Combination therapy using human growth differentiation factor 15 (GDF-15) inhibitors and immune checkpoint blockers

Abstract

To solve the problem that, to date, many cancers are still areas of unmet medical needs, and accordingly, means to more effectively treat cancer are needed.SOLUTION: The present invention relates to uses of inhibitors of human Growth and Differentiation Factor 15 (GDF-15), and to combined uses of such inhibitors with immune checkpoint blockers, in treatment of solid cancers.SELECTED DRAWING: None

Description

[Technical Field]

[0001] This invention relates to the use of human growth differentiation factor 15 (GDF-15) inhibitors in the treatment of solid tumors, and to the use of such inhibitors in combination with immune checkpoint blockers. [Background technology]

[0002] To this day, numerous cancers remain areas of unmet medical needs, and therefore, there is a need for effective means of treating them.

[0003] Numerous types of cancer are known to express growth factors, including VEGF, PDGF, TGF-β, and GDF-15.

[0004] GDF-15, growth differentiation factor-15, is a diverse member of the TGF-β superfamily. It is a protein that is expressed intracellularly as a precursor, subsequently processed, and ultimately secreted from the cell into the environment. Both the active, fully processed (mature) form and the precursor of GDF-15 can be found outside the cell. The precursor is covalently bound to the extracellular matrix via a COOH-terminal amino acid sequence (Bauskin AR et al., Cancer Research 2005), thus existing outside the cell. The active, fully processed (mature) form of GDF-15 is soluble and found in serum. Therefore, the processed form of GDF-15 can potentially act on any target cell in the body connected to the blood circulation, as long as the potential target cell expresses a receptor for the soluble GDF-15 ligand.

[0005] During pregnancy, GDF-15 is found in the placenta under physiological conditions. However, numerous malignancies (particularly high-grade brain tumors, melanoma, lung cancer, gastrointestinal tumors, colon cancer, pancreatic cancer, prostate cancer, and breast cancer (Mimeault M and Batra SK, J. Cell Physiol 2010)) show increased GDF-15 levels in tumors and in serum blood. Similarly, correlations have been described between high GDF-15 expression and chemotherapy resistance (Huang CY et al., Clin. Cancer Res. 2009) and between high GDF-15 expression and poor prognosis (Brown DA et al., Clin. Cancer Res. 2009).

[0006] GDF-15 is expressed in various WHO-grade gliomas, as assessed by immunohistochemistry (Roth et al., Clin. Cancer Res. 2010). Furthermore, Roth et al. stably expressed a DNA construct or control construct expressing a small hairpin RNA targeting endogenous GDF-15 in SMA560 glioma cells. When using these pre-established and stable cell lines, they observed that tumorigenesis in mice with GDF-15 knockdown SMA560 cells was delayed compared to mice with the control construct.

[0007] Patent applications WO2005 / 099746 and WO2009 / 021293 relate to an anti-human GDF-15 antibody (Mab26) that can antagonist the effect of human GDF-15 (hGDF-15) on tumor-induced mass loss in vivo in mice. Similarly, Johnen H et al. (Nature Medicine, 2007) reported the effect of an anti-human GDF-15 monoclonal antibody on cancer-induced anorexia and mass loss, but observed no effect of the anti-human GDF-15 antibody on tumor size formed by cancer.

[0008] WO2014 / 049087 and PCT / EP2015 / 056654 relate to monoclonal antibodies against hGDF-15 and their medical use.

[0009] A recently developed approach to cancer therapy is the use of immune checkpoint blockers, such as human PD-1 inhibitors and human PD-L1 inhibitors. The rationale behind the use of these immune checkpoint blockers is that blocking immune checkpoints, which prevent the immune system from targeting cancer antigens and their respective cancer cells, may make the immune response to cancer more effective. While immune checkpoint blockers and certain combinations of immune checkpoint blockers have been shown to improve patient survival in melanoma patients (Cully M, "Combinations with checkpoint inhibitors at wavefront of cancer immunotherapy," Nat Rev Drug Discov. June 14, 2015 (6):374-5), not all melanoma patients achieved complete response, and results for numerous other cancers have not been published, and there are still reasons to suggest that the results in other indications may not be as favorable (such as mutational burden). [Prior art documents] [Patent Documents]

[0010] [Patent Document 1] WO2005 / 099746 [Patent Document 2] WO2009 / 021293 [Patent Document 3] WO2014 / 049087 [Patent Document 4] PCT / EP2015 / 056654 [Patent Document 5] WO2014 / 100689 [Non-patent literature]

[0011] [Non-Patent Document 1] Bauskin AR et al., Cancer Research 2005. [Non-licensed Document 2] Mimeault M and Batra SK, J. Cell Physiol 2010 [Non-licensed Document 3] Huang CYら, Clin. Cancer Res. 2009 [Non-licensed Document 4] Brown DAら, Clin. Cancer Res. 2009 [Non-licensed Document 5] Roth, Clin. Cancer Res. 2010 [Non-licensed Document 6] Johnen Hら(Nature Meicine, 2007) [Non-licensed Document 7] Cully M, "Combinations with checkpoint inhibitors at wavefront of cancer immunotherapy", Nat Rev Drug Discov. June 14, 2015 (6): pages 374-5 [Non-licensed Document 8] Cheng PFら: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. 2015 Sep 16;145:w14183 [Non-licensed Document 9] Li B and Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. 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[Non-Patent Document 27] Van der Burg SH et al.: "Immunoguiding, the final frontier in the immunotherapy of cancer." (2014), Cancer Immunotherapy meets oncology (edited by CM Britten, S Kreiter, M. Diken & HG Rammensee). Springer International Publishing Switzerland pp. 37-51 ISBN: 978-3-319-05103-1 [Non-Patent Document 28] Tanno T et al.: "Growth differentiation factor 15 in erythroid health and disease." Curr Opin Hematol. May 2010; 17(3): pp. 184-190. [Non-Patent Document 29] C. Robert et al. N Engl J Med 2015;372:2521-2532 [Non-Patent Document 30] Jackson and Linsley, Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application, Nat Rev Drug Discov. January 2010; 9(1): 57-67 pp. [Non-Patent Document 31] Knoepfel SA et al., "Selection of RNAi-based inhibitors for antiHIV gene therapy," World J Virol. June 12, 2012; 1(3): pp. 79-90. 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Mass Spectrom. 13, pp. 69-75 (2007) [Non-Patent Document 43] Zhang, J., Yao, Y.-H., Li, B.-G., Yang, Q., Zhang, P.-Y. and Wang, H.-T. (2015). Prognostic value of pretreatment serum lactate dehydrogenase level in patients with solid tumors: a systematic review and meta-analysis. Scientific Reports 5, 9800 [Non-Patent Document 44] Tumeh et al., Nature. November 27, 2014; 515(7528): pp. 568-571. [Non-Patent Document 45] Yadav M et al., Nature. November 27, 2014; 515(7528): pp. 572-576. [Non-Patent Document 46] Lasithiotakis, KG et al. Cancer / 107 / 1331~9. 2006 [Overview of the Initiative] [Problems that the invention aims to solve]

[0012] Therefore, to this day, there is still a need in this field for means to treat cancer more efficiently. More specifically, there is still a lack of means that can be used for more effective cancer immunotherapy. [Means for solving the problem]

[0013] The present invention satisfies the above-mentioned needs and solves the above-mentioned problems in the art by providing embodiments described below:

[0014] In particular, in attempts to identify means of effectively treating cancer, the inventors surprisingly found that as levels of hGDF-15 in patient serum increased, the likelihood of response to treatment with immune checkpoint blockers decreased significantly. Therefore, according to the present invention, the negative effect of hGDF-15 on the patient's response to treatment with immune checkpoint blockers can be inhibited by using an hGDF-15 inhibitor, thereby improving the patient's response to treatment with immune checkpoint blockers.

[0015] Unexpectedly, the inventors also found that hGDF-15 is associated with CD8 in cancer metastasis. + We also found an inverse correlation with the percentage of T lymphocytes. CD8 + This is noteworthy because the presence of T lymphocytes is clearly necessary for tumor regression after immune checkpoint inhibition using anti-PD-1 antibodies. Therefore, according to the present invention, therapeutic inhibition of hGDF-15 is used to inhibit CD8 in solid tumors, including tumor metastases. + This can increase the percentage of T lymphocytes in solid tumors. + The increase in T lymphocytes can be suitably used for the therapy of solid tumors, particularly immunotherapy. Therefore, in an embodiment of the present invention, a particularly preferred therapeutic combination is the combination of an hGDF-15 inhibitor with an immune checkpoint blocker. The advantageous effect of this combination is that inhibition of hGDF-15 leads to the suppression of CD8 in solid tumors. + The goal is to increase the percentage of T lymphocytes, thereby leading to a synergistic therapeutic effect with immune checkpoint inhibition.

[0016] hGDF-15 inhibitors are effective in treating CD8 tumors in solid tumors. + In an attempt to further elucidate methods for increasing the percentage of T lymphocytes, the inventors found that hGDF-15 reduces the adhesion of T cells to endothelial cells. Therefore, according to the present invention, treatment using an hGDF-15 inhibitor can be used to increase the percentage of CD8 + This can increase the adhesion of T cells, including T cells, to endothelial cells. Such treatments of the present invention can increase the adhesion of CD8 cells to solid tumors from the bloodstream.+ will increase the infiltration of T cells. The increase in the percentage of CD8 + T cells in solid cancers resulting from such treatment with an hGDF-15 inhibitor is advantageous for cancer therapies, such as cancer immunotherapy, and can be used therein. The infiltration of CD8 + T cells into solid cancers and the presence of these CD8 + T cells in solid cancers are particularly advantageous for therapeutic approaches using immune checkpoint blockers, and thus a particularly advantageous use of the hGDF-15 inhibitor according to the invention is its use in combination with an immune checkpoint blocker.

[0017] Thus, the present invention provides improved means for cancer therapy by providing the preferred embodiments described below:

[0018] 1. An hGDF-15 inhibitor for use in a method for increasing the percentage of CD8 + T cells in solid cancers in a human patient, the hGDF-15 inhibitor being intended for administration to a human patient. 2. The hGDF-15 inhibitor for use according to item 1, wherein the patient has an hGDF-15 serum level of at least 1.2 ng / ml prior to the start of administration of the hGDF-15 inhibitor, the patient is preferably a patient having an hGDF-15 serum level of at least 1.5 ng / ml prior to the start of administration of the hGDF-15 inhibitor, and the patient is more preferably a patient having an hGDF-15 serum level of at least 1.8 ng / ml prior to the start of administration of the hGDF-15 inhibitor. 3. An hGDF-15 inhibitor for use according to any one of items 1 to 2, wherein the cancer is selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, stomach cancer, pancreatic cancer, liver cancer, testicular cancer, ovarian cancer, endometrial cancer, cervical cancer, brain tumor, breast cancer, gastric cancer, renal cell carcinoma, Ewing's sarcoma, non-small cell lung cancer, and small cell lung cancer; preferably, the cancer is selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, stomach cancer, pancreatic cancer, liver cancer, testicular cancer, ovarian cancer, endometrial cancer, and cervical cancer; more preferably, the cancer is selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, and stomach cancer. 4. An hGDF-15 inhibitor for use as described in any one of items 1 to 3, wherein the cancer is selected from the group consisting of melanoma, oral squamous cell carcinoma, colorectal cancer, and prostate cancer. 5. If the cancer is melanoma, an hGDF-15 inhibitor for use as described in any one of items 1 through 4. 6. An hGDF-15 inhibitor for use as described in any one of items 1 to 5, which is a monoclonal antibody or antigen-binding moiety thereof capable of binding to hGDF-15. 7. An hGDF-15 inhibitor for use as described in item 6, wherein the binding is to a conformational or discontinuous epitope on hGDF-15, and the conformational or discontinuous epitope is comprised of the amino acid sequences of SEQ ID NOs. 25 and SEQ ID NOs. 26. 8. An hGDF-15 inhibitor for use as described in item 6 or 7, wherein the antibody or its antigen-binding portion comprises a heavy chain variable domain comprising a CDR1 region containing the amino acid sequence of SEQ ID NO: 3, a CDR2 region containing the amino acid sequence of SEQ ID NO: 4, and a CDR3 region containing the amino acid sequence of SEQ ID NO: 5, and the antibody or its antigen-binding portion comprises a light chain variable domain comprising a CDR1 region containing the amino acid sequence of SEQ ID NO: 6, a CDR2 region containing the amino acid sequence ser-ala-ser, and a CDR3 region containing the amino acid sequence of SEQ ID NO: 7. 9. hGDF-15 inhibitors for use as described in any of items 1 to 5, which are short interfering RNA or siRNA hairpin constructs. 10. An hGDF-15 inhibitor for use as described in any one of items 1 to 9, wherein the method is a method for the treatment of cancer. 11. A method for treating cancer, which is a method for treating cancer by cancer immunotherapy, an hGDF-15 inhibitor for use as described in item 10. 12. hGDF-15 inhibitors for use as described in any of items 1 to 11, which are methods for the treatment of cancer metastases. 13. CD8 + This increases the adhesion of T cells to endothelial cells, thereby increasing the transmission of CD8 from the bloodstream to cancer cells. + By increasing T cell invasion, CD8 in cancer + An hGDF-15 inhibitor for use as described in any of items 1 through 12, which increases the percentage of T cells. 14. hGDF-15 inhibitors for use as described in any of items 1 through 13, where use is in combination with an immune checkpoint blocker. 15. Immune checkpoint blockers, i) Preferably, a human PD-1 inhibitor, which is a monoclonal antibody capable of binding to human PD-1 or the antigen-binding portion thereof. ii) Preferably, a human PD-L1 inhibitor, which is a monoclonal antibody capable of binding to human PD-L1 or the antigen-binding portion thereof. One or more of the group consisting of the above, an hGDF-15 inhibitor for use as described in any of items 1 to 14. 16. An hGDF-15 inhibitor for use as described in item 15, wherein the immune checkpoint blocker comprises a monoclonal antibody or its antigen-binding moiety capable of binding to human PD-1. 17. An hGDF-15 inhibitor for use as described in item 15 or 16, wherein the immune checkpoint blocker comprises a monoclonal antibody or its antigen-binding moiety capable of binding to human PD-L1. 18. A composition comprising an hGDF-15 inhibitor and an immune checkpoint blocker. 19. The composition according to item 18, wherein the hGDF-15 inhibitor is as defined in any one of items 6 to 9. 20. The composition according to item 18 or 19, wherein the immune checkpoint blocker is as specified in any one of items 15 to 17. 21. A composition according to any one of items 18 to 20, for use in medical settings. 22. A kit containing an hGDF-15 inhibitor and at least one immune checkpoint blocker. 23. A kit as described in item 22, wherein the hGDF-15 inhibitor is as specified in any one of items 6 through 9. 24. A kit as described in item 22 or 23, wherein the immune checkpoint blocker is as specified in any one of items 15 to 17. 25. A kit as described in any of items 1 to 24, wherein the hGDF-15 inhibitor and one or more or all immune checkpoint blockers are contained in separate containers or in a single container. 26. A kit or composition for medical use as described in any one of items 21 to 25, for use in a method for treating solid tumors. 27. A kit or composition for medical use as described in item 26, wherein the method is a method for cancer immunotherapy. 28. A kit or composition for medical use as described in item 27, wherein cancer is as defined in item 3, 4, or 5. 29. hGDF-15 inhibitors for use in a method of treating solid tumors with immune checkpoint blockers in human patients, which are intended to be administered to human patients. 30. The method is a method for cancer immunotherapy, an hGDF-15 inhibitor for use as described in item 29. 31. An hGDF-15 inhibitor for use as described in item 29 or 30, provided the patient is as specified in item 2. 32. An hGDF-15 inhibitor for use as described in any one of items 29 to 31, wherein the cancer is as defined in item 3, 4, or 5. 33. An hGDF-15 inhibitor for use as specified in any one of items 29 to 32, as provided for in any one of items 6 to 9. 34. An immune checkpoint blocker is an hGDF-15 inhibitor for use as described in any one of items 29 to 33, as specified in any one of items 15 to 17. 35. CD8 in cancer patients + An hGDF-15 inhibitor for use as described in any one of items 29 to 34, which increases the percentage of T cells. 36. CD8 + T cell adhesion to endothelial cells or CD8 on endothelial cells + Increased T cell rolling, thereby increasing the reach of CD8 cells from the bloodstream to cancer cells. + By increasing T cell invasion, CD8 in cancer + An hGDF-15 inhibitor for use as described in item 35, which increases the percentage of T cells. 37. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use in a method of treating solid tumors in human patients, wherein the hGDF-15 inhibitor and the immune checkpoint blocker are intended to be administered to human patients. 38. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in item 36, which is a method for cancer immunotherapy. 39. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in any one of items 1 through 38, as specified in item 2. 40. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in any one of items 1 through 39, provided that the cancer is as defined in item 3, 4, or 5. 41. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in any one of items 1 to 40, wherein the hGDF-15 inhibitor is as specified in any one of items 6 to 9. 42. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in any one of items 1 to 41, wherein the immune checkpoint blocker is as specified in any one of items 15 to 17. 43. hGDF-15 inhibitors are used in cancer to reduce CD8 + A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in any one of items 1 through 42, which increases the percentage of T cells. 44. hGDF-15 inhibitors, CD8 + This increases the adhesion of T cells to endothelial cells, thereby increasing the transfer of CD8 from the bloodstream to solid tumors. + By increasing T cell invasion, CD8 in solid tumors + Increase the percentage of T cells, Preferably, CD8 + The aforementioned increase in T cell adhesion to endothelial cells is due to CD8 on endothelial cells. + Increased T cell rolling, resulting in CD8 cells entering solid tumors from the bloodstream. + The combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in item 43 increases the aforementioned entry of T cells. 45. An in vitro method for determining whether a target substance is an hGDF-15 inhibitor, a) A step to activate endothelial cells, b) A step of incubating a first sample containing T cells in the presence of a solution containing hGDF-15 and in the presence of the substance of interest, c) A step of measuring the adhesion of the endothelial cells activated in step a) to the T cells derived from the first sample to obtain a first adhesion measurement result, d) A step of determining whether the target substance is an hGDF-15 inhibitor based on the first adhesion measurement result of step c), A method that includes this. 46. ​​The method according to item 45, wherein the endothelial cells are human umbilical vein endothelial cells. 47. The method according to any one of items 1 to 46, wherein the endothelial cells are human endothelial cells. 48. The method according to any one of items 1 to 47, wherein endothelial cells are activated by TNF-α and IFN-γ, and in the activation step, TNF-α and IFN-γ are preferably present in the culture medium at a final concentration of 5 to 20 ng / ml, and more preferably at a final concentration of 10 ng / ml, and IFN-γ in the culture medium. 49. The method according to any one of items 1 to 48, wherein the target substance is a substance capable of binding to hGDF-15, preferably an antibody capable of binding to hGDF-15 or an antigen-binding fragment thereof. 50. The method according to any one of items 1 to 49, wherein in step c), the endothelial cells and the T cells are used in a numerical ratio of 1:2 to 2:1, preferably in a numerical ratio of 1:1. 51. The method according to any one of items 1 to 50, wherein during step c), the endothelial cells are present on a coated cell culture surface, preferably on a cell culture surface coated with fibronectin. 52. The method according to any one of items 1 to 51, wherein during step b), hGDF-15 is present at a concentration of 50 to 200 ng / ml, preferably 100 ng / ml. 53. The method according to any one of items 1 to 52, wherein adhesion is measured by counting the number of rolling T cells in step c). 54. The method according to any one of items 1 to 53, wherein adhesion is measured by counting the number of adherent T cells in step c). 55. The method according to any one of items 1 to 54, wherein adhesion is measured in step c) by measuring the rolling speed of T cells. 56. The method according to any one of items 1 to 55, wherein in step d), the substance of interest is determined to be an hGDF-15 inhibitor if it increases the adhesion. 57. The method according to any one of items 1 to 56, wherein in step d), the substance in question is determined not to be an hGDF-15 inhibitor if it does not increase the adhesion. 58. In step b), the second sample is incubated in the presence of the solution containing hGDF-15 in the absence of the substance of interest, and the second sample contains T cells. Step c) further includes measuring the adhesion of the endothelial cells activated in step a) to the T cells derived from the second sample to obtain a second adhesion measurement result, The method according to any one of items 1 to 57, wherein in step d), if the first adhesion measurement result is increased compared to the second adhesion measurement result, the substance of interest is determined to be an hGDF-15 inhibitor. 59. In step b), the third sample is incubated in the absence of the solution containing hGDF-15 and in the absence of the substance of interest, and the third sample contains T cells, Step c) further includes measuring the adhesion of the endothelial cells activated in step a) to the T cells derived from a third second sample to obtain a third adhesion measurement result, The method according to any one of items 1 to 58, wherein in step d), the third adhesion measurement result is used as a reference adhesion measurement result indicating complete hGDF-15 inhibition. 60. T cells, CD8 + A T cell, as described in any one of items 1 through 59. 61. The method according to any one of items 45 to 59, wherein the T cells are pan-T cells. 62. The method according to any one of items 1 to 61, wherein the T cells are human T cells. 63. Use is in combination with polyinosinate:polycytidylic acid, or in combination with an hGDF-15 inhibitor and an immune checkpoint blocker for use as described in any one of items 37 to 44, wherein the combination is a polyinosinate:polycytidylic acid combination, and the hGDF-15 inhibitor for use as described in any one of items 1 to 17. 64. An hGDF-15 inhibitor for use according to any one of items 1 to 17 and 63, wherein the use is in combination with an anti-human CD40 antibody, preferably a monoclonal anti-human CD40 antibody, or in combination for use as described in any one of items 37 to 44 and 63, wherein the combination is in combination with an anti-human CD40 antibody, preferably a monoclonal anti-human CD40 antibody. 65. hGDF-15 inhibitors and for use in methods of treating solid tumors in human patients a) Polyinosinic acid: polycytidylic acid, b) Anti-human CD40 antibody, preferably monoclonal anti-human CD40 antibody, c) Polyinosinic acid: Polycytidylic acid and anti-human CD40 antibody, preferably monoclonal anti-human CD40 antibody A combination of any one of the following, which optionally includes an immune checkpoint blocker. [Brief explanation of the drawing]

[0019] [Figure 1] Figure 1 shows the GDF-15 serum levels of responders and non-responders in response to a treatment regimen. [Figure 2] Figure 2 shows the number of responders and non-responders in patient groups with hGDF-15 serum levels of <1.8 ng / ml, 1.8–4.2 ng / ml, and >4.2 ng / ml, respectively. [Figure 3] Figure 3 shows the probability of a response to treatment (responder 1) as predicted by a generalized linear model using GDF-15 as a continuous predictor variable. Circles represent data, and curves represent the model. The vertical line represents the GDF-15 concentration when the probability of treatment response is 0.5. [Figure 4] Figure 4 shows the Kaplan-Meier curves for survival in three groups defined by GDF-15 serum levels (<1.8, 1.8–4.2, >4.2 ng / ml). [Figure 5A]Figure 5A shows the probability of response to treatment (responder 1) predicted by a generalized linear model using LDH as a continuous predictor variable. Circles represent data, and curves represent the model. The vertical line represents the LDF concentration when the probability of treatment response is 0.5. The patient cohort was identical. However, in four patients, a reliable determination of LDH levels could not be made due to hemolysis. [Figure 5B] Figure 5B shows graphs of responders and non-responders, along with their respective hGDF-15 and LDH levels. When a cutoff value is selected to include all responders, the GDF-15-based analysis allows for the identification of 6 non-responders (out of 9), while the LDH-based analysis can only identify 4 non-responders (out of 9). For the LDH analysis, four hemolytic samples that would have resulted in data loss had to be excluded. [Figure 6] Figure 6 shows exemplary tissue sections obtained from melanoma brain metastases that were immunostained for GDF-15 and T cell marker proteins CD3 and CD8, respectively, as shown in the figure. The sections are either GDF-15 unresponsive (upper panel) or highly GDF-15 responsive (lower panel). CD3 and CD8-positive cells are indicated by arrows in the high-GDF-15 samples. CD3 and CD8 staining was performed from the same region of serial sections (but not from the same section). [Figure 7A] Figure 7A shows a plot of the percentage of CD3+ cells relative to the GDF-15 score across various melanoma brain metastases (7A). [Figure 7B] Figure 7B shows a plot of the percentage of CD8+ cells relative to the GDF-15 score across various melanoma brain metastases (7B). [Figure 8] Figure 8 shows a plot of GDF-15 scores against the percentage of CD8+ and CD3+ T cells in brain metastases from various tumor entities (melanoma, CRC, RCC, NSCLC, and SCLC). [Figure 9-1] Figure 9A shows the number of rolling T cells per field of view per second. Data were obtained from channel number 3 ("GDF-15") and channel number 2 ("control"). [Figure 9-2] Figure 9B shows the rolling velocity of T cells (measured at pixels per 0.2 seconds). Data were obtained from channel number 3 ("GDF-15") and channel number 2 ("control"). Figure 9C shows the number of adherent cells per field of view. Data were obtained from channel number 3 ("GDF-15") and channel number 2 ("control"). [Figure 9-3] Figure 9D shows the number of adherent cells per field of view. Data were obtained from channel number 3 ("GDF-15") and channel number 2 ("control"). [Figure 10A] Figure 10A shows the number of rolling T cells per field of view per second. Data were obtained from channel 1 (control T cells in unstimulated HUVEC as "negative control"), channel 2 (control T cells in stimulated HUVEC as "positive control"), channel 3 ("GDF-15"), channel 4 ("UACC257": T cells cultured in the supernatant of UACC257 melanoma cells containing secreted GDF-15), and channel 5 ("UACC257 + anti-hGDF-15": T cells cultured in the supernatant of UACC257 melanoma cells depleted of secreted GDF-15 using anti-hGDF-15 antibody B1-23 as an hGDF-15 inhibitor). [Figure 10B] Figure 10B shows the flow / adhesion assay performed as described in Example 3. T cells were pre-incubated with 100 ng / ml GDF-15 for 1 hour, or with 10 μg / ml antibody for 1 hour, as shown. The following anti-GDF-15 antibodies were used: H1L5 (humanized B1-23), 01G06, and 03G05 (genetically engineered humanized anti-GDF-15 antibodies according to the sequence from WO2014 / 100689). The results are shown in the figure, indicating the number of rolling cells per field of view per 20 seconds. [Figure 11]Figure 11 shows C57BL / 6J mice subcutaneously inoculated with 2 × 10⁵ colonic MC38tghGDF-15 cells. Treatment with anti-GDF-15 antibody (20 mg / kg body weight) was initiated on day 0 and repeated on days 3, 7, 10, 14, 17, and 21. On day 13, animals with tumors of similar size (100–150 mm³) were treated with or not treated with poly-ICLC (also abbreviated as "poly-IC") and anti-CD40 antibody. Mice that rejected the tumor, as previously established, were followed for 57 days. Mice with tumors were sacrificed according to criteria for animal well-being. [Figure 12] Figure 12 shows the cumulative survival rates in patient groups with GDF-15 levels of <1.5 ng / ml and ≥1.5 ng / ml, respectively. [Figure 13] Figure 13 shows the cumulative survival rates in the patient group with high GDF-15 levels (i.e., 50 patients with the highest GDF-15 levels) and the patient group with low GDF-15 levels (i.e., 49 patients with the lowest GDF-15 levels), respectively (median half of the entire study cohort). [Figure 14A]Figure 14A shows that serum hGDF-15 levels do not significantly correlate with tumor mutational load. hGDF-15 mRNA levels in samples obtained from cancer patients were plotted against the number of somatic mutations identified in the cancer. Somatic mutations were determined using exome sequencing. Data were analyzed using the UZH web tool obtained from University Hospital Zurich (Cheng PF et al.: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. 2015 / 9 / 16;145:w14183). Figure 14A shows a plot of cancer patient data obtained from the Cancer Genome Atlas (TGCA), which considers only patients with high-grade melanoma (the Cancer Genome Atlas is referenced in Cheng PF et al.: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. September 16, 2015;145:w14183). GDF-15 expression was assessed by normalization using the RSEM ("Expected Value Maximization RNA Seq") software package (Li B and Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. August 4, 2011;12:323.doi:10.1186 / 1471-2105-12-323). [Figure 14B]Figure 14B shows that serum hGDF-15 levels do not significantly correlate with tumor mutational load. hGDF-15 mRNA levels in samples obtained from cancer patients were plotted against the number of somatic mutations identified in the cancer. Somatic mutations were determined using exome sequencing. Data were analyzed using the UZH web tool obtained from University Hospital Zurich (Cheng PF et al.: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. 2015 / 9 / 16;145:w14183). Figure 14B shows plots of cancer patient data obtained from 40 additional metastatic melanoma patients from University Hospital Zurich, analyzed individually. [Figure 15] Figure 15 shows immunocytochemical images of CD8a in mice with wild-type tumors or tumors overexpressing transgenic (tg) hGDF15. Tissue sections were stained with anti-CD8a (1:100 dilution; 4SM15 antibody purchased from eBioscience). [Modes for carrying out the invention]

[0020] Definitions and General Techniques Unless otherwise defined below, terms used in this invention should be understood in accordance with their general meanings known to those skilled in the art.

[0021] The term “antibody” in this specification refers to any functional antibody capable of specifically binding to a target antigen, as generally outlined in Chapter 7 of Paul, WE (ed.): Fundamental Immunology, 2nd edition, Raven Press, Ltd., New York, 1989, which is incorporated herein by reference. Without specific limitations, the term “antibody” includes antibodies derived from any suitable source species, including chickens and mammals such as mice, goats, non-human primates, and humans. Preferably, the antibody is a humanized antibody. Preferably, the antibody is a monoclonal antibody that can be prepared by methods well known in the art. The term “antibody” includes IgG-1, -2, -3 or 4, IgE, IgA, IgM or IgD isotype antibodies. The term “antibody” includes monomeric antibodies (IgD, IgE, IgG, etc.) or oligomeric antibodies (IgA or IgM, etc.). The term "antibody" also encompasses isolated antibodies and genetically modified antibodies, such as chimeric antibodies, without any specific limitations.

[0022] The nomenclature of antibody domains follows terminology known in the art. Each monomer of an antibody contains two heavy chains and two light chains, as is commonly known in the art. Of these, each heavy chain and light chain contains a variable domain (V for the heavy chain) that is important for antigen binding. H And, regarding the light chain, V LThese heavy and light chain variable domains include (in order from the N-terminus to the C-terminus) regions FR1, CDR1, FR2, CDR2, FR3, CDR3, and FR4 (FR, framework region; CDR, complementarity-determining region, also known as hypervariable region). The identification and assignment of the above-mentioned antibody regions within antibody sequences can generally be performed using the IMGT / V-QUEST software described by Giudicelli et al. (IMGT / V-QUEST, an integrated software program for immunoglobulin and T cell receptor VJ and VDJ rearrangement analysis. Nucleic Acids Res. July 1, 2004; 32(Web Server issue):W435-40), which is consistent with Kabat et al. (Sequences of proteins of immunological interest, US Dept. of Health and Human Services, Public Health Service, National Institutes of Health, Bethesda, Md. 1983) or Chothia et al. (Conformations of immunoglobulin hypervariable regions. Nature. December 21-28, 1989; 342(6252): pp. 877-883), or is incorporated herein by reference. It is preferable that the antibody regions described above are identified and assigned using the IMGT / V-QUEST software.

[0023] A "monoclonal antibody" is an antibody derived from an essentially homogeneous population of antibodies, and the antibodies are substantially identical in sequence (i.e., identical except for a small percentage of antibodies containing naturally occurring sequence modifications such as N-terminal and C-terminal amino acid modifications). Unlike polyclonal antibodies, which contain a mixture of various antibodies directed to multiple epitopes, monoclonal antibodies are directed to a single epitope and are therefore highly specific. The term "monoclonal antibody" includes, but is not limited to, antibodies obtained from monoclonal cell populations derived from single-cell clones, such as antibodies produced by hybridoma methods described by Kohler and Milstein (Nature, August 7, 1975; 256(5517): pp. 495-497) or Harlow and Lane ("Antibodies: A Laboratory Manual," Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York 1988). Monoclonal antibodies can also be obtained by other suitable methods, including phage display techniques, such as those described by Clackson et al. (Nature. August 15, 1991; 352(6336): pp. 624-628) or Marks et al. (J Mol Biol. December 5, 1991; 222(3): pp. 581-587). Monoclonal antibodies may be antibodies optimized for antigen-binding properties, such as reduced Kd values, optimized association and dissociation kinetics, by methods known in the art. For example, Kd values ​​can be optimized by display methods, including phage display, which result in affinity-mature monoclonal antibodies. The term "monoclonal antibody" is not limited to antibody sequences derived from a specific species of origin or a single species of origin. Therefore, the meaning of the term "monoclonal antibody" includes chimeric monoclonal antibodies, such as humanized monoclonal antibodies.

[0024] A "humanized antibody" is an antibody that contains a human sequence and a small portion of a non-human sequence that confers binding specificity to the target antigen (e.g., human GDF-15). Typically, humanized antibodies are prepared by substituting the hypervariable region sequence derived from a human acceptor antibody with a hypervariable region sequence derived from a non-human donor antibody (e.g., mouse, rabbit, or rat donor antibody) that binds to the target antigen (e.g., human GDF-15). In some cases, the framework region sequence of the acceptor antibody may also be substituted with the corresponding sequence of the donor antibody. In addition to the sequences derived from the donor and acceptor antibodies, a "humanized antibody" may or may not contain other (further or alternative) residues or sequences. Such other residues or sequences may help to further improve antibody properties such as binding properties (e.g., to reduce the Kd value) and / or immunogenic properties (e.g., to reduce antigenicity in humans). Non-limiting examples of methods for producing humanized antibodies are known in the art, for example, from Riechmann et al. (Nature, March 24, 1988; 332(6162): pp. 323-327) or Jones et al. (Nature, May 29 - June 4, 1986; 321(6069): pp. 522-525).

[0025] The term "human antibody" refers to antibodies containing human variable and constant domain sequences. This definition includes antibodies having human sequences with single amino acid substitutions or modifications that may help to further improve antibody properties such as binding properties (e.g., to reduce the Kd value) and / or immunogenic properties (e.g., to reduce antigenicity in humans). The term "human antibody" excludes humanized antibodies in which the non-human sequence portion confers binding specificity to the target antigen.

[0026] In this specification, the “antigen-binding moiety” of an antibody refers to the portion of the antibody that retains the ability to specifically bind to an antigen (e.g., hGDF-15, PD-1, or PD-L1). This ability can be determined, for example, by determining the ability of antigen-binding moieties that compete with the antibody for specific binding to the antigen, by methods known in the art. The antigen-binding moiety may contain one or more fragments of the antibody. Without particular limitation, the antigen-binding moiety can be produced by any suitable method known in the art, including recombinant DNA methods and preparation by chemical or enzymatic fragmentation of the antibody. The antigen-binding moiety may be a Fab fragment, an F(ab') fragment, an F(ab')2 fragment, a single-chain antibody (scFv), a single-domain antibody, a diabody, or any other portion of the antibody that retains the ability to specifically bind to an antigen.

[0027] The “antibody” (e.g., a monoclonal antibody) or “antigen-binding moiety” may be derivatized or linked to a different molecule. For example, molecules that can be linked to an antibody include other proteins (e.g., other antibodies), molecular labels (e.g., fluorescent, luminescent, colored, or radioactive molecules), pharmaceuticals, and / or poisons. The antibody or antigen-binding moiety may be linked directly (e.g., in the form of a fusion between two proteins) or via a linker molecule (e.g., any suitable type of chemical linker known in the art).

[0028] In this specification, the terms “binding” or “binding” refer to specific binding to the target antigen (e.g., human GDF-15). Preferably, the Kd value is less than 100 nM, more preferably less than 50 nM, even more preferably less than 10 nM, even more preferably less than 5 nM, and most preferably less than 2 nM.

[0029] In this specification, an antibody or its antigen-binding moiety that is "competitive" with a second antibody capable of binding to human GDF-15 means that the "competitive" (first) antibody or its antigen-binding moiety can reduce the binding of a 10 nM reference solution of the second antibody to human or recombinant human GDF-15 by 50%. Generally, "competitive" means that the concentration of the (first) antibody or its antigen-binding moiety required to reduce the binding of a 10 nM reference solution of the second antibody to human or recombinant human GDF-15 by 50% is less than 1000 nM, preferably less than 100 nM, and more preferably less than 10 nM. Binding is measured by surface plasmon resonance assay or by enzyme-linked immunosorbent assay (ELISA), preferably by surface plasmon resonance assay.

[0030] In this specification, the term "epitope" refers to a small portion of an antigen that forms a binding site for an antibody.

[0031] In connection with the present invention, the binding or competitive binding of an antibody or its antigen-binding moiety to a target antigen (e.g., human GDF-15) is preferably measured using surface plasmon resonance assay as a reference standard assay, as described below.

[0032] The term “K D " or "K D The term "value" refers to equilibrium dissociation constants known in the art. In relation to the present invention, these terms refer to the equilibrium dissociation constants of antibodies with respect to a specific target antigen (e.g., human GDF-15). The equilibrium dissociation constant is a measure of the tendency of a complex (e.g., an antigen-antibody complex) to reversibly dissociate into its constituent components (e.g., antigen and antibody). For the antibodies of the present invention, K D The value (for example, for the antigen human GDF-15) is preferably determined by using surface plasmon resonance measurement, as described below.

[0033] "Isolated antibody" as used herein means an antibody that has been identified and isolated (by mass) from the majority of the components of its source environment, for example, from the components of the hybridoma cell culture or a different cell culture (e.g., production cells such as CHO cells that recombinantly express the antibody) used for its production. The isolation is carried out to sufficiently remove components that may otherwise interfere with the suitability of the antibody for the desired application (e.g., using the therapeutic use of the anti-human GDF-15 antibody of the present invention). Methods for preparing isolated antibodies are known in the art and include protein A chromatography, anion exchange chromatography, cation exchange chromatography, virus-retaining filtration, and ultrafiltration. Preferably, the isolated antibody preparation is at least 70% pure (w / w), more preferably at least 80% pure (w / w), even more preferably at least 90% pure (w / w), even more preferably at least 95% pure (w / w), and most preferably at least 99% pure (w / w), as measured by using a Lowry protein assay.

[0034] A “diabodies” as defined herein is a small, bivalent antigen-binding antibody moiety containing a heavy-chain variable domain linked to a light-chain variable domain on the same polypeptide chain, linked by a peptide linker that is too short to allow pairing between two domains on the same chain. This results in pairing with a complementary domain on another chain and the assembly of a dimer molecule having two antigen-binding sites. Diabodies may be bivalent and monospecific (e.g., a diabodies with two antigen-binding sites for human GDF-15) or bivalent and bispecific (e.g., a diabodies with two antigen-binding sites, one of which is a binding site for human GDF-15 and the other for a different antigen). A detailed description of diabodies can be found in Holliger P et al. ("Diabodies: small bivalent and bispecific fragments," Proc Natl Acad Sci US A. July 15, 1993; 90(14): pp. 6444-648).

[0035] A "single-domain antibody" (also known as a "Nanobody®") is, in this specification, an antibody fragment consisting of a single monomer variable antibody domain. The structure of single-domain antibodies and methods for producing them are publicly known in the art, for example, from Holt LJ et al. ("Domain antibodies: proteins for therapy," Trends Biotechnol. November 2003; 21(11): pp. 484-4890), Saerens D et al. ("Single-domain antibodies as building blocks for novel therapeutics," Curr Opin Pharmacol. October 2008; 8(5): pp. 600-688. Epub August 22, 2008), and Arbabi Ghahroudi M et al. ("Selection and identification of single-domain antibody fragments from camel heavy-chain antibodies," FEBS Lett. September 15, 1997; 414(3): pp. 521-526).

[0036] The terms “cancer” and “cancer cell” are used herein in accordance with their common meanings in the art (see, for example, Weinberg R. et al.: The Biology of Cancer. Garland Science: New York 2006, p. 850).

[0037] The cancer to be treated by the present invention is a solid tumor. A "solid tumor" is a cancer that forms one or more solid tumors. Such solid tumors are generally known in the art. The term "solid tumor" encompasses both the primary tumor formed by the cancer and any possible secondary tumors, also known as metastases. The preferred solid tumors to be treated by the present invention are selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, stomach cancer, pancreatic cancer, liver cancer, testicular cancer, ovarian cancer, endometrial cancer, cervical cancer, brain tumor, breast cancer, gastric cancer, renal cell carcinoma, Ewing's sarcoma, non-small cell lung cancer, and small cell lung cancer; more preferably selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, stomach cancer, pancreatic cancer, liver cancer, testicular cancer, ovarian cancer, endometrial cancer, and cervical cancer; more preferably selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, and stomach cancer; and most preferably selected from the group consisting of melanoma, colorectal cancer, and prostate cancer.

[0038] As used herein, the term “brain cancer” means all brain tumors known in the art, including, but not limited to, gliomas (WHO grades I–IV), astrocytomas, meningiomas, and medulloblastomas.

[0039] As used herein, the term “head and neck cancer” means all head and neck cancers known in the art, including, but not limited to, esophageal cancer, oral squamous cell carcinoma, and hypopharyngeal cancer. The particularly preferred head and neck cancer to be treated by the present invention is oral squamous cell carcinoma.

[0040] The term "cancer growth" in this specification refers to any measurable growth of cancer. For cancers that form solid tumors, "cancer growth" refers to the measurable increase in tumor volume over time. If cancer forms only a single tumor, "cancer growth" refers only to the increase in volume of that single tumor. If cancer forms multiple tumors, such as metastases, "cancer growth" refers to the increase in volume of all measurable tumors. For solid tumors, tumor volume can be measured by any method known in the art, including magnetic resonance imaging and computed tomography (CT scan).

[0041] In this invention, terms such as "cancer treatment" or "treating cancer" refer to therapeutic procedures. The effectiveness of a therapeutic procedure can be evaluated, for example, by assessing whether the treatment inhibits cancer growth in the treated patient. Preferably, the inhibition is statistically significant, as can be assessed by appropriate statistical tests known in the art. Inhibition of cancer growth can be evaluated by comparing cancer growth in a group of patients treated according to this invention to a control group of untreated patients, or by comparing a group of patients receiving standard cancer treatment in the art and treatment according to this invention to a control group of patients receiving only standard cancer treatment in the art. Such studies for evaluating inhibition of cancer growth are designed according to standards approved for clinical research, e.g., double-blind randomized studies with sufficient power. The term "treating cancer" includes inhibition of cancer growth where cancer growth is partially inhibited (i.e., cancer growth in the patient is delayed compared to a control group of patients), inhibition where cancer growth is completely inhibited (i.e., cancer growth in the patient is stopped), and inhibition where cancer growth is reversed (i.e., the cancer shrinks). Preferably, the evaluation of whether therapeutic treatment is effective can be performed based on the classification of responders and non-responders by using the response evaluation criteria in solid tumors, version 1.1 (RECIST v1.1) (Eisenhauer et al.: New response evaluation criteria in solid tumors: revised RECIST guideline (version 1.1), Eur. J. Cancer. Vol. 45, No. 2, January 2009, pp. 228-227). Alternatively, the evaluation of whether therapeutic treatment is effective can be performed based on known clinical indicators of cancer progression.

[0042] The cancer treatment according to the present invention may be a first-line therapy, a second-line therapy, a third-line therapy, or a therapy beyond a third-line therapy. The meanings of these terms are publicly known in the art and follow the technical terminology commonly used by the U.S. National Cancer Institute.

[0043] The cancer treatment according to the present invention does not rule out the possibility of further or secondary therapeutic effects occurring in the patient. For example, further or secondary benefits may include an effect on cancer-induced mass loss. However, it is understood that primary treatment, for which protection is sought, is intended to treat the cancer itself, and any secondary or further effects reflect only the additional advantages of optional treatment of cancer growth.

[0044] The term "cancer immunotherapy" is well known in the art and generally refers to cancer treatment in which the patient's immune system is used to treat cancer. Cancer cells have genomic mutations that produce cancer cell antigens that are specific to cancer cells and different from the antigens of non-cancerous cells. Therefore, in a preferred embodiment of cancer immunotherapy according to the present invention, cancer immunotherapy is a cancer immunotherapy in which such cancer cell antigens are recognized by the immune system and cancer cells expressing these antigens are killed by the immune system. In an embodiment not limited to the present invention, such cancer cells expressing these cancer cell antigens are killed by the immune system's CD8 + It can be killed by T cells. Cancer immunotherapy involves monitoring the immune system in a blood sample (e.g., CD8) using immunomonitoring methods known in the art. + Measuring intracellular IFN-γ expression (in T cells and / or NK cells), and CD107a cell surface expression (e.g., CD8) in blood samples. + Measuring intracellular TNF-α expression (e.g., on T cells and / or NK cells), intracellular interleukin-2 expression (e.g., on leukocytes) in a blood sample, and intracellular interleukin-2 expression (e.g., on CD8) in a blood sample. + In T cells and / or CD4 + CD154 cell surface expression in blood samples (e.g., CD8) in T cells + In T cells and / or CD4 +This can be evaluated by measuring tetramer or dextramer staining for tumor antigen-specific T cells in blood samples, CTL activity against autologous tumor cells, or the presence of T cells against neoantigens derived from tumor-specific mutations. Preferred methods for evaluating cancer immunotherapy include the method described in Gouttefangeas C et al.: "Flow Cytometry in Cancer Immunotherapy: Applications, Quality Assurance and Future." (2015), Cancer Immunology: Translational Medicine from Bench to Bedside (N. Rezaei editor). Springer. Chapter 25: pp. 471-486, and the method described in Van der Burg SH et al.: "Immunoguiding, the final frontier in the immunotherapy of cancer." (2014), Cancer Immunotherapy meets oncology (CM Britten, S Kreiter, M. Diken & HG Rammensee editors). Springer International Publishing Switzerland, pp. 37-51, ISBN: 978-3-319-05103-1.

[0045] In this specification, “cancer immunotherapy” is optional and includes therapies in which additional mechanisms of cancer treatment are used in addition to the immune system used to treat cancer. For example, it has been previously shown that hGDF-15 inhibitors can be used for cancer treatment in a mouse model system with a severely impaired immune system (WO2014 / 049087). Therefore, according to the present invention, cancer immunotherapy with hGDF-15 inhibitors in human patients may also include additional therapeutic effects of hGDF-15 inhibitors that are independent of the immune system. Another example of cancer immunotherapy in which additional mechanisms of cancer treatment may be used is combination therapy with known chemotherapeutic agents. Such combination therapy with known chemotherapeutic agents may include, for example, not only cancer treatment in which the immune system is used to treat cancer, but also cancer treatment in which cancer cells are directly killed by the chemotherapeutic agent.

[0046] In this specification, the term "CD8 in solid tumors" + "Increasing the percentage of T lymphocytes" refers to CD8 in tumors formed by solid cancers. + The percentage of T cells (i.e., CD8 calculated for all cells) + This relates to any measurable increase in the percentage of T cells. Preferably, this increase is statistically significant so as to be evaluated by appropriate statistical tests known in the art. CD8 in tumors formed by solid cancers + An increase in the percentage of T cells indicates CD8 in solid tumors. + This can be determined by known methods for the analysis of T cells. Such methods include CD8 + This includes analysis of tumor biopsies for T cells, for example, by immunohistochemistry using antibodies against CD8 and staining for the total number of cells. This increase is due to the CD8 in tumors of a group of patients treated by the present invention. + The percentage of T cells can be evaluated by comparing it to a control group of untreated patients, or by comparing a group of patients who received standard cancer treatment in the art and the treatment of the present invention with a control group of patients who received only standard cancer treatment in the art.

[0047] In this specification, "CD8 + T cells are preferably endogenously occurring cells in human patients.

[0048] The hGDF-15 serum level can be measured by any method known in the art. For example, a preferred method for measuring the hGDF-15 serum level is by enzyme-linked immunosorbent assay (ELISA) using an antibody against GDF-15. Such an ELISA method is illustrated in Example 1. Alternatively, the hGDF-15 serum level can be determined by a known electrochemiluminescence immunoassay using an antibody against GDF-15. For example, Roche Elecsys® technology can be used for such an electrochemiluminescence immunoassay.

[0049] Patients to be treated by the present invention are preferably patients with elevated hGDF-15 serum levels. The term “elevated hGDF-15 serum levels” means, as used herein, that a human patient has higher hGDF-15 levels in his ore serum compared to moderate hGDF-15 levels in the ore serum of a healthy human control individual used as a reference, prior to administration of the hGDF-15 inhibitor of the present invention.

[0050] Moderate hGDF-15 serum levels in healthy human controls are <0.8 ng / ml. The predicted range for healthy human controls is between 0.2 ng / ml and 1.2 ng / ml (Reference: Tanno T et al.: "Growth differentiation factor 15 in erythroid health and disease," Curr Opin Hematol. May 2010; 17(3): pp. 184-190).

[0051] Therefore, in a preferred embodiment of the present invention, the patients to be treated by the present invention are patients having a serum hGDF-15 level of at least 1.2 ng / ml prior to the initiation of administration of the hGDF-15 inhibitor, preferably patients having a serum hGDF-15 level of at least 1.5 ng / ml prior to the initiation of administration of the hGDF-15 inhibitor, and more preferably patients having a serum hGDF-15 level of at least 1.8 ng / ml prior to the initiation of administration of the hGDF-15 inhibitor.

[0052] In a more preferred embodiment of the present invention, the patients to be treated by the present invention are patients having a serum hGDF-15 level of at least 1.2 ng / ml and 12 ng / ml or less before initiating administration of the hGDF-15 inhibitor, preferably patients having a serum hGDF-15 level of at least 1.5 ng / ml and 12 ng / ml or less before initiating administration of the hGDF-15 inhibitor, and more preferably patients having a serum hGDF-15 level of at least 1.8 ng / ml and 12 ng / ml or less before initiating administration of the hGDF-15 inhibitor.

[0053] In further embodiments of the present invention, following all of the above embodiments, the patients to be treated by the present invention are patients having a serum hGDF-15 level of at least 1.2 ng / ml and 10 ng / ml or less before initiating administration of the hGDF-15 inhibitor, preferably patients having a serum hGDF-15 level of at least 1.5 ng / ml and 10 ng / ml or less before initiating administration of the hGDF-15 inhibitor, and more preferably patients having a serum hGDF-15 level of at least 1.8 ng / ml and 10 ng / ml or less before initiating administration of the hGDF-15 inhibitor.

[0054] In further embodiments of the present invention, following all of the above embodiments, the patients to be treated by the present invention are patients having a serum hGDF-15 level of at least 1.2 ng / ml and 8 ng / ml or less before initiating administration of the hGDF-15 inhibitor, preferably patients having a serum hGDF-15 level of at least 1.5 ng / ml and 8 ng / ml or less before initiating administration of the hGDF-15 inhibitor, and more preferably patients having a serum hGDF-15 level of at least 1.8 ng / ml and 8 ng / ml or less before initiating administration of the hGDF-15 inhibitor.

[0055] In another embodiment, the patient to be treated by the present invention is a patient having an hGDF-15 serum level of at least 2 ng / ml, at least 2.2 ng / ml, at least 2.4 ng / ml, at least 2.6 ng / ml, at least 2.8 ng / ml, at least 3.0 ng / ml, at least 3.2 ng / ml, at least 3.4 ng / ml, at least 3.6 ng / ml, at least 3.8 ng / ml, at least 4.0 ng / ml, or at least 4.2 ng / ml before initiating administration of the hGDF-15 inhibitor. In this embodiment, the patient is preferably a patient having an hGDF-15 serum level of 12 ng / ml or less before initiating administration of the hGDF-15 inhibitor. More preferably, in this embodiment, the patient is a patient having an hGDF-15 serum level of 10 ng / ml or less before initiating administration of the hGDF-15 inhibitor. Most preferably, in this embodiment, the patient is a patient having an hGDF-15 serum level of 8 ng / ml or less before initiating administration of the hGDF-15 inhibitor.

[0056] In this specification, the term "before the commencement of administration" means the time period immediately preceding the administration of the hGDF-15 inhibitor of the present invention. Preferably, the term "before the commencement of administration" means the 30-day period immediately preceding the administration, or the 1-week period immediately preceding the administration.

[0057] In this specification, the terms "significant," "significantly," etc., refer to a statistically significant difference between values ​​that can be evaluated by appropriate methods known in the art.

[0058] The hGDF-15 inhibitors and immune checkpoint blockers used in the present invention can be administered by methods known in the art. Such methods are selected by those skilled in the art based on well-known considerations, including the chemical properties of each inhibitor (for example, depending on whether the inhibitor is a short interfering RNA or an antibody). The administration of known immune checkpoint blockers may be based on known administration schemes for these immune checkpoint blockers. For example, the administration of immune checkpoint blockers may be based on the administration scheme used in the KEYNOTE-006 study (C. Robert et al. N Engl J Med 2015;372:2521-2532).

[0059] Each use of the term "comprising" in this invention is optional and may be replaced with the term "consisting of".

[0060] hGDF-15 inhibitor to be used according to the present invention The "hGDF-15 inhibitor" of the present invention may be any molecule capable of specifically inhibiting the function of human GDF-15 (hGDF-15).

[0061] An example of such hGDF-15 inhibitors is a molecule that specifically downregulates hGDF-15 expression and thereby inhibits hGDF-15 function. For example, short interfering RNA or siRNA hairpin constructs can be used to specifically downregulate hGDF-15 expression and inhibit hGDF-15 function. The rules for designing and selecting short interfering RNA and siRNA hairpin construct sequences are known in the art and are outlined, for example, in Jackson and Linsley, Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application, Nat Rev Drug Discov. January 2010;9(1):57-67. Short interfering RNA and siRNA hairpin constructs can be delivered to human patients by any suitable method, including viral delivery methods (e.g., as outlined in Knoepfel SA et al., "Selection of RNAi-based inhibitors for antiHIV gene therapy," World J Virol. June 12, 2012; 1(3): pp. 79-90) and other delivery methods such as methods using conjugate groups to facilitate delivery to cells (e.g., as outlined in Kanasty R et al., "Delivery materials for siRNA therapeutics," Nat Mater. November 2013; 12(11): pp. 967-97).

[0062] Whether or not the substance in question is an "hGDF-15 inhibitor" can be determined by using the methods disclosed herein, as detailed in preferred embodiments. A preferred method according to a preferred embodiment is the method used in Example 3.

[0063] It has been shown that the human GDF-15 protein can be advantageously targeted by a monoclonal antibody (WO2014 / 049087), and that such an antibody has advantageous properties, including a high binding affinity to human GDF-15, as demonstrated by the equilibrium dissociation constant of approximately 790 pM for recombinant human GDF-15 (see Reference Example 1). Therefore, in a preferred embodiment of the present invention, the hGDF-15 inhibitor to be used is an antibody or its antigen-binding moiety capable of binding to hGDF-15. Preferably, the antibody is a monoclonal antibody or its antigen-binding moiety capable of binding to hGDF-15.

[0064] Therefore, in a more preferred embodiment, the hGDF-15 inhibitor according to the present invention is a monoclonal antibody or its antigen-binding moiety capable of binding to human GDF-15, wherein the heavy chain variable domain includes a CDR3 region containing the amino acid sequence of SEQ ID NO: 5 or an amino acid sequence identical thereto by at least 90%, and the light chain variable domain includes a CDR3 region containing the amino acid sequence of SEQ ID NO: 7 or an amino acid sequence identical thereto by at least 85%. In this embodiment, preferably, the antibody or its antigen-binding moiety includes a heavy chain variable domain including a CDR1 region containing the amino acid sequence of SEQ ID NO: 3 and a CDR2 region containing the amino acid sequence of SEQ ID NO: 4, and the antibody or its antigen-binding moiety includes a light chain variable domain including a CDR1 region containing the amino acid sequence of SEQ ID NO: 6 and a CDR2 region containing the amino acid sequence ser-ala-ser.

[0065] Therefore, in a more preferred embodiment, the hGDF-15 inhibitor according to the present invention is a monoclonal antibody or its antigen-binding portion that can bind to human GDF-15, wherein the antibody or its antigen-binding portion includes a heavy chain variable domain including a CDR1 region containing the amino acid sequence of SEQ ID NO: 3, a CDR2 region containing the amino acid sequence of SEQ ID NO: 4, and a CDR3 region containing the amino acid sequence of SEQ ID NO: 5, and the antibody or its antigen-binding portion includes a light chain variable domain including a CDR1 region containing the amino acid sequence of SEQ ID NO: 6, a CDR2 region containing the amino acid sequence ser-ala-ser, and a CDR3 region containing the amino acid sequence of SEQ ID NO: 7.

[0066] In another embodiment according to the above embodiment of a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain includes a region containing FR1, CDR1, FR2, CDR2 and FR3 regions containing the amino acid sequence of SEQ ID NO: 1 or a sequence that is 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identical thereto, and the light chain variable domain includes a region containing FR1, CDR1, FR2, CDR2 and FR3 regions containing the amino acid sequence of SEQ ID NO: 2 or a sequence that is 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identical thereto.

[0067] In preferred embodiments according to the above embodiments of a monoclonal antibody or its antigen-binding moiety capable of binding to human GDF-15, the antibody is a humanized antibody or its antigen-binding fragment. The constant domain of the heavy chain of this monoclonal antibody or its antigen-binding moiety may contain the amino acid sequence of SEQ ID NO: 29 or an amino acid sequence identical thereto by at least 85%, preferably at least 90%, and more preferably at least 95%, and the constant domain of the light chain of this monoclonal antibody or its antigen-binding moiety may contain the amino acid sequence of SEQ ID NO: 32 or an amino acid sequence identical thereto by at least 85%, preferably at least 90%, and more preferably at least 95%. More preferably, the constant domain of the heavy chain of this monoclonal antibody or its antigen-binding moiety contains the amino acid sequence of SEQ ID NO: 29 or an amino acid sequence identical thereto by at least 98%, preferably at least 99%, and the constant domain of the light chain of this monoclonal antibody or its antigen-binding moiety contains the amino acid sequence of SEQ ID NO: 32 or an amino acid sequence identical thereto by at least 98%, and more preferably at least 99%. More preferably, the constant domain of the heavy chain of the monoclonal antibody or its antigen-binding moiety contains the amino acid sequence of SEQ ID NO: 29, and the constant domain of the light chain of the monoclonal antibody or its antigen-binding moiety contains the amino acid sequence of SEQ ID NO: 32. The variable heavy chain domain of the monoclonal antibody or its antigen-binding moiety may contain the amino acid sequence of SEQ ID NO: 28 or an amino acid sequence identical thereto by at least 90%, preferably at least 95%, more preferably at least 98%, and even more preferably at least 99%, and the variable light chain domain of the monoclonal antibody or its antigen-binding moiety may contain the amino acid sequence of SEQ ID NO: 31 or an amino acid sequence identical thereto by at least 90%, preferably at least 95%, more preferably at least 98%, and even more preferably at least 99%. Most preferably, the variable heavy chain domain of the monoclonal antibody or its antigen-binding moiety contains the amino acid sequence of SEQ ID NO: 28, and the variable light chain domain of the monoclonal antibody or its antigen-binding moiety contains the amino acid sequence of SEQ ID NO: 31.

[0068] In another embodiment according to the above embodiment of a monoclonal antibody or its antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain includes a CDR1 region containing the amino acid sequence of SEQ ID NO: 3 and a CDR2 region containing the amino acid sequence of SEQ ID NO: 4, and the light chain variable domain includes a CDR1 region containing the amino acid sequence of SEQ ID NO: 6 and a CDR2 region containing the amino acid sequence of SEQ ID NO: 7. In a preferred embodiment of this embodiment, the antibody may have a CDR3 sequence as defined in any of the embodiments of the present invention described above.

[0069] In another embodiment relating to a monoclonal antibody or its antigen-binding moiety capable of binding to human GDF-15, the antigen-binding moiety is a single-domain antibody (also known as "Nanobody"). In one aspect of this embodiment, the single-domain antibody comprises the CDR1, CDR2, and CDR3 amino acid sequences of SEQ ID NO: 3, SEQ ID NO: 4, and SEQ ID NO: 5, respectively. In another aspect of this embodiment, the single-domain antibody comprises the CDR1, CDR2, and CDR3 amino acid sequences of SEQ ID NO: 6, ser-ala-ser, and SEQ ID NO: 7, respectively. In a preferred aspect of this embodiment, the single-domain antibody is a humanized antibody.

[0070] Preferably, the antibody or antigen-binding moiety capable of binding to human GDF-15 has an equilibrium dissociation constant of human GDF-15 such that it is 100 nM or less, 20 nM or less, preferably 10 nM or less, more preferably 5 nM or less, and most preferably between 0.1 nM and 2 nM.

[0071] In another embodiment according to the above embodiment of a monoclonal antibody or antigen-binding moiety conjugable to human GDF-15, the antibody or antigen-binding moiety conjugable to human GDF-15 conjugates to the same human GDF-15 epitope as the antibody against human GDF-15 that can be obtained from cell line B1-23 deposited with Deutsche Sammlung fur Mikroorganismen und Zellkulturen GmbH (DMSZ) under accession number DSM ACC3142. As described herein, antibody binding to human GDF-15 according to the present invention is preferably evaluated by surface plasmon resonance assay as a reference standard method, following the procedure described in Reference Example 1. The binding of an antibody to the same epitope on human GDF-15 can be similarly evaluated by surface plasmon resonance competitive binding assays of an antibody against human GDF-15 obtainable from cell line B1-23, and an antibody predicted to bind to the same human GDF-15 epitope as the antibody against human GDF-15 obtainable from cell line B1-23.

[0072] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 39 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 40 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0073] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 41 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 42 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0074] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 43 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 44 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0075] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 45 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 46 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0076] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 47 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 48 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0077] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 49 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 50 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0078] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, the heavy chain variable domain comprises the amino acid sequence of SEQ ID NO: 51 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, and the light chain variable domain comprises the amino acid sequence of SEQ ID NO: 52 or a sequence identical thereto by at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%.

[0079] In another preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of competing with any one of the human GDF-15-binding antibodies referred to herein for binding to human GDF-15, preferably recombinant human GDF-15.

[0080] In a highly preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a humanized monoclonal antibody or its antigen-binding moiety. For any given non-human antibody sequence (i.e., donor antibody sequence) according to the present invention, the humanized monoclonal anti-human GDF-15 antibody or its antigen-binding moiety according to the present invention can be prepared according to techniques known in the art, as described above.

[0081] In a highly preferred embodiment, the antibody or antigen-binding moiety capable of binding to human GDF-15 is a monoclonal antibody or antigen-binding moiety capable of binding to human GDF-15, wherein the binding is to a conformal or discontinuous epitope on human GDF-15 consisting of the amino acid sequences of SEQ ID NOs. 25 and SEQ ID NOs. 26. In a preferred aspect of this embodiment, the antibody or antigen-binding moiety is an antibody or antigen-binding moiety as defined by any one of the sequences in the above embodiments.

[0082] An antibody capable of binding to human GDF-15, or its antigen-binding moiety, may be linked to a drug. In lesser-known embodiments of this model, the drug may be a known anticancer agent and / or immunostimulant molecule. Known anticancer agents include alkylating agents such as cisplatin, carboplatin, oxaliplatin, mechloretamine, cyclophosphamide, chlorambucil, and ifosfamide; antimetabolites such as azathioprine and mercappurine; alkaloids such as vinca alkaloids (e.g., vincristine, vinblastine, vinorelbine, and vindesine), taxanes (e.g., paclitaxel, docetaxel), etoposide, and teniposide; topoisomerase inhibitors such as camptothecines (e.g., irinotecan and topotecan); cytotoxic antibiotics such as actinomycin, anthracyclines, doxorubicin, daunorubicin, barurubicin, idarubicin, epirubicin, bleomycin, plicamycin, and mitomycin; and radioisotopes.

[0083] In further embodiments according to the above embodiments, an antibody or its antigen-binding moiety capable of binding to human GDF-15 is modified with an amino acid tag. Non-limiting examples of such tags include polyhistidine (His-) tags, FLAG- tags, hemagglutinin (HA) tags, glycoprotein D (gD) tags, and c-myc tags. The tags can be used for a variety of purposes. For example, they can be used to assist in the purification of an antibody or its antigen-binding moiety capable of binding to human GDF-15. Preferably, such tags are located at the C-terminus or N-terminus of the antibody or its antigen-binding moiety capable of binding to human GDF-15.

[0084] Immune checkpoint blockers to be used according to the present invention Cancer cells possess genomic mutations that produce cancer cell antigens that are specific to cancer cells and distinct from those of non-cancerous cells. Therefore, an unimpaired, intact immune system should recognize these cancer cell antigens, thereby triggering an immune response to them. However, most cancers have developed mechanisms of immune tolerance to these antigens. One class of mechanisms by which cancer cells achieve such immune tolerance is the use of immune checkpoints. “Immune checkpoint” as used herein generally refers to an immunological mechanism by which an immune response can be inhibited. More specifically, an immune checkpoint is a mechanism characterized by the inhibition of an immune response by a molecule (or group of molecules) of the immune system by inhibiting the activation of cells of the immune system. Such molecules (or groups of molecules) of the immune system that inhibit an immune response by inhibiting the activation of cells of the immune system are also known as checkpoint molecules.

[0085] In this specification, “immune checkpoint blocker” refers to a molecule capable of blocking immune checkpoints. While it is understood that hGDF-15 inhibitors, such as those used in the present invention, have effects on the immune system, including effects on CD8+ T cells, the term “immune checkpoint blocker” in this specification does not refer to hGDF-15 inhibitors, but rather to molecules distinct from hGDF-15 inhibitors.

[0086] The most common immune checkpoint blockers known to date are inhibitors of immune checkpoint molecules, such as human PD-1 inhibitors and human PD-L1 inhibitors. Further immune checkpoint blockers include inhibitors of anti-LAG-3, anti-B7H3, anti-TIM3, anti-VISTA, anti-TIGIT, anti-KIR, anti-CD27, anti-CD137, and IDO. Therefore, when used in the present invention, the preferred form of immune checkpoint blocker is an inhibitor of an immune checkpoint molecule. Alternatively, an immune checkpoint blocker may be an activator of a co-stimulatory signal that disables an immune checkpoint.

[0087] Methods for measuring the efficacy of immune checkpoint blockers include in vitro binding assays, primary T cell-based cytokine release assays, and in vivo model systems. Furthermore, Promega has now developed a commercially available bioluminescent reporter system for PD-1 / PD-L1, as mentioned, for example, in Mei Cong, Ph.D. et al.: Advertorial: Novel Bioassay to Assess PD-1 / PD-L1 Therapeutic Antibodies in Development for Immunotherapy Bioluminescent Reporter-Based PD-1 / PD-L1 Blockade Bioassay. (http: / / www.genengnews.com / gen-articles / advertorial-novel-bioassay-to-assess-pd-1-pd-l1-therapeutic-antibodies-in-development-for-immun / 5511 / ).

[0088] Preferred immune checkpoint blockers include human PD-1 inhibitors and human PD-L1 inhibitors. In one preferred embodiment according to all embodiments of the present invention, the immune checkpoint blocker is not a human CTLA4 inhibitor.

[0089] In this specification, “human PD-1 inhibitor” can be any molecule capable of specifically inhibiting the function of human PD-1. Non-limiting examples of such molecules include antibodies capable of binding to human PD-1 and DARPins (Designed Ankyrin Repeat Proteins) capable of binding to human PD-1. Preferably, the PD-1 inhibitor to be used in the present invention is an antibody capable of binding to human PD-1, more preferably a monoclonal antibody capable of binding to human PD-1. Most preferably, the monoclonal antibody capable of binding to human PD-1 is selected from the group consisting of nivolumab, pembrolizumab, pidilizumab, and AMP-224.

[0090] In this specification, “human PD-L1 inhibitor” can be any molecule capable of specifically inhibiting the function of human PD-L1. Non-limiting examples of such molecules include antibodies capable of binding to human PD-L1 and DARPins (Designed Ankyrin Repeat Proteins) capable of binding to human PD-L1. Preferably, the human PD-L1 inhibitor to be used in the present invention is an antibody capable of binding to human PD-L1, more preferably a monoclonal antibody capable of binding to human PD-L1. Most preferably, the monoclonal antibody capable of binding to human PD-L1 is selected from the group consisting of BMS-936559, MPDL3280A, MEDI4736, and MSB0010718C.

[0091] Methods and Techniques Generally, unless otherwise defined herein, the methods used in the present invention (e.g., cloning methods for antibodies) are carried out according to procedures known in the art, such as those described herein by reference, including Sambrook et al. ("Molecular Cloning: A Laboratory Manual," 2nd edition, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York 1989), Ausubel et al. ("Current Protocols in Molecular Biology," Greene Publishing Associates and Wiley Interscience; New York 1992), and Harlow and Lane ("Antibodies: A Laboratory Manual," Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York 1988).

[0092] The binding of an antibody to its respective target protein can be evaluated by methods known in the art. The binding of a monoclonal antibody to its respective target is preferably evaluated by surface plasmon resonance (SPR) measurements. These measurements are preferably performed using a Biorad ProteOn XPR36 system and a Biorad GLC sensor chip, as exemplified for anti-human GDF-15 mAb-B1-23 in Reference Example 1.

[0093] Sequence alignment of the present invention is performed using the BLAST algorithm (see Altschul et al. (1990) "Basic local alignment search tool," Journal of Molecular Biology 215, pp. 403-410; Altschul et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25: pp. 3389-3402). Preferably, the following parameters are used: maximum target sequence 10; word size 3; BLOSUM 62 matrix; gap cost: presence 11, extension 1; conditional compositional score matrix adjustment. Therefore, when used in relation to sequences, terms such as "identity" or "identical" refer to the identity value obtained by using the BLAST algorithm.

[0094] The monoclonal antibodies of the present invention can be prepared by any method known in the art, including, but not limited to, the method referred to in Siegel DL ("Recombinant monoclonal antibody technology," Transfus Clin Biol. January 2002; 9(1): pp. 15-22). In one embodiment, the antibodies of the present invention are prepared using hybridoma cell line B1-23, deposited under the Budapest Convention with Deutsche Sammlung fur Mikroorganismen und Zellkulturen GmbH (DMSZ) under accession number DSM ACC3142. The deposit was filed on September 29, 2011.

[0095] Cell proliferation can be measured using (but not limited to) visible microscopy, metabolic assays such as those measuring mitochondrial redox potential (e.g., MTT (3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyltetrazolium bromide) assay; also known as the Alamar Blue® assay, or laserzlin staining), staining for known endogenous proliferation biomarkers (e.g., Ki-67), and methods for measuring cellular DNA synthesis (e.g., BrdU and [ 3 It can be measured by suitable methods known in the art, including the [H]-thymidine integration assay.

[0096] The level of human GDF-15 (hGDF-15) can be measured by any method known in the art, including measurement of hGDF-15 protein levels by methods including (but not limited to) mass spectrometry of proteins or peptides derived from human GDF-15, Western blotting using antibodies specific to human GDF-15, flow cytometry using antibodies specific to human GDF-15, strip tests using antibodies specific to human GDF-15, or immunocytochemistry using antibodies specific to human GDF-15. A preferred method for measuring hGDF-15 serum levels is measurement of hGDF-15 serum levels by enzyme-linked immunosorbent assay (ELISA) using antibodies against GDF-15. Such an ELISA method is illustrated in Example 1. Alternatively, hGDF-15 serum levels can be determined by known electrochemiluminescence immunoassays using antibodies against GDF-15. For example, Roche Elecsys® technology can be used for such electrochemiluminescence immunoassays.

[0097] Preparation of the composition of the present invention The composition according to the present invention is prepared in accordance with known standards for the preparation of pharmaceutical compositions.

[0098] For example, the composition is prepared in a manner that allows for appropriate storage and administration by using pharmaceutically acceptable components such as carriers, excipients, or stabilizers.

[0099] Such pharmaceutically acceptable components are not toxic in the amounts used when the pharmaceutical composition is administered to a patient. The pharmaceutically acceptable components added to a pharmaceutical composition may vary depending on the chemical properties of the inhibitors present in the composition (e.g., whether the inhibitor is an antibody, siRNA hairpin construct, or short interfering RNA), the specific intended use of the pharmaceutical composition, and the route of administration.

[0100] Generally, pharmaceutically acceptable components used in connection with the present invention are used in accordance with knowledge available in the art, for example, from Remington's Pharmaceutical Sciences, edited by AR Gennaro, 20th edition, 2000, Williams & Wilkins, PA, USA.

[0101] Therapeutic methods and products for use in these methods The present invention relates to an hGDF-15 inhibitor for use as defined above.

[0102] Furthermore, in accordance with these hGDF-15 inhibitors and their use, the present invention also relates to corresponding therapeutic methods.

[0103] Therefore, in one embodiment, the present invention relates to CD8 in solid tumors in human patients. + A method for increasing the percentage of T lymphocytes, comprising the step of administering an hGDF-15 inhibitor to a human patient.

[0104] In another embodiment, the present invention relates to a method for treating solid tumors in human patients with an immune checkpoint blocker, comprising the steps of administering an hGDF-15 inhibitor to a human patient and administering an immune checkpoint blocker to a human patient.

[0105] Preferred embodiments of these methods are as defined above for hGDF-15 inhibitors for use according to the present invention.

[0106] In the above-described method, the hGDF-15 inhibitor for use, the kit for use, and another embodiment of the composition, the hGDF-15 inhibitor is the only component that is pharmaceutically active against cancer.

[0107] In the above-described method, the hGDF-15 inhibitor for use, the kit for use, and alternative embodiments of the composition, the hGDF-15 inhibitor and the immune checkpoint blocker are the only components that are pharmaceutically active against cancer.

[0108] In alternative embodiments of the above-described method, hGDF-15 inhibitor for use, kit for use, and composition, the hGDF-15 inhibitor is used in combination with one or more further components that are pharmaceutically active against cancer. In one aspect of this embodiment, the one or more further components that are pharmaceutically active against cancer are known anticancer agents and / or immunostimulant molecules. Known anticancer agents include, but are not limited to, alkylating agents such as cisplatin, carboplatin, oxaliplatin, mechloretamine, cyclophosphamide, chlorambucil, and ifosfamide; antimetabolites such as azathioprine and mercappurine; alkaloids such as vinca alkaloids (e.g., vincristine, vinblastine, vinorelbine, and vindesine), taxanes (e.g., paclitaxel, docetaxel), etoposide, and teniposide; topoisomerase inhibitors such as camptothecines (e.g., irinotecan and topotecan); cytotoxic antibiotics such as actinomycin, anthracyclines, doxorubicin, daunorubicin, barurubicin, idarubicin, epirubicin, bleomycin, plicamycin, and mitomycin; and radioisotopes. The following pharmaceutically active components against cancer are particularly preferred to be used in combination with hGDF-15 inhibitors, and as immunostimulatory molecules, these include anti-LAG-3, anti-B7H3, anti-TIM3, anti-VISTA, anti-TIGIT, anti-KIR, anti-CD27, anti-CD137, anti-Ox40, anti-4-1BB, anti-GITR, anti-CD28, anti-CD40, or IDO-inhibitors. Furthermore, other antibody therapies such as anti-Her2, anti-EGFR, anti-claudin, or their glyco-optimized successors are also particularly preferred, as they benefit from combination with hGDF-15 inhibitors, for example, by enhancing immune cell infiltration in solid tumors caused by hGDF-15 inhibitors. Similarly, vaccination approaches (e.g., using peptides or dendritic cells) or adoptive cell therapies, tumor-responsive T cells, or dendritic cells are also particularly preferred, as they benefit from combination with hGDF-15 inhibitors. Furthermore, the following therapies are also particularly preferred, as they work in conjunction with hGDF-15 inhibitors: Treatment using antibodies or antibody-like molecules (e.g., Bites, DARTS, DARPINS, catumaxomab) that have one or more specificities for tumors and immune cells; For example, treatment with vaccine-based immunotherapy against tumor-associated peptides using multipeptide vaccines such as IMA901, ISA203, or RNA-based vaccines (e.g., CV9104) and / or • Therapy using immune cell activators (for example, FAA derivatives that activate macrophages or ligands for Toll-like receptors such as SLP-AMPLIVANT conjugates).

[0109] Combination for use according to the present invention The present invention encompasses combinations of hGDF-15 inhibitors and immune checkpoint blockers for use in methods of treating solid tumors in human patients, where the hGDF-15 inhibitor and immune checkpoint blocker are to be administered to human patients. These combinations and preferred embodiments thereof are as defined above.

[0110] The combination of hGDF-15 inhibitors and immune checkpoint blockers may be administered together or separately.

[0111] For example, in one preferred embodiment, administration of the hGDF-15 inhibitor is to be initiated before the initiation of immune checkpoint blocker administration. This setting is advantageous because it increases the percentage of T cells in solid tumors, particularly CD8 + It increases the percentage of T cells, and as a result, CD8 in solid tumors + An increase in the starting percentage of T cells may make subsequent treatments using immune checkpoint blockers more effective.

[0112] kit The present invention also provides a kit comprising an hGDF-15 inhibitor and at least one immune checkpoint blocker, as defined above.

[0113] hGDF-15 inhibitors and one or more or all immune checkpoint blockers may be contained in separate containers or in a single container.

[0114] The containers used may be any type of container suitable for storing hGDF-15 inhibitors and / or at least one immune checkpoint blocker. Non-limiting examples of such containers include vials and pre-filled syringes.

[0115] The kit may contain an hGDF-15 inhibitor and at least one immune checkpoint blocker, in addition to further therapeutic agents. For example, the kit may contain one or more further components that are pharmaceutically active against cancer. One or more further components that are pharmaceutically active against cancer may be as defined above. Such further components that are pharmaceutically active against cancer can be used in conjunction with the hGDF-15 inhibitor and at least one immune checkpoint blocker in the method of the present invention.

[0116] Preferably, the kit of the present invention further includes instructions for use.

[0117] array The amino acid sequence referred to in this application is as follows (from N-terminus to C-terminus; represented by a single-letter amino acid code): Sequence ID 1 (region of the heavy chain variable domain including the FR1, CDR1, FR2, CDR2 and FR3 regions derived from the polypeptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): QVKLQQSGPGILQSSQTLSLTCSFSGFSLSTSGMGVSWIRQPSGKGLEWLAHIYWDDDKRYNPTLKSRLTISKDPSRNQVFLKITSVDTADTATYYC Sequence ID 2 (region of the light chain variable domain including the FR1, CDR1, FR2, CDR2 and FR3 regions derived from the polypeptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): DIVLTQSPKFMSTSVGDRVSVTCKASQNVGTNVAWFLQKPGQSPKALIYSASYRYSGVPDRFTGSGSGTDFTLTISNVQSEDLAEYFC Sequence ID 3 (heavy chain CDR1 region peptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): GFSLSTSGMG Sequence ID No. 4 (heavy chain CDR2 region peptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): IYWDDDK Sequence ID No. 5 (heavy chain CDR3 region peptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): ARSSYGAMDY Sequence ID 6 (light chain CDR1 region peptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): QNVGTN Light chain CDR2 region peptide sequence of monoclonal anti-human GDF-15 mAb-B1-23: SAS Sequence ID 7 (light chain CDR3 region peptide sequence of monoclonal anti-human GDF-15 mAb-B1-23): QQYNNFPYT Sequence ID No. 8 (recombinant mature human GDF-15 protein): GSARNGDHCPLGPGRCCRLHTVRASLEDLGWADWVLSPREVQVTMCIGACPSQFRAANMHAQIKTSLHRLKPDTVPAPCCVPASYNPMVLIQKTDTGVSLQTYDDLLAKDCHCI Sequence ID 9 (Human GDF-15 precursor protein): MPGQELRTVNGSQMLLVLLVLSWLPHGGALSLAEASRASFPGPSELHSEDSRFRELRKRYEDLLTRLRANQSWEDSNTDLVPAPAVRILTPEVRLGSGGHLHLRISRAALPEGLPEASRLHRALFRLSPTASRSWDVTRPLRRQLSLARPQAPA LHLRLSPPSQSDQLLAESSSARPQLELHLRPQAARGRRRARARNGDHCPLGPGRCCRLHTVRASLEDLGWADWVLSPREVQVTMCIGACPSQFRAANMHAQIKTSLHRLKPDTVPAPCCVPASYNPMVLIQKTDTGVSLQTYDDLLAKDCHCI SEQ ID NO: 10 (Human GDF-15 precursor protein + N-terminal and C-terminal GSGS linker): GSGSGSGMPGQELRTVNGSQMLLVLLVLSWLPHGGALSLAEASRASFPGPSELHSEDSRFRELRKRYEDLLTRLRANQSWEDSNTDLVPAPAVRILTPEVRLGSGGHLRISRAALPEGLPEASRLHRALFRLSPTASRSWDVTRPLRRQLSLARPQAPA LHLRLSPPSQSDQLLAESSSARPQLELHLRPQAARGRRRARARNGDHCPLGPGRCCRLHTVRASLEDLGWADWVLSPREVQVTMCIGACPSQFRAANMHAQIKTSLHRLKPDTVPAPCCVPASYNPMVLIQKTDTGVSLQTYDDLLAKDCHCIGSGSGSG Sequence ID 11 (Flag Peptide): DYKDDDDKGG SEQ ID NO: 12 (HA peptide): YPYDVPDYAG Sequence ID No. 13 (Human GDF-15 derived peptide): ELHLRPQAARGRR Sequence ID No. 14 (Human GDF-15 derived peptide): LHLRPQAARGRRR Sequence ID No. 15 (Human GDF-15 derived peptide): HLRPQAARGRRRA Sequence ID No. 16 (Human GDF-15 derived peptide): LRPQAARGRRRAR Sequence ID No. 17 (Human GDF-15 derived peptide): RPQAARGRRRARA Sequence ID No. 18 (Human GDF-15 derived peptide): PQAARGRRRARAR Sequence ID No. 19 (Human GDF-15 derived peptide): QAARGRRRARARN Sequence ID No. 20 (Human GDF-15 derived peptide): MHAQIKTSLHRLK Sequence ID No. 25 (GDF-15 peptide containing a portion of the GDF-15 epitope that binds to B1-23): EVQVTMCIGACPSQFR Sequence ID No. 26 (GDF-15 peptide containing a portion of the GDF-15 epitope that binds to B1-23): TDTGVSLQTYDDLLAKDCHCI

[0118] The nucleic acid sequences referred to in this application are as follows (in 5' to 3' order; represented according to the standard nucleic acid code): Sequence ID 21 (DNA nucleotide sequence encoding the amino acid sequence defined in Sequence ID 1): CAAGTGAAGCTGCAGCAGTCAGGCCCTGGGATATTGCAGTCTCCCAGACCCTCAGTCTGACTTGTTCTTTCTCTGGGTTTTCACTGAGTACTTCTGGTATGGGTTGAGCTGGATTCGTCAGCCTTCAGGAAAGGGTCTGGAGT GGCTGGCACACATTTACTGGGATGATGACAAGCGCTATAACCCAACCCTGAAGAGCCGGCTCACAATCTCCAAGGATCCCTCCAGAAACCAGGTATTCCTCAAGATCACCAGTGTGGACACTGCAGATACTGCCACATACTACTGT Sequence ID 22 (DNA nucleotide sequence encoding the amino acid sequence defined in Sequence ID 2): GACATTGTGCTCACCCAGTCTCCAAAATTCATGTCCACATCAGTAGGAGACAGGGTCAGCGTCACCTGCAAGGCCAGTCAGAATGTGGGTACTAATGTGGCCTGGTTTCTACAGAAACCAGGGCAATCTCCT AAAGCACTTATTTACTCGGCATCCTACCGGTACAGTGGAGTCCCTGATCGCTTCACAGGCAGTGGATCTGGGACAGATTTCACTCTCACCATCAGCAACGTGCAGTCTGAAGACTTGGCAGAGTATTTCTGT Sequence ID 23 (DNA nucleotide sequence encoding the amino acid sequence defined in Sequence ID 5): GCTCGAAGTTCCTACGGGGCAATGGACTAC Sequence ID 24 (DNA nucleotide sequence encoding the amino acid sequence defined in Sequence ID 7): CAGCAATATAACAACTTTCCGTACACG

[0119] The further amino acid sequence is as follows (in order from the N-terminus to the C-terminus; represented by a single-letter amino acid code): Sequence ID No. 27 (Amino acid sequence of the heavy chain of the H1L5 humanized B1-23 anti-GDF-15 antibody): QITLKESGPTLVKPTQTLTLTCTFSGFSLSTSGMGVSWIRQPPGKGLEWLAHIYWDDDKRYNPTLKSRLTITKDPSKNQVVLTMTNMDPPVDTATYYCARSSYGAMDYWGQGT LVTVSSASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKKVEPKSCDKT HTCPCPAPELLGGPSVFLFPPKPKDTLMISRTPEVTCVVVDVSHEDPEVKFNWYVDGVEVHNAKTKPREEQYNSTYRVVSVLTVLHQDWLNGKEYKCKVSNKALPAPIEKT ISKAKGQPREPQVYTLPSREEMTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSKLTVDKSRWQQGNVFSCSVMHEALHNHYTQKSLSLSPGK Sequence ID No. 28 (amino acid sequence of the heavy chain variable domain of the H1L5 humanized B1-23 anti-GDF-15 antibody): QITLKESGPTLVKPTQTLTLTCTFSGFSLSTSGMGVSWIRQPPGKGLEWLAHIYWDDDKRYNPTLKSRLTITKDPSKNQVVLTMTTNMDPVDTATYYCARSSYGAMDYWGQGTLVTVSS Sequence ID No. 29 (amino acid sequence of the heavy chain constant domain of the H1L5 humanized B1-23 anti-GDF-15 antibody): ASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKKVEPKSCDKTHTCPPCPAPELLGGPSVFLFPPKPKDTLMISRTPEVTCVVVDVSHEDPEVKFNWYVDGV EVHNAKTKPREEQYNSTYRVVSVLTVLHQDWLNGKEYKCKVSNKALPAPIEKTISKAKGQPREPQVYTLPPSREEMTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSKLTVDKSRWQQGNVFSCSVMHEALHNHYTQKSLSLSPGK Sequence ID No. 30 (Amino acid sequence of the light chain of the H1L5 humanized B1-23 anti-GDF-15 antibody): DIVLTQSPSFLSASVGDRVTITCKASQNVGTNVAWFQQKPGKSPKALIYSASYRYSGVPDRFTGSGSGTEFTLTISSLQPEDFAAYFCQQYNNFPYTFGGGTKLE IKRAPSVFIFPPSDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRGEC Sequence ID 31 (amino acid sequence of the light chain variable domain of the H1L5 humanized B1-23 anti-GDF-15 antibody): DIVLTQSPSFLSASVGDRVTITCKASQNVGTNVAWFQQKPGKSPKALIYSASYRYSGVPDRFTGSGSGTEFTLTISSLQPEDFAAYFCQQYNNFPYTFGGGTKLEIKR Sequence ID 32 (amino acid sequence of the light chain constant domain of the H1L5 humanized B1-23 anti-GDF-15 antibody): APSVFIFPPSDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRGEC Sequence ID 33 (Amino acid sequence of the heavy chain of the chimeric B1-23 anti-GDF-15 antibody): QVKLQQSGPGILQSSQTLSLTCSFSGFSLSTSGMGVSWIRQPSGKGLEWLAHIYWDDDKRYNPTLKSRLTISKDPSRNQVFLKITSVDTADTATYYCARSSYGAMDYWGQGT SVTVSSASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKKVEPKSCDKT HTCPCPAPELLGGPSVFLFPPKPKDTLMISRTPEVTCVVVDVSHEDPEVKFNWYVDGVEVHNAKTKPREEQYNSTYRVVSVLTVLHQDWLNGKEYKCKVSNKALPAPIEKT ISKAKGQPREPQVYTLPSREEMTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSKLTVDKSRWQQGNVFSCSVMHEALHNHYTQKSLSLSPGK Sequence ID No. 34 (amino acid sequence of the heavy chain variable domain of the chimeric B1-23 anti-GDF-15 antibody): QVKLQQSGPGILQSSQTLSLLTCSFSGFSLSTSGMGVSWIRQPSGKGLEWLAHIYWDDDKRYNPTLKSRLTISKDPSRNQVFLKITSVDTADTATYYCARSSYGAMDYWGQGTSVTVSS SEQ ID NO: 35 (amino acid sequence of the heavy chain constant domain of the chimeric B1-23 anti-GDF-15 antibody): ASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKKVEPKSCDKTHTCPPCPAPELLGGPSVFLFPPKPKDTLMISRTPEVTCVVVDVSHEDPEVKFNWYVDGV EVHNAKTKPREEQYNSTYRVVSVLTVLHQDWLNGKEYKCKVSNKALPAPIEKTISKAKGQPREPQVYTLPPSREEMTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSKLTVDKSRWQQGNVFSCSVMHEALHNHYTQKSLSLSPGK Sequence ID 36 (Amino acid sequence of the light chain of the chimeric B1-23 anti-GDF-15 antibody): DIVLTQSPKFMSTSVGDRVSVTCKASQNVGTNVAWFLQKPGQSPKALIYSASYRYSGVPDRFTGSGSGTDFTLTISNVQSEDLAEYFCQQYNNFPYTFGGGTKLEIK RTVAAPSVFIFPPSDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRGEC Sequence ID 37 (amino acid sequence of the light chain variable domain of the chimeric B1-23 anti-GDF-15 antibody): DIVLTQSPKFMSTSVGDRVSVTCKASQNVGTNVAWFLQKPGQSPKALIYSASYRYSGVPDRFTGSGSGTDFTLTISNVQSEDLAEYFCQQYNNFPYTFGGGTKLEIKRTVA Sequence ID 38 (amino acid sequence of the light chain constant domain of the chimeric B1-23 anti-GDF-15 antibody): APSVFIFPPSDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRGEC SEQ ID NO: 39 (amino acid sequence of the heavy chain variable domain of the 01G06 antibody): QVQLVQSGAEVKKPGASVKVSCKASGYTFTDYNMDWVRQAPGQSLEWMGQINPNNGLIFFNQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYYCAREAITTVGAMDYWGQGTLVTVSS SEQ ID NO: 40 (amino acid sequence of the light chain variable domain of the 01G06 antibody): DIQMTQSPSSLSASVGDRVTITCRTSENLHNYLAWYQQKPGKSPKLLIYDAKTLADGVPSRFSGSGSGTDY TLTISSLQPEDFATYYCQHFWSDPYTFGQGTKLEIK SEQ ID NO: 41 (amino acid sequence of the heavy chain variable domain of the 03G05 antibody): QVQLQQPGAELVKPGASVKLSCKASGYTFTSYWIHWVNQRPGQGLEWIGDINPSNGRSKYNEKFKNKATMT ADKSSNTAYMQLSSLTSEDSAVYYCAREVLDGAMDYWGQGTSVTVSS Sequence ID No. 42 (amino acid sequence of the light chain variable domain of the 03G05 antibody): DIVLTQSPASLAVSLGQRATISCRASESVDNYGISFMNWFQQKPGQPPKLLIYAASNQGSGVPARFSGSGS GTDFSLNIHPMEEDDTAMYFCQQSKEVPWTFGGGSKLEIK SEQ ID NO: 43 (amino acid sequence of the heavy chain variable domain of the 04F08 antibody): QVTLKESGPGILQPSQTLSLTCSSGFSLSTYGMVTWIRQPSGKGLEWLAHIYWDDDKRYNPSLKSRLTI SKDTSNNQVFLKITSVDTADTATYYCAQTGYSNLFAYWGQGTLVTVSA Sequence ID No. 44 (amino acid sequence of the light chain variable domain of the 04F08 antibody): DIVMTQSQKFMSTSVGDRVSVTCKASQNVGTNVAWYQQKLGQSPKTLIYSASYRYSGVPDRFTGSGSGTDF TLTISNVQSEDLAEYFCQQYNSYPYTFGGGTKLEIK SEQ ID NO: 45 (amino acid sequence of the heavy chain variable domain of the 06C11 antibody): QVTLKESGPGILQPSQTLSLTCSFSGFSLNTYGMGFSWIRQPSGKGLEWLAHIYWDDDKRYNPSLKSRLTI SKDASNNRVFLKITSVDTADTATYYCAQRGYDDYWGYWGQGTLVTISA Sequence ID No. 46 (amino acid sequence of the light chain variable domain of the 06C11 antibody): DIVMTQSQKFMSTSVGDRVSVTCKASQNVGTNVAWFQQKPGQSPKALIYSASYRYSGVPDRFTGSGSGTDF ILTISNVQSEDLAEYFCQQYNNYPLTFGAGTKLELK Sequence ID No. 47 (amino acid sequence of the heavy chain variable domain of the 08G01 antibody): EVLLQQSGPEVVKPGASVKIPCKASGYTFTDYNMDWVKQSHGKSLEWIGEINPNNGGTFYNQKFKGKATLT VDKSSSTAYMELRSLTSEDTAVYYCAREAITTVGAMDYWGQGTSVTVSS Sequence ID No. 48 (amino acid sequence of the light chain variable domain of the 08G01 antibody): DIQMTQSPASLSASVGETTVTITCRASGNIHNYLAWYQQKQGKSPQLLVYNAKTLADGVPSRFSGSGSGTQY SLKINSLQPEDFGSYYCQHFWSSPYTFGGGTKLEIK Sequence ID No. 49 (amino acid sequence of the heavy chain variable domain of the 14F11 antibody): QVTLKESGPGILQPSQTLSLTCSFSGFSLSTYGMGVGWIRQPSGKGLEWLADIWWDDDKYYNPSLKSRLTI SKDTSSNEVFLKIAIVDTADTATYYCARRGHYSAMDYWGQGTSVTVSS Sequence ID No. 50 (amino acid sequence of the light chain variable domain of the 14F11 antibody): DIVMTQSQKFMSTSVGDRVSVTCKASQNVGTNVAWYQQKPGQSPKALIYSPSYRYSGVPDRFTGSGSGTDF TLTISNVQSEDLAEYFCQQYNSYPHTFGGGTKLEMK Sequence ID 51 (amino acid sequence of the heavy chain variable domain of the 17B11 antibody): QVTLKESGPGILQPSQTLSLTCSFSGFSLSTSGMGVSWIRQPSGKGLEWLAHNDWDDDKRYKSSLKSRLTI SKDTSRNQVFLKITSVDTADTATYYCARRVGGLEGYFDYWGQGTTLTVSS Sequence ID No. 52 (amino acid sequence of the light chain variable domain of the 17B11 antibody): DIVLTQSPASLAVSLGQRATISCRASQSVSTSRFSYMHWFQQKPGQAPKLLIKYASNLESGVPARFSGSGS GTDFTLNIHPVEGEDTATYYCQHSWEIPYTFGGGTKLEIK [Examples]

[0120] Reference Examples 1-3 illustrate hGDF-15 inhibitors that can be used in the compositions, kits, methods, and uses according to the present invention. These hGDF-15 inhibitors are monoclonal antibodies known from WO2014 / 049087, the full text of which is incorporated herein by reference:

[0121] Reference Example 1: Preparation and Characterization of GDF-15 Antibody B1-23 Antibody B1-23 was produced in GDF-15 knockout mice. Recombinant human GDF-15 (SEQ ID NO: 8) was used as the immunogen.

[0122] The hybridoma cell line B1-23, which produces mAb-B1-23, was deposited with Deutsche Sammlung fur Mikroorganismen und Zellkulturen GmbH (DMSZ) under accession number DSM ACC3142 by Julius-Maximilians-Universitat Wurzburg, Sanderring 2, 97070 Wurzburg, Germany, in accordance with the Budapest Convention.

[0123] Using a commercially available test strip system, B1-23 was identified as the IgG2a (κ chain) isotype. The dissociation constant (Kd) was determined using surface plasmon resonance (SPR) measurements as follows:

[0124] The binding of the monoclonal anti-human GDF-15 antibody anti-human GDF-15 mAb-B1-23 of the present invention was measured using surface plasmon resonance measurement with the Biorad ProteOn XPR36 system and Biorad GLC sensor chip.

[0125] To prepare the biosensor, recombinant mature human GDF-15 protein was immobilized on flow cells 1 and 2. One flow cell used recombinant GDF-15 derived from baculovirus-transfected insect cells (HighFive insect cells), while the other used recombinant protein derived from expression in Escherichia coli (E. coli). The GLC sensor chip was activated using sulfo-NHS (N-hydroxysulfosuccinimide) and EDC (1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride) (Biorad ProteOn amine coupling kit) according to the manufacturer's recommendations, and then the protein was immobilized on the sensor surface to a maximum of approximately 600 RU (1 Ru = 1 pg mm²). -2The cells were loaded at a density of ). Unreacted coupling groups were then quenched by perfusing with 1M ethanolamine pH 8.5, and the biosensor was equilibrated by perfusing the tip with running buffer (10M HEPES, 150mM NaCl, 3.4mM EDTA, 0.005% Tween-20, pH 7.4, called HBS150). As a control, two flow cells were used: one empty flow cell with no protein coupling, and the other flow cell coupled with a non-physiological protein partner (human interleukin-5) immobilized using the same coupling chemistry and coupling density. For interaction measurements, anti-human GDF-15 mAb-B1-23 was dissolved in HBS150 and used as analytes at six different concentrations (concentrations: 0.4, 0.8, 3, 12, 49, and 98 nM). To avoid intermittent regeneration, use a one-shot kinetics setting to perfuse the analyte into the biosensor, and perform all measurements at 25°C in 100 μl increments. -1 The analysis was performed using the specified flow velocity. For processing, the bulk face effect and nonspecific binding with the sensor matrix were removed by subtracting the SPR data of an empty flow cell (flow cell 3) from all other SPR data. The resulting sensorgrams were analyzed using the ProteOn Manager software version 3.0. A 1:1 Langmuir interaction was assumed for the coupling dynamics analysis. The association rate constant was set to 5.4 ± 0.06 × 10⁻⁶. 5 M -1 s -1 (k on The value of ) and the dissociation rate constant are 4.3 ± 0.03 × 10 -4 s -1 (k off The value of ) was determined (the value concerns the interaction of anti-human GDF-15 mAb-B1-23 with GDF-15t derived from insect cell expression). Equation K D =k off / k onThe equilibrium dissociation constant was calculated using [a specific method], yielding a value of approximately 790 pM. The affinity values ​​of the interaction between GDF-15 expressed in Escherichia coli (E. coli) and anti-human GDF-15 mAb-B1-23 differed by less than twofold. The rate constants of GDF-15 from insect cells and E. coli (E. coli) deviated by approximately 45%, and therefore, within the accuracy of the SPR measurement, it is likely that this does not reflect the true difference in affinity. Under the conditions used, anti-human GDF-15 mAb-B1-23 did not show binding to human interleukin-5, thus confirming the interaction data and the specificity of anti-human GDF-15 mAb-B1-23.

[0126] The amino acid sequence of recombinant human GDF-15 (as expressed in insect cells transfected with baculovirus) is: GSARNGDHCP LGPGRCCRLH TVRASLEDLG WADWVLSPRE VQVTMCIGAC PSQFRAANMH AQIKTSLHRL KPDTVPAPCC VPASYNPMVL IQKTDTGVSL QTYDDLLAKD CHCI That is the case. (Sequence 8)

[0127] Therefore, surface plasmon resonance (SPR) was used to determine the dissociation constant (Kd) at 790 pM. For comparison, the therapeutically used antibody rituximab has a significantly lower affinity (Kd = 8 nM).

[0128] To date, it has been shown that mAb B1-23 inhibits cancer cell proliferation in vitro and inhibits tumor growth in vivo (WO2014 / 049087).

[0129] Reference Example 2: mAb B1-23 recognizes conformational or discontinuous epitopes of human GDF-15. Epitope mapping: Monoclonal mouse antibody GDF-15 against a 13-mer linear peptide derived from GDF-15.

[0130] Antigen: GDF-15: GSGSGSGMPGQELRTVNGSQMLLVLLVLSWLPHGGALSLAEASRASFPGPSELHSEDSRFRELRKRYEDLLTRLRANQSWEDSNTDLVPAPAVRILTPEVRLGSGGHLHLRISRAALPEGLPEASRLHRALFRLSPTASRSWDVTRPLRRQLSLARPQAPALHLRLSPPPSQSDQLLAESSSARPQLELHLRPQAARGRRRARARNGDHCPLGPGRCCRLHTVRASLEDLGWADWVLSPREVQVTMCIGACPSQFRAANMHAQIKTSLHRLKPDTVPAPCCVPASYNPMVLIQKTDTGVSLQTYDDLLAKDCHCIGSGSGSG (322 amino acids with linker) (SEQ ID NO: 10)

[0131] The protein sequence was translated into 13-mer peptides with a 1 amino acid shift. To avoid C-terminal and N-terminal truncated peptides, the C-terminus and N-terminus were extended with neutral GSGS linkers (bold).

[0132] Control peptide: Flag: DYKDDDDKGG (SEQ ID NO: 13), 78 spots; HA: YPYDVPDYAG (SEQ ID NO: 14), 78 spots (per array copy)<OO00897>

[0133] Peptide chip identifier: 000264_01 (10 / 90, Ala2Asp linker)

[0134] Staining conditions: Standard buffer: PBS, pH 7.4 + 0.05% Tween 20 Blocking buffer: Rockland blocking buffer MB-070 Incubation buffer: Standard buffer and 10% Rockland blocking buffer MB-070 Primary sample: Monoclonal mouse antibody GDF-15 (1 μg / μl): Diluted 1:100 in incubation buffer at 4°C, stained for 16 hours with gentle shaking at 500 rpm. Secondary antibody: Goat anti-mouse IgG(H+L) IRDye680, diluted 1:5000 in incubation buffer, stained at room temperature (RT) for 30 minutes. Control antibodies: Monoclonal anti-HA(12CA5)-LL-Atto680 (1:1000), monoclonal anti-FLAG(M2)-FluoProbes752 (1:1000); staining in incubation buffer at RT for 1 hour.

[0135] scanner: Odyssey Imaging System, LI-COR Biosciences Settings: Offset: 1mm; Resolution: 21μm; Brightness Green / Red: 7 / 7

[0136] result: After pre-swelling in standard buffer for 30 minutes and in blocking buffer for 30 minutes, peptide arrays containing 10, 12, and 15-mer linear peptides derived from B7H3 were incubated with secondary goat anti-mouse IgG(H+L) IRDye680 antibody at a dilution of 1:5000 only, at room temperature for 1 hour, to analyze the background interaction of the secondary antibody. PEPperCHIP® was washed 2 × 1 minute with standard buffer, rinsed with distilled water, and dried in a stream of air. Readouts were performed using the Odyssey imaging system with a resolution of 21 μm and a green / red brightness of 7 / 7. The inventors observed weak interactions of arginine-rich peptides known as high-frequency binders (ELHLRPQAARGRR (SEQ ID NO: 15), LHLRPQAARGRRR (SEQ ID NO: 16), HLRPQAARGRRRA (SEQ ID NO: 17), LRPQAARGRRRAR (SEQ ID NO: 18), RPQAARGRRRARA (SEQ ID NO: 19), PQAARGRRRARAR (SEQ ID NO: 20), and QAARGRRRARARN (SEQ ID NO: 21)), and used the basic peptide MHAQIKTSLHRLK (SEQ ID NO: 22) due to ionic interactions with charged antibody dyes.

[0137] After pre-swelling in standard buffer for 10 minutes, the peptide microarray was incubated overnight at 4°C with a 1:100 dilution of monoclonal mouse antibody GDF-15. Repeated washing with standard buffer (2 × 1 min) was performed, followed by incubation at room temperature for 30 minutes with a 1:5000 dilution of secondary antibody. After washing with standard buffer for 2 × 10 seconds and a brief rinse with distilled water, the PEPperCHIP® was dried in a stream of air. Readouts were performed using the Odyssey imaging system at a resolution of 21 μm and a green / red brightness of 7 / 7 before and after staining of control peptides with anti-HA and anti-FLAG(M2) antibodies.

[0138] None of the linear 13-mer peptides derived from GDF-15 interacted with the monoclonal mouse antibody GDF-15, even under hyperregulated brightness. However, staining of the Flag and HA control peptides constituting the array did not produce good, uniform spot brightness.

[0139] summary: Epitope mapping of the monoclonal mouse GDF-15 antibody against GDF-15 showed no linear epitopes with 13-mer peptides derived from the antigen. This finding strongly suggests that the monoclonal mouse antibody GDF-15 recognizes conformational or discontinuous epitopes with low affinity partial epitopes. Since there was clearly no GDF-15 signal exceeding the background staining of the secondary antibody alone, quantification of spot brightness using a PepSlide® analyzer and subsequent peptide annotation were omitted.

[0140] Reference Example 3: Structural identification of peptide ligand epitopes by mass spectrometry-based epitope cleavage and epitope extraction. The recombinant human GDF-15 epitope that binds to antibody B1-23 was identified by epitope excision and epitope extraction (Suckau et al., Proc Natl Acad Sci US A. December 1990; 87(24): pp. 9848-9852; R. Stefanescu et al., Eur. J. Mass Spectrom. 13, pp. 69-75 (2007)).

[0141] For antibody column preparation, antibody B1-23 was added to Sepharose coupled with NHS-activated 6-aminohexanoic acid. Then, antibody B1-23 coupled with Sepharose was loaded into a 0.8 ml microcolumn and washed with blocking and washing buffer.

[0142] Epitope extraction experiment: Recombinant human GDF-15 was digested with trypsin at 37°C (in solution) for 2 hours to obtain various peptides according to the trypsin cleavage sites in the protein. After complete digestion, the peptides were loaded onto an affinity column containing immobilized antibody B1-23. Unbound and potentially bound peptides of GDF-15 were used for mass spectrometry analysis. Peptide identification by mass spectrometry was not possible. This was a further indicator that the binding region of GDF-15 in the immune complex B1-23 contained discontinuous or conformational epitopes. In the case of continuous linear epitopes, the digested peptide should bind to its interaction partner unless there is a trypsin cleavage site in the epitope peptide. Discontinuous or conformational epitopes can be confirmed by the epitope cleavage method described in the following section.

[0143] Epitope extraction experiment: Next, antibody B1-23, immobilized on an affinity column, was incubated with recombinant GDF-15 for 2 hours. The immunocomplex formed on the affinity column was then incubated with trypsin at 37°C for 2 hours. The cleavage yielded various peptides derived from recombinant GDF-15. The immobilized antibody itself is proteolytically stable. The resulting peptides from the digested GDF-15 protein, shielded by the antibody and thus protected from proteolytic cleavage, were eluted under acidic conditions (TFA, pH 2), collected, and identified by mass spectrometry.

[0144] Epitope excision using MS / MS identification yielded the following peptides:

[0145] [Table 1]

[0146] A portion of human GDF-15 that binds to antibody B1-23 contains discontinuous or conformational epitopes. Mass spectrometry identified two peptides within the GDF-15 protein that participate in immune complex formation. These peptides are limited to positions 40-55 (EVQVTMCIGACPSQFR) and 94-114 (TDTGVSLQTYDDLLAKDCHCI) in the GDF-15 amino acid sequence. Therefore, these two peptides contain epitopes in the GDF-15 protein that bind to antibody B1-23.

[0147] The present invention is illustrated by the following non-limiting examples:

[0148] (Example 1) In human melanoma patients who had previously received ipilimumab (monoclonal anti-CTLA4 antibody) and failed to achieve a complete response, and who were then treated with pembrolizumab (monoclonal anti-PD-1 antibody), serum hGDF-15 levels correlated with insufficient treatment response at 4 months after the initiation of pembrolizumab treatment.

[0149] The inventors set out to investigate whether cancer patients receiving immune checkpoint blockers could benefit from the inhibition of hGDF-15. To examine this possibility, sera obtained from melanoma patients who had received treatment with pembrolizumab (a monoclonal anti-PD-1 antibody) in a clinical study and who had received pre-treatment with ipilimumab (a monoclonal anti-CTLA4 antibody) were analyzed for hGDF-15 serum levels. Subsequently, the obtained hGDF-15 serum levels were correlated with patient responses to investigate whether hGDF-15 affects patient responses to immune checkpoint blockers. The sera were collected from patients before treatment with pembrolizumab.

[0150] The study and subsequent analysis were conducted as follows:

[0151] Inclusion criteria for the clinical study: Eligible patients are 18 years of age or older, have histologically or cytologically confirmed unresectable stage III or stage IV melanoma, are unsuitable for local therapy, have experienced disease progression within 24 weeks of the last ipilimumab dose (minimum 2 doses, 3 mg / kg once every 3 weeks), have received prior BRAF or MEK inhibitor therapy or both (if BRAFV600 variant positive), have resolved or improved an ipilimumab-related adverse event to grade 0-1, and have received prednisone ≤10 mg / day for at least 2 weeks prior to the first dose of the study drug, have an Eastern Cooperative Oncology Group (ECOG) status of 0 or 1, and meet the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST). The following conditions were measured within pre-specified ranges for diseases measurable in v1.1), as well as absolute neutrophil count (≥1500 cells per mL), platelets (≥100000 cells per mL), hemoglobin (≥90 g / L), serum creatinine (≤1.5 upper limit of normal [ULN]), serum total bilirubin (≤1.5 ULN or direct bilirubin ≤ULN for patients with total bilirubin concentration >1.5 ULN), aspartic acid and alanine aminotransferase (≤2.5 ULN or ≤5 ULN for patients with liver metastases), international normalized ratio or prothrombin time (≤1.5 ULN if no anticoagulants were used), and activated partial thromboplastin time (≤1.5 ULN if no anticoagulants were used). Patients had a washout period of at least 4 weeks between the last dose of their most recent therapy and the first dose of pembrolizumab. Patients with known active brain metastases or carcinomatous meningitis, active autoimmune disease, active infection requiring systemic therapy, a known history of HIV infection, active hepatitis B or C virus infection, a history of grade 4 or grade 3 ipilimumab-related adverse events lasting longer than 12 weeks, or prior treatment with any other anti-PD-1 or anti-PD-L1 therapy were excluded from the study.

[0152] Patient treatment: Human melanoma patients who met the inclusion criteria defined above (with two exceptions) had already been treated with ipilimumab (monoclonal anti-CTLA4 antibody) and had not achieved a complete response. Pembrolizumab (monoclonal anti-PD-1 antibody) was administered at either 2 mg / kg body weight or 10 mg / kg body weight. No dose-dependent differences were observed between the two treatment groups, so treated patients were evaluated together.

[0153] Criteria for determining effectiveness: We classified patients into responders, non-responders, and those with ongoing responses to treatment using the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) (Eisenhauer et al.: New response evaluation criteria in solid tumors: revised RECIST guideline (version 1.1), Eur. J. Cancer. 45, No. 2, January 2009, pp. 228-227).

[0154] Analysis of hGDF-15 serum levels by enzyme-linked immunosorbent assay (ELISA): Human GDF-15 serum levels were measured using enzyme-linked immunosorbent assay (ELISA).

[0155] Buffers and reagents: Buffer blocking solution: 1% BSA in PBS (Fraction V, pH 7.0, PAA Co.) Washing solution: PBS-Tween (0.05%) Standard: Human GDF-15 (stock concentration 120 μg / ml, manufactured by R&D Systems) Capture antibodies: Human GDF-15 MAb (clone 147627), manufactured by R&D Systems; Mouse IgG2B (catalog number MAB957, manufactured by R&D Systems, stock concentration 360 μg / ml) Detection antibodies: Human GDF-15 biotinylated affinity-purified PAb, goat IgG (catalog number BAF940, R&D Systems, stock concentration 9 μl / ml) Streptoavidin-HRP (Catalog No. DY998, manufactured by R&D Systems) Substrate solution: 10ml 0.1M NaOAc pH6.0+100μl TMB+2μl H2O2 Stop solution: 1M H2SO4

[0156] Analysis procedure: 1. Plate preparation: a. The capture antibody was diluted to a working concentration of 2 μg / ml in PBS. A 96-well microplate (Nunc maxisorp®) was immediately coated with 50 μl of diluted capture antibody per well, except for the outer rows (A and H). Rows A and H were filled with buffer to prevent sample evaporation during the experiment. The plate was gently tapped to ensure that the bottom of each well was completely covered. The plate was placed in a humidification chamber and incubated overnight at room temperature (RT). b. Each well was aspirated and washed three times with PBS-Tween (0.05%). c. 150 μl of blocking solution was added to each well, followed by incubation in RT for 1 hour. d. Each well was aspirated and washed three times with PBS-Tween (0.05%).

[0157] 2. Assay procedure: a. Standards were prepared. GDF-15 was diluted to a final concentration of 1 ng / ml with buffered blocking solution (4.17 μl GDF + 496 μl buffered blocking solution). Two 1:2 serial dilutions were prepared. b. A 1:20 ratio of two samples (6 μl + 114 μl buffered blocking solution) was prepared. 50 μl of diluted sample or standard was added to each well, followed by incubation in RT for 1 hour.

[0158] [Table 2]

[0159] a. Each well was aspirated and washed three times with PBS-Tween (0.05%). b. The detection antibody was diluted to a final concentration of 50 ng / ml (56 μl + 10 ml blocking buffer). 50 μl of the diluted detection antibody was added to each well, followed by incubation in RT for 1 hour. c. Each well was aspirated and washed three times with PBS-Tween (0.05%). d. Streptavidin-HRP was diluted 1:200 (50 μl + 10 ml blocking buffer). 50 μl of the working dilution of streptavidin-HRP was added to each well, followed by incubation in RT for 20 minutes. e. Each well was aspirated and washed three times with PBS-Tween (0.05%). f. Substrate solutions were prepared. 50 μL of substrate solution was added to each well, followed by incubation in RT for 20 minutes. g. 50 μL of stop solution was added to each well. The optical density of each well was immediately determined using a microplate reader set to h.450nm.

[0160] 3. Calculation of GDF-15 serum titer: a. Each sample / GDF-15 standard dilution was applied in two sets. To determine the GDF-15 titer, the average of the two sets was calculated and the background (samples without GDF-15) was subtracted. b. To construct a standard curve, values ​​obtained from the linear range were plotted on an XY-figure (X-axis: GDF-15 concentration, Y-axis: OD450), and linear curve fitting was applied. The GDF-15 serum titer of the test sample was calculated by interpolation from the OD450 values ​​of standard dilutions with known concentrations. c. The respective dilution factors were considered to calculate the final GDF-15 concentration of each sample. Samples that yielded OD values ​​below or above the standard range were re-analyzed with appropriate dilutions.

[0161] Comparison with patient data on hGDF-15 serum levels: Next, the measured hGDF-15 serum levels were compared with patient response data obtained from the study.

[0162] Figure 1 shows the GDF-15 serum levels of responders and non-responders for each treatment regimen. As can be seen from the figure, most non-responders have higher GDF-15 serum levels than all responders.

[0163] These results are also reflected in Figure 2, which shows the number of responders and non-responders among patients with hGDF-15 serum levels of <1.8 ng / ml, 1.8–4.2 ng / ml, and >4.2 ng / ml, respectively.

[0164] These findings suggested that high GDF-15 levels were associated with insufficient treatment response. Therefore, we tested these findings for their statistical significance:

[0165] Statistical correlation with patient data on hGDF-15 serum levels: data: Data analysis was based on a data file containing data from samples obtained from 35 patients, including column (variable) sample display, GDF-15 (ng / ml), responder / non-responder, days (to death or censoring), and progression (exponential variable of ongoing life). Responder / non-responder classification of these data was performed at 4 months after the initiation of pembrolizumab treatment. Since some serum samples were only obtained shortly before analysis, response could only be assessed in 29 patients. One partial responder (>30% reduction in tumor size) was evaluated as a responder. Four samples had to be eliminated by hemolysis for LDH determination.

[0166] Outcome variables (endpoints): a. Overall survival (time to death). This endpoint consists of an event metric for death derived from the data file (1=death / 0=survival), and the time to death or censoring (the last time the patient was known to be alive), corresponding to the variable "days". b. Response to treatment, e.g., whether the patient was a responder or not (coded as 1 = responder, 0 = non-responder). Partial responders were considered responders.

[0167] [Table 3]

[0168] Data analysis: Overall survival was analyzed using the Cox proportional hazards survival model. One model was fitted with GDF-15 (ng / ml) as the continuous predictor, and another model was fitted with GDF-15-based grouping variables as the categorical predictor (groups were defined as GDF-15 <1.8 ng / ml, 1.8–4.2 ng / ml, and >4.2 ng / ml). Overall, survival data were available from 35 patients.

[0169] The response to treatment (a binary variable) was analyzed using a generalized linear model (GLM) with a binomial error distribution and a logit link function (logistic regression). For the response to treatment as assessed by the RECIST 1.1 criteria at 4 months, the model was fitted using GDF-15 (ng / ml) as a continuous predictor variable. Since no patients responded in the group with GDF-15 > 4.2 ng / ml, the estimated odds ratio for this group versus the group with GDF-15 < 1.8 ng / ml was extremely large, resulting in a very wide confidence interval. Instead of fitting another model using a grouping variable based on GDF-15 as a categorical predictor, the chi-squared (χ²) was used. 2The groups were compared using a test (to examine the equivalence of the proportion of responders). Because the number of responders / non-responders was extremely small (<5), a sensitivity analysis was further performed using Fisher's exact test. Patients who had received anti-PD-1 alone within the last four months could not yet be classified as responders or non-responders. Therefore, only 29 patients could be evaluated for response to therapy.

[0170] Data analysis was performed using the statistical software package R (R Core Team, 2014, version 3.1.0).

[0171] result: Tables 1 and 2 show the results obtained from a model using GDF-15 as a continuous predictor variable. The hazard for death was significantly increased for high concentrations of GDF-15 (HR>1, Table 1), but the probability of response to treatment was significantly decreased, as indicated by the odds ratio (OR) (OR<1, Table 2). Figure 3 shows the corresponding data for responders / non-responders and the probability of response to treatment predicted by the model.

[0172] Table 3 shows the results obtained from a Cox proportional hazards model using groups based on GDF-15 as a categorical predictor. The group with GDF-15 < 1.8 ng / ml is used as the reference group (not shown in the table). The two hazard ratios in Table 3 represent comparisons between the reference group and the group with GDF-15 between 1.8 and 4.2, and the group with GDF-15 > 4.2. In both of these groups, the hazard to death is increased (compared to the reference group), but to a greater extent than in the group with GDF-15 > 4.2. Figure 4 shows the Kaplan-Meier curves for survival in the three groups.

[0173] The proportion of responders differed significantly between groups (responder 1:χ²). 2 df=2(=16.04, P=0.0003). This result was confirmed by Fisher's exact test (P=0.0003). The number of deaths and responders per group is shown in Table 1. Furthermore, Table 2 shows some descriptive statistics for GDF-15 for each group.

[0174] [Table 4]

[0175] [Table 5]

[0176] [Table 6]

[0177] [Table 7]

[0178] [Table 8]

[0179] Next, in order to compare the statistical results obtained for GDF-15 levels, a statistical analysis was also performed on the levels of the known prognostic factor lactate dehydrogenase (LDH) in the patients' serum.

[0180] Lactate dehydrogenase (LDH) is considered a prognostic marker for solid tumors. This was recently confirmed by a comprehensive meta-analysis based on a large pool of clinical studies (31,857 patients). A consistent effect of elevated LDH on overall survival (HR=1.48, 95% CI=1.43–1.53) was observed across all disease subgroups and stages. Furthermore, there was a stronger trend towards prognostic LDH values ​​in metastatic disease compared to non-metastatic disease, which was thought to reflect a greater tumor burden. Although the exact mechanism remains unknown, LDH may be associated with metabolic reprogramming due to hypoxia and the Warburg effect, and it can be interpreted as reflecting high tumor burden or tumor aggressiveness (Zhang, J., Yao, Y.-H., Li, B.-G., Yang, Q., Zhang, P.-Y., and Wang, H.-T. (2015). Prognostic value of pretreatment serum lactate dehydrogenase level in patients with solid tumors: a systematic review and meta-analysis. Scientific Reports 5, 9800). Since serum LDH levels are incorporated into the melanoma staging scheme, this parameter is routinely measured at university reference research facilities during clinical diagnosis.

[0181] [Table 9]

[0182] In the four blood samples, LDH determination failed due to hemolysis.

[0183] Table 7 is analogous to Table 2, except that LDH was used as a continuous predictor of treatment response (responder 1) instead of GDF-15. The probability of treatment response decreased slightly but significantly as the LDH value increased (OR < 1, p < 0.1). Figure 5 shows the corresponding data for responders / non-responders and the probability of treatment response predicted by the model.

[0184] To determine whether GDF-15 is a better predictor than LDH for treatment response (responder 1), two further models were fitted: a model containing both markers as predictors (automatically including only patients with measurements for both markers) and a model using GDF-15 as the sole predictor but only including patients with measurements for LDH. Akaike's information criterion (AIC) was then calculated for all three models (Table 5). A smaller AIC indicates a more efficient model. Indeed, the AIC of the model using GDF-15 as a predictor was smaller than that of the model using LDH. The model using only GDF-15 had an even smaller AIC than the model using both predictors, indicating that LDH as an additional predictor does not improve the model. Of course, the model using both predictors should not explain treatment response worse, but as a measure of "model efficiency," AIC penalizes models using predictors that do not significantly improve the model, thus favoring simpler models. Alternative model comparisons were performed by analyzing the deviance (similar to ANOVA, but for generalized linear models), that is, comparing the difference in explained deviance between a more complex model using both predictors and a simpler model using only one of the predictors (corresponding to model reduction by either LDH or GDF-15). Removing GDF-15 from the more complex model resulted in a significant reduction in explained deviance (P=0.02), but removing LDH did not (P=0.41).

[0185] [Table 10]

[0186] [Table 11]

[0187] Figure 5A shows the probability of response to treatment (responder 1) as predicted by a generalized linear model using LDH as a continuous predictor variable. Circles represent data, and curves represent the model. Vertical lines represent the LDH concentration at which the probability of treatment response is 0.5. The patient cohort was identical. However, in four patients, reliable determination of LDH levels failed due to hemolysis. Figure 5B shows graphs of responders and non-responders, along with their respective hGDF-15 and LDH levels. If the cutoff value is selected to cover all responders, the GDF-15-based trial allows for the identification of six non-responders (out of nine), while the LDH-level-based analysis can only identify four non-responders (out of nine). For the LDH trial, four hemolytic samples that would cause data loss had to be excluded.

[0188] summary: In summary, the statistical results of Example 1 above showed that the likelihood of a response to treatment significantly decreased as the patient's serum hGDF-15 level increased. For example, the odds ratio of 0.389 shown in Table 2 indicates that a 1 ng / ml increase in the hGDF-15 serum level reduces the likelihood of a response to treatment to 0.389 times the original value, or approximately a 60% reduction. A 2 ng / ml increase in the hGDF-15 serum level reduces the likelihood of a response to treatment to 0.389 × 0.389 = 0.151 times the original value, or approximately an 85% reduction.

[0189] The results of Example 1 suggest that hGDF-15 acts to negatively affect the patient's response to immune checkpoint blocker therapy. Therefore, according to the present invention, inhibitors of hGDF-15 are useful in improving the patient's response to immune checkpoint blocker therapy, not only in melanoma but in all solid tumors referred to herein, by inhibiting the negative effect of hGDF-15 on the patient's response to immune checkpoint blocker therapy.

[0190] (Example 2) GDF-15 levels are associated with CD8 metastasis from various tumor entities. + It is inversely correlated with tumor-infiltrating lymphocytes (TILs). To identify the mechanisms by which hGDF-15 may contribute to the negative effects of hGDF-15 on patient response, we analyzed brain metastases from various solid tumors for hGDF-15 expression and the presence of immune system cells.

[0191] Tissue specimens and tissue processing: Formalin-fixed and paraffin-embedded (FFPE) tissues obtained from recorded brain metastases were analyzed and collected and processed as tissue microarrays (TMAs). All specimens were obtained from the UCT tumor bank (Goethe-University, Frankfurt am Main, Germany, member of the German Cancer Consortium (DKTK), Heidelberg, Germany and German Cancer Research Center (DKFZ), Heidelberg, Germany) or the cancer registry tumor bank "Blut-und Gewebebank zur Erforschung des malignen Melanoms" (Department of Dermato-oncolgy, University Hospital Tubingen, Germany). Approval for this study was granted by two independent ethics committees (Ethics Committee UCT Frankfurt / Goethe University Frankfurt am Main, Germany: Project No.: GS 4 / 09; SNO_01-12; Ethics Committee University of Tubingen: Project No.: 408 / 2013BO2). A total of 190 patients with brain metastases were examined, including specimens of melanoma (n=98), NSCLC (n=33), breast cancer (n=18), RCC (n=10), SCLC (n=7), colorectal cancer (n=7), cancers not specified (cancer NOS n=11), and rare tumors grouped as others (n=6). Survival data (survival time after tumor resection) were collected from 155 patients, and the number of brain metastases in 169 patients and the size of brain metastases in a subcohort of 55 melanoma patients were further analyzed.

[0192] Immunohistochemistry: Immunohistochemistry of all antibodies was performed using a Discovery XT automated IHC staining system (Roche / Ventana, Tucson, Arizona, USA) with 3 μm thick slides and standard protocols. The following antibodies were used: anti-GDF-15 (HPA011191, dilution 1:50, Sigma / Atlas, protocol number 730), CD3 (clone A0452, dilution 1:500, DAKO, Glostrup, Denmark), CD8 (clone C8 / 144B, dilution 1:100, DAKO, Glostrup, Denmark), PD-1 (clone NAT105; dilution 1:50; Abcam, Cambridge, United Kingdom), PD-L1 (E1L3N; dilution 1:200; Cell Signaling, Boston, USA), and FOXP3 (clone 236A / E7; dilution 1:100; eBioscience, San Diego, USA). Slides were counterstained with hematoxylin and mounted.

[0193] Statistical analysis: All samples were scored according to the frequency (as a percentage) of all cells on the stained TMA core and associated positive cells. For hGDF-15 expression, the scores described in detail previously [21,22] were used: frequency 0-1% score 0; 1-10% score 1; 10-25% score 2; 25-50% score 3; >50% score 4; and finally, the frequency score was multiplied by the staining intensity (1 weak staining, 2 moderate staining, 3 strong staining) to obtain an ordinal scale hGDF-15 score (0, 1, 2, 3, 4, 6, 8, 9, 12). The ordinal scale variables were corrected for multiple tests by comparing them with the non-parametric Wilcoxon / Kruskal-Wallis test and Dunn's method. For continuous variables, ANOVA and the subsequent Tukey-Kramer HSD post-Hock test were used to compare the means among various brain metastasis entities. For correlation analysis between brain metastasis size and marker expression, linear fitting followed by ANOVA was performed, and for ordinal scaled variables, Spearman's low correlation analysis was used. A significance level of p<0.05 was set for all statistical analyses.

[0194] All statistical analyses were performed using JMP8 and JMP11 (SAS, Cary, USA), and further graphs were created using Prism 6 (GraphPad software, La Jolla, USA).

[0195] result: Figure 6 shows exemplary tissue sections obtained from melanoma brain metastases that do not exhibit high GDF-15 immunoreactivity (upper panel) or exhibit high GDF-15 immunoreactivity (lower panel), as shown in the figure, and stained immunohistochemically for GDF-15 and T cell marker proteins CD3 and CD8, respectively. In sections without GDF-15 expression, numerous invasive immune cells are seen as dark spots. In the photograph showing metastases expressing high levels of GDF-15, rare invasive immune cells are indicated by arrows (CD3 and CD8-positive cells are indicated by arrows). Surprisingly, as can be seen from the figure, tissue sections with high hGDF-15 immunoreactivity (lower panel) show a higher CD3 level compared to tissue sections without hGDF-15 immunoreactivity (upper panel). + and CD8 + A significant reduction in the number of cells was observed. Notably, other stained markers such as PD-L1 and PD-1 all indicated tumor-infiltrating CD3 + and CD8 + It showed a positive correlation with the number of T cells.

[0196] Therefore, across various melanoma brain metastases, hGDF-15 levels and CD3 + We analyzed whether there was an inverse correlation between the percentages of T cells. Figure 7A shows the relationship between CD3 and the GDF-15 score (obtained as described above in the "Statistical Analysis" section). + The percentage of cells is plotted. As shown in Figure 7A, CD3 + There was a statistically significant inverse phase between the percentage of cells and the GDF-15 score (p=0.0015).

[0197] Similarly, across various melanoma brain metastases, hGDF-15 levels and CD8 + We also analyzed whether there was an inverse correlation between the percentages of T cells. Figure 7B shows the relationship between CD8 (obtained as described above in the "Statistical Analysis" section) and the GDF-15 score. + The percentage of cells is plotted. As shown in Figure 7B, CD8 + There was a statistically significant inverse phase between the percentage of cells and the GDF-15 score (p=0.0038).

[0198] In contrast, Spearman's rank correlation coefficient (Rhoe) test did not yield statistically significant results in correlating GDF-15 with FOXP3 (p=0.8495 across various tumor entities; p=0.2455 when evaluating melanoma metastases only).

[0199] Finally, across brain metastases from various tumor entities, hGDF-15 levels and CD8 + and CD3 + We also analyzed whether there was an inverse correlation between the percentages of T cells. Figure 8 shows the CD8 levels in brain metastases from 168 (for CD3) or 169 (for CD8) cases from various tumor entities (melanoma, CRC, RCC, breast cancer, NSCLC, and SCLC). + and CD3 + The plot shows the GDF-15 score against the percentage of T cells. The plot was obtained as described above in the "Statistical Analysis" section. As shown in Figure 8, CD8 + A statistically significant inverse correlation (p=0.0311) was found between the percentage of cells and the GDF-15 score, as well as CD3 + A statistically significant inverse phase (p=0.0093) was observed between the percentage of cells and the GDF-15 score. Other markers (PD-L1, PD-1, FOXP3) also showed positive correlations with CD3 and CD8 T cell infiltration.

[0200] summary: The results above show not only an inverse correlation between hGDF-15 in metastasis and the percentage of T cells expressing the common T cell marker protein CD3, but also a correlation with CD8 in metastasis. + This also shows an inverse correlation with the percentage of T lymphocytes. (CD8) + The presence of T lymphocytes has been shown to be particularly necessary for tumor regression after immune checkpoint inhibition using anti-PD-1 antibodies, so this is noteworthy (Tumeh et al., Nature. November 27, 2014; 515(7528): pp. 568-71).

[0201] Therefore, according to the present invention, therapeutic inhibition of hGDF-15 is used to inhibit CD8 in solid tumors, including tumor metastases. + It can increase the percentage of T lymphocytes. CD8 in solid tumors + This increase in T lymphocytes can be used for the therapy of solid tumors. In an embodiment not limited to the present invention, a particularly preferred therapeutic combination is the combination of an hGDF-15 inhibitor with an immune checkpoint blocker. The advantageous effect of this combination is that inhibition of hGDF-15 leads to CD8 in solid tumors. + This increases the percentage of T lymphocytes, thereby leading to a synergistic therapeutic effect with immune checkpoint inhibition. Therefore, the present invention can be applied to all solid tumors, as described in the preferred embodiments.

[0202] (Example 3) GDF-15 reduces the adhesion of T cells to endothelial cells. The inventors then attempted to determine how hGDF-15 affects the percentage of T cells in solid tumors.

[0203] The steps necessary for the infiltration of T cells from the bloodstream into tumor tissue are that the T cells must first adhere to the endothelium, after which they can enter the tumor. To stimulate this step and to evaluate whether this step can be affected by hGDF-15, the inventors used a model system to measure the adhesion of T cells to human umbilical vein endothelial cells (HUVEC):

[0204] T cell flow / adhesion experiment (in HUVEC): Day 1: a. μ-Slide VI 0.4 (ibidi GmbH, Germany) was coated with fibronectin (100 μg / mL): 30 μL per loading port. They were incubated at 37 °C for 1 hour (or pre-coated slides were used). b. The fibronectin was aspirated and subsequently washed with HUVEC medium. c. HUVEC obtained from a 6-well plate were trypsinized (count: 2×10 5 cells / mL (total 2 mL)). d. They were washed and diluted to 1×10 6 cells / mL. e. 30 μL of HUVEC was applied into the loading ports of the μ-Slide VI and checked under the microscope. f. The μ-Slide VI was covered with a lid and incubated at 37 °C, 5% CO2i.

[0205] Day 2: a. HUVEC were activated with TNFα (10 ng / mL) and IFNγ (10 ng / mL) in channels 2 - 5 (see the following table): All medium was aspirated from the channels and replaced with pre-warmed medium containing cytokines.

[0206] Day 3: a. T cells were isolated (negative isolation of pan T cells). b. T cells were added to wells 1 (1×10 6The cells were pre-incubated for 1 hour in individual cells / mL. c. HUVEC was pre-incubated for 1 hour in channels 4 and 5 containing GDF-15 (100 ng / mL): all medium in the loading port was aspirated and both loading ports were filled with pre-warmed medium containing GDF15. d. The stage-top incubator adjacent to the microscope was preheated and a gas mix was connected (5% CO2, 16% O2, 79% N2). e. Prepared a 3×50mL syringe: iT cells (1×10 6 individual cells / mL): 1mL ii.T cell GDF15 (1×10 6 individual cells / mL): 1mL iii. Culture medium f. Connect syringe 1 to channel 1 (see the table below) and start the flow (0.5 dyn / cm 2 :0.38mL / min=22.8mL / h). gT cells were run for 3 minutes, during which time 10 fields of view were predefined on the microscope. h. Each field of view was video recorded for 5 seconds. i. The remaining channels were evaluated similarly to channel 1 (f~h) using T cell samples, as shown in the table below.

[0207] [Table 12]

[0208] Statistical analysis: We compared all data using the Mann-Whitney test for testing non-normally distributed data. A value of p<0.05 was considered statistically significant.

[0209] result: The experimental results are shown in Figure 9. This figure shows several adhesion parameters, namely Rolling T cell count per field per second reflects the morphology of moderate adhesion between aT cells and endothelial cells (9A; data obtained from channel 3 ("GDF-15") and channel 2 ("Control"). The rolling rate of T cells (measured at pixels per 0.2 seconds) (9B; data obtained from channel number 3 ("GDF-15") and channel number 2 ("control")) increases the restriction of adhesion between bT cells and endothelial cells, and c. Number of adherent cells per field of view (9C; data obtained from channel number 3 ("GDF-15") and channel number 2 ("Control"); and 9D) The analysis is shown below.

[0210] As can be seen in Figure 9C, treatment of T cells with hGDF-15 significantly reduced adhesion to endothelial cells, as reflected in the number of adherent cells per field of view. Similar results were obtained when adhesion was analyzed by counting the number of rolling T cells (Figure 9A). Furthermore, in line with the above results, treatment of T cells with hGDF-15 significantly increased the rolling speed, which indicates a reduction in the interaction time between T cells and endothelial cells, and also a reduction in adhesion between T cells and endothelial cells (Figure 9B).

[0211] The inventors then analyzed which cells are targeted by hGDF-15 (Figure 9D). In samples treated only with hGDF-15, a moderate reduction in T cell adhesion to endothelial cells (HUVECs) was observed. In contrast, when only T cells were treated with hGDF-15, or when both T cells and endothelial cells (HUVECs) were treated with hGDF-15, a strong reduction in T cell adhesion to endothelial cells (HUVECs) was observed. These results indicate that hGDF-15 acts on both T cells and endothelial cells, but they also indicate that the primary adhesion effect of hGDF-15 is on T cells.

[0212] Next, the inventors tested whether the effect of hGDF-15 secreted by tumor cells on T cell adhesion could be inhibited using an hGDF-15 inhibitor. To test this, the inventors used the melanoma cell line, UACC257, which secretes hGDF-15:

[0213] T cell flow / adhesion experiments (on HUVEC) in the presence or absence of GDF-15 in the tumor cell supernatant: Day 1: a. One μ-slide VI 0.4 (ibidi GmbH, Germany; hereinafter referred to as μ-slide) was coated with fibronectin (100 μg / mL): 30 μL per loading port. They were incubated at 37°C for 1 hour (or pre-coated slides were used). b. The fibronectin was aspirated and subsequently washed with HUVEC medium. c. HUVEC obtained from a 6-well plate was trypsinized (count: 2×10 5 cells / mL (total 2 mL)). d. They were washed and diluted to 1×10 6 cells / mL. e. 30 μL of HUVEC was applied into the loading ports of the μ-slide VI and checked under a microscope. f. The μ-slide VI was covered with a lid and incubated at 37°C, 5% CO2.

[0214] Day 2: a. HUVEC was activated with TNFα (10 ng / mL) and IFNγ (10 ng / mL) in channels 2 - 5 of the μ-slide (see the following table): All media were aspirated from the channels and replaced with pre-warmed medium containing cytokines.

[0215] Day 3: a. T cells were isolated (negative isolation of pan T cells). b. In parallel, 24 wells of a 96-well ELISA plate (Nunc maxisorb) were coated with 200 μL of anti-GDF-15 (10 μg / mL diluted in PBS), incubated for 45 minutes, and washed with PBS. c. To deplete GDF-15 from the supernatant obtained from the melanoma cell line UACC257, which secretes GDF-15 (data not shown), the supernatant was incubated in wells of an ELISA plate pre-coated with anti-GDF-15 (see b.). d. As a control, the supernatant of the melanoma cell line UACC257 was incubated in wells of an ELISA plate that was not pre-coated with anti-GDF-15 (see b.). e. In the supernatant of melanoma cell line UACC257 depleted of GDF-15 (see c.), or in the supernatant of melanoma cell line UACC257 containing GDF-15 (see d.), with GDF-15 (100 ng / mL) and without GDF-15, in a 12-well cell culture plate (1 × 10⁶ 6 T cells were pre-incubated for 1 hour in (individual cells / mL). f. The stage-top incubator adjacent to the microscope was preheated and a gas mix was connected (5% CO2, 16% O2, 79% N2). g. Prepared 4 × 2 mL tubes for the microfluidic flow system: iT cells (1×10 6 individual cells / mL): 1mL ii.T cell GDF15 (1×10 6 individual cells / mL): 1mL iii. T cells UACC257 (containing GDF-15) iv. T cells UACC257 with depleted GDF-15 h. Connect tube 1 to channel 1 (see the table below) and start the flow (0.4 mL / min = 24 mL / hour). iT cells were run for 3 minutes, during which time 5 fields of view were predefined on the microscope. j. Each field of view was video recorded for 5 seconds. k. The remaining channels were evaluated similarly to channel 1 (f~h) using T cell samples, as shown in the table below.

[0216] [Table 13]

[0217] result: The experimental results are shown in Figure 10A. This figure shows the analysis of rolling T cell count per field of view per second. Data were obtained from channel 1 (control T cells on unstimulated HUVEC as "negative control"), channel 2 (control T cells on stimulated HUVEC as "positive control"), channel 3 ("GDF-15"), channel 4 ("UACC257": T cells cultured in the supernatant of UACC257 melanoma cells containing secreted GDF-15), and channel 5 ("UACC257 + anti-hGDF-15": T cells cultured in the supernatant of UACC257 melanoma cells in which secreted GDF-15 was depleted using anti-GDF-15 B1-23).

[0218] Compared to T cells flowing over unstimulated HUVECs ("negative control"; median = 28 rolling cells per field of view per second), flowing T cells over stimulated HUVECs ("positive control") increased the number of rolling cells per field of view per second (median = 46). Treatment of T cells with hGDF-15 substantially reduced the number of rolling cells per field of view per second (median = 29). Furthermore, pre-incubation of T cells with the supernatant of the melanoma cell line UACC257, which secretes GDF-15, substantially reduced the number of rolling cells per field of view per second compared to T cells flowing over stimulated HUVECs ("positive control") (median = 36). In contrast, pre-incubation of T cells with the supernatant of melanoma cell line UACC257, in which secreted GDF-15 was depleted using anti-GDF-15 B1-23, resulted in a median number of rolling cells per field of view per second (45), comparable to T cells flowing on stimulated HUVEC (positive control).

[0219] Therefore, according to the present invention, the adhesion of T cells, including CD8+ cells, to endothelial cells can be increased using an hGDF-15 inhibitor, for example, in the treatment of solid tumors.

[0220] Furthermore, the above assay provides a simple in vitro system for determining whether a substance of interest is an hGDF-15 inhibitor.

[0221] summary: This example demonstrates that GDF-15, including GDF-15 secreted by tumor cells, reduces the adhesion of T cells to endothelial cells. Therefore, according to the present invention, treatment with an hGDF-15 inhibitor is used to reduce CD8 + This can increase the adhesion of T cells, including T cells, to endothelial cells. Such treatment can increase the adhesion of CD8 + This would increase the invasion of T cells, including T cells, from the bloodstream into solid tumors. CD8 in solid tumors resulting from such treatment with hGDF-15 inhibitors. + An increase in the percentage of T cells is advantageous for cancer therapy, such as cancer immunotherapy, and can be used in that. CD8 + T cell invasion into solid tumors and these CD8 cells in solid tumors + Since the presence of T cells is particularly advantageous for therapeutic approaches using immune checkpoint blockers, a particularly advantageous use of the hGDF-15 inhibitor of the present invention is its use in combination with immune checkpoint blockers.

[0222] Flow-adhesion assay including antibody neutralization with antibody H1L5 (humanized B1-23) and 01G06 and 03G05 (humanized anti-GDF-15 antibodies genetically modified according to the sequence of WO2014 / 100689). This experiment was conducted to further confirm the effects observed above, including the finding that the use of hGDF-15 inhibitors can increase T cell adhesion to endothelial cells or T cell rolling.

[0223] Experimental procedure: The flow / adhesion assay was performed in this embodiment as described above. T cells were pre-incubated with 100 ng / ml GDF-15 for 1 hour or with 100 ng / ml GDF-15 pre-incubated with 10 μg / ml antibody for 1 hour. The following anti-GDF-15 antibodies were used: H1L5 (humanized B1-23), 01G06, and 03G05 (humanized anti-GDF-15 antibodies genetically modified according to the sequence obtained from WO2014 / 100689).

[0224] result: The results are shown in Figure 10B. Compared to T cells flowed on unstimulated HUVECs (negative control), flowing T cells on stimulated HUVECs ("positive control") increased the number of rolling cells per field of view per 20 seconds. Treatment of T cells with hGDF-15 substantially reduced the number of rolling cells per field of view per 20 seconds. In contrast, pre-incubation of T cells using hGDF-15 pre-incubated with anti-GDF-15 antibodies H1L5 (humanized B1-23), O1G06, or O3G05 resulted in a substantially increased number of rolling cells per field of view per 20 seconds compared to samples without the addition of anti-GDF-15 antibodies. This effect was present for all anti-GDF-15 antibodies tested and was evident for the H1L5 (humanized B1-23) antibody, which almost completely reversed the effect of hGDF-15 on T cell rolling.

[0225] conclusion Therefore, according to the present invention, the adhesion of CD8+ cells (T cells) to endothelial cells, or the rolling of said CD8+ cells (T cells), can be increased using hGDF-15 inhibitors. The present invention allows hGDF-15 inhibitors to increase the percentage of CD8+ cells in solid tumors and to be used for the treatment of these cancers. These hGDF-15 inhibitors may be any known anti-GDF-15 antibodies, including, but are not limited to, antibodies H1L5 (humanized B1-23), O1G06, and O3G05.

[0226] (Example 4) Same MC38 tg hGDF-15+ Evaluation of the antitumor efficacy of test antibody immunotherapy combined with an adjuvant in tumor-carrying mice. Inhibition of human growth and differentiation factor (GDF)-15 is associated with improved response to immunotherapy, particularly in tumors with CD8 + To evaluate whether this could improve the response to T cell-dependent immunotherapy, mouse MC38 colon cancer cells were transfected to express human GDF-15 at levels similar to those found in human cancer cell lines. As assessed by enzyme-linked immunosorbent assay (ELISA, R&D Systems, mouse GDF-15 DuoSet ELISA), MC38 cells did not express detectable levels of mouse GDF-15 (detection limit: 7.81 pg / ml).

[0227] On day 0, 9-week-old female C57BL / 6J mice (Charles River Laboratories, BP 0109, F 69592 L'Arbresle, provided by Cedex) were anesthetized and 2 × 10⁶ mice were fed. 5 Individual colon MC38 tg hGDF-15 Cells were used for subcutaneous inoculation. On day 0, treatment with anti-GDF-15 antibody (20 mg / kg body weight, i.e., approximately 400 μg per mouse, in 100 μl of phosphate-buffered saline containing 0.5% bovine serum albumin) was initiated (approximately 6 hours after tumor cell inoculation) and repeated on days 3, 7, 10, 14, 17, and 21. On day 13, the tumors were 100 to 150 mm. 3 When the volume reached the intermediate level, the animals were randomized to different treatment groups, and each animal was intraperitoneally injected with an adjuvant (100 μg polyinosinate:polycytidylic acid (Poly-ICLC (Hiltonol®, Oncovir, Washington DC, USA)) and 50 μg InVivoMAb anti-mouse (m)CD40 antibody (clone FGK4.5 / FGK45)) in 50 μl of total volume of phosphate-buffered saline.

[0228] Poly-ICLC stimulates infection due to its structural similarity to double-stranded RNA present in some viruses that stimulates TLR3. Agonist anti-CD40 antibodies provide further signaling to antigen-presenting cells. "Licensing" of dendritic cells by CD40 stimulation leads to antigen-specific CD8 + It supports T cell activation. Therefore, adjuvant therapy works to induce tumor-specific immune cells in mice maintained under conditions free of specific pathogens (Yadav M et al., Nature. November 27, 2014; 515(7528): pp. 572-576).

[0229] Therefore, this adjuvant therapy stimulates immune cells in the tumor, particularly CD8 in the tumor. + This represents a model system for cancer immunotherapy that requires T cells. Therefore, treatment using hGDF-15 inhibitors such as anti-hGDF-15 antibodies is effective in stimulating the presence of CD8 cells in the tumor. + This model system is suitable for further confirming its collaboration with cancer immunotherapy, including cancer immunotherapy that requires T cells.

[0230] To summarize, the following animal groups (10 mice per group) were investigated: • Vehicle groups that do not use adjuvant immunotherapy • Group treated with anti-hGDF-15 antibody B1-23 without adjuvant immunotherapy • Vehicle groups using adjuvant immunotherapy • Group treated with anti-hGDF-15 antibody B1-23 using adjuvant immunotherapy

[0231] The size of the tumor was measured three times a week using calipers to measure its length and width.

[0232] The tumor volume is given by the formula V = length × width 2 2,000mm as calculated by / 2 3Mice were slaughtered when the condition exceeded a certain threshold. Similarly, mice were slaughtered when their condition deteriorated beyond generally acceptable limits for animal well-being (mass loss ≥ 15%, loss of mobility, exhausted behavior, poor fur condition).

[0233] In surviving mice, the presence of tumors was determined by physical examination up to 57 days after tumor inoculation. The results are shown in Figure 11.

[0234] Previous studies conducted by the inventors have shown that while cancer can be treated advantageously using anti-GDF-15 antibody alone, it does not completely eradicate tumors, i.e., it does not cure cancer. Similarly, in Figure 11, neither vehicle-treated mice nor mice treated with anti-hGDF-15 alone were cured. Treatment with an adjuvant (i.e., poly-ICLC and anti-CD40 antibody) cured 3 out of 10 mice. In particular, when the adjuvant treatment was combined with the treatment with anti-hGDF-15 antibody, 8 out of 10 mice were cured. Therefore, treatment with anti-hGDF-15 antibody strongly cooperates with treatment with an adjuvant.

[0235] Conclusion: The results obtained from this model system suggest that hGDF-15 inhibitors exert cytotoxic activity in cancer immunotherapy, particularly in tumor tissue, and that CD8 + Further confirmation is that it works in conjunction with cancer immunotherapy that requires the activation of immune cells such as T cells. The results also show that the use of the hGDF-15 inhibitor of the present invention triggers the activation of CD8 cells in cancer. + Further confirmation is provided that increasing the percentage of T cells can be advantageously utilized in cancer therapy.

[0236] Under selected experimental conditions, the mouse immune model system exhibits antigen-specific CD8 against rapidly growing cancers. +There is very little time to build up a T cell response. Therefore, adjuvants were used to further support the spontaneous immune response in the mouse system. In contrast, in human patients where cancer develops over a long period (e.g., several years), antigen-specific T cells directed at cancer antigens are usually already present at diagnosis; that is, induction of an immune response usually occurs even before cancer is diagnosed. In humans, these cancer antigen-specific CD8 + T cells are already present, but in mouse model systems they are present to a considerably lower degree than in humans. Therefore, according to the present invention, the use of the hGDF-15 inhibitor will be even more effective in humans compared to this mouse model system. Thus, the hGDF-15 inhibitor can be effectively used for the treatment of human cancer patients according to the present invention, for example, in CD8 in solid tumors. + These can increase the percentage of T cells, and include other cancer immunotherapies in humans, particularly cancer immunotherapy using immune checkpoint blockers such as anti-PD-1 and anti-PD-L1 antibodies, and CD8 in cancer. + It collaborates with cancer immunotherapy that requires T cells.

[0237] (Example 5) Serum levels of GDF-15 determine survival in melanoma patients treated with anti-PD-1. The study in this example was conducted to further verify, through further independent research, the results obtained in the study in Example 1, for example, the finding that hGDF-15 affects patients' responses to immune checkpoint blockers.

[0238] In relation to this study, the following terms were used: "Discontinued" = If further follow-up data could not be obtained, the patient was removed from the study cohort. "Event" = The patient died. "Survival" = The patient was alive during follow-up.

[0239] With a view to the future, patients with histologically confirmed melanoma from the Department of Dematology, University of Tubingen, Germany were identified in the Central Malignant Melanoma Registry (CMMR) database, which records patients from more than 60 dermatology centers throughout Germany. Ninety-nine patients were selected who (a) had recorded serum samples, (b) had available follow-up data, (c) had a history of or presence of local or distal metastasis at the time of blood collection, and (d) had undergone experimental treatment with anti-PD-1 antibodies. The purpose and methods of data collection by CMMR have been published in detail previously (Lasithiotakis, KG et al., Cancer / 107 / 1331~9, 2006). Data obtained for each patient included age, sex, date of last follow-up, and, where applicable, date and cause of death. All patients had given written informed consent to have their clinical data recorded by the CMMR registry. The Tubbingen Institutional Ethics Committee approved the study (Ethical Statement 125 / 2015BO2). Eligible patients were 18 years of age or older, had histologically or cytologically confirmed unresectable stage III or stage IV melanoma, were unsuitable for topical therapy, and had shown disease progression despite prior therapy in accordance with current guidelines. Patients with BRAFV600 variant tumors had received recommended first-line therapy, experimental therapy including BRAF or MEK inhibitor therapy, or both. Where applicable, patients received a minimum of two doses, 3 mg / kg once every three weeks, and prior ipilimumab therapy was considered a failure if disease progression was confirmed within 24 weeks of the last ipilimumab dose. Prior to administration of anti-PD-1, resolution or improvement of ipilimumab-related adverse events to grade 0-1 and a prednisone dose of 10 mg / day or less at least two weeks prior to the first dose of the study drug were required.Eligible patients had an Eastern Cooperative Oncology Group (ECOG) status of 0 or 1, disease measurable by the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1), and the following criteria: absolute neutrophil count (≥1500 cells per mL), platelets (≥100000 cells per mL), hemoglobin (≥90 g / L), serum creatinine (≤1.5 upper limit of normal [ULN]), serum total bilirubin (≤1.5 ULN or direct bilirubin ≤ULN for patients with total bilirubin concentration >1.5 ULN), aspartic acid and alanine aminotransferase (≤2.5 ULN or ≤5 ULN for patients with liver metastases), international normalized ratio or prothrombin time (≤1.5 ULN without anticoagulants), and activated partial thromboplastin time (≤1.5 ULN without anticoagulants). The patient had a washout period of at least four weeks between the last dose of the most recent therapy and the first dose of pembrolizumab or nivolumab.

[0240] Analysis of hGDF-15 serum levels by enzyme-linked immunosorbent assay (ELISA): Human GDF-15 serum levels were measured by enzyme-linked immunosorbent assay (ELISA).

[0241] Buffers and reagents: Buffered blocking solution: 1% BSA in PBS (Fraction V, pH 7.0, PAA, Pasting, Austria) Washing solution: PBS-Tween (0.05%) Standard: Human GDF-15 (stock concentration 120 μg / ml, manufactured by R&D Systems) Capture antibodies: Human GDF-15 MAb (clone 147627), manufactured by R&D Systems; Mouse IgG2B (catalog number MAB957, manufactured by R&D Systems, stock concentration 360 μg / ml) Detection antibodies: Human GDF-15 biotinylated affinity-purified PAb, goat IgG (catalog number BAF940, R&D Systems, stock concentration 9 μl / ml) Streptoavidin-HRP (Catalog No. DY998, manufactured by R&D Systems) Substrate solution: 10ml 0.1M NaOAc pH6.0+100μl TMB+2μl H2O2 Stop solution: 1M H2SO4

[0242] Analysis procedure: 1. Plate preparation: e. The capture antibody was diluted to a working concentration of 2 μg / ml in PBS. A 96-well microplate (Nunc maxisorp®) was immediately coated with 50 μl of diluted capture antibody per well, except for the outer rows (A and H). Rows A and H were filled with buffer to prevent sample evaporation during the experiment. The plate was gently tapped to ensure that the bottom of each well was completely covered. The plate was placed in a humidification chamber and incubated overnight at room temperature (RT). f. Each well was aspirated and washed three times with PBS-Tween (0.05%). g. 150 μl of blocking solution was added to each well, followed by incubation in RT for 1 hour. h. Each well was aspirated and washed three times with PBS-Tween (0.05%).

[0243] 2. Assay procedure: d. Standards were prepared. GDF-15 was diluted to a final concentration of 1 ng / ml with buffered blocking solution (4.17 μl GDF + 496 μl buffered blocking solution). Two 1:2 serial dilutions were prepared. e. A 1:20 ratio of two samples (6 μl + 114 μl buffered blocking solution) was prepared. 50 μl of diluted sample or standard was added to each well, followed by incubation in RT for 1 hour.

[0244] [Table 14]

[0245] i. Each well was aspirated and washed three times with PBS-Tween (0.05%). j. The detection antibody was diluted to a final concentration of 50 ng / ml (56 μl + 10 ml blocking buffer). 50 μl of the diluted detection antibody was added to each well, followed by incubation in RT for 1 hour. k. Each well was aspirated and washed three times with PBS-Tween (0.05%). l. Streptoavidin-HRP was diluted 1:200 (50 μl + 10 ml blocking buffer). 50 μl of the working dilution of streptavidin-HRP was added to each well, followed by incubation in RT for 20 minutes. m. Each well was aspirated and washed three times with PBS-Tween (0.05%). n. A substrate solution was prepared. 50 μL of substrate solution was added to each well, followed by incubation in RT for 20 minutes. o. 50 μL of stop solution was added to each well. The optical density of each well was immediately determined using a microplate reader set to p.450nm.

[0246] 3. Calculation of GDF-15 serum titer: d. Each sample / GDF-15 standard dilution was applied in two series. To determine the GDF-15 titer, the average of the two series was calculated and the background (sample without GDF-15) was subtracted. e. To construct a standard curve, values ​​obtained from the linear range were plotted on an XY-figure (X-axis: GDF-15 concentration, Y-axis: OD450), and linear curve fitting was applied. The GDF-15 serum titer of the test sample was calculated by interpolation from the OD450 values ​​of standard dilutions with known concentrations. f. To calculate the final GDF-15 concentration of each sample, the respective dilution factors were considered. Samples that yielded OD values ​​below or above the standard range were re-analyzed with appropriate dilutions.

[0247] Comparison with patient data on hGDF-15 serum levels: Next, the measured hGDF-15 serum levels were compared with patient response data obtained from the study.

[0248] Statistical correlation with patient data on hGDF-15 serum levels: data: The data analysis was based on a data file containing data from samples obtained from 99 patients, including column (variable) sample display, GDF-15 (ng / ml), days (to death or censoring), and progression (exponential variable of ongoing life).

[0249] Outcome variables (endpoints): a. Overall survival (time to death). This endpoint consists of an event metric for death derived from the data file (1=death / 0=survival), and the time to death or censoring (the last time the patient was known to be alive), corresponding to the variable "days".

[0250] The effectiveness of the treatment, for example, whether the patient was a responder or not (coded as 1=r).

[0251] Data analysis: For survival analysis, the follow-up time was defined as the period from the date of blood sampling to the last follow-up (i.e., the last information obtained from the patient) or death. All blood samples were collected within a date prior to treatment with anti-PD1 antibodies. For OS analysis, patients who were alive at the last follow-up were censored, and patients who had died were considered "events." Cumulative survival probabilities according to Kaplan-Meier were calculated with 95% confidence intervals (CIs) and compared using two-sided log-rank tests. The p-value for overall survival was calculated using two-sided log-rank tests. One model was fitted using a grouping variable based on GDF-15 as a categorical predictor (groups were <1.5 ng / ml (n=62), ≥1.5 ng / ml (n=37), or GDF-15 based on median splitting).low (n=49), GDF-15 high (n=50). The resulting Kaplan-Meier curves are shown in Figures 12 and 13, where censoring is indicated by a vertical line. Furthermore, the following tables include a case summary Table 9, patient survival data for patient groups with GDF-15 levels <1.5 ng / ml and ≥1.5 ng / ml (Tables 10 and 11), and an overall statistical comparison of patient groups with GDF-15 levels <1.5 ng / ml and ≥1.5 ng / ml (Table 12).

[0252] [Table 15]

[0253] [Table 16]

[0254] [Table 17]

[0255] [Table 18]

[0256] Results and conclusions: The above statistical results from this example further confirmed the results of Example 1. For example, the likelihood of response to treatment, as indicated by patient survival, was found to decrease significantly as patient serum hGDF-15 levels increased. For instance, Table 12 shows that survival differed significantly between the two patient groups with GDF-15 levels <1.5 ng / ml and ≥1.5 ng / ml, respectively, as evidenced by a significance level of 0.004. Similarly, Table 9 demonstrates that a higher percentage of patients (82.3%) survived in the group with GDF-15 levels <1.5 ng / ml, and Tables 10 and 11 and Figures 12 and 13 demonstrate that survival time was significantly longer for patients with GDF-15 levels <1.5 ng / ml compared to patients with GDF-15 levels ≥1.5 ng / ml.

[0257] Therefore, the results of this embodiment further confirm that hGDF-15 acts to negatively affect the patient response to immune checkpoint blocker therapy. Accordingly, according to the present invention, inhibitors of hGDF-15 would be useful in inhibiting the negative effect of hGDF-15 on the patient response to immune checkpoint blocker therapy, and in improving the patient response to immune checkpoint blocker therapy not only in melanoma but also in all other solid tumors mentioned herein.

[0258] (Example 6) In human non-small cell lung cancer (NSCLC) patients treated with anti-PD1 antibodies, median hGDF-15 serum levels were higher in patients with progressive disease compared to those showing a partial response. This example was conducted to further validate the results obtained in the study of Example 1, for example, the finding that hGDF-15 affects patient response to immune checkpoint blockers, in further independent studies in various solid tumors.

[0259] patient: NSCLC patients were treated with anti-PD1 antibodies according to the approved drug labeling for the anti-PD1 antibodies. The patients included those who had previously been treated with other cancer therapies. Due to the fact that complete responses are rarely observed in NSCLC patients, the patient group included patients who showed progressive disease and partial responses to PD-1 treatment, but did not include patients who showed complete responses to PD-1 treatment.

[0260] Serum sample: Serum samples were collected from patients prior to treatment with anti-PD1 antibodies.

[0261] Analysis of hGDF-15 serum levels by enzyme-linked immunosorbent assay (ELISA): The hGDF-15 serum levels in serum samples were analyzed by enzyme-linked immunosorbent assay (ELISA) as described in Example 1.

[0262] result: hGDF-15 serum levels were obtained from five patients who showed a partial response to anti-PD-1 therapy and from five patients who showed progressive disease to anti-PD-1 therapy. In particular, the median hGDF-15 serum level in patients with a partial response was 0.55 ng / ml, while the median hGDF-15 serum level in patients with progressive disease was 1.56 ng / ml. Therefore, the median hGDF-15 serum level in patients with progressive disease was approximately 2.8 times higher than in patients with a partial response.

[0263] Conclusion: The results of this embodiment further confirm that hGDF-15 levels are negatively correlated with patient response to immune checkpoint blockers. The results of this embodiment also further confirm that hGDF-15 acts to negatively affect patient response to treatment with immune checkpoint blockers such as PD-1. Therefore, according to the present invention, inhibitors of hGDF-15 would be useful in inhibiting the negative effect of hGDF-15 on patient response to treatment with immune checkpoint blockers, and in improving patient response to treatment with immune checkpoint blockers not only in melanoma but also in lung cancers such as NSCLC, and all other solid tumors mentioned herein.

[0264] (Example 7) hGDF-15 serum levels do not significantly correlate with tumor mutational load. Mutational load is a known positive prognostic factor for the response of cancer patients to immune checkpoint blockers. Generally, cancer cells have genomic mutations that produce cancer cell antigens that are specific to cancer cells and different from those of non-cancerous cells. High mutational loads lead to a large number of such cancer cell-specific antigens. In cancers with such a large number of cancer cell-specific antigens, stimulation of the immune response by immune checkpoint blockers is considered particularly effective because more cancer cell-specific antigens are available as target antigens for the immune response.

[0265] To further confirm that hGDF-15 is not simply a surrogate marker for tumor mutational load, and to further confirm that treatment with hGDF-15 inhibitors acts through a mechanism independent of tumor mutational load, hGDF-15 mRNA levels in cancer samples obtained from cancer patients were plotted against the number of somatic mutations identified in the cancer. Somatic mutations were determined using exome sequencing. Data were analyzed using the UZH web tool from University Hospital Zurich (Cheng PF et al.: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. September 16, 2015;145:w14183). The results are shown in Figure 14. Figure 14A shows a plot of cancer patient data obtained from the Cancer Genome Atlas (TGCA), which considers only patients with high-grade melanoma (the Cancer Genome Atlas is referenced in Cheng PF et al.: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. September 16, 2015;145:w14183). GDF-15 expression was evaluated by normalization using the RSEM ("RNA Seq by expectation maximization") software package (Li B and Dewey CN: RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. August 4, 2011;12:323. doi:10.1186 / 1471-2105-12-323). Figure 14B shows a plot of cancer patient data obtained from 40 additional metastatic melanoma patients from University Hospital Zurich, analyzed individually.

[0266] In particular, both Figures 14A and 14B show a p-value of 0.5, indicating that there is no significant correlation between the amount of mutations in cancer and the level of hGDF-15. These results further confirm that hGDF-15 is not simply a surrogate marker for tumor mutations, and that treatment with hGDF-15 inhibitors acts through mechanisms independent of tumor mutations.

[0267] (Example 8) CD8 in wild-type tumors or human GDF-15 (overexpressing) tumors + T cell infiltration In a pilot study using either wild-type or human GDF-15 (over)expressing MC38 colon cancer cells transplanted into the right flank of immunocompetent syngeneic mice C57BL / 6, GDF-15 overexpression was associated with reduced immune cell infiltration. Immunocytochemical images of CD8a in mice sacrificed at 29 days, either with wild-type tumors or tumors overexpressing transgenic (tg)hGDF15, are shown in Figure 15. As can be seen from the figure, wild-type tumors contained more CD8a-positive cells than tumors overexpressing transgenic (tg)hGDF15.

[0268] These results indicate that, according to the present invention, hGDF-15 is present in CD8 in solid tumors. + To reduce the percentage of T cells, or conversely, to use hGDF-15 inhibitors such as anti-GDF-15 antibodies to reduce CD8 in solid tumors in human patients + This further supports the finding that the percentage of T cells can be increased. [Industrial applicability]

[0269] The combinations, compositions, and kits of inhibitors of the present invention may be manufactured industrially in accordance with known standards for the manufacture of pharmaceutical formulations and sold as products for the claimed methods and uses (e.g., for treating cancer as defined herein). Thus, the present invention is industrially applicable.

[0270] [References] TIFF0007869820000019.tif227170TIFF0007869820000020.tif243168TIFF0007869820000021.tif227166TIFF0007869820000022.tif189169[Deposit Certificate] TIFF0007869820000023.tif238170TIFF0007869820000024.tif132146

Claims

1. CD8 in solid tumors in human patients + A pharmaceutical composition comprising an hGDF-15 inhibitor for use in a method for increasing the percentage of T cells, wherein the hGDF-15 inhibitor is administered to a human patient, the method is a method for treating cancer by cancer immunotherapy, the use is in combination with tumor-responsive T cells, and the composition is an antibody capable of binding to hGDF-15 or an hGDF-15-binding fragment thereof.

2. The composition according to claim 1, wherein the patient is a patient having a serum hGDF-15 level of at least 1.2 ng / ml prior to the initiation of administration of the hGDF-15 inhibitor.

3. The composition according to claim 1 or 2, wherein the cancer is selected from the group consisting of melanoma, colorectal cancer, prostate cancer, head and neck cancer, urothelial carcinoma, gastric cancer, pancreatic cancer, liver cancer, testicular cancer, ovarian cancer, endometrial cancer, cervical cancer, brain tumor, breast cancer, gastric cancer, renal cell carcinoma, Ewing's sarcoma, oral squamous cell carcinoma, non-small cell lung cancer, and small cell lung cancer.

4. The composition according to any one of claims 1 to 3, wherein the hGDF-15 inhibitor is a monoclonal antibody or an antigen-binding portion thereof capable of binding to hGDF-15, and the antibody or antigen-binding portion thereof comprises a heavy chain variable domain comprising a CDR1 region containing the amino acid sequence of SEQ ID NO: 3, a CDR2 region containing the amino acid sequence of SEQ ID NO: 4, and a CDR3 region containing the amino acid sequence of SEQ ID NO: 5, and also comprises a light chain variable domain comprising a CDR1 region containing the amino acid sequence of SEQ ID NO: 6, a CDR2 region containing the amino acid sequence ser-ala-ser, and a CDR3 region containing the amino acid sequence of SEQ ID NO:

7.

5. The composition according to any one of claims 1 to 4, wherein the method is a method for treating cancer metastasis.

6. hGDF-15 inhibitors, CD8 + This increases the adhesion of T cells to endothelial cells, thereby allowing CD8 to enter cancer cells from the bloodstream. + By increasing the invasion of T cells, CD8 in cancer + A composition according to any one of claims 1 to 5, which increases the percentage of T cells.

7. The aforementioned use is in combination with an immune checkpoint blocker, and the immune checkpoint blocker is i) A monoclonal antibody capable of binding to human PD-1 or a human PD-1 inhibitor which is the antigen-binding portion thereof, and ii) A monoclonal antibody capable of binding to human PD-L1, or a human PD-L1 inhibitor whose antigen-binding portion is such an antibody. A composition according to any one of claims 1 to 6, selected from one or more of the group consisting of the following.

8. A pharmaceutical composition comprising an hGDF-15 inhibitor for use in a method of treating solid tumors with an immune checkpoint blocker in a human patient, wherein the hGDF-15 inhibitor is administered to a human patient, the method is a method for cancer immunotherapy, and in the method, the hGDF-15 inhibitor is used in combination with tumor-responsive T cells, and the immune checkpoint blocker is i) A monoclonal antibody capable of binding to human PD-1 or a human PD-1 inhibitor which is the antigen-binding portion thereof, and ii) A monoclonal antibody capable of binding to human PD-L1, or a human PD-L1 inhibitor whose antigen-binding portion is such an antibody. Selected from one or more of the group consisting of, A composition wherein the hGDF-15 inhibitor is an antibody capable of binding to hGDF-15 or an hGDF-15-binding fragment thereof.

9. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use in a method for treating solid tumors in human patients, wherein the hGDF-15 inhibitor and the immune checkpoint blocker are administered to a human patient, the method being a method for cancer immunotherapy, wherein the hGDF-15 inhibitor is used in combination with tumor-responsive T cells, and the immune checkpoint blocker is i) A monoclonal antibody capable of binding to human PD-1 or a human PD-1 inhibitor which is the antigen-binding portion thereof, and ii) A monoclonal antibody capable of binding to human PD-L1, or a human PD-L1 inhibitor whose antigen-binding portion is such an antibody. Selected from one or more of the group consisting of, A combination wherein the hGDF-15 inhibitor is an antibody capable of binding to hGDF-15 or an hGDF-15-binding fragment thereof.

10. A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use according to claim 9, wherein the patient is as defined in claim 2, and / or the cancer is as defined in claim 3, and / or the hGDF-15 inhibitor is as defined in claim 4, or the composition according to claim 8.

11. hGDF-15 inhibitors affect CD8 in cancer cells. + A combination of an hGDF-15 inhibitor and an immune checkpoint blocker for use according to claim 9 or 10, or the composition according to claim 8 or 10, for increasing the percentage of T cells.

12. hGDF-15 inhibitors and for use in methods of treating solid tumors in human patients a) Polyinosinic acid: polycytidylic acid, b) Monoclonal anti-human CD40 antibody, c) Polyinosinic acid: Polycytidylic acid and monoclonal anti-human CD40 antibody Any one combination thereof, wherein in the method, the hGDF-15 inhibitor is used in combination with tumor-responsive T cells, A combination wherein the hGDF-15 inhibitor is an antibody capable of binding to hGDF-15 or an hGDF-15-binding fragment thereof.

13. comprising an immune checkpoint blocker, wherein the immune checkpoint blocker is i) A monoclonal antibody capable of binding to human PD-1 or a human PD-1 inhibitor which is the antigen-binding portion thereof, and ii) A monoclonal antibody capable of binding to human PD-L1, or a human PD-L1 inhibitor whose antigen-binding portion is such an antibody. A combination according to claim 12, selected from one or more of the group consisting of the following.

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