity was 76.5% (Figure 2A), and when the PD-Ala determination value was set to 1.57, the positive rate was 92.0% and the specificity was 92.6% (Figure 2B). Furthermore, when the PD-Ser determination value for esophageal cancer was set to 1.89, the positive rate was 100% and the specificity was 92.6% (Figure 2C), and when the PD-Ala determination value was set to 2.31, the positive rate was 100% and the specificity was 95.1% (Figure 2D).

[0070] By conducting a panel test of PD-AA of multiple chiral amino acid types in each individual subject suspected of having cancer, it is possible to mutually verify the test and diagnostic results.

[0071] In esophageal cancer, analysis of the ROC curve using the regression equation obtained from the test values ​​of PD-Ser and PD-Ala: 2.03 x D-Ser + 0.268 x D-Ala - 7.75 showed that when the judgment value of the value calculated from this equation was set at -3.10, the positive rate was 100% and the specificity was 97.5% (Figure 3).

[0072] (2) Evaluation Using "P%D" as an Index PD% is shown in FIG. 4 for Asn, Ser, Ala, and Pro detected in the plasma of the cancer-bearing subjects and the healthy subjects.

[0073] The results of a t-test between the cancer subject group and the healthy control group for P%D-Asn, P%D-Ser, P%D-Ala, and P%D-Pro are shown in the table below. Since the P%D-AA detected in the plasma from cancer subjects was significantly elevated, the "ratio of D-amino acid content to L-amino acid content in blood," expressed as P%D-AA, can be used as an index of D-amino acids in blood to verify test and diagnostic results.

[0074] Analysis of the ROC curve showed that when the P% D-Ala determination value for gastric cancer was set at 54.6%, the positive rate was 88.0% and the specificity was 93.8% (FIG. 5).

[0075] By conducting a panel test on the P%D of multiple chiral amino acid species in individual subjects with cancer, the test and diagnostic results can be mutually verified.

[0076] Analysis of the ROC curve for the regression equation obtained from the test values ​​of P%D-Ala and P%D-Asn: 2.45 × %D-Ala + 1.06 × %D-Asn -3.57. When the judgment value of the value calculated from this equation was set at -1.85, the positive rate was 92.0% and the specificity was 92.6% (Figure 6).

[0077] (3) Determination using "PD-AA / PCre" as an index Figure 7 shows PD-AA / PCre corrected by Cre, an index of renal function, for D-Asn, D-Ser, D-Ala, and D-Pro detected in the plasma of the cancer subject group and the healthy control group.

[0078] The results of the t-test between the cancer subject group and the healthy control group for PD-Asn / PCre, PD-Ser / PCre, PD-Ala / PCre, and PD-Pro / PCre are shown in the table below. Since the PD-AA / Pcre detected in the plasma from cancer patients was significantly elevated, the "amount of D-amino acids in the blood," expressed as PD-AA, can be used as an index using D-amino acids in the blood to verify test and diagnostic results.

[0079] ROC curve analysis revealed that when the PD-Ser / PCre determination value for gastric cancer was set at 1.87, the positive rate was 96.0% and the specificity was 70.4% (Figure 8A), and when the PD-Ala / PCre determination value was set at 2.18, the positive rate was 92.0% and the specificity was 93.8% (Figure 8B). By conducting a panel test of multiple chiral amino acid PD-AAs for each individual subject suspected of having cancer, it is possible to mutually verify the test and diagnostic results.

[0080] Analysis of the ROC curve for the regression equation obtained from the test values ​​of PD-Ser / Cre and PD-Ala / PCre: 0.983 x D-Ala / Cre + 1.96 x D-Ser / Cre - 8.10 showed that when the judgment value of the value calculated from this equation was set to -2.02, the positive rate was 96.0% and the specificity was 93.8% (Figure 9).

[0081] (4) Classification of cancer progression using "PD-AA" and "P%D-AA" as indicators PD-AA and P%D-AA in gastric cancer were classified into stages (Stages I to IV) according to the 6th edition of the Gastric Cancer Guidelines (Japan Gastric Cancer Association, July 2021), and a t-test was performed (Figures 10 and 11).

[0082] PD-AA and P%D-AA, which are indicators of D-Asn, D-Ala, and D-Pro, were significantly elevated in the Stage-I group compared to the healthy control group, and were useful for verifying early testing and diagnosis. By conducting a panel test of PD-AA of multiple chiral amino acid species in individual subjects suspected of having cancer, it is possible to mutually verify the test and diagnosis results and determine the stage of the disease.

[0083] When one or more of PD-Ala and PD-Pro are elevated, the progression can be classified as Stage-I to III, and when there is a simultaneous increase in PD-Ser, the progression can be classified as Stage-IV. Furthermore, when one or more of P%D-Asn, P%D-Ala, and P%D-Pro are elevated, the progression can be classified as Stage-I to III, and when there is a simultaneous increase in P%D-Ser, the progression can be classified as Stage-IV.

[0084] [Example 2] Prognosis prediction using an index based on the amount of D-amino acids in the blood

[0085] The test subjects were 28 patients with unresectable, advanced, and recurrent gastric cancer who were receiving the anti-PD-1 antibody formulation nivolumab, an immune checkpoint inhibitor (ICI) anti-cancer drug. The amount of D-amino acids in plasma collected before the start of drug treatment was analyzed to determine the prognostic indicators. Treatment and use of immune checkpoint inhibitors were in accordance with the Gastric Cancer Guidelines, 6th Edition (July 2021, Japan Gastric Cancer Association). Nivolumab was administered intravenously at a dose of 480 mg daily every two or four weeks, within the scope of insurance coverage. According to the Gastric Cancer Guidelines, patients with highly microsatellite instability (MSI-High) tumors are eligible for second-line treatment with anti-PD-1 antibodies as an exception. To evaluate prognosis, patients were classified into complete response (CR) (signs of cancer have disappeared), partial response (PR) (condition has improved), stable SD (no change), and progressive PD (condition has worsened), which are criteria for measuring the effectiveness of cancer treatment. There were seven cases of CR to PR, where the condition improved for six months or more, eight cases of SD, where the progression-free survival period was less than six months, and 13 cases of refractory PD.

[0086] (1) Prognosis prediction for SD to PD using "PD-AA" as an index

[0087] By analyzing the ROC curve with outcomes of CR-PR and SD-PD after nivolumab administration, when the PD-Ser judgment value was set to 2.00, the poor prognosis rate (sensitivity) was 100% and the specificity was 75.0% (Figure 12).

[0088] By conducting a panel test for each indicator of multiple chiral amino acid species in an individual subject with cancer, it is possible to mutually verify the prognosis prediction.

[0089] By analyzing the ROC curve of the values ​​calculated from the regression equation obtained from the test values ​​of each index, when the prognostic value (judgment value) was set to −1.24 using −21.6 × D-Ser − 0.0370 × L-Ala + 46.7, the SD to PD (poor prognosis rate) was 100% and the specificity was 90.0% ( FIG. 13A ).

[0090] When the prognostic value (judgment value) was set to −0.72 using −87.4 × D-Ser −0.151 × L-Ala −6.11 × D-Pro + 195.6, the SD to PD (poor prognosis rate) was 100% and the specificity was 95.0% ( FIG. 13B ).

[0091] When the prognosis prediction value was set to −1.12 for −18.0 × D-Ser −0.0332 × L-Ala + 3.47 × D-Asn / Cre + 38.5, the poor prognosis rate was 100% and the specificity was 95.0% (FIG. 13C).

[0092] When the threshold calculated from the 95% confidence interval of the PD-Ser test value of the healthy subject group was set at 2.12, the SD to PD (poor prognosis rate) for subjects with an index above that was 100%, with a specificity of 75.0%. These prognostic predictions can assist in the selection of therapeutic measures, such as drug administration.

[0093] (2) Prognosis prediction of PD using "PD-AA" as an index

[0094] A t-test of PD-AA was performed between the CR-SD group (non-PD group) and the PD group after administration of nivolumab, and PD-Ser (p = 0.0021) and PD-Asn (p = 0.0158) showed significantly higher values.

[0095] When the threshold calculated from the 95% confidence interval of the PD-Ser test value of the healthy subject group was set at 2.12, the PD (poor prognosis rate) of subjects exceeding this threshold was 100%, and the specificity was 75.0%.

[0096] By conducting a panel test for each indicator of multiple chiral amino acid species (for example, D-Ser, D-Ala) in an individual subject with cancer, it is possible to verify the prognosis prediction of each.

[0097] Analysis using stepwise analysis and ROC curves revealed that the prediction formula for nivolumab non-responsiveness (PD) was -4.65 x D-Ser + 0.32 x D-Ala + 8.28, and the prognostic value (determined value) was set to -9.01 (D-Ser 2.18, D-Ala 3.56). PD (poor prognosis rate) was 76.9%, and non-responsive cases were detected with a specificity of 100%. The area under the curve (AUC) in the ROC curve was 0.9333 (Figure 14).

[0098] Furthermore, when the patients were divided into two groups based on the judgement score of -9.01 and the progression-free survival or overall survival was analyzed, the median progression-free survival was 1.1 months (95% confidence interval: 0.5-1.8) vs. 3.8 months (95% confidence interval: 3.0-6.1), with a hazard ratio of 5.1 (95% confidence interval: 2.0-13.1), p=0.0003, and the median overall survival was 3.4 months (95% confidence interval: 0.6-5.9) vs. 18.9 months (95% confidence interval: 5.2-not reached), with a hazard ratio of 7.1 (2.1-24.6), p=0.001, showing significant differences in both cases (Figure 15).

[0099] These prognostic predictions can assist in the selection of therapeutic measures such as drug administration.

[0100] In general, the median overall survival of patients with advanced, unresectable, recurrent gastric cancer who receive anticancer drug treatment after the third line is said to be less than six months, and if the selected anticancer drug is ineffective, there is a possibility that they will suffer significant health and economic disadvantages. Predicting treatment response and success and selecting an appropriate treatment (anticancer drug, etc.) can be of great benefit to patients, and the use of appropriate efficacy prediction markers has the special effect of improving quality of life and reducing the overall burden on the medical economy.

[0101] [Example 3] Prognosis by controlling the amount of D-amino acids in the body

[0102] Female Ly. 5.1 mice (6-8 weeks old) were given water containing no D-amino acids (control group: n=11), 1% D-Ser solution (D-Ser group: n=11), or 1% D-Ala solution (D-Ala group: n=12) on Day 14. Two weeks later (Day 0), MC38 cells (5×10 ５ After a further 3 weeks (Day-20, 21), the tumor volume and weight were measured and subjected to analysis.

[0103] The D-Ser group showed elevated PD-Ser levels, and both tumor volume and weight were significantly increased compared to the control group, indicating poor cancer prognosis (FIG. 16).

[0104] These data indicate that maintaining low levels of D-Ser and PD-Ser in the body suppresses the progression of cancer.

[0105] [Example 4] Inhibition of tumor growth by NMDA receptor antagonists

[0106] Female Ly. 5.1 mice (6-8 weeks old) were started to drink water containing no D-amino acids (control group) or 1% D-Ser solution (D-Ser group), and then colon cancer cell line MC38 cells (5 × 10 ５ After subcutaneous implantation, the mice were divided into a memantine treatment group and a control group. From Day 4 onwards, the NMDA receptor antagonist memantine was administered intraperitoneally daily (10-20 μg / BW(g)) to the treatment group. As a result, the increase in tumor volume caused by D-Ser was suppressed by the administration of memantine (Figure 18).

[0107] This demonstrates that an anticancer effect, namely, suppression of tumor growth, can be achieved by reducing the amount of D-amino acids that act on proteins that are receptors for D-amino acids.

[0108] [Example 5] Detection and classification of cancer progression using an index based on the amount of D-amino acids in urine

[0109] Urine samples were collected from 71 health screening patients (healthy individuals) and 78 gastric cancer patients (Stage I: 33, Stage II and III: 20, Stage IV: 25) after diagnosis and before treatment. UD-AA levels were measured, and UD-AA / Cre and excretion rates were calculated. Like PD-AA levels, UD-AA / Cre levels tended to increase, enabling the detection of cancer and the provision of information on its progression (Figure 19, top row; Figure 20, left row). In particular, UD-Leu / Cre levels are not detected in many healthy individuals, allowing for effective qualitative testing. Panel testing using multiple UD-AA and PD-AA-based indicators enabled more accurate cancer detection, validation of diagnostic results, and classification of cancer progression.

[0110] Excretion rates of D-Asn and D-Leu (FE Ｄ－ＡＡ ) also increased as the cancer progressed, making it possible to provide information on the stage of cancer progression.

[0111] Although UL-AA / Cre has the ability to detect cancer at Stage I (FIG. 21), UD-AA / Cre was able to provide information on the stage of progression with higher accuracy.

[0112] [Example 6] Detection and classification of cancer progression using an index based on the amount of D-amino acids in feces

[0113] FD-AA and FL-AA were measured in 24 healthy subjects and 33 subjects with gastric cancer (Stage IV: 30, Stage I: 3), and F%D was calculated. FD-AA, FL-AA, and F%D-Ala tended to increase with the progression of cancer, providing information on the classification of the stage of cancer (Figure 22). These results demonstrate that panel testing using multiple indicators based on FD-AA, UD-AA, and PD-AA can enable more accurate cancer detection, validation of diagnostic results, and classification of the stage of cancer.

[0114] Example 7: Demonstration and validation of Example 1

[0115] Validation of PD-AA in Examples 1 and 2 was performed on 84 healthy subjects and 137 gastric cancer patients (Stage I: 52, Stage II, III: 24, Stage IV: 32 (all patients at all stages were pre-treatment)) (Figure 23). As a result, all PD-AA and P%D showed trends similar to those in Example 1 (see Figures 10 and 11), demonstrating the concept and validity of various cancer assessments using an index based on the amount of PD-AA. Furthermore, this trend remained the same even after correction for renal function (Figure 24).

[0116] It has been shown that each PD-AA, particularly PD-Ala and PD-Pro, increases significantly from early Stage I. From data from 84 healthy individuals and 52 patients with early gastric cancer, analysis by ROC curve using values ​​corrected for renal function showed high accuracy in detecting and classifying early gastric cancer, with an AUC of 0.976, a sensitivity of 92.3%, and a specificity of 98.8%. Furthermore, by limiting the range of renal function from these data, more precise information on the stage of cancer progression can be provided. Specifically, in patients with relatively normal renal function (eGFR>60), PD-Ala and PD-Pro were able to classify the stage of progression with higher resolution. Furthermore, patients with relatively normal renal function and high PD-AA (e.g., D-Ser>3.0 nmol / mL) had a poor prognosis (P<0.001).

Claims

1. 1. A method for providing information about cancer in a subject using an index based on the amount of D-amino acids in a biological sample of said subject, comprising: Said information: a validation result of the cancer test or diagnosis result in the subject; staging the cancer in said subject; a prognostic result of the cancer in the subject; and Information for selecting a treatment for cancer in said subject The method is selected from the group consisting of:

2. The method according to claim 1, wherein the index is a formula or value obtained by correcting the amount of the D-amino acid by the amount of the substance in the subject's living body.

3. The method according to claim 2, wherein the biological substance is an L-amino acid.

4. The method according to claim 1, wherein the index is a formula or value obtained by correcting the amount of the D-amino acid by an index of renal function of the subject.

5. The method according to claim 4, wherein the indicator of renal function is the amount of one or more factors selected from the group consisting of creatinine, cystatin C, inulin clearance, creatinine clearance, urinary protein, urinary albumin, β2-MG, α1-MG, NAG, L-FABP, and NGAL.

6. The method according to any one of claims 1 to 5, wherein the D-amino acid is one or more selected from the group consisting of D-proline, D-serine, D-alanine, D-asparagine, and D-leucine.

7. The method according to any one of claims 1 to 5, wherein the cancer is a gastrointestinal cancer.

8. The method according to claim 7, wherein the gastrointestinal cancer is gastric cancer, esophageal cancer, or colon cancer.

9. The method according to any one of claims 1 to 5, wherein the cancer treatment is an anti-cancer drug.

10. The method of claim 9, wherein the anti-cancer drug is an immune checkpoint inhibitor and / or an NMDA receptor antagonist.

11. 11. The method of claim 10, wherein the immune checkpoint inhibitor is an inhibitor of an immune checkpoint molecule selected from the group consisting of CTLA-4, PD-1, PD-L1, PD-L2, LAG-3, TIM3, BTLA, B7H3, B7H4, 2B4, CD160, A2aR, KIR, VISTA, and TIGIT.

12. The method according to any one of claims 1 to 5, wherein the index is compared with a determination value determined from the amount of D-amino acids in a biological sample from a subject having cancer, thereby providing a verification result of the validity of a test or diagnosis result for the cancer in the subject.

13. The method according to any one of claims 1 to 5, wherein the index is compared with a judgment value determined from the amount of D-amino acids in a biological sample of a patient with cancer who responds and / or does not respond to cancer treatment, thereby providing information for selecting a cancer treatment in the subject.

14. The method according to any one of claims 1 to 5, wherein the index is compared with a judgment value determined from the amount of D-amino acids in a biological sample from a patient with cancer whose stage of cancer has been classified, thereby providing information about the stage of cancer in the subject.

15. The method according to any one of claims 1 to 5, wherein information about the prognosis of cancer in a subject is provided by comparing the index with a judgment value determined from the amount of D-amino acids in a biological sample of a patient having cancer, the judgment value providing information about the prognosis.

16. A pharmaceutical composition for treating cancer in a subject by a cancer treatment method selected based on information provided by the method of any one of claims 1 to 15, the pharmaceutical composition comprising an amino acid amount controller that adjusts the amount of D-amino acids in the subject's biological sample so that the value of an index based on the amount of D-amino acids in the subject's biological sample falls within or approaches a predetermined range as the cancer treatment method.

17. 17. The pharmaceutical composition of claim 16, wherein the agent for controlling the amount of the amino acid is selected from a D-aspartate oxidase (DDO) inhibitor, a sodium / glucose cotransporter (SGLT2) inhibitor, an angiotensin 2 receptor antagonist (ARB), and an N-methyl-D-aspartate (NMDA) receptor antagonist.

18. 1. A system for providing information about cancer in a subject, comprising: a memory unit; an input unit; an analysis and measurement unit; a data processing unit; and an output unit, The memory unit stores the amount of D-amino acid in the biological sample and a judgment value related to cancer, wherein the judgment value is: a judgment value regarding the validity of a cancer test or diagnosis result determined from the amount of D-amino acids in a biological sample of a patient with cancer; a determination value for the stage of cancer determined from the amount of D-amino acids in a biological sample from a patient with cancer; A prognostic value for cancer determined from the amount of D-amino acids in a biological sample from a patient with cancer; and a decision value for selecting a cancer treatment method determined from the amount of D-amino acids in a biological sample of a patient with cancer; the analytical measurement unit separates and quantifies D-amino acids in the subject's biological sample; the data processing unit selects information about the cancer in the subject by comparing the index based on the amount of D-amino acid in the subject with the determination value stored in the storage unit; The output unit outputs the information.