WO2020246846A1 - Tox-based method for predicting treatment response to cancer immunotherapy - Google Patents

Tox-based method for predicting treatment response to cancer immunotherapy Download PDF

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WO2020246846A1
WO2020246846A1 PCT/KR2020/007335 KR2020007335W WO2020246846A1 WO 2020246846 A1 WO2020246846 A1 WO 2020246846A1 KR 2020007335 W KR2020007335 W KR 2020007335W WO 2020246846 A1 WO2020246846 A1 WO 2020246846A1
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tox
cells
expression
expression level
predicting
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French (fr)
Korean (ko)
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이인석
김경수
하상준
박세연
김혜련
김가민
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연세대학교 산학협력단
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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer

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  • the present invention relates to a method for predicting a treatment response to an immune anticancer therapy, and more specifically, to a method for predicting the treatment response of an immune anticancer therapy to non-small cell lung cancer and melanoma by using a biomarker.
  • Lung cancer is one of the most common cancers in both sexes.
  • non small lung cancer (NSLC) is a type of carcinoma and refers to all epithelial lung cancers, not small lung cancer.
  • Such non-small cell lung cancer occupies a high proportion in the incidence of total lung cancer.
  • non-small cell lung cancer is divided into several sub-types according to the size, shape, and chemical composition of cancer cells, and representatively, adenocarcinoma, squamous cell carcinoma, and large cell carcinoma.
  • Adenocarcinoma is found in the outer region of the lung and tends to progress more slowly than other lung cancers, but shows a high tendency to metastasize at an early stage and also shows high radiation resistance.
  • Squamous cell carcinoma starts in the early version of the cells that make up the airway, and it has a high incidence mainly in smokers.
  • large-cell cancer can develop anywhere in the lung, and its treatment is still rising as a challenge since its progression is fast enough to be similar to that of small cell lung cancer.
  • Non-small cell lung cancer may include persistent cough, chest pain, weight loss, nail damage, joint pain, and shortness of breath.
  • non-small cell lung cancer progresses more slowly than other cancers, it hardly shows any symptoms at the beginning. Therefore, early detection and treatment of non-small cell lung cancer is difficult, and it is highly likely to be detected after metastasis to the whole body such as bone, liver, small intestine, and brain. Accordingly, when the diagnosis of non-small cell lung cancer, more than half of the patients are in a state that they cannot perform surgery, so early treatment is practically difficult.
  • prior surgery such as radical resection is performed, but only about 30% of cases can perform radical resection.
  • the majority of all patients who underwent radical resection appear to recur and die from more aggressive disease after surgical resection.
  • PD-1 programmed cell death-1
  • PD-L1 programmed cell death ligand-1
  • tumor PD-L1 expression by immunohistochemistry can be used as the best predictive biomarker for PD-1 blockade at present.
  • IHC immunohistochemistry
  • the accuracy of predicting the treatment response of PD-L1 dependent on tumor PD-L1 expression is not high enough to confirm drug efficacy. More specifically, PD-L1 expression negative patients may respond to PD-1 blockade, and PD-L1 expression positive patients may not respond to PD-1 blockade. Furthermore, some responding patients without PD-L1 may have similar duration of response if they are positive for PD-L1 in clinical trial Checkmate 057. Moreover, PD-L1 expression is dynamic and can change temporally and spatially. This change in PD-L1 expression may be adaptive immune resistance exerted by tumors.
  • the inventors of the present invention noted that the tumor induces a transcriptional network to exhaust T cells (T-cell exhaustion). Furthermore, due to T cell exhaustion, immune checkpint molecules such as PD-1, CTLA-4, LAG-3 and TIM-3 are expressed, and the functioning functions of T cells are gradually lost due to immune checkpoint molecules. I could recognize that I was in a state of dysfunction.
  • T cell exhaustion can be overcome and effective anti-tumor responses can be restored by blocking a transcription factor that promotes T cell exhaustion in the tumor microenvironment.
  • the pathogens of the present invention were able to discover TOX, a T cell-specific intra T cell transcription factor that promotes T cell exhaustion in the tumor microenvironment.
  • the inventors of the present invention suppress the expression of TOX in T cells specific to T cells existing in the tumor microenvironment, thereby expressing immune checkpoint molecules such as PD-1, CTLA-4 and TIM-3 expressed by T cell exhaustion. It could be recognized that it could be suppressed. Furthermore, it was found that it can improve the effect of immune chemotherapy and a method of predicting the treatment response to PD-1 blockade, an immune chemotherapy that suppresses these immune checkpoint molecules.
  • the inventors of the present invention improve the effectiveness of immuno-anticancer treatment systems and methods of predicting therapeutic response to PD-1 blockade, in particular, based on the expression of TOX in T cells specific to T cells in the tumor microenvironment. It has come to develop a treatment system that can be used.
  • the problem to be solved by the present invention is to measure the expression level of TOX with respect to a biological sample isolated from an individual, and based on this, immune anticancer therapy, in particular, configured to predict a therapeutic response to PD-1 blockade, It is to provide a method of predicting a treatment response to therapy,
  • Another problem to be solved by the present invention is to provide a kit for predicting a therapeutic response to an immune anticancer therapy, configured to include an agent measuring the expression level of TOX with respect to a biological sample isolated from an individual.
  • kits for predicting a therapeutic response to an immune anticancer therapy configured to include an agent for measuring the expression level of TOX in T cells specific to T cells present in a tumor microenvironment with respect to a biological sample.
  • measuring the expression level of TOX for a biological sample isolated from the subject and predicting the treatment response of the immunological anticancer therapy to the subject based on the measured expression level of TOX.
  • a method of predicting a treatment response to an immune anticancer therapy comprising it is provided.
  • measuring the expression level of TOX in a biological sample may be a step of measuring the expression level of TOX in T cells specific to T cells existing in the tumor microenvironment.
  • tumor microenvironment refers to a physicochemical environment in direct contact with a tumor, and due to the composition of the microenvironment, tumor generation, growth, and metastasis are smooth, and immune cells Can be avoided from Meanwhile, the tumor microenvironment composition may include factors such as normal epithelial cells, dendritic cells, cancer stem cells, lymphocytes, normal blood vessels, fibroblasts, vascular endothelial progenitor cells, granulocytes, and monocyte cancer cells, but is not limited thereto. Furthermore, the heterogeneity of cancer increases due to factors present in the microenvironment of these tumors.
  • the individual is a non-small cell lung cancer and melanoma suspected individual
  • the biological sample may include at least one selected from the group consisting of peripheral blood, serum, and plasma.
  • the immune anticancer therapy may preferably be an anti-PD-1 treatment, but is not limited thereto.
  • non-small cell lung cancer is a type of epithelial cancer and refers to all epithelial lung cancers other than small lung cancer.
  • anti-PD-1 treatment may be used, but is not limited thereto, and anti-CTLA-4 treatment, anti-CD28 treatment, anti-KIR treatment, anti-TCR treatment, anti-LAG- 3 treatment, anti TIM-3 treatment, anti TIGIT treatment, anti A2aR treatment, anti ICOS treatment, anti OX40 treatment, anti 4-1BB treatment, and anti-GITR treatment.
  • melanoma refers to a tumor of melanocytes, which is a cell originating from a neural tube.
  • anti-PD-1 treatment may be used, but is not limited thereto, and anti-CTLA-4 treatment, anti-CD28 treatment, anti-KIR treatment, anti-TCR treatment, anti-LAG-3 treatment , Anti TIM-3 treatment, anti TIGIT treatment, anti A2aR treatment, anti ICOS treatment, anti OX40 treatment, anti 4-1BB treatment, and anti-GITR treatment.
  • the immune anticancer therapy may be an anti-PD-1 treatment.
  • the anti-PD-1 therapy can be applied as an anti-cancer therapy to individuals suspected of various types of cancer.
  • individuals who want to predict the treatment response to anti-PD-1 treatment are non-small cell lung cancer, skin melanoma, head and neck cancer, stomach cancer, liver cancer, bone cancer, pancreatic cancer, skin cancer, uterine cancer, ovarian cancer, rectal cancer, and colon Cancer, colon cancer, breast cancer, uterine sarcoma, fallopian tube carcinoma, endometrial carcinoma, cervical carcinoma, vaginal carcinoma, vulvar carcinoma, esophageal cancer, laryngeal cancer, small intestine cancer, thyroid cancer, parathyroid cancer, soft tissue sarcoma, urethral cancer, penile cancer, prostate Cancer, chronic or acute leukemia, childhood solid tumor, differentiated lymphoma, bladder cancer, kidney cancer, renal cell carcinoma, renal pelvic carcinoma, primary central nervous system lymphom
  • the individual who wants to predict the response to the anti-PD-1 treatment of the present invention may be an individual having non-small cell lung cancer and melanoma, but is not limited thereto, and cancer responding to anti-PD-1 therapy It can be a variety of individuals.
  • anti-PD-1 treatment may be a therapy configured to block a mechanism in which T cells cannot attack cancer cells. More specifically, anti-PD-1 treatment may be based on blocking the binding of PD-L1, the surface proteins of cancer cells, and PD-L2, to PD-1, which is a protein on the surface of T cells. For example, when an immune anticancer agent binds to the PD-1 receptor of T cells, it is possible to inhibit the evasion function of T cells against cancer cells. Thus, in the present specification, “anti-PD-1 treatment” may be used in the same meaning as "PD-1 blocking".
  • the step of predicting a therapeutic response to an immune anticancer therapy comprises predicting a positive therapeutic response to an anti-PD-1 treatment when the measured expression level of TOX is less than a predetermined level.
  • a method of predicting a treatment response to an immune anti-cancer therapy can be provided.
  • kits for predicting a therapeutic response to an immune anticancer therapy comprising an agent measuring the expression of TOX in a biological sample isolated from an individual.
  • the formulation for measuring the expression level of TOX in a biological sample may be a formulation measuring the expression level of TOX in T cells specific for T cells present in the tumor microenvironment.
  • the present invention has an effect of providing a novel biomarker capable of predicting a treatment response to PD-1 blockade.
  • the present invention has the effect of predicting a treatment response to PD-1 blockade based on the expression of TOX. Accordingly, the present invention uses the expression of TOX to predict an early treatment response to PD-1 blockade for an individual, thereby providing information to quickly determine whether to proceed with anti-PD-1 treatment. have.
  • the present invention can distinguish between a patient who can be effective anti-PD-1 treatment and a patient who does not, so that it can be helpful to maximize the therapeutic effect when applied to the clinic.
  • FIG. 1 is an exemplary view showing a procedure of a method for predicting a treatment response to an immuno-cancer therapy according to an embodiment of the present invention.
  • 2A to 2G show results of confirming candidate genes related to T cell exhaustion using T cell-derived single cell transcriptome data.
  • 3A to 3C show the results of activity of immune checkpoint molecules according to the expression level of TOX in tumor tissues of patients with non-small cell lung cancer and melanoma.
  • 4A to 4D show the results of the activity of immune checkpoint molecules according to the expression level of TOX in tumor tissues of non-small cell lung cancer and melanoma mouse models.
  • FIG. 5 shows the expression results of immune checkpoint molecules in cancer tissue-derived T cells by knocking down TOX mRNA and the increase in the number of cells expressing IFN-gamma and TNF-alpha, which are inflammatory reaction derivatives.
  • 6A to 6C show comparison of the expression level of TOX by cell and the evaluation results of survival rate of patients with non-small cell lung cancer and melanoma according to the TOX level.
  • FIG. 1 is an exemplary view showing a procedure of a method for predicting a treatment response to an immuno-cancer therapy according to an embodiment of the present invention.
  • the expression level of TOX is measured for a biological sample isolated from an individual (S110), and the measured expression level of TOX It is configured to predict the treatment response of the immune chemotherapy for the individual based on (S120).
  • the measurement of the expression level of TOX in the step (S110) of measuring the expression level of TOX for a biological sample isolated from an individual is the expression of TOX in T cells specific to T cells in the tumor microenvironment. You can measure your level.
  • the expression level of TOX measured in the step (S120) of predicting a treatment response to an immune anticancer therapy is less than a predetermined level, it may be determined as a positive treatment response to the anti-PD-1 treatment.
  • the individual is a suspected non-small cell lung cancer individual and a suspected melanoma individual
  • the biological sample may include immune T cells and blood cells derived from cancer tissue.
  • the immune anticancer therapy may be an anti-PD-1 treatment. However, it is not limited thereto.
  • the method for predicting a treatment response provides information to early predict a treatment response to an individual immuno-anticancer therapy, particularly anti-PD-1, by measuring the levels of various markers. Can provide.
  • Example 1 Biomarker for predicting the therapeutic response of immune chemotherapy for non-small cell lung cancer and melanoma patients and target setting for therapeutic agent
  • 2A and 2B show the results of confirming a candidate gene related to T cell exhaustion using T cell-derived single cell transcriptome data.
  • CD8+ T cells distribution of CD8+ T cells according to the expression level of PDCD1 (PD-1 coding gene), which is a T cell exhaustion marker, is shown.
  • PDCD1 PD-1 coding gene
  • CD8+ T cells include heterogeneous cells in the tumor microenvironment.
  • CD8+ T cells are divided into high PDCD1 cells and low PDCD1 cell groups by the median expression level of PDCD1.
  • the expression levels of differentially expressed genes (DEGs) in high PDCD1 T cells and low PDCD1 T cell groups are shown in a violin plot.
  • the violin plot is a method of expressing the distribution density in the box and beard data in a symmetric way.
  • High PDCD1 T cells and low PDCD1 T cell groups have different shapes of violin plots, which may mean that the expression of differential expression genes is different according to the expression level of PDCD1.
  • FIG. 2A(d) a result of visualizing the distribution of CD8+ T cells according to the level of the differential expression gene in a two-dimensional map is shown. It appears that the highly differentially expressed T cells are distributed in the upper part of the distribution map.
  • differential expression genes with different distributions and patterns in the population divided according to the level of PDCD1 expression appear as potential candidate genes related to T cell exhaustion.
  • single-cell transcript data was obtained from tumor samples of melanoma and non-small cell lung cancer using single-cell RNA sequencing, and Wilcoxon rank sum test was performed.
  • the results of identifying the transcription factors associated with T cell exhaustion in T cells based on adjusted p ⁇ 0.05 are shown.
  • Transcription factors in melanoma were selected from IRF8, ETV1, TSC22D1, BATF, CALCOCO1, AATF, NFATC1, HCFC1, TOX, NAB1, ZNF638, PRDM1 and FAIM3, and transcription factors in non-small cell lung cancer were TOX, IVNS1ABP, SNRPBM.
  • IRF7 and BIN1 were selected.
  • TOX a common factor among transcription factors of melanoma and non-small cell lung cancer, was selected as the transcription factor involved in final T cell exhaustion.
  • FIG. 2C a two-dimensional map of the distribution according to the expression level of the immune checkpoint molecule gene and the transcription factor TOX in CD8+ T cells of a melanoma patient is shown.
  • the high-expression group and the low-expression group in which the immune checkpoint molecule genes PDCD1, HAVCR2, CTLA4 and TIGIT and the transcription factor TOX were highly expressed and low-expressed group showed different expression patterns. More specifically, it appears that the high expression group is distributed at the lower part of the map, and the low expression group is distributed at the upper part of the map.
  • the immune checkpoint molecule gene, the high PDCD1 T cells and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p ⁇ 0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is low.
  • the immune checkpoint molecule gene the groups of high PDCD1 T cells and low PDCD1 T cells had different shapes of violin plots, and the distribution between the groups showed significant differences (p ⁇ 0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is low.
  • the high and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p ⁇ 0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the expression level of TOX is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TOX expression level is low.
  • FIG. 2D (a) a two-dimensional map of the distribution according to the expression level of the immune checkpoint molecule gene and the transcription factor TOX in CD8+ T cells of a patient with non-small cell lung cancer is shown.
  • the high-expression group and the low-expression group in which the immune checkpoint molecule genes PDCD1, HAVCR2, CTLA4 and TIGIT and the transcription factor TOX were highly expressed and low-expressed group showed different expression patterns. More specifically, it appears that the high expression group is distributed at the upper part of the map, and the low expression group is distributed at the lower part of the map.
  • the immune checkpoint molecule gene, the high PDCD1 T cells and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p ⁇ 0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is low.
  • the immune checkpoint molecule gene the groups of high PDCD1 T cells and low PDCD1 T cells had different shapes of violin plots, and the distribution between the groups showed significant differences (p ⁇ 0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is low.
  • the high and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p ⁇ 0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the expression level of TOX is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TOX expression level is low.
  • FIG. 2e (a) shows the trajectory configured according to the state of the CD8 + T cells. Each is shown in three branches, and each branch appears to have a dominant cell type.
  • FIG. 2F the expression kinetics of immune checkpoint molecule genes and transcription factor TOX according to T cell status are shown.
  • the immune checkpoint molecule genes appear to have a tendency to increase in expression levels compared to when CD8+ T cells are exhausted.
  • FIG. 2G a result of a structural analysis of linking the states of the immune checkpoint molecule genes and the transcription factor TOX is shown.
  • the expression level of each immune checkpoint molecule gene showed a tendency to increase as T cells progressed from the running state to the exhausted state, and decreased as the T cell progressed from the running state to the memory state. This appears to be the same trend in the transcription factor TOX. Accordingly, it appears that transcription factor TOX and immune checkpoint molecule genes are associated with each other.
  • TOX a transcription factor in T cells present in the tumor microenvironment
  • the expression level of immune checkpoint molecule genes is related to exhaustion of T cells. It was confirmed that the expression level was also related.
  • the expression level of TOX in T cell-specific T cells existing in the tumor microenvironment can be used as a biomarker for predicting a therapeutic response to immuno-anticancer therapy according to various embodiments of the present invention.
  • TOX is also associated with the mechanism of immune checkpoint molecule genes, it can also be used as a therapeutic agent for lowering the expression of immune checkpoint molecules by using a targeted therapeutic agent that inhibits TOX.
  • Example 2 Expression of TOX according to expression of immune checkpoint molecule in tumor and method for predicting treatment response based thereon
  • 3A to 3C show the expression results of TOX according to the expression of immune checkpoint molecules in tumors of non-small cell lung cancer patients and squamous cell cancer patients.
  • 3A shows the results of analysis of tumor T cells of patients with non-small cell lung cancer and squamous cell cancer according to the expression of immune checkpoint molecules and TOX.
  • the expression of the immune checkpoint molecule when the expression of the immune checkpoint molecule is increased in the tumor of a patient with non-small cell lung cancer, the expression of TOX is shown to be increased. More specifically, the values of the first and third quadrants tend to increase proportionally. In addition, when the expression of the immune checkpoint molecule is increased in the tumor of the patient with squamous cell carcinoma, the expression of TOX appears to be increased. More specifically, the values of the first and third quadrants tend to increase proportionally.
  • 3B shows the results of the number of positive cells expressing TOX according to the expression of an immune checkpoint molecule in tumors of non-small cell lung cancer patients and squamous cell cancer patients.
  • 3C shows the expression of TOX according to the expression of immune checkpoint molecules PD-1 and TIM-3 in tumors of non-small cell lung cancer patients and squamous cell cancer patients.
  • FIG. 3C the results of analyzing tumor T cells of patients with non-small cell lung cancer and squamous cell cancer patients according to PD-1 expression and TIM-3 expression are shown.
  • the first quadrant region was classified as PD-1(+) positive-TIM-3(+) positive cells
  • the third quadrant region was classified as PD-1(-) negative-TIM-3(-) negative cells
  • the quadrant area was classified as PD-1(+) positive-TIM-3(-) negative cells.
  • the results shown in the histogram plot for TOX of cells classified according to the expression of PD-1 and TIM-3 are shown.
  • the fluorescence intensity for TOX is indicated in parentheses.
  • the red PD-1 positive-TIM-3 positive cell group had a large amount of TOX expression, and the fluorescence intensity was also the highest at 1577.
  • the red PD-1 positive-TIM-3 positive cell group had a large amount of TOX expression, and the fluorescence intensity was also the highest at 4970.
  • FIG. 3C (b) the results of TOX expression of cells classified according to PD-1 expression and TIM-3 expression are shown.
  • PD-1 positive-TIM-3 positive cells expressed significantly higher TOX than PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM-3 negative cells. Indicates the amount.
  • PD-1 positive-TIM-3 positive cells had significantly higher TOX than PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM-3 negative cells. It indicates the expression level.
  • 4A shows the results of analyzing tumor T cells of the MC37 mouse model according to PD-1 expression and TOX expression.
  • 4B shows the results of the number of cells expressing positive TOX according to the expression of PD-1 molecules in CT26, TC1 and LLC1 mouse models.
  • Figure 4c shows the expression of TOX according to the expression of PD-1 and TIM-3 in the tumor of the MC38 mouse model.
  • FIG. 4C the results of analyzing tumor T cells of the MC38 mouse model according to PD-1 expression and TIM-3 expression are shown.
  • the red quadrant area is classified as PD-1 positive-TIM-3 positive cells
  • the orange quadrant area is classified as PD-1 negative-TIM-3 negative cells
  • the blue quadrant area is classified as PD-1 negative-TIM-3 negative cells. They were classified as PD-1 positive-TIM-3 negative cells.
  • the cells classified according to the expression of PD-1 and TIM-3 are shown in the histogram plot for TOX.
  • the fluorescence intensity for TOX is indicated in parentheses. In the tumor of the MC38 mouse model, the red PD-1 positive-TIM-3 positive cell group had a large amount of TOX expression, and the fluorescence intensity was also the highest at 1048.
  • FIG. 4C (c) the results of TOX expression of cells classified according to PD-1 expression and TIM-3 expression are shown.
  • PD-1 positive-TIM-3 positive cells showed significantly higher TOX expression than PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM-3 negative cells.
  • PD-1 positive-TIM-3 positive cells are PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM in tumors of CT26, TC1 and LLC1 mouse models.
  • -3 shows a significantly higher expression of TOX than negative cells.
  • FIG. 5 shows the expression results of immune checkpoint molecules of cancer tissue-derived T cells by knocking down TOX mRNA.
  • FIG. 5 (a) the results of the analysis of the T cells knocked down TOX mRNA according to the expression of the immune checkpoint molecule and TOX is shown.
  • the expression of PD-1 when the expression of PD-1 is increased, the expression of TIGIT, TIM-3 and TOX appears to be increased. More specifically, the values of the first and third quadrants tend to increase proportionally.
  • the expression of TIGIT, TIM-3 and TOX did not increase as PD-1 expression increased.
  • the immune checkpoint molecule and the number of TOX-expressing cells in T cells and control T cells in which TOX mRNA was knocked down are shown.
  • Example 2 it appears that the expression of the transcription factor TOX and the expression of immune checkpoint molecules have a proportional relationship. That is, it was confirmed that immune checkpoint molecules were promoted by the expression of TOX. Accordingly, the expression level of TOX can predict the expression of conventional immune checkpoint molecules, and can predict a therapeutic response to an immune anticancer therapy according to various embodiments of the present invention.
  • Example 3 Anti-PD-1 treatment response prediction based on the expression level of TOX_Non-small cell lung cancer and melanoma
  • 6A shows the results of comparing the expression distribution of TOX in each cell derived from a tumor of a melanoma patient.
  • the distribution of TOX expression in individual cells derived from tumors of melanoma patients appears to be more expressed in T cells than in other immune cells or cancer cells.
  • 6B shows the results of evaluating the survival rate of patients with non-small cell lung cancer and melanoma according to the TOX level.
  • FIG. 6B (a) the evaluation results of prediction of anti-PD-1 treatment response according to the expression level of TOX in melanoma are shown.
  • FIG. 6C(a) the difference in anti-PD-1 treatment results of actual patients according to the expression level of TOX in melanoma is shown. Further referring to (b) and (c) of Figure 6c, the difference in anti-PD-1 treatment results of actual patients according to the level of expression of TOX in non-small cell lung cancer is shown. More specifically, in all three cases, patients who responded to anti-PD-1 treatment appeared to be more distributed when the expression level of TOX was low. In particular, according to the AUC analysis result of FIG. 6C (d), in all three cases including YCC, a cohort applied to various examples of the present invention, the distribution of the expression level of TOX between the responder and the non-responder group was significant. Appears to have a difference (AUC> 0.65).
  • Example 3 it may mean that the expression level of TOX in T cells-specific T cells may be an excellent marker in predicting anti-PD-1 treatment response. Furthermore, it may mean that the survival rate can be increased by inhibiting the expression of TOX in T cell-specific T cells. As a result, an inhibitor that suppresses the expression of TOX in T cell-specific T cells has an effect of increasing the survival rate.

Abstract

The present specification provides a method for predicting a treatment response to cancer immunotherapy, the method comprising the steps of: measuring an expression level of TOX with respect to a biological sample isolated from a subject; and predicting, on the basis of the measured expression level of TOX, a treatment response to cancer immunotherapy with respect to the subject.

Description

TOX에 기초한 면역 항암 요법에 대한 치료 반응 예측 방법TOX-based method for predicting treatment response to immunotherapy
본 발명은 면역 항암 요법에 대한 치료 반응 예측 방법에 관한 것으로, 보다 구체적으로 바이오 마커를 이용하여 비소세포성 폐암 및 흑색종에 대한 면역 항암 요법의 치료 반응을 예측하는 방법에 관한 것이The present invention relates to a method for predicting a treatment response to an immune anticancer therapy, and more specifically, to a method for predicting the treatment response of an immune anticancer therapy to non-small cell lung cancer and melanoma by using a biomarker.
폐암(lung cancer) 은 남녀 모두의 성별에서 흔히 발생하는 암 중 하나이다. 폐암 중에서 비소세포성 폐암(non small lung cancer, NSLC) 은 상피성 암(carcinoma) 의 일종으로 폐소성암(small lung cancer) 이 아닌 모든 상피성 폐암(epithelial lung cancer) 을 일컫는다. 이러한, 비소세포성 폐암은, 전체 폐암의 발병률에 있어서 높은 비율을 차지한다. Lung cancer is one of the most common cancers in both sexes. Among lung cancers, non small lung cancer (NSLC) is a type of carcinoma and refers to all epithelial lung cancers, not small lung cancer. Such non-small cell lung cancer occupies a high proportion in the incidence of total lung cancer.
한편, 비소세포성 폐암은 암세포의 크기, 모양 및 화학적 구성에 따라 몇 가지 하위 종류로 나뉘며, 대표적으로는 선암(adenocarcinoma), 편평상피암(squamous cell carcinoma), 대세포암(large cell carcinoma) 등이 있다. 선암은 폐의 바깥부위(outer region) 에서 발견되며 다른 폐암보다 천천히 진행되는 경향이 있으나, 초기에 높은 전이 경향을 보이고 또한 높은 방사선 저항성을 보인다. 편평상피암은 기도 (airway) 를 이루고 있는 세포의 초기 단계(early version) 에서 시작되며, 주로 흡연자에게서 높은 발병률을 보인다. 나아가, 대세포암은 폐의 어느 부위에서나 발병할 수 있으며, 그 진행속도가 소세포성 폐암(small cell lung cancer) 과 유사할 만큼 빠르기 때문에 그 치료는 현재까지도 난제로 떠오르고 있다.On the other hand, non-small cell lung cancer is divided into several sub-types according to the size, shape, and chemical composition of cancer cells, and representatively, adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. have. Adenocarcinoma is found in the outer region of the lung and tends to progress more slowly than other lung cancers, but shows a high tendency to metastasize at an early stage and also shows high radiation resistance. Squamous cell carcinoma starts in the early version of the cells that make up the airway, and it has a high incidence mainly in smokers. Furthermore, large-cell cancer can develop anywhere in the lung, and its treatment is still rising as a challenge since its progression is fast enough to be similar to that of small cell lung cancer.
이와 같은 비소세포성 폐암의 증상으로는 지속적인 기침, 흉부 통증, 체중감소, 손톱 손상, 관절 통증, 호흡의 단기화(shortness of breath) 등이 나타날 수 있다. 그러나, 비소세포성 폐암은 다른 암 보다 천천히 진행되기 때문에 초기에는 그 증상을 거의 보이지 않는다. 따라서, 비소세포성 폐암의 조기 발견 및 치료가 어려우며, 뼈, 간, 소장, 및 뇌 등 전신에 전이된 후에 발견할 가능성이 높다. 이에, 비소세포성 폐암의 진단 시 환자의 반수 이상이 수술을 할 수 없을 정도로 진행된 상태이므로 조기치료는 현실적으로 어렵다. 또한, 비소세포 암은 외과적 수술을 할 수 있을 만큼 진행되지 않은 경우라면 근치절제술과 같은 우선 수술을 시행하는데, 근치절제술을 시행할 수 있는 경우는 약 30 %에 불과한 실정이다. 나아가, 근치절제술을 시행한 전체환자들 대다수는 수술 절제 후에 보다 공격적인 질환으로 재발하여 사망하는 것으로 나타난다. Symptoms of such non-small cell lung cancer may include persistent cough, chest pain, weight loss, nail damage, joint pain, and shortness of breath. However, since non-small cell lung cancer progresses more slowly than other cancers, it hardly shows any symptoms at the beginning. Therefore, early detection and treatment of non-small cell lung cancer is difficult, and it is highly likely to be detected after metastasis to the whole body such as bone, liver, small intestine, and brain. Accordingly, when the diagnosis of non-small cell lung cancer, more than half of the patients are in a state that they cannot perform surgery, so early treatment is practically difficult. In addition, if the non-small cell carcinoma is not advanced enough to perform surgical operation, prior surgery such as radical resection is performed, but only about 30% of cases can perform radical resection. Furthermore, the majority of all patients who underwent radical resection appear to recur and die from more aggressive disease after surgical resection.
이러한 이유로 비소세포성 폐암의 조기 치료를 위해, 새로운 치료법의 개발, 나아가 기존의 치료법에 대한, 치료 반응을 예측할 수 있는 새로운 방법에 대한 개발이 지속적으로 요구되고 있는 실정이다. For this reason, for the early treatment of non-small cell lung cancer, the development of new treatments and further development of new methods for predicting treatment response to existing treatments is continuously required.
발명의 배경이 되는 기술은 본 발명에 대한 이해를 보다 용이하게 하기 위해 작성되었다. 발명의 배경이 되는 기술에 기재된 사항들이 선행기술로 존재한다고 인정하는 것으로 이해되어서는 안 된다.The technology that is the background of the present invention has been prepared to facilitate understanding of the present invention. It should not be understood as an admission that the matters described in the technology behind the invention exist as prior art.
비소세포성 폐암의 치료 방법으로 면역 관문 차단제(Immune checkpoint blockade) 의 이용이 제안되었다. 특히, 식품 의약청에 의해 승인된 PD-1(programmed cell death-1) / PD-L1(programmed cell death ligand-1) 차단은 비소세포성 폐암의 치료에 효과적인 것으로 나타났다. The use of an immune checkpoint blockade has been proposed as a treatment method for non-small cell lung cancer. In particular, PD-1 (programmed cell death-1) / PD-L1 (programmed cell death ligand-1) blockade approved by the Food and Drug Administration has been shown to be effective in the treatment of non-small cell lung cancer.
나아가, PD-L1 차단의 치료 반응 예측에 있어서, 면역 조직 화학 법(immunohistochemistry, IHC) 에 의한 종양 PD-L1 발현이 현재 PD-1 차단에 대한 최선의 예측 바이오 마커로 사용될 수 있다. 그러나, 종양 PD-L1 발현 의존적인 PD-L1의 치료 반응 예측의 정확도는 약물 효능을 확정할 정도로 높지 않다. 보다 구체적으로, PD-L1 발현 음성 환자가 PD-1 차단에 반응 할 수 있고, PD-L1 발현 양성 환자가 PD-1 차단에 반응하지 않을 수 있다. 나아가, PD-L1이 없는 일부 반응 환자는 임상시험 Checkmate 057에서 PD-L1 양성인 경우 비슷한 반응 지속 기간을 보일 수 있다. 더욱이, PD-L1 발현은 동적이며, 시간적 및 공간적으로 변화할 수 있다. 이러한 PD-L1 발현의 변화 현상은 종양에 의해 발휘되는 적응 면역 저항성일 수 있다.Furthermore, in predicting the therapeutic response of PD-L1 blockade, tumor PD-L1 expression by immunohistochemistry (IHC) can be used as the best predictive biomarker for PD-1 blockade at present. However, the accuracy of predicting the treatment response of PD-L1 dependent on tumor PD-L1 expression is not high enough to confirm drug efficacy. More specifically, PD-L1 expression negative patients may respond to PD-1 blockade, and PD-L1 expression positive patients may not respond to PD-1 blockade. Furthermore, some responding patients without PD-L1 may have similar duration of response if they are positive for PD-L1 in clinical trial Checkmate 057. Moreover, PD-L1 expression is dynamic and can change temporally and spatially. This change in PD-L1 expression may be adaptive immune resistance exerted by tumors.
한편, 본 발명의 발명자들은 종양이 전사 네트워크를 유도하여 T세포를 탈진(T-cell exhaustion)시킨다는 것에 주목하였다. 나아가, T세포 탈진으로 PD-1, CTLA-4, LAG-3 및 TIM-3과 같은 면역 관문 분자(immune checkpint molecule)들이 발현되고, 면역 관문 분자들로 인하여 T세포의 작용 기능들이 점차적으로 상실되는 기능 장애(dysfunction) 상태가 된다는 것을 인지할 수 있었다.On the other hand, the inventors of the present invention noted that the tumor induces a transcriptional network to exhaust T cells (T-cell exhaustion). Furthermore, due to T cell exhaustion, immune checkpint molecules such as PD-1, CTLA-4, LAG-3 and TIM-3 are expressed, and the functioning functions of T cells are gradually lost due to immune checkpoint molecules. I could recognize that I was in a state of dysfunction.
보다 구체적으로, 본 발명의 발명자들은 종양 미세환경(tumor microenvironment)에서 T세포 탈진을 촉진하는 전사인자를 차단함으로써 T세포 탈진이 극복되고 효과적인 항 종양 반응들이 복구될 수 있다는 것에 주목하였다. 그 결과, 본 발명의 발병자들은종양 미세환경에서 T세포 탈진을 촉진하는 T세포 특이적인 T세포 내 전사인자인 TOX를 발견할 수 있었다.More specifically, the inventors of the present invention have noted that T cell exhaustion can be overcome and effective anti-tumor responses can be restored by blocking a transcription factor that promotes T cell exhaustion in the tumor microenvironment. As a result, the pathogens of the present invention were able to discover TOX, a T cell-specific intra T cell transcription factor that promotes T cell exhaustion in the tumor microenvironment.
나아가, 본 발명의 발명자들은 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현을 억제함으로써 T세포 탈진으로 발현되는 PD-1, CTLA-4 및 TIM-3과 같은 면역 관문 분자의 발현을 억제시킬 수 있음을 인지할 수 있었다. 더 나아가, 이러한 면역 관문 분자들을 억제하는 면역 항암치료 인 PD-1 차단에 대한 치료 반응 예측 방법과 면역 항암 치료의 효과를 증진시킬 수 있음을 발견할 수 있었다.Furthermore, the inventors of the present invention suppress the expression of TOX in T cells specific to T cells existing in the tumor microenvironment, thereby expressing immune checkpoint molecules such as PD-1, CTLA-4 and TIM-3 expressed by T cell exhaustion. It could be recognized that it could be suppressed. Furthermore, it was found that it can improve the effect of immune chemotherapy and a method of predicting the treatment response to PD-1 blockade, an immune chemotherapy that suppresses these immune checkpoint molecules.
그 결과, 본 발명의 발명자들은 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현에 기초한 면역 항암 치료 시스템, 특히 PD-1 차단에 대한 치료 반응 예측 방법과 면역 항암 치료의 효과를 증진시킬 수 있는 치료 시스템을 개발하기에 이르렀다.As a result, the inventors of the present invention improve the effectiveness of immuno-anticancer treatment systems and methods of predicting therapeutic response to PD-1 blockade, in particular, based on the expression of TOX in T cells specific to T cells in the tumor microenvironment. It has come to develop a treatment system that can be used.
이에, 본 발명이 해결하고자 하는 과제는, 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하고, 이를 기초로 면역 항암 요법, 특히 PD-1 차단에 대한 치료 반응을 예측하도록 구성된, 면역 항암 요법에 대한 치료 반응 예측 방법을 제공하는 것이다,Accordingly, the problem to be solved by the present invention is to measure the expression level of TOX with respect to a biological sample isolated from an individual, and based on this, immune anticancer therapy, in particular, configured to predict a therapeutic response to PD-1 blockade, It is to provide a method of predicting a treatment response to therapy,
보다 바람직하게는, 생물학적 시료에 대하여 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정하는, 면역 항암 요법에 대한 치료 반응 예측 방법을 제공하는 것이다,More preferably, it is to provide a method for predicting a treatment response to immuno-anticancer therapy by measuring the expression level of T-cell-specific T-cells present in the tumor microenvironment with respect to a biological sample.
본 발명이 해결하고자 하는 또 다른 과제는, 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 제제를 포함하도록 구성된, 면역 항암 요법에 대한 치료 반응 예측용 키트를 제공하는 것이다.Another problem to be solved by the present invention is to provide a kit for predicting a therapeutic response to an immune anticancer therapy, configured to include an agent measuring the expression level of TOX with respect to a biological sample isolated from an individual.
보다 바람직하게는, 생물학적 시료에 대하여 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정하는 제제를 포함하도록 구성된, 면역 항암 요법에 대한 치료 반응 예측용 키트를 제공하는 것이다.More preferably, it is to provide a kit for predicting a therapeutic response to an immune anticancer therapy, configured to include an agent for measuring the expression level of TOX in T cells specific to T cells present in a tumor microenvironment with respect to a biological sample.
본 발명의 과제들은 이상에서 언급한 과제들로 제한되지 않으며, 언급되지 않은 또 다른 과제들은 아래의 기재로부터 당업자에게 명확하게 이해될 수 있을 것이다.The problems of the present invention are not limited to the problems mentioned above, and other problems that are not mentioned will be clearly understood by those skilled in the art from the following description.
본 발명의 일 실시예에 따르면, 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 단계, 및 측정된 TOX의 발현 수준을 기초로 개체에 대한 면역 항암 요법의 치료 반응을 예측하는 단계를 포함하는 면역 항암 요법에 대한 치료 반응 예측 방법이 제공된다.According to an embodiment of the present invention, measuring the expression level of TOX for a biological sample isolated from the subject, and predicting the treatment response of the immunological anticancer therapy to the subject based on the measured expression level of TOX. A method of predicting a treatment response to an immune anticancer therapy comprising it is provided.
본 발명의 특징에 따르면, 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 단계는 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정하는 단계일 수 있다.According to a feature of the present invention, measuring the expression level of TOX in a biological sample may be a step of measuring the expression level of TOX in T cells specific to T cells existing in the tumor microenvironment.
본 명세서에서 사용되는 용어 "종양 미세환경(tumor microenvironment)"은 종양에 직접 접해있는 물리화학적 주위환경을 의미하며, 미세환경의 조성으로 인하여 종양의 생성, 성장, 및 전이가 원활하게 되고, 면역세포로부터 회피할 수 있다. 한편, 종양 미세환경 조성물은 정상 상피세포, 수지상세포, 암 줄기세포, 림프구, 정상혈관, 섬유아세포, 혈관내피 전구세포, 과립구 및 단핵구 암세포 등의 인자들을 포함할 수 있으나, 이에 제한되는 것은 아니다. 나아가, 이러한 종양의 미세환경에 존재하는 인자들로 인하여 암의 이질성이 증가하게 된다.The term "tumor microenvironment" as used herein refers to a physicochemical environment in direct contact with a tumor, and due to the composition of the microenvironment, tumor generation, growth, and metastasis are smooth, and immune cells Can be avoided from Meanwhile, the tumor microenvironment composition may include factors such as normal epithelial cells, dendritic cells, cancer stem cells, lymphocytes, normal blood vessels, fibroblasts, vascular endothelial progenitor cells, granulocytes, and monocyte cancer cells, but is not limited thereto. Furthermore, the heterogeneity of cancer increases due to factors present in the microenvironment of these tumors.
본 발명의 다른 특징에 따르면, 개체는 비소세포성 폐암 및 흑색종 의심 개체이고, 생물학적 시료는 말초 혈액, 혈청 및 혈장으로 이루어진 그룹에서 선택된 적어도 하나를 포함할 수 있다. 나아가, 면역 항암 요법은 바람직하게 항 PD-1 치료일 수 있으나 이에 제한되는 것은 아니다.According to another feature of the present invention, the individual is a non-small cell lung cancer and melanoma suspected individual, and the biological sample may include at least one selected from the group consisting of peripheral blood, serum, and plasma. Furthermore, the immune anticancer therapy may preferably be an anti-PD-1 treatment, but is not limited thereto.
본 명세서에서 사용되는 용어 "비소세포성 폐암"은 상피성 암의 일종으로 폐소성암(small lung cancer) 이 아닌 모든 상피성 폐암을 의미한다. 한편, 이러한 비소세포성 폐암의 면역 항암 요법으로, 항 PD-1 치료가 이용될 수 있으나 이에 제한되는 것은 아니며, 항 CTLA-4 치료, 항 CD28 치료, 항 KIR 치료, 항 TCR 치료, 항 LAG-3 치료, 항 TIM-3 치료, 항 TIGIT 치료, 항 A2aR 치료, 항 ICOS 치료, 항 OX40 치료, 항 4-1BB 치료 및 항 GITR 치료로 구성된 그룹 중 선택된 적어도 하나를 포함할 수 있다. The term "non-small cell lung cancer" as used herein is a type of epithelial cancer and refers to all epithelial lung cancers other than small lung cancer. On the other hand, as an immune anti-cancer therapy for non-small cell lung cancer, anti-PD-1 treatment may be used, but is not limited thereto, and anti-CTLA-4 treatment, anti-CD28 treatment, anti-KIR treatment, anti-TCR treatment, anti-LAG- 3 treatment, anti TIM-3 treatment, anti TIGIT treatment, anti A2aR treatment, anti ICOS treatment, anti OX40 treatment, anti 4-1BB treatment, and anti-GITR treatment.
본 명세서에서 사용되는 용어 "흑색종"은 신경관으로부터 기원하는 세포인, 멜라닌세포의 종양을 의미한다. 한편, 이러한 흑색종의 면역 항암 요법으로, 항 PD-1 치료가 이용될 수 있으나 이에 제한되는 것은 아니며, 항 CTLA-4 치료, 항 CD28 치료, 항 KIR 치료, 항 TCR 치료, 항 LAG-3 치료, 항 TIM-3 치료, 항 TIGIT 치료, 항 A2aR 치료, 항 ICOS 치료, 항 OX40 치료, 항 4-1BB 치료 및 항 GITR 치료로 구성된 그룹 중 선택된 적어도 하나를 포함할 수 있다. The term "melanoma" as used herein refers to a tumor of melanocytes, which is a cell originating from a neural tube. On the other hand, as an immune anticancer therapy for melanoma, anti-PD-1 treatment may be used, but is not limited thereto, and anti-CTLA-4 treatment, anti-CD28 treatment, anti-KIR treatment, anti-TCR treatment, anti-LAG-3 treatment , Anti TIM-3 treatment, anti TIGIT treatment, anti A2aR treatment, anti ICOS treatment, anti OX40 treatment, anti 4-1BB treatment, and anti-GITR treatment.
본 발명의 또 다른 특징에 따르면, 면역 항암 요법은, 항 PD-1 치료일 수 있다. 이때, 항 PD-1 치료법은 다양한 종류의 암에 대한 의심 개체에 대하여 항암 요법으로서 적용될 수 있다. 예를 들어, 항 PD-1 치료에 대하여 치료 반응을 예측하고자 하는 개체는, 비소세포성 폐암, 피부 흑색종, 두경부암, 위암, 간암, 골암, 췌장암, 피부암, 자궁암, 난소암, 직장암, 대장암, 결장암, 유방암, 자궁 육종, 나팔관 암종, 자궁내막 암종, 자궁경부 암종, 질 암종, 외음부 암종, 식도암, 후두 암, 소장암, 갑상선암, 부갑상선암, 연조직의 육종, 요도암, 음경암, 전립선암, 만성 또는 급성 백혈병, 유년기의 고상 종양, 분화 림프종, 방광암, 신장암, 신장 세포 암종, 신장 골반 암종, 제 1 중추신경계 림프종, 척수축 종양, 뇌간 신경교종 또는 뇌하수체 선종을 갖는 개체일 수 있다. 바람직하게, 본원 발명의 항 PD-1 치료에 대한 반응을 예측하고자 하는 개체는, 비소세포성 폐암 및 흑색종을 갖는 개체일 수 있으나, 이에 제한되지 않고 항 PD-1 치료 요법에 반응하는 암을 갖는 다양한 개체일 수 있다. According to another feature of the present invention, the immune anticancer therapy may be an anti-PD-1 treatment. At this time, the anti-PD-1 therapy can be applied as an anti-cancer therapy to individuals suspected of various types of cancer. For example, individuals who want to predict the treatment response to anti-PD-1 treatment are non-small cell lung cancer, skin melanoma, head and neck cancer, stomach cancer, liver cancer, bone cancer, pancreatic cancer, skin cancer, uterine cancer, ovarian cancer, rectal cancer, and colon Cancer, colon cancer, breast cancer, uterine sarcoma, fallopian tube carcinoma, endometrial carcinoma, cervical carcinoma, vaginal carcinoma, vulvar carcinoma, esophageal cancer, laryngeal cancer, small intestine cancer, thyroid cancer, parathyroid cancer, soft tissue sarcoma, urethral cancer, penile cancer, prostate Cancer, chronic or acute leukemia, childhood solid tumor, differentiated lymphoma, bladder cancer, kidney cancer, renal cell carcinoma, renal pelvic carcinoma, primary central nervous system lymphoma, spinal contraction tumor, brain stem glioma, or pituitary adenoma. . Preferably, the individual who wants to predict the response to the anti-PD-1 treatment of the present invention may be an individual having non-small cell lung cancer and melanoma, but is not limited thereto, and cancer responding to anti-PD-1 therapy It can be a variety of individuals.
본 명세서에서 사용되는 용어 "항 PD-1 치료"는, T세포가 암세포를 공격하지 못하는 기전을 차단하도록 구성된 치료법일 수 있다. 보다 구체적으로, 항 PD-1 치료는, 암세포의 표면 단백질인 PD-L1, 및 PD-L2가 T세포의 표면에 있는 단백질인 PD-1과 결합하는 것을 차단하는 것에 기초할 수 있다. 예를 들어, 면역 항암제가 T세포의 PD-1 수용체에 결합하면, T세포의 암세포에 대한 회피 기능을 억제할 수 있다. 이에, 본 명세서에서 "항 PD-1 치료"는 "PD-1 차단"과 동일한 의미로 이용될 수 있다.As used herein, the term "anti-PD-1 treatment" may be a therapy configured to block a mechanism in which T cells cannot attack cancer cells. More specifically, anti-PD-1 treatment may be based on blocking the binding of PD-L1, the surface proteins of cancer cells, and PD-L2, to PD-1, which is a protein on the surface of T cells. For example, when an immune anticancer agent binds to the PD-1 receptor of T cells, it is possible to inhibit the evasion function of T cells against cancer cells. Thus, in the present specification, "anti-PD-1 treatment" may be used in the same meaning as "PD-1 blocking".
본 발명의 다양한 특징에 따르면, 면역 항암 요법에 대한 치료 반응을 예측하는 단계는, 측정된 TOX의 발현 수준이 미리 결정된 수준 미만일 경우 항 PD-1 치료에 대한 치료 반응 양성으로 예측하는 단계를 포함하는 면역 항암 요법에 대한 치료 반응 예측 방법이 제공될 수 있다.According to various features of the present invention, the step of predicting a therapeutic response to an immune anticancer therapy comprises predicting a positive therapeutic response to an anti-PD-1 treatment when the measured expression level of TOX is less than a predetermined level. A method of predicting a treatment response to an immune anti-cancer therapy can be provided.
본 발명의 일 실시예에 따르면, 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현을 측정하는 제제를 포함하는, 면역 항암 요법에 대한 치료 반응 예측용 키트가 제공된다.According to an embodiment of the present invention, there is provided a kit for predicting a therapeutic response to an immune anticancer therapy, comprising an agent measuring the expression of TOX in a biological sample isolated from an individual.
본 발명의 특징에 따르면, 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 제제는 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정하는 제제일 수 있다.According to a feature of the present invention, the formulation for measuring the expression level of TOX in a biological sample may be a formulation measuring the expression level of TOX in T cells specific for T cells present in the tumor microenvironment.
이하, 실시예를 통하여 본 발명을 보다 상세히 설명한다. 다만, 이들 실시예는 본 발명을 예시적으로 설명하기 위한 것에 불과하므로 본 발명의 범위가 이들 실시예에 의해 한정되는 것으로 해석되어서는 아니 된다.Hereinafter, the present invention will be described in more detail through examples. However, these examples are for illustrative purposes only, and the scope of the present invention should not be construed as being limited by these examples.
본 발명은, PD-1 차단에 대한 치료 반응을 예측할 수 있는 새로운 바이오 마커를 제공할 수 있는 효과가 있다. The present invention has an effect of providing a novel biomarker capable of predicting a treatment response to PD-1 blockade.
보다 구체적으로, 본 발명은 TOX의 발현을 기초로 PD-1 차단에 대한 치료 반응을 예측할 수 있는 효과가 있다. 이에, 본 발명은 TOX의 발현을 이용하여, 개체에 대한 PD-1 차단에 대한 조기 치료 반응을 예측함에 따라, 항 PD-1 치료에 대한 진행 여부를 빠르게 결정하도록 정보를 제공할 수 있는 효과가 있다.More specifically, the present invention has the effect of predicting a treatment response to PD-1 blockade based on the expression of TOX. Accordingly, the present invention uses the expression of TOX to predict an early treatment response to PD-1 blockade for an individual, thereby providing information to quickly determine whether to proceed with anti-PD-1 treatment. have.
나아가 본 발명은, 항 PD-1 치료가 효과적일 수 있는 환자와 그렇지 않은 환자를 구별할 수 있어, 임상에 적용될 경우 치료 효과를 극대화하는 데 도움이 될 수 있다.Furthermore, the present invention can distinguish between a patient who can be effective anti-PD-1 treatment and a patient who does not, so that it can be helpful to maximize the therapeutic effect when applied to the clinic.
본 발명에 따른 효과는 이상에서 예시된 내용에 의해 제한되지 않으며, 더욱 다양한 효과들이 본 명세서 내에 포함되어 있다.The effects according to the present invention are not limited by the contents exemplified above, and more various effects are included in the present specification.
도 1은 본 발명의 일 실시예에 따른 면역 항암 요법에 대한 치료 반응 예측 방법의 절차를 예시적으로 도시한 것이다.1 is an exemplary view showing a procedure of a method for predicting a treatment response to an immuno-cancer therapy according to an embodiment of the present invention.
도 2a 내지 2g는 T세포 탈진과 관련된 후보 유전자를 T세포 유래 단세포 전사체 데이터를 이용하여 확인하는 결과를 도시한 것이다.2A to 2G show results of confirming candidate genes related to T cell exhaustion using T cell-derived single cell transcriptome data.
도 3a 내지 3c는 비소세포성 폐암 및 흑색 종 환자들의 종양 조직에서 TOX의 발현 수준에 따른 면역 관문 분자들의 활성 결과를 도시한 것이다.3A to 3C show the results of activity of immune checkpoint molecules according to the expression level of TOX in tumor tissues of patients with non-small cell lung cancer and melanoma.
도 4a 내지 4d는 비소세포성 폐암 및 흑색종 마우스 모델의 종양 조직에서 TOX의 발현 수준에 따른 면역 관문 분자들의 활성 결과를 도시한 것이다.4A to 4D show the results of the activity of immune checkpoint molecules according to the expression level of TOX in tumor tissues of non-small cell lung cancer and melanoma mouse models.
도 5는 TOX mRNA를 넉다운(Knockdown)한 암조직 유래 T세포의 면역 관문 분자들의 발현 결과와 이에 따른 염증반응 유도체인 IFN-gamma와 TNF-alpha를 발현하는 세포수의 증가를 도시한 것이다.FIG. 5 shows the expression results of immune checkpoint molecules in cancer tissue-derived T cells by knocking down TOX mRNA and the increase in the number of cells expressing IFN-gamma and TNF-alpha, which are inflammatory reaction derivatives.
도 6a 내지 6c는 세포별 TOX의 발현 수준 비교와 TOX 수준에 따른 비소세포성 폐암 및 흑색종 환자의 생존률 평가 결과를 도시한 것이다.6A to 6C show comparison of the expression level of TOX by cell and the evaluation results of survival rate of patients with non-small cell lung cancer and melanoma according to the TOX level.
본 발명의 이점 및 특징, 그리고 그것들을 달성하는 방법은 첨부되는 도면과 함께 상세하게 후술되어 있는 실시예들을 참조하면 명확해질 것이다. 그러나, 본 발명은 이하에서 개시되는 실시예들에 한정되는 것이 아니라 서로 다른 다양한 형태로 구현될 것이며, 단지 본 실시예들은 본 발명의 개시가 완전하도록 하며, 본 발명이 속하는 기술분야에서 통상의 지식을 가진 자에게 발명의 범주를 완전하게 알려주기 위해 제공되는 것이며, 본 발명은 청구항의 범주에 의해 정의될 뿐이다. Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in a variety of different forms, only these embodiments make the disclosure of the present invention complete, and common knowledge in the technical field to which the present invention pertains. It is provided to completely inform the scope of the invention to those who have, and the invention is only defined by the scope of the claims.
이하에서는 도 1을 참조하여, 본 발명의 일 실시예에 따른 면역 항암 요법의 치료 반응 예측 방법의 절차에 대하여 구체적으로 설명한다.Hereinafter, a procedure of a method for predicting a treatment response of an immune anticancer therapy according to an embodiment of the present invention will be described in detail with reference to FIG. 1.
도 1은 본 발명의 일 실시예에 따른 면역 항암 요법에 대한 치료 반응 예측 방법의 절차를 예시적으로 도시한 것이다.1 is an exemplary view showing a procedure of a method for predicting a treatment response to an immuno-cancer therapy according to an embodiment of the present invention.
도 1을 참조하면, 본 발명의 일 실시예에 따른 면역 항암 요법에 대한 치료 반응 예측 방법은 먼저 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하고(S110), 측정된 TOX의 발현 수준을 기초로 개체에 대한 면역 항암 요법의 치료 반응을 예측하도록 구성된다(S120).Referring to FIG. 1, in the method for predicting a treatment response to an immunological anticancer therapy according to an embodiment of the present invention, first, the expression level of TOX is measured for a biological sample isolated from an individual (S110), and the measured expression level of TOX It is configured to predict the treatment response of the immune chemotherapy for the individual based on (S120).
본 발명의 특징에 따르면, 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 단계(S110)에서 TOX의 발현 수준의 측정은 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정할 수 있다.According to a feature of the present invention, the measurement of the expression level of TOX in the step (S110) of measuring the expression level of TOX for a biological sample isolated from an individual is the expression of TOX in T cells specific to T cells in the tumor microenvironment. You can measure your level.
본 발명의 다른 특징에 따르면, 면역 항암 요법에 대한 치료 반응을 예측하는 단계(S120)에서 측정된 TOX의 발현 수준이 미리 결정된 수준 미만일 경우 항 PD-1 치료에 대한 치료 반응 양성으로 결정될 수 있다.According to another feature of the present invention, when the expression level of TOX measured in the step (S120) of predicting a treatment response to an immune anticancer therapy is less than a predetermined level, it may be determined as a positive treatment response to the anti-PD-1 treatment.
본 발명의 또 다른 특징에 따르면, 개체는 비소세포성 폐암 의심 개체 및 흑색종 의심 개체이고, 생물학적 시료는, 암조직에 유래된 면역 T 세포, 혈액 세포를 포함할 수 있다. 나아가, 면역 항암 요법은 항 PD-1 치료일 수 있다. 그러나, 이에 제한되는 것은 아니다.According to another feature of the present invention, the individual is a suspected non-small cell lung cancer individual and a suspected melanoma individual, and the biological sample may include immune T cells and blood cells derived from cancer tissue. Furthermore, the immune anticancer therapy may be an anti-PD-1 treatment. However, it is not limited thereto.
이상의 절차에 따라, 본 발명의 일 실시예에 따른 치료 반응 예측 방법은, 다양한 마커의 수준을 측정함으로써 개체에 대한 면역 항암 요법, 특히 항 PD-1에 대한 치료 반응을 조기에 예측할 수 있도록 정보를 제공할 수 있다.According to the above procedure, the method for predicting a treatment response according to an embodiment of the present invention provides information to early predict a treatment response to an individual immuno-anticancer therapy, particularly anti-PD-1, by measuring the levels of various markers. Can provide.
이하에서는 실시예 1 내지 실시예 3을 참조하여, 본 발명의 다양한 실시예에 따른 항 PD-1 치료 반응 예측 방법에서 이용되는 TOX의 발현 수준과, 이를 이용한 치료 반응 예측 방법에 대하여 설명한다. Hereinafter, with reference to Examples 1 to 3, the expression level of TOX used in the anti-PD-1 treatment response prediction method according to various embodiments of the present invention and a treatment response prediction method using the same will be described.
실시예 1: 비소세포성 폐암 및 흑색종 환자에 대한 면역 항암 치료의 치료 반응을 예측하기 위한 바이오 마커와 치료제를 위한 표적 설정Example 1: Biomarker for predicting the therapeutic response of immune chemotherapy for non-small cell lung cancer and melanoma patients and target setting for therapeutic agent
이하에서는, 도 2a 내지 2g를 참조하여, 본 발명의 일 실시예에 따른 항 PD-1 치료 반응을 예측하는 방법에 이용되는 바이오 마커 및 표적에 대하여 구체적으로 설명한다.Hereinafter, a biomarker and a target used in a method for predicting an anti-PD-1 treatment response according to an embodiment of the present invention will be described in detail with reference to FIGS. 2A to 2G.
도 2a 및 2b는 T세포 탈진과 관련된 후보 유전자를 T세포 유래 단세포 전사체 데이터를 이용하여 확인하는 결과가 도시된다. 2A and 2B show the results of confirming a candidate gene related to T cell exhaustion using T cell-derived single cell transcriptome data.
도 2a의 (a)를 참조하면, T세포 탈진 마커인 PDCD1(PD-1 coding gene) 발현 수준에 따른 CD8+ T세포의 분포가 도시된다. 이때, CD8+ T세포는 종양 미세환경에서 이질성 세포들도 포함된다. CD8+ T세포는 PDCD1의 발현 수준의 중간 값에 의해 고 PDCD1 세포 및 저 PDCD1 세포 그룹으로 나뉜다.Referring to FIG. 2A (a), distribution of CD8+ T cells according to the expression level of PDCD1 (PD-1 coding gene), which is a T cell exhaustion marker, is shown. At this time, CD8+ T cells include heterogeneous cells in the tumor microenvironment. CD8+ T cells are divided into high PDCD1 cells and low PDCD1 cell groups by the median expression level of PDCD1.
다음으로, 도 2a의 (b)를 참조하면, 중간 값에 의해 나누어진 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹을 2차원의 지도로 시각화한 결과가 도시된다. 고 PDCD1 T세포들은 분포도의 상위에 분포되어 있는 것이 나타난다. Next, referring to (b) of FIG. 2A, a result of visualizing a group of high PDCD1 T cells and low PDCD1 T cells divided by a median value in a two-dimensional map is shown. The high PDCD1 T cells appear to be distributed at the top of the distribution map.
다음으로, 도 2a의 (c)를 참조하면, 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹에서의 차별발현유전자(differentially expressed gene, DEG)의 발현양이 바이올린 플롯(violin plot)으로 도시된다. 바이올린 플롯은 상자수염데이터에서 분포 밀도를 좌우 대칭으로 나타내어 구체적으로 표현하는 방법이다. 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯을 가지며, 이는 PDCD1의 발현 수준에 따라 차별발현유전자의 발현이 차이가 있는 것을 의미할 수 있다.Next, referring to (c) of FIG. 2A, the expression levels of differentially expressed genes (DEGs) in high PDCD1 T cells and low PDCD1 T cell groups are shown in a violin plot. The violin plot is a method of expressing the distribution density in the box and beard data in a symmetric way. High PDCD1 T cells and low PDCD1 T cell groups have different shapes of violin plots, which may mean that the expression of differential expression genes is different according to the expression level of PDCD1.
다음으로, 도 2a의 (d)를 참조하면, 차별발현유전자의 수준에 따른 CD8+ T세포의 분포를 2차원의 지도로 시각화한 결과가 도시된다. 고 차별발현유전자 T세포들은 분포도의 위쪽에 분포되어 있는 것이 나타난다.Next, referring to FIG. 2A(d), a result of visualizing the distribution of CD8+ T cells according to the level of the differential expression gene in a two-dimensional map is shown. It appears that the highly differentially expressed T cells are distributed in the upper part of the distribution map.
이상의 과정에 따라, PDCD1 발현 수준에 따라 나누어진 집단에서 다른 분포와 양상을 보인 차별발현유전자들은 T세포 탈진과 관련된 잠재적 후보 유전자로 나타난다.According to the above process, differential expression genes with different distributions and patterns in the population divided according to the level of PDCD1 expression appear as potential candidate genes related to T cell exhaustion.
도 2b를 참조하면, 흑색종과 비소세포성 폐암의 종양 샘플에서 동정된 차별발현유전자들 결과를 도시한 것이다.Referring to FIG. 2B, the results of differential expression genes identified in tumor samples of melanoma and non-small cell lung cancer are shown.
도 2b의 (a) 및 (b)를 참조하면, 흑색종과 비소세포성 폐암의 종양 샘플에서 단세포 RNA 시퀀싱(sing-cell RNA sequencing)을 이용하여 단세포 전사체 데이터를 얻고, Wilcoxon rank sum test를 통하여 T세포 내 T세포 탈진 연관 전사 인자들을 adjusted p<0.05기준으로 동정한 결과가 도시된다. 흑색종에서의 전사 인자들은 IRF8, ETV1, TSC22D1, BATF, CALCOCO1, AATF, NFATC1, HCFC1, TOX, NAB1, ZNF638, PRDM1 및 FAIM3이 선택되었으며, 비소세포성 폐암에서의 전사 인자들은 TOX, IVNS1ABP, SNRPBM IRF7 및 BIN1이 선택되었다. 결과적으로, 흑색종과 비소세포성 폐암의 전사 인자 중 공통 인자인 TOX가 최종 T세포 탈진 관여 전사 인자로 선택되었다.Referring to Figure 2b (a) and (b), single-cell transcript data was obtained from tumor samples of melanoma and non-small cell lung cancer using single-cell RNA sequencing, and Wilcoxon rank sum test was performed. The results of identifying the transcription factors associated with T cell exhaustion in T cells based on adjusted p<0.05 are shown. Transcription factors in melanoma were selected from IRF8, ETV1, TSC22D1, BATF, CALCOCO1, AATF, NFATC1, HCFC1, TOX, NAB1, ZNF638, PRDM1 and FAIM3, and transcription factors in non-small cell lung cancer were TOX, IVNS1ABP, SNRPBM. IRF7 and BIN1 were selected. As a result, TOX, a common factor among transcription factors of melanoma and non-small cell lung cancer, was selected as the transcription factor involved in final T cell exhaustion.
도 2c의 (a)를 참조하면, 흑색종 환자의 CD8+ T세포에서 면역 관문 분자 유전자와 전사 인자 TOX의 발현 수준에 따른 분포를 2차원의 지도로 시각화한 결과가 도시된다. 면역 관문 분자 유전자인 PDCD1, HAVCR2, CTLA4 및 TIGIT 와 전사 인자 TOX가 많이 발현된 고 발현 그룹과 적게 발현된 저 발현 그룹은 각각 다른 발현 양상을 보이는 것으로 나타난다. 보다 구체적으로, 고 발현 그룹은 지도의 하위에 분포되어 있고, 저 발현 그룹은 지도의 상위에 분포되어 있는 것으로 나타난다.Referring to (a) of FIG. 2C, a two-dimensional map of the distribution according to the expression level of the immune checkpoint molecule gene and the transcription factor TOX in CD8+ T cells of a melanoma patient is shown. The high-expression group and the low-expression group in which the immune checkpoint molecule genes PDCD1, HAVCR2, CTLA4 and TIGIT and the transcription factor TOX were highly expressed and low-expressed group showed different expression patterns. More specifically, it appears that the high expression group is distributed at the lower part of the map, and the low expression group is distributed at the upper part of the map.
도 2c의 (b)를 참조하면, 흑색종 환자의 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹에서의 면역 관문 분자 유전자 및 전사 인자 TOX의 발현 수준에 따른 결과가 바이올린 플롯(violin plot)으로 도시된다. Referring to Figure 2c (b), the result according to the expression level of the immune checkpoint molecule gene and transcription factor TOX in the high PDCD1 T cells and low PDCD1 T cell groups of melanoma patients is shown in a violin plot (violin plot). .
면역 관문 분자 유전자인 HAVCR2 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 HAVCR2 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 HAVCR2 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.High PDCD1 T cells and low PDCD1 T cells groups according to the expression level of HAVCR2, an immune checkpoint molecule gene, had different shapes of violin plots, and the distribution between groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the HAVCR2 expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the HAVCR2 expression level is low.
면역 관문 분자 유전자인 CTLA4 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 CTLA4 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 CTLA4 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.According to the expression level of CTLA4, the immune checkpoint molecule gene, the high PDCD1 T cells and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is low.
면역 관문 분자 유전자인 TIGIT 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다 (p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 TIGIT 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 TIGIT 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.According to the expression level of TIGIT, the immune checkpoint molecule gene, the groups of high PDCD1 T cells and low PDCD1 T cells had different shapes of violin plots, and the distribution between the groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is low.
전사 인자인 TOX의 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 TOX의 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 TOX의 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.According to the expression level of the transcription factor TOX, the high and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the expression level of TOX is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TOX expression level is low.
도 2d의 (a)를 참조하면, 비소세포성 폐암 환자의 CD8+ T세포에서 면역 관문 분자 유전자와 전사 인자 TOX의 발현 수준에 따른 분포를 2차원의 지도로 시각화한 결과가 도시된다. 면역 관문 분자 유전자인 PDCD1, HAVCR2, CTLA4 및 TIGIT 와 전사 인자 TOX가 많이 발현된 고 발현 그룹과 적게 발현된 저 발현 그룹은 각각 다른 발현 양상을 보이는 것으로 나타난다. 보다 구체적으로, 고 발현 그룹은 지도의 상위에 분포되어 있고, 저 발현 그룹은 지도의 하위에 분포되어 있는 것으로 나타난다.Referring to FIG. 2D (a), a two-dimensional map of the distribution according to the expression level of the immune checkpoint molecule gene and the transcription factor TOX in CD8+ T cells of a patient with non-small cell lung cancer is shown. The high-expression group and the low-expression group in which the immune checkpoint molecule genes PDCD1, HAVCR2, CTLA4 and TIGIT and the transcription factor TOX were highly expressed and low-expressed group showed different expression patterns. More specifically, it appears that the high expression group is distributed at the upper part of the map, and the low expression group is distributed at the lower part of the map.
도 2d의 (b)를 참조하면, 비소세포성 폐암 환자의 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹에서의 면역 관문 분자 유전자 및 전사 인자 TOX의 발현 수준에 따른 결과가 바이올린 플롯(violin plot)으로 도시된다. Referring to Figure 2d (b), the result according to the expression level of the immune checkpoint molecule gene and the transcription factor TOX in high PDCD1 T cells and low PDCD1 T cell groups of non-small cell lung cancer patients as a violin plot (violin plot). Is shown.
면역 관문 분자 유전자인 HAVCR2 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 HAVCR2 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 HAVCR2 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.High PDCD1 T cells and low PDCD1 T cells groups according to the expression level of HAVCR2, an immune checkpoint molecule gene, had different shapes of violin plots, and the distribution between groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the HAVCR2 expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the HAVCR2 expression level is low.
면역 관문 분자 유전자인 CTLA4 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 CTLA4 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 CTLA4 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.According to the expression level of CTLA4, the immune checkpoint molecule gene, the high PDCD1 T cells and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the CTLA4 expression level is low.
면역 관문 분자 유전자인 TIGIT 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 TIGIT 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 TIGIT 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.According to the expression level of TIGIT, the immune checkpoint molecule gene, the groups of high PDCD1 T cells and low PDCD1 T cells had different shapes of violin plots, and the distribution between the groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TIGIT expression level is low.
전사 인자인 TOX의 발현 수준에 따른 고 PDCD1 T세포 및 저 PDCD1 T세포 그룹은 다른 모양의 바이올린 플롯 형태를 가지며, 그룹 간 분포는 유의적 차이를 보인다(p<0.001). 보다 구체적으로, 고 PDCD1 T세포 그룹은 TOX의 발현 수준이 높은 구간의 분포 밀도가 높은 것으로 나타나고, 저 PDCD1 T세포 그룹은 TOX의 발현 수준이 낮은 구간의 분포 밀도가 높은 것으로 나타난다.According to the expression level of the transcription factor TOX, the high and low PDCD1 T cells groups had different shapes of violin plots, and the distribution between the groups showed significant differences (p<0.001). More specifically, the high PDCD1 T cell group appears to have a high distribution density in the section where the expression level of TOX is high, and the low PDCD1 T cell group appears to have a high distribution density in the section where the TOX expression level is low.
도 2e의 (a)를 참조하면, CD8+ T세포의 상태에 따라 구성된 궤도를 도시한 것이다. 각각 3가지 가지로 도시되며, 각 가지별 우세한 세포 종류가 있는 것으로 나타난다.Referring to Figure 2e (a), it shows the trajectory configured according to the state of the CD8 + T cells. Each is shown in three branches, and each branch appears to have a dominant cell type.
도 2e의 (b)를 참조하면, CD8+ T세포의 궤도에서 가지 별 위치한 상태별 우세한 T세포를 분류한 결과가 도시된다. T세포의 상태는 실행(effector), 탈진(exhausted) 및 기억(memory) 상태로 분류되었다. Referring to (b) of FIG. 2E, the result of classifying the dominant T cells according to the states located by branches in the orbit of the CD8+ T cells is shown. The states of T cells were classified into effector, exhausted and memory states.
도 2f를 참조하면, T세포 상태에 따른 면역 관문 분자 유전자들과 전사 인자 TOX의 표현역학이 도시된다. 면역 관문 분자 유전자들은 CD8+ T세포 탈진상태에서 보다 발현 수준이 증가하는 경향으로 나타난다.Referring to FIG. 2F, the expression kinetics of immune checkpoint molecule genes and transcription factor TOX according to T cell status are shown. The immune checkpoint molecule genes appear to have a tendency to increase in expression levels compared to when CD8+ T cells are exhausted.
도 2g를 참조하면, 면역 관문 분자 유전자들과 전사 인자 TOX의 상태들을 연결 구조 분석한 결과가 도시된다. 각 면역 관문 분자 유전자들의 발현량은 T세포가 실행 상태에서 탈진 상태로 진행될수록 증가하는 경향을 보였고, 실행 상태에서 기억 상태로 진행될수록 감소하는 경향을 보였다. 이는, 전사 인자인 TOX에서도 동일한 경향으로 나타난다. 이에 따라, 전사 인자 TOX와 면역 관문 분자 유전자 들이 서로 연관되어 있는 것으로 나타난다.Referring to FIG. 2G, a result of a structural analysis of linking the states of the immune checkpoint molecule genes and the transcription factor TOX is shown. The expression level of each immune checkpoint molecule gene showed a tendency to increase as T cells progressed from the running state to the exhausted state, and decreased as the T cell progressed from the running state to the memory state. This appears to be the same trend in the transcription factor TOX. Accordingly, it appears that transcription factor TOX and immune checkpoint molecule genes are associated with each other.
이상의 실시예 1의 결과로 종양 미세환경에 존재하는 T세포 내 전사 인자인 TOX가 면역 관문 분자 유전자들과 연관되어 있으며, 면역 관문 분자 유전자들의 발현 수준이 T세포의 탈진과 연관되어 있으므로, TOX의 발현 수준도 연관되어 있는 것을 확인할 수 있었다. 이에, 종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준은, 본 발명의 다양한 실시예에 따른 면역 항암 요법에 대한 치료 반응의 예측을 위한 바이오 마커로서 이용될 수 있다. 더 나아가, TOX는 면역 관문 분자 유전자들과의 메커니즘 또한 연관되어 있는 것으로 보아 TOX를 억제하는 표적 치료제를 병용하여 면역 관문 분자의 발현을 저하시키는 치료제로도 이용될 수 있다.As a result of Example 1 above, TOX, a transcription factor in T cells present in the tumor microenvironment, is associated with immune checkpoint molecule genes, and the expression level of immune checkpoint molecule genes is related to exhaustion of T cells. It was confirmed that the expression level was also related. Thus, the expression level of TOX in T cell-specific T cells existing in the tumor microenvironment can be used as a biomarker for predicting a therapeutic response to immuno-anticancer therapy according to various embodiments of the present invention. Furthermore, because TOX is also associated with the mechanism of immune checkpoint molecule genes, it can also be used as a therapeutic agent for lowering the expression of immune checkpoint molecules by using a targeted therapeutic agent that inhibits TOX.
실시예 2: 종양에서의 면역 관문 분자 발현에 따른 TOX의 발현 및 이에 기초한 치료 반응 예측 방법Example 2: Expression of TOX according to expression of immune checkpoint molecule in tumor and method for predicting treatment response based thereon
이하에서는 도 3a 내지 3c, 도 4a 내지 4d 및 도 5를 참조하여, 본 발명의 일 실시예에 따른 면역 관문 분자 발현에 따른 TOX의 발현 및 이에 기초한 치료 반응 예측 방법을 설명한다. Hereinafter, with reference to FIGS. 3A to 3C, 4A to 4D, and 5, the expression of TOX according to the expression of the immune checkpoint molecule and a method for predicting a treatment response based thereon will be described.
도 3a 내지 3c는 비소세포성 폐암 환자와 편평세포암 환자의 종양에서 면역 관문 분자 발현에 따른 TOX의 발현 결과를 도시한 것이다. 3A to 3C show the expression results of TOX according to the expression of immune checkpoint molecules in tumors of non-small cell lung cancer patients and squamous cell cancer patients.
도 3a는 비소세포성 폐암 환자와 편평세포암 환자의 종양 T세포를 면역 관문 분자 발현과 TOX의 발현에 따라 분석한 결과를 도시한 것이다. 3A shows the results of analysis of tumor T cells of patients with non-small cell lung cancer and squamous cell cancer according to the expression of immune checkpoint molecules and TOX.
도 3a를 참조하면, 비소세포성 폐암 환자의 종양에서 면역 관문 분자 발현이 증가되면, TOX의 발현이 증가되는 것으로 나타난다. 보다 구체적으로, 1사분면과 3사분면의 수치가 비례적으로 증가하는 경향을 나타낸다. 또한, 편평세포암 환자의 종양에서도 면역 관문 분자 발현이 증가되면, TOX의 발현이 증가되는 것으로 나타난다. 보다 구체적으로, 1사분면과 3사분면의 수치가 비례적으로 증가하는 경향을 나타낸다. Referring to FIG. 3A, when the expression of the immune checkpoint molecule is increased in the tumor of a patient with non-small cell lung cancer, the expression of TOX is shown to be increased. More specifically, the values of the first and third quadrants tend to increase proportionally. In addition, when the expression of the immune checkpoint molecule is increased in the tumor of the patient with squamous cell carcinoma, the expression of TOX appears to be increased. More specifically, the values of the first and third quadrants tend to increase proportionally.
도 3b는 비소세포성 폐암 환자와 편평세포암 환자의 종양에서 면역 관문 분자의 발현에 따른 TOX의 발현 양성 세포수 결과를 도시한 것이다.3B shows the results of the number of positive cells expressing TOX according to the expression of an immune checkpoint molecule in tumors of non-small cell lung cancer patients and squamous cell cancer patients.
도 3b의 (a) 및 (b)를 참조하면, 비소세포성 폐암 환자의 종양에서 면역 관문 분자 발현이 양성인 경우 TOX의 발현 양성 세포수도 유의적으로 증가하는 것으로 나타난다. 또한, 편평세포암 환자의 종양에서도 면역 관문 분자 발현이 양성인 경우 TOX의 발현 양성 세포수도 유의적으로 증가되는 것이 나타난다.Referring to Figure 3b (a) and (b), when the immune checkpoint molecule expression is positive in the tumor of a non-small cell lung cancer patient, the number of positive cells expressing TOX is also significantly increased. In addition, even in the tumor of a squamous cell carcinoma patient, when the expression of the immune checkpoint molecule is positive, the number of positive cells expressing TOX is also significantly increased.
도 3c는 비소세포성 폐암 환자와 편평세포암 환자의 종양에서 면역 관문 분자인 PD-1과 TIM-3 발현에 따른 TOX의 발현을 도시한 것이다.3C shows the expression of TOX according to the expression of immune checkpoint molecules PD-1 and TIM-3 in tumors of non-small cell lung cancer patients and squamous cell cancer patients.
도 3c의 (a)를 참조하면, 비소세포성 폐암 환자와 편평세포암 환자의 종양 T세포를 PD-1 발현과 TIM-3의 발현에 따라 분석한 결과가 도시된다. 1사 분면 영역은 PD-1(+)양성-TIM-3(+)양성 세포로 분류하고, 3사 분면 영역은 PD-1(-)음성-TIM-3(-)음성세포로 분류하고, 4사 분면 영역은 PD-1(+)양성-TIM-3(-)음성 세포로 분류하였다.Referring to (a) of FIG. 3C, the results of analyzing tumor T cells of patients with non-small cell lung cancer and squamous cell cancer patients according to PD-1 expression and TIM-3 expression are shown. The first quadrant region was classified as PD-1(+) positive-TIM-3(+) positive cells, and the third quadrant region was classified as PD-1(-) negative-TIM-3(-) negative cells, The quadrant area was classified as PD-1(+) positive-TIM-3(-) negative cells.
도 3c의 (b)를 참조하면, PD-1 발현과 TIM-3의 발현에 따라 분류된 세포를 TOX에 대한 히스토그램 플롯에 나타난 결과가 도시된다. TOX에 대한 형광세기는 괄호 안에 표시하였다. 비소세포성 폐암 환자의 종양에서는 붉은색의 PD-1양성-TIM-3양성 세포 그룹이 TOX의 발현 양도 많으며, 형광세기 또한 1577로 가장 높은 수치를 나타낸다. 또한, 편평세포암 환자의 종양에서도 붉은색의 PD-1양성-TIM-3양성 세포 그룹이 TOX의 발현 양도 많으며, 형광세기 또한 4970으로 가장 높은 수치를 나타낸다.Referring to (b) of FIG. 3C, the results shown in the histogram plot for TOX of cells classified according to the expression of PD-1 and TIM-3 are shown. The fluorescence intensity for TOX is indicated in parentheses. In tumors of patients with non-small cell lung cancer, the red PD-1 positive-TIM-3 positive cell group had a large amount of TOX expression, and the fluorescence intensity was also the highest at 1577. In addition, even in the tumors of squamous cell carcinoma patients, the red PD-1 positive-TIM-3 positive cell group had a large amount of TOX expression, and the fluorescence intensity was also the highest at 4970.
도 3c의 (b)를 참조하면, PD-1 발현과 TIM-3의 발현에 따라 분류된 세포의 TOX의 발현 결과가 도시된다. 비소세포성 폐암 환자의 종양에서는 PD-1양성-TIM-3양성 세포들은 PD-1양성-TIM-3음성 세포들과 PD-1음성-TIM-3음성 세포들 보다 유의적으로 높은 TOX의 발현량을 나타낸다. 또한, 편평세포암 환자의 종양에서도 PD-1양성-TIM-3양성 세포들은 PD-1양성-TIM-3음성 세포들과 PD-1음성-TIM-3음성 세포들 보다 유의적으로 높은 TOX의 발현량을 나타낸다.Referring to FIG. 3C (b), the results of TOX expression of cells classified according to PD-1 expression and TIM-3 expression are shown. In tumors of patients with non-small cell lung cancer, PD-1 positive-TIM-3 positive cells expressed significantly higher TOX than PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM-3 negative cells. Indicates the amount. In addition, in the tumors of squamous cell carcinoma patients, PD-1 positive-TIM-3 positive cells had significantly higher TOX than PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM-3 negative cells. It indicates the expression level.
도 4a는 MC37 마우스 모델의 종양 T세포를 PD-1 발현과 TOX의 발현에 따라 분석한 결과를 도시한 것이다. 4A shows the results of analyzing tumor T cells of the MC37 mouse model according to PD-1 expression and TOX expression.
도 4a를 참조하면, MC37 마우스 모델의 종양 T세포에서 PD-1 발현이 증가되면, TOX의 발현이 증가하는 것으로 나타난다. 보다 구체적으로, 1사분면과 3사분면의 수치가 비례적으로 증가하는 경향을 나타낸다. Referring to FIG. 4A, when the expression of PD-1 is increased in tumor T cells of the MC37 mouse model, it is shown that the expression of TOX is increased. More specifically, the values of the first and third quadrants tend to increase proportionally.
도 4b는 CT26, TC1 및 LLC1 마우스 모델에서 PD-1 분자 발현에 따른 TOX의 발현 양성 세포수 결과를 도시한 것이다. 4B shows the results of the number of cells expressing positive TOX according to the expression of PD-1 molecules in CT26, TC1 and LLC1 mouse models.
도 4b의 (a), (b) 및 (c)를 참조하면, CT26, TC1 및 LLC1 마우스 모델에서 PD-1 분자 발현이 양성인 경우 TOX의 발현 양성 세포수도 유의적으로 증가하는 것으로 나타난다. Referring to Figure 4b (a), (b) and (c), when the PD-1 molecule expression is positive in the CT26, TC1 and LLC1 mouse models, the number of cells expressing positive TOX is also significantly increased.
도 4c는 MC38 마우스 모델의 종양에서 PD-1과 TIM-3 발현에 따른 TOX의 발현을 도시한 것이다.Figure 4c shows the expression of TOX according to the expression of PD-1 and TIM-3 in the tumor of the MC38 mouse model.
도 4c의 (a)를 참조하면, MC38 마우스 모델의 종양 T세포를 PD-1 발현과 TIM-3의 발현에 따라 분석한 결과가 도시된다. 붉은색의 1사 분면 영역은 PD-1양성-TIM-3양성 세포로 분류하고, 주황색의 3사 분면 영역은 PD-1음성-TIM-3음성 세포로 분류하고, 파란색의 4사 분면 영역은 PD-1양성-TIM-3음성 세포로 분류하였다. 도 4c의 (b)를 참조하면, PD-1 발현과 TIM-3의 발현에 따라 분류된 세포를 TOX에 대한 히스토그램 플롯에 나타난 결과가 도시된다. TOX에 대한 형광세기는 괄호 안에 표시하였다. MC38 마우스 모델의 종양에서는 붉은색의 PD-1양성-TIM-3양성 세포 그룹이 TOX의 발현 양도 많으며, 형광세기 또한 1048로 가장 높은 수치를 나타낸다.Referring to (a) of FIG. 4C, the results of analyzing tumor T cells of the MC38 mouse model according to PD-1 expression and TIM-3 expression are shown. The red quadrant area is classified as PD-1 positive-TIM-3 positive cells, the orange quadrant area is classified as PD-1 negative-TIM-3 negative cells, and the blue quadrant area is classified as PD-1 negative-TIM-3 negative cells. They were classified as PD-1 positive-TIM-3 negative cells. Referring to (b) of FIG. 4C, the cells classified according to the expression of PD-1 and TIM-3 are shown in the histogram plot for TOX. The fluorescence intensity for TOX is indicated in parentheses. In the tumor of the MC38 mouse model, the red PD-1 positive-TIM-3 positive cell group had a large amount of TOX expression, and the fluorescence intensity was also the highest at 1048.
도 4c의 (c)를 참조하면, PD-1 발현과 TIM-3의 발현에 따라 분류된 세포의 TOX의 발현 결과가 도시된다. MC38 마우스 모델의 종양에서는 PD-1양성-TIM-3양성 세포들은 PD-1양성-TIM-3음성 세포들과 PD-1음성-TIM-3음성 세포들 보다 유의적으로 높은 TOX의 발현량을 나타낸다. 또한, 도 4c의(d)를 참조하면 CT26, TC1 및 LLC1 마우스 모델의 종양에서도 PD-1양성-TIM-3양성 세포들은 PD-1양성-TIM-3음성 세포들과 PD-1음성-TIM-3음성 세포들 보다 유의적으로 높은 TOX의 발현량을 나타낸다.Referring to FIG. 4C (c), the results of TOX expression of cells classified according to PD-1 expression and TIM-3 expression are shown. In tumors of the MC38 mouse model, PD-1 positive-TIM-3 positive cells showed significantly higher TOX expression than PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM-3 negative cells. Show. In addition, referring to FIG. 4C(d), PD-1 positive-TIM-3 positive cells are PD-1 positive-TIM-3 negative cells and PD-1 negative-TIM in tumors of CT26, TC1 and LLC1 mouse models. -3 shows a significantly higher expression of TOX than negative cells.
도 5는 TOX mRNA를 넉다운(Knockdown)한 암조직 유래 T세포의 면역 관문 분자들의 발현 결과를 도시한 것이다.5 shows the expression results of immune checkpoint molecules of cancer tissue-derived T cells by knocking down TOX mRNA.
도 5의 (a)를 참조하면, TOX mRNA를 넉다운(Knockdown)한 T세포를 면역 관문 분자 발현과 TOX의 발현에 따라 분석한 결과가 도시된다. 컨트롤 그룹에서는 PD-1 발현이 증가되면 TIGIT, TIM-3 및 TOX의 발현이 증가되는 것으로 나타난다. 보다 구체적으로, 1사분면과 3사분면의 수치가 비례적으로 증가하는 경향을 나타낸다. 그러나, TOX mRNA를 넉다운(Knockdown)한 그룹에서는 PD-1 발현이 증가됨에 따라 TIGIT, TIM-3 및 TOX의 발현이 증가되는 경향은 나타내지 않았다.Referring to Figure 5 (a), the results of the analysis of the T cells knocked down TOX mRNA according to the expression of the immune checkpoint molecule and TOX is shown. In the control group, when the expression of PD-1 is increased, the expression of TIGIT, TIM-3 and TOX appears to be increased. More specifically, the values of the first and third quadrants tend to increase proportionally. However, in the group in which TOX mRNA was knocked down (Knockdown), the expression of TIGIT, TIM-3 and TOX did not increase as PD-1 expression increased.
도 5의 (b)를 참조하면, TOX mRNA를 넉다운(Knockdown)한 T세포와 컨트롤 T세포에서의 면역 관문 분자과 TOX가 발현된 세포수가 도시된다. 면역 관문 분자인 PD-1, TIGIT, CTLA-4 및 TIM-3과 TOX의 발현은 컨트롤 그룹에서 유의적으로 높은 것으로 나타난다. 그러나 면역 관문 분자인 LAG-3와 2B4에서는 차이가 나타나지 않았다.Referring to FIG. 5B, the immune checkpoint molecule and the number of TOX-expressing cells in T cells and control T cells in which TOX mRNA was knocked down are shown. The expression of immune checkpoint molecules PD-1, TIGIT, CTLA-4 and TIM-3 and TOX appeared to be significantly higher in the control group. However, there was no difference between the immune checkpoint molecules LAG-3 and 2B4.
도 5의 (c)를 참조하면, TOX mRNA를 넉다운(Knockdown)한 T세포와 컨트롤 T세포에서의 염증반응 유도체 INF-gamma와 TNF-alpha가 발현된 세포수가 도시된다. 염증반응 유도체들의 발현은 TOX 넉다운 그룹에서 유의적으로 높은 것으로 나타난다. Referring to (c) of FIG. 5, the number of cells expressing the inflammatory reaction derivatives INF-gamma and TNF-alpha in T cells knocked down TOX mRNA and control T cells is shown. The expression of inflammatory derivatives appeared to be significantly higher in the TOX knockdown group.
이상의 실시예 2의 결과로 전사 인자인 TOX의 발현과 면역 관문 분자들의 발현이 비례적 관계인 것으로 나타난다. 즉, TOX의 발현으로 인하여 면역 관문 분자들이 촉진되는 것을 확인할 수 있었다. 이에, TOX의 발현 수준은 종래의 면역 관문 분자들의 발현을 예측할 수 있으며, 본 발명의 다양한 실시예에 따른 면역 항암 요법에 대한 치료 반응 예측을 할 수 있다. As a result of Example 2 above, it appears that the expression of the transcription factor TOX and the expression of immune checkpoint molecules have a proportional relationship. That is, it was confirmed that immune checkpoint molecules were promoted by the expression of TOX. Accordingly, the expression level of TOX can predict the expression of conventional immune checkpoint molecules, and can predict a therapeutic response to an immune anticancer therapy according to various embodiments of the present invention.
실시예 3: TOX의 발현 수준에 기초한 항 PD-1 치료 반응 예측_비소세포성 폐암 및 흑색종Example 3: Anti-PD-1 treatment response prediction based on the expression level of TOX_Non-small cell lung cancer and melanoma
이하에서는 도 6a 내지 6c를 참조하여, 본 발명의 일 실시예에 따른 TOX의 발현에 기초한 항 PD-1 치료 반응 예측 방법을 설명한다.Hereinafter, a method for predicting anti-PD-1 treatment response based on TOX expression according to an embodiment of the present invention will be described with reference to FIGS. 6A to 6C.
도 6a는 흑색종 환자의 종양으로부터 유래된 각 세포에서의 TOX의 발현 분포을 비교한 결과를 도시한 것이다.6A shows the results of comparing the expression distribution of TOX in each cell derived from a tumor of a melanoma patient.
도 6a를 참조하면, 흑색종 환자의 종양으로부터 유래된 개별 세포의 TOX의 발현 분포는 다른 면역 세포나 암세포에서 보다 T세포에서 많이 발현되는 것으로 나타난다.Referring to FIG. 6A, the distribution of TOX expression in individual cells derived from tumors of melanoma patients appears to be more expressed in T cells than in other immune cells or cancer cells.
도 6b는 TOX 수준에 따른 비소세포성 폐암 및 흑색종 환자의 생존률 평가 결과를 도시한 것이다.6B shows the results of evaluating the survival rate of patients with non-small cell lung cancer and melanoma according to the TOX level.
도 6b의 (a)를 참조하면, 흑색종에서의 TOX의 발현 수준에 따른 항 PD-1 치료 반응의 예측의 평가 결과가 도시된다. 저 TOX의 발현군과 고 TOX의 발현군은 유의한 차이로 나타나며(p=0.002), 저 TOX의 발현군이 고 TOX의 발현군보다 생존률이 긴 것으로 나타난다. Referring to FIG. 6B (a), the evaluation results of prediction of anti-PD-1 treatment response according to the expression level of TOX in melanoma are shown. The low TOX expression group and the high TOX expression group showed a significant difference (p=0.002), and the low TOX expression group showed a longer survival rate than the high TOX expression group.
나아가, 도 6b의 (b)를 참조하면, 비소 세포성 폐암에서의 TOX의 발현 수준에 따른 항 PD-1 치료 반응의 예측의 결과가 도시된다. 저 TOX의 발현군과 고 TOX의 발현군은 유의한 차이로 나타나며(p=0.0393), 저 TOX의 발현군이 고 TOX의 발현군보다 생존률이 긴 것으로 나타난다. Further, referring to (b) of FIG. 6B, the prediction result of anti-PD-1 treatment response according to the expression level of TOX in non-small cell lung cancer is shown. The low TOX expression group and the high TOX expression group showed a significant difference (p=0.0393), and the low TOX expression group showed a longer survival rate than the high TOX expression group.
도 6c의 (a)를 참조하면, 흑색종에서 TOX의 발현 수준에 따른 실제 환자들의 항 PD-1 치료 결과 차이가 도시된다. 도 6c의 (b) 및 (c)를 더욱 참조하면, 비소 세포성 폐암에서의 TOX 별현 수준에 따른 실제 환자들의 항 PD-1 치료 결과 차이가 도시된다. 보다 구체적으로, 세 경우 모두 TOX의 발현 수준이 낮은 경우에서 항 PD-1 치료에 반응한 환자가 더 많이 분포하는 것으로 나타난다. 특히, 도 6c의 (d)의 AUC 분석 결과에 따르면, 본 발명의 다양한 실시예에 적용되는 코호트인 YCC를 포함한 세 경우 모두에서 반응군과 비 반응군 사이에 TOX의 발현 수준의 분포가 유의한 차이를 갖는 것으로 나타난다(AUC > 0.65).Referring to FIG. 6C(a), the difference in anti-PD-1 treatment results of actual patients according to the expression level of TOX in melanoma is shown. Further referring to (b) and (c) of Figure 6c, the difference in anti-PD-1 treatment results of actual patients according to the level of expression of TOX in non-small cell lung cancer is shown. More specifically, in all three cases, patients who responded to anti-PD-1 treatment appeared to be more distributed when the expression level of TOX was low. In particular, according to the AUC analysis result of FIG. 6C (d), in all three cases including YCC, a cohort applied to various examples of the present invention, the distribution of the expression level of TOX between the responder and the non-responder group was significant. Appears to have a difference (AUC> 0.65).
이상의 실시예 3의 결과로, T세포 특이적인 T세포 내 TOX의 발현 수준이 항 PD-1 치료 반응 예측에 있어서 우수한 마커일 수 있음을 의미할 수 있다. 나아가, T세포 특이적인 T세포 내 TOX의 발현을 저해시킴으로써 생존률을 증가시킬 수 있음을 의미할 수 있다. 그 결과, T세포 특이적인 T세포 내 TOX의 발현을 억제하는 억제제는 생존률을 증가시킬 수 있는 효과가 있다.As a result of Example 3 above, it may mean that the expression level of TOX in T cells-specific T cells may be an excellent marker in predicting anti-PD-1 treatment response. Furthermore, it may mean that the survival rate can be increased by inhibiting the expression of TOX in T cell-specific T cells. As a result, an inhibitor that suppresses the expression of TOX in T cell-specific T cells has an effect of increasing the survival rate.
본 발명의 여러 실시예들의 각각 특징들이 부분적으로 또는 전체적으로 서로 결합 또는 조합 가능하며, 당업자가 충분히 이해할 수 있듯이 기술적으로 다양한 연동 및 구동이 가능하며, 각 실시예들이 서로에 대하여 독립적으로 실 시 가능할 수도 있고 연관 관계로 함께 실시 가능할 수도 있다. Each of the features of the various embodiments of the present invention can be partially or totally combined or combined with each other, and as a person skilled in the art can fully understand, technically various interlocking and driving are possible, and each embodiment may be independently implemented with respect to each other. It may be possible to do it together in a related relationship.
이상 첨부된 도면을 참조하여 본 발명의 실시예들을 더욱 상세하게 설명하였으나, 본 발명은 반드시 이러한 실시예로 국한되는 것은 아니고, 본 발명 의 기술사상을 벗어나지 않는 범위 내에서 다양하게 변형 실시될 수 있다. 따라서, 본 발명에 개시된 실시예들은 본 발명의 기술 사상을 한정하기 위한 것이 아니라 설명하기 위한 것이고, 이러한 실시예에 의하여 본 발명의 기술 사상의 범 위가 한정되는 것은 아니다. 그러므로, 이상에서 기술한 실시예들은 모든 면에서 예시적인 것이며 한정적이 아닌 것으로 이해해야만 한다. 본 발명의 보호 범위는 아래의 청구범위에 의하여 해석되어야 하며, 그와 동등한 범위 내에 있는 모든 기술 사상은 본 발명의 권리범위에 포함되는 것으로 해석되어야 할 것이다.The embodiments of the present invention have been described in more detail with reference to the accompanying drawings, but the present invention is not necessarily limited to these embodiments, and various modifications may be made without departing from the spirit of the present invention. . Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical idea of the present invention, but to explain the technical idea, and the scope of the technical idea of the present invention is not limited by these embodiments. Therefore, it should be understood that the embodiments described above are illustrative and non-limiting in all respects. The scope of protection of the present invention should be interpreted by the following claims, and all technical ideas within the scope equivalent thereto should be interpreted as being included in the scope of the present invention.
과제고유번호: 2018M3C9A5064709Assignment identification number: 2018M3C9A5064709
과제번호: 1711104142Task number: 1711104142
부처명: 과학기술정보통신부 Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 포스트게놈 다부처유전체 사업 Research Project Name: Post-genome Multi-Ministry Genomics Project
연구과제명: 유전체 빅데이터 활용을 위한 네트워크증강분석 웹서비스 개발Research Title: Development of Network Augmentation Analysis Web Service for Using Genomic Big Data
주관기관 : 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
연구기간: 2018.07.01 ~ 2021.12.31Research Period: 2018.07.01 ~ 2021.12.31
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부처명: 과학기술정보통신부Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 선도연구센터지원사업Research Project Name: Leading Research Center Support Project
연구과제명: 질환 데이터 네트워크 증강분석 기술 개발Research Project Title: Development of disease data network enhancement analysis technology
주관기관: 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
연구기간: 2018.06.01 ~ 2022.02.28Research Period: 2018.06.01 ~ 2022.02.28
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부처명: 과학기술정보통신부Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 바이오의료기술개발사업Research Project Name: Biomedical Technology Development Project
연구과제명: 암미세환경 면역리액톰 및 유도인자 발굴을 위한 단일세포 다중오믹스 통합 분석기술 개발Research Project Title: Development of integrated analysis technology for single-cell multi-omics for discovery of immune reactors and inducers in cancer microenvironments
주관기관 : 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
연구기간: 2019.06.01 ~ 2023.12.31Research Period: 2019.06.01 ~ 2023.12.31
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부처명: 과학기술정보통신부Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 중견연구자지원사업Research Project Name: Mid-sized Researcher Support Project
연구과제명: 암-면역 분자네트워크를 활용한 환자별 면역억제에 대한 분자기전 규명 및 정밀 면역항암치료 플랫폼 개발Research Project Title: Identification of molecular mechanisms for immunosuppression of each patient using cancer-immune molecular network and development of precision immunotherapy platform
주관기관 : 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
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부처명: 과학기술정보통신부Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 바이오의료기술개발사업-차세대응용오믹스사업Research Project Name: Biomedical Technology Development Project-Next Generation Applied Ohmics Project
연구과제명: 단일세포 다중오믹스 기술을 활용한 면역리액톰 유도기전 규명Research Project Title: Identification of immune reactor induction mechanism using single cell multi-omics technology
주관기관 : 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
연구기간 : 2019.06.01 ~ 2021.12.31Research period: 2019.06.01 ~ 2021.12.31
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부처명: 과학기술정보통신부Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 의료기관 창업 캠퍼스 연계 원천 기술 개발사업Research Project Name: Original technology development project linked to medical institution start-up campus
연구과제명: 환자유래 순환 종양세포를 이용한 고정밀 전임상 모델 구축을 통한 항암제에 대한 획득 내성 기전 규명과 치료전략 제시Research Project Title: Identification of the mechanism of acquired resistance to anticancer drugs and suggestion of treatment strategies by constructing a high-precision preclinical model using patient-derived circulating tumor cells
주관기관: 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
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기여율: 1/10Contribution Rate: 1/10
과제고유번호: 2019M3A9B6065231Assignment identification number: 2019M3A9B6065231
과제번호 : 1711104016Task number: 1711104016
부처명: 과학기술정보통신부Ministry name: Ministry of Science and Technology Information and Communication
연구관리 전문기관: 한국연구재단 Research Management Professional Institution: Korea Research Foundation
연구사업명: 바이오의료기술개발사업-차세대응용오믹스사업Research Project Name: Biomedical Technology Development Project-Next Generation Applied Ohmics Project
연구과제명: 단일세포 다중오믹스 기반 정밀 면역항암치료에 대한 임상 유용성 검증Research Project Title: Clinical Usefulness Verification for Precision Immuno-chemotherapy Based on Single Cell Multiomics
주관기관: 연세대학교 산학협력단Organizer: Yonsei University Industry-Academic Cooperation Foundation
연구기간 : 2019.06.01 ~ 2021.12.31Research period: 2019.06.01 ~ 2021.12.31
기여율: 1/10Contribution Rate: 1/10

Claims (7)

  1. 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 단계; 및 Measuring the expression level of TOX with respect to the biological sample isolated from the subject; And
    측정된 상기 TOX의 발현 수준을 기초로 상기 개체에 대한 면역 항암 요법의 치료 반응을 예측하는 단계를 포함하는, 면역 항암 요법에 대한 치료 반응 예측 방법.Comprising the step of predicting the treatment response of the immune anti-cancer therapy to the individual based on the measured expression level of the TOX, a method for predicting a treatment response to an immuno-cancer therapy.
  2. 제 1항에 있어서,The method of claim 1,
    상기 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 단계는,Measuring the expression level of TOX for the biological sample,
    종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정하는 단계인, 면역 항암 요법에 대한 치료 반응 예측 방법.A method of predicting a treatment response to immuno-cancer therapy, which is a step of measuring the expression level of TOX in T-cell-specific T cells present in the tumor microenvironment.
  3. 제1항에 있어서,The method of claim 1,
    상기 개체는, 비소세포성 폐암 의심 또는 흑색종 의심 개체이고,The individual is a suspected non-small cell lung cancer or melanoma individual,
    상기 생물학적 시료는, 말초 혈액, 혈청 및 혈장으로 이루어진 그룹에서 선택된 적어도 하나를 포함하는, 면역 항암 요법에 대한 치료 반응 예측 방법.The biological sample, comprising at least one selected from the group consisting of peripheral blood, serum, and plasma, a method for predicting a treatment response to an immune anticancer therapy.
  4. 제1항에 있어서,The method of claim 1,
    상기 면역 항암 요법은, The immune anticancer therapy,
    항 PD-1 치료인, 면역 항암 요법에 대한 치료 반응 예측 방법.Anti-PD-1 therapy, a method of predicting a treatment response to immunotherapy.
  5. 제1항에 있어서,The method of claim 1,
    상기 면역 항암 요법에 대한 치료 반응을 예측하는 단계는,The step of predicting a treatment response to the immune anticancer therapy,
    측정된 상기 TOX의 발현 수준이 미리 결정된 수준 미만일 경우 상기 항 PD-1 치료에 대한 치료 반응양성으로 평가하는 단계를 포함하는, 면역 항암 요법에 대한 치료 반응 예측 방법.If the measured expression level of the TOX is less than a predetermined level, comprising the step of evaluating as a positive treatment response to the anti-PD-1 treatment, a method for predicting a treatment response to immune anticancer therapy.
  6. 개체로부터 분리된 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 제제를 포함하는, 면역 항암 요법에 대한 치료 반응 예측용 키트.A kit for predicting a therapeutic response to an immune anticancer therapy comprising an agent for measuring the expression level of TOX with respect to a biological sample isolated from an individual.
  7. 제 6항에 있어서,The method of claim 6,
    상기 생물학적 시료에 대하여 TOX의 발현 수준을 측정하는 제제는,The agent for measuring the expression level of TOX in the biological sample,
    종양 미세환경에 존재하는 T세포 특이적인 T세포 내 TOX의 발현 수준을 측정하는 제제인, 면역 항암 요법에 대한 치료 반응 예측용 키트.A kit for predicting the therapeutic response to immune anticancer therapy, which is an agent measuring the expression level of TOX in T cells specific to T cells present in the tumor microenvironment.
PCT/KR2020/007335 2019-06-05 2020-06-05 Tox-based method for predicting treatment response to cancer immunotherapy WO2020246846A1 (en)

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