WO2019151712A1 - Procédé de prédiction de l'effet d'une immunothérapie sur un patient atteint d'un cancer - Google Patents

Procédé de prédiction de l'effet d'une immunothérapie sur un patient atteint d'un cancer Download PDF

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WO2019151712A1
WO2019151712A1 PCT/KR2019/001037 KR2019001037W WO2019151712A1 WO 2019151712 A1 WO2019151712 A1 WO 2019151712A1 KR 2019001037 W KR2019001037 W KR 2019001037W WO 2019151712 A1 WO2019151712 A1 WO 2019151712A1
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cancer
measured value
day
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cell number
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신의철
김경환
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한국과학기술원
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5044—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics involving specific cell types
    • G01N33/5047—Cells of the immune system
    • G01N33/505—Cells of the immune system involving T-cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5011—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing antineoplastic activity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1486—Counting the particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2500/00—Screening for compounds of potential therapeutic value
    • G01N2500/10—Screening for compounds of potential therapeutic value involving cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Definitions

  • the present invention relates to a method for predicting the effects of immunotherapy in cancer patients, and more particularly, to a method for predicting the effects of anti-PD-1 immune chemotherapy.
  • Immune anticancer drugs mean drugs that enhance the body's own immune system to fight against cancer. There is a fundamental difference from the concept of looking at conventional cancer treatment in that it inhibits cancer by the inherent power of the human body. Immune anticancer drugs make up for the shortcomings of conventional cancer therapies. If a first-generation chemotherapy agent directly attacks cancer cells, and a second-generation target anticancer agent attacks cancer-related genes, then an anti-cancer drug called third-generation anticancer drugs enhances immunity. It will cure cancer.
  • Anti-PD-1 antibody is a therapeutic agent that blocks the binding of PD-1, a protein on the surface of activated T cells (immune cells) and PD-L1, PD-L2, proteins on the surface of cancer cells .
  • PD-L1 and PD-L2 on the surface of cancer cells bind to PD-1, a protein on the surface of T cells, the function of T cells is reduced and the cancer cells cannot be attacked. Therefore, anti-PD-1 immunocancer agent adheres to PD-1 receptor of T cells and inhibits the binding of PD-L1, PD-L2 of cancer cells and PD-1 of T cells, thereby inhibiting T cell activity on cancer cells. And inhibit the avoidance of cancer cells.
  • Kitruda and Obdibo have been released as anti-PD-1 anticancer drugs, they are being used in cancer treatment in the medical field.However, there is no way to distinguish between the patients who are effective and the ineffective patients. Thus, the ineffective patient group is losing the cost and time for anti-PD-1 immunotherapy treatment.
  • the present invention relates to a method for predicting the effect of immunotherapy in cancer patients, and according to the method of the present invention, it is possible to distinguish between a patient group having an anti-PD-1 immunocancer drug and an ineffective patient group, It is expected to be used greatly.
  • immune anticancer agent refers to a therapeutic agent that helps to cure cancer by increasing the immunity of a patient instead of a drug or a drug that directly attacks cancer cells such as radiation or an anticancer agent.
  • T cells immune cells
  • the immune system in the body plays a role in activating the attack on cancer cells, it can be applied to a variety of cancers and can also reduce side effects such as indigestion, vomiting, leukopenia, and hair loss.
  • Various antibodies that block immune checkpoint proteins are currently being used or are being tested.
  • Anti-PD-1 antibodies include opdivo (nivolumab), keytruda (pembrolizumab), MEDI0680, pidizilumab, and anti-PD-L1 antibodies are tecentriq (atezolizumab). , Imfinzi (duvuralumab), Bavencio (Avelumab), MDX-1105, and the anti-CTLA-4 antibody has Yervoy (ipilimumab) (Topalian et al., 2015 Cancer Cell 27: 450-461; Alsaab et al., 2017 Front Pharmacol 23: 561).
  • PD-1 means PD-1 (also referred to as CD279) is a 55 KD receptor protein associated with the CD28 / CTLA4 co-stimulatory / inhibitory receptor family.
  • CD279 is a 55 KD receptor protein associated with the CD28 / CTLA4 co-stimulatory / inhibitory receptor family.
  • the extracellular domain consists of 1-167 amino acid residues and the cytoplasmic C-terminal tail comprises 191-288 residues, which are two hypothetical immune-modulating motifs, an immunoreceptor tyrosine based inhibitory motif (ITIM; Vivier et al. , 1997 Immunol Today 18: 286-291) and immunoreceptor tyrosine switch motifs (ITSM; Chemnitz et al., 2004 J Immunol 173: 945-954).
  • ITIM immunoreceptor tyrosine based inhibitory motif
  • ITSM immunoreceptor tyrosine switch motifs
  • PD-1 PD-1 protein-binding protein-1
  • T-cells T-cells
  • B-cells B-cells
  • monocytes NK cells
  • PD-1 expression is often associated with the activity of immune cells.
  • PHA phytohaemagglutinin
  • phorbol ester (12-O-tetradecanoylphorbol-13-acetate or TPA)
  • TPA phytohaemagglutinin
  • TPA phorbol ester
  • the expression of PD-1 is upward as shown in Western blot. Regulated (Vibharka et al., 1997 Exp Cell Res 232: 25-28).
  • TILs tumor-infiltrating lymphocytes
  • PD-1 ligand expression of tumor cells have been reported, and other types of tissues and organs such as lung (Konishi et al., 2004).
  • Clin Cancer Res 10: 5094-5100 liver (Shi et al., 2008 Int J Cancer 128: 887-896; Gao et al., 2009 Clin Cancer Res 15: 971-979), stomach (Wu et al., 2006 Acta Histochem 108: 19-24), kidneys (Thompson et al., 2004 Proc Natl Acad Sci 101: 17174-17179; Thompson et al., 2007 Clin Cancer Res 13: 1757-1761), breast (Ghebeh et al.
  • TILs tumor-infiltrating lymphocytes
  • Upregulation of PD-1 signaling leads to cancer proliferation of immune tolerance, as well as to viral infection and expansion in humans.
  • Pandemic liver infection viruses HBV and HCV induce overexpression of PD-1 ligand in hepatocytes and activate PD-1 signaling in effect T cells, causing T-cell depletion and tolerance to viral infection (Boni et al. , 2007 J Virol 81: 4215-4225; Golden-Mason et al., 2008 J Immunol 180: 3637-3641).
  • HIV infection frequently evades the human immune system with similar mechanisms.
  • Therapeutic regulation of PD-1 signaling by antagonistic molecules can restore immune cells from tolerance and can be reactivated to eliminate cancer and chronic viral infections (Blank et al., 2005 Cancer Immunol Immunother 54: 307-314; Okazaki et al., 2007 Int Immunol 19: 813-824).
  • the T cell number provides a method for predicting the effects of immuno-cancer drug treatment in cancer patients, characterized in that measuring the T cell number in T cell number, T cell activation secretion, and T cell activation degree, It provides a method characterized in that the T cell number is measured by Ki-67 expression value, the expression value is a gene expression value, or a protein expression value, the measured value of step (c) is (a And 2.8 times or more than the measured value of step), the method comprising the step of predicting that the anti-cancer drug treatment effect of the subject is high, the measured value of step (c) is the measured value of step (a) In the case of more than 2.8 times, it provides a method comprising the step of predicting that the prognosis of the subject is good, when the measured value of step (c) is less than 2.8 times the measured value of step (a), Immunity of Subject A method comprising the step of predicting that the cancer drug treatment effect is low, and when the measured value of step (c) is less than 2.8 times
  • the cancer may be breast cancer, cervical cancer, glioma, brain cancer, melanoma, lung cancer, bladder cancer, prostate cancer, leukemia, kidney cancer, liver cancer, colon cancer, pancreatic cancer, gastric cancer, gallbladder cancer, ovarian cancer, lymphoma, osteosarcoma, uterine cancer,
  • a method for predicting the effects of an anticancer drug in cancer patients of at least one selected from the group consisting of oral cancer, bronchial cancer, nasopharyngeal cancer, laryngeal cancer, skin cancer, blood cancer, thyroid cancer, parathyroid cancer, ureter cancer, adenocarcinoma, and thymic cancer To provide a method, wherein the cancer is lung cancer or thymic cancer.
  • the immuno-cancer agent provides an anti-PD-1 antibody, an anti-PD-L1 antibody, or an anti-CTLA-4 antibody.
  • step (c) provides a method characterized in that performed in 1 day to 14 days from step (b), the T cell number provides a method characterized in that measured by Ki-67 expression value
  • the method comprising the step of determining the immune anticancer drug candidates for cancer treatment, wherein the cancer is Breast cancer, cervical cancer, glioma, brain cancer, melanoma, lung cancer, bladder cancer, prostate cancer, leukemia, kidney cancer, liver cancer, colon cancer, pancreatic cancer, stomach cancer, gallbladder cancer,
  • FIG. 1 is a diagram showing a time diagram of drug administration and blood collection in an anti-PD-1 treated thymic epithelial tumor patient, according to an embodiment of the present invention.
  • 3A and 3B show the effects of anti-PD-1 treatment based on antigen specificity of T cells in an anti-PD-1 treated thymic epithelial tumor patient, according to an embodiment of the invention.
  • FIG. 5 is a diagram showing the predictive response of treatment response of 135 parameters after anti-PD-1 treatment in an anti-PD-1 treated thymic epithelial tumor patient according to an embodiment of the present invention.
  • Figure 6 is a change in Ki-67 expression in PD-1 + CD8 + T cells according to the treatment response of patients in anti-PD-1 treated thymic epithelial tumors according to an embodiment of the present invention (Ki-67 D7 / D0 ).
  • FIG. 7 shows disease control rate and disease progression-free survival rate of patients whose Ki-67 D7 / D0 cutoff values are divided based on 2.8 in anti-PD-1 treated thymic epithelial tumor patients according to an embodiment of the present invention. Is a diagram showing.
  • FIG. 9 shows PD-1 + CD8 + T cells before, after 1 week and after 3 weeks of anti-PD-1 treatment in anti-PD-1 treated non-small cell lung cancer patients according to an embodiment of the present invention. It is a figure which shows the frequency change of Ki-67 + .
  • Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) in the disease control control group were 90.9%, 75.0%, 93.8%, and 66.7%, respectively.
  • High sensitivity and negative predictiveness mean that Ki-67 D7 / D0 can accurately predict patients who are not expected to benefit from anti-PD-1 treatment.
  • Patients with a Ki-67 D7 / D0 cutoff value of less than 2.8 were found to have low disease control rates. These patients also had very low disease progression-free survival (PFS).
  • stage 4 non-small cell lung cancer who received pembrolizumab (pembrolizumab (200 mg / 3 weeks) or nivolumab (2 mg / Kg / 2 weeks)) from April 2016 to April 2017.
  • Blood was also collected from 29 patients with non-small cell lung cancer (NSCLC). Their data were used to verify the predictive markers found in the TET cohort. In some patients blood collection was performed on days 0, 7, and 21 to monitor changes in the immune response.
  • PBMCs Peripheral blood mononuclear cells
  • Tumor response was assessed every nine weeks by computed tomography or magnetic resonance imaging according to the solid tumor response evaluation criteria (RECIST, version 1.1.). Objective responses were categorized as complete or partial response, and Durable disease control was divided into partial or stable cancer patients lasting more than 6 months.
  • pembrolizumab or nivolumab human IgG4 agents to PD-1 expressing cells interferes with PD-1 staining in the sample after treatment
  • anti-human IgG4 Fc staining is performed with anti-PD-1 staining. It was. Live / dead cell identification was performed using a red-fluorescent reactive dye (Invitrogen, Carlsbad, Calif.), And intracellular staining for Ki-67, granzyme B, FoxP3, and CTLA-4 was performed using FoxP3 transcription factor staining. Buffer kit (eBioscience) was used.
  • Tumor antigen specific CD8 T cells were detected using PE-conjugated MHC I dextramer NY-ESO-1 157-165 (SLLMWITQV / HLA-A * 0201, Immudex, Copenhagen, Denmark) and CD8 T specific for HCMV Cells were detected using PE-conjugated MHC I pentamer HCMV pp65 495-504 (NLVPMVATV / HLA-A * 0201, Proimmune, Oxford, UK). All flow cytometry was performed with LSR II flow cytometer (BD Biosciences) and data analyzed with FlowJo software (Treestar, San Carlos, CA). Gate strategies of flow cytometry used in the present invention are shown in FIG. 2. Specifically, (a) shows the gating strategy of PD-1 + CD8 T cells, (b) multimer-positive CD8 T cells.
  • the change in the expression level of the marker was analyzed by converting the positive cell frequency of the 7-day sample based on the frequency of the 0-day sample.
  • Categorical variables were compared using chi-square test, or Fisher's exact test. Paired with unpaired values using Student's t-test and paired t-test for normal distribution continuous variables and Mann-Whitney U-test and Wilcoxon signed-rank test for nonnormal distribution The values were compared respectively.
  • One-way analysis of variance (ANOVA) analysis was used to compare two or more groups, and the Kruskal-Wallis test was used when the data were abnormally distributed. Correlation between the two parameters was evaluated using the Pearson correlation coefficient.
  • AUC area under curve
  • ROC receiver operating characteristic curve
  • TET patients underwent treatment with Pembrolizumab median 8 ranges (cycles 1-22). Six patients had an objective tumor response and the disease control control group consisted of 11 patients. Thirteen patients received pembrolizumab and 16 patients received nivolumab in a validation cohort of NSCLC patients. Eight of them presented an objective tumor response, and ten patients represented disease control controls. The median nivolumab or pembrolizumab administration cycle was 4 cycles (1-32 cycles).
  • tumor-specific NY-ESO-1 + CD8 + T cells showed a significant increase in the frequency of Ki-67 + and HLA-DR + CD38 + but without HCMV-specific pp65 + CD8 + T cells showed minimal increase (FIG. 3B).
  • FIG. 3B The results are shown in FIG. An increase in the frequency of Ki-67 + and HLA-DR + CD38 + was also observed in PD-1 + CD8 + T cells, and the results are shown in FIG. 4.
  • the results indicate that anti-PD-1 treatment activates PD-1 + CD8 + T cells, and this phenomenon increases and decreases over time after drug administration.
  • 135 derived from multicolor flow cytometry, including frequency and phenotypic markers of PD-1 + CD8 + T cells, CD8 + T cells, and CD4 + T cells. Dog parameters were analyzed together. The detailed analysis values are shown in Tables 4 and 5.
  • Ki-67 D7 / D0 is a progressive disease states ( The measurements were higher in the group of patients with partial response (PR) than those with progressive disease (PD).
  • Immune anticancer drugs mean drugs that enhance the body's own immune system to fight against cancer.
  • Anti-PD-1 antibody the most representative immune anticancer agent, is a therapeutic agent that blocks the binding of PD-1, a protein on the surface of activated T cells (immune cells) and PD-L1, PD-L2, proteins on the surface of cancer cells .
  • PD-1 a protein on the surface of activated T cells
  • PD-L1, PD-L2 proteins on the surface of cancer cells
  • the present invention relates to a method for predicting the effects of immunotherapy in cancer patients, and according to the method of the present invention, it is possible to distinguish between a patient group in which an anti-PD-1 immunocancer drug is effective and an ineffective patient group. It is expected to be used.

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Abstract

La présente invention concerne un procédé de prédiction de l'effet d'une immunothérapie sur des patients atteint d'un cancer et, plus spécifiquement, un procédé de prédiction de l'effet thérapeutique d'agents immunothérapeutiques anti-PD-1. Bien que le Keytruda et l'Opdivo, en tant qu'agents immunothérapeutiques anti-PD-1, qui sont les agents immunothérapeutiques contre le cancer les plus importants, aient été mis sur le marché et soient utilisés pour traiter le cancer dans le domaine médical, il n'y a aucune manière de distinguer à l'avance un groupe de patients chez qui les agents immunothérapeutiques anti-PD-1 auraient un effet d'un groupe de patients chez qui ils n'auraient pas d'effet; le groupe de patients ne connaissant aucun effet perdant ainsi du temps et de l'argent du fait du traitement par un agent immunothérapeutique anti-PD -1. Par conséquent, la présente invention concerne le procédé de prédiction des effets de l'immunothérapie sur des patients atteints d'un cancer, et selon le procédé de la présente invention, il est possible de faire la distinction à l'avance entre un groupe de patients chez qui les agents immunothérapeutiques anti-PD-1 ont un effet et un groupe de patients chez qui ils n'ont pas d'effet; la présente invention est ainsi censée être largement utilisée en médecine.
PCT/KR2019/001037 2018-02-05 2019-01-24 Procédé de prédiction de l'effet d'une immunothérapie sur un patient atteint d'un cancer WO2019151712A1 (fr)

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KR102182091B1 (ko) 2019-10-07 2020-11-23 한국과학기술원 면역항암제에 대한 저항성을 예측하는 방법 및 분석장치
KR102371903B1 (ko) * 2019-12-24 2022-03-08 주식회사 테라젠바이오 면역 항암 요법의 치료 반응에 관한 정보 제공 방법 및 이를 이용한 디바이스
KR102395580B1 (ko) * 2020-02-18 2022-05-10 (주)이노베이션바이오 동반진단용 바이오마커 조성물 및 이를 포함하는 동반진단용 키트
KR102428863B1 (ko) 2020-08-11 2022-08-03 서울대학교병원 자가면역 뇌염 발생 가능성 예측을 위한 정보 제공 방법
WO2022145879A1 (fr) * 2020-12-28 2022-07-07 연세대학교 산학협력단 Méthode de criblage d'inhibiteur de point de contrôle immunitaire

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