Biomarkers for predicting treatment effect of tumor patient and application of biomarkers

Abstract

The invention belongs to the technical field of biological medicines, and particularly relates to a group of biomarkers for predicting the treatment effect of tumor patients and application thereof. On the basis of considering the synergistic effect of the immune cells, the prognosis of the patient is predicted, and the clinical diagnosis and treatment scheme is helped to be determined. The invention finds that by quantitatively calculating the MT2 abundance in the body of the patient or in the tumor tissue of the patient, the effect of the tumor patient after treatment can be well predicted. Wherein for patients with high MT2 abundance in tumor tissues, the treatment effect after treatment is relatively good, and the lifetime after treatment is relatively long.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology, and specifically relates to a group of biomarkers for predicting the treatment effect of tumor patients and their applications. Background Art

[0002] At present, tumor immunotherapy occupies a central position in the progress of cancer and its treatment strategies. Tumor immunotherapy refers to a therapy in which immune cells penetrate into the tumor site to initiate an anti-cancer immune response and control or kill tumor cells. However, tumor cells can evade the recognition and attack of the body's immune system by hijacking immune checkpoints, remodeling the extracellular matrix of the tumor to form a barrier that prevents immune cell infiltration, and by affecting immunosuppressive cells and related signaling pathways in the immune microenvironment to form an immunosuppressive tumor microenvironment (Gao Renchi, Chen Tong, Meng Landi Yang, et al. Tumor immune microenvironment and its application in targeted therapy [J]. Chinese Journal of New Drugs and Clinical Remedies, 2024, 43(02): 120-127; Chu Guoliang, Feng Zhihui. Research progress on targeting tumor-associated macrophages for tumor immunotherapy [J]. Chinese Journal of Pharmacology and Toxicology, 2023, 37(04): 281-288.). The tumor microenvironment is a complex tumor ecosystem with the tumor as the main body, composed of tumor cells, stromal cells, immune cells, and extracellular matrix. In the tumor microenvironment, the intensive dialogue between macrophages and tumor cells, immune cells, and stromal cells can drive pro- or anti-tumor phenotypes (Xiao Lianlian, Yu Lingjing, Liu Yipeng, et al. Research on the active ingredients of ginseng vesicles regulating the tumor immune microenvironment [J]. Chinese Traditional and Herbal Drugs, 2024, 55(09): 3006-3014.). Therefore, detecting specific immune cell interactions or the expression of specific immune-related molecules in the tumor microenvironment is helpful for determining the clinical diagnosis and treatment plan of patients and judging the clinical prognosis of patients.

[0003] Tumor-infiltrating lymphocytes (TILs) are the most important components of the tumor microenvironment (TME), mainly including immune cells such as T lymphocytes, B lymphocytes, and NK cells, and play an important role in promoting or inhibiting the occurrence and development of tumors and affecting tumor outcomes (Pedrosa L, Esposito F, Thomson T M, et al. The tumor microenvironment in colorectal cancertherapy [J]. Cancers (Basel). 2019. 11(8): 1172.). T cells play a leading role in mediating cell-mediated immune responses. Mature peripheral T lymphocytes (labeled as CD3 + ) can be divided into helper T lymphocytes (labeled as CD4+ ) and cytotoxic T lymphocytes (labeled as CD8 + ). Helper T cells can assist cell-mediated and humoral immune responses and help the body fight inflammation; while cytotoxic T cells have killing functions and can inhibit cell-mediated immune responses, and have a certain impact on inducing and maintaining immune tolerance (WANG Wenqing, WANG Qing, XIONG Xudong, et al. Experimental study on the inhibition of T lymphocyte exhaustion in septic rats by Yantiao Prescription through the PD-1 / PD-L1 pathway [J]. Hebei Medical Journal, 2024, 46(10): 1463-1467.). Natural killer T (NKT) cells are CD1d-restricted T cells that co-express a highly biased T cell receptor (TCR) and NK cell markers in mice and humans (PMID: 15039760). After activation, NKT cells can produce a large amount of interferon-γ, IL-4 (interleukin 4), and granulocyte-macrophage colony-stimulating factor to perform specific immune functions. Classically activated macrophages (M1) can highly express a large number of cell surface markers including inducible nitric oxide synthase (iNOS), CD86, TLR4, and major histocompatibility complex-II (MHC-II) (WU J, ZHAO X, XIAO C, et al. The role of lung macrophages in chronic obstructive pulmonary disease [J]. Respir Med, 2022, 205: 107035.), mainly responsible for regulating T cell antigen expression, promoting inflammatory responses and Th1 cell functions, actively participating in Th1-type immune responses, and playing a key role in the pro-inflammatory responses of host defense, which is beneficial to the elimination of foreign pathogens by the body (EAPEN M S, HANSBRO P M, MCALINDEN K, et al. Abnormal M1 / M2 macrophage phenotype profiles in the small airway wall and lumen in smokers and chronic obstructive pulmonary disease (COPD) [J]. Sci Rep, 2017, 7(1): 13392.).

[0004] The method for detecting the distribution of CD8+ combined with CD163+ immune cells in tumor tissues is disclosed in CN 113092762 A. This invention can clarify the distribution and expression of CD8+ and CD163+ immune cells in the tumor center and tumor invasion margin of breast cancer, determine the correlation between the distribution and expression of CD8+ and CD163+ immune cells in TC and IM and clinicopathological indicators, understand the correlation between the tissue distribution and expression of CD8+ and CD163+ immune cells in the breast cancer microenvironment and the DFS and OS of patients, and clarify the feasibility of using the expression distribution of CD8+ combined with CD163+ in TC+IM as a prognostic marker for breast cancer. The application of PD-L1 splice variant B as a marker for guiding the use of anti-PD-L1 / PD1 immunotherapy is disclosed in CN 108823307 A. Through the detection of PD-L1 splice variant B, this invention found that PD-L1 with differential expression in colorectal cancer cell lines, and this difference in expression level can be used as a marker for guiding the use of anti-PD-L1 / PD1 immunotherapy. However, the above methods still have their deficiencies. In patent CN 113092762 A, there are situations where the judgment indicators are unclear or even contradictory when detecting anti-tumor CD8+ T cells and pro-tumor CD163+ macrophages simultaneously; when using CD8+ combined with CD163+ to correlate with clinical information such as prognosis, the patent does not specifically consider the cooperative interaction / antagonistic effect of immune cells; only staining the corresponding immune cells with CD8 and CD163, although the operation is somewhat simplified, from an immunological perspective, CD8 and CD163 cannot be completely localized on CD8+ T cells and M2 macrophages. For example, cells such as DC, macrophages, monocytes, and NK cells all express CD8. These cells have different functions, and staining with a single marker will bring uncertain variables to subsequent predictions. In patent CN 108823307 A, the expression of PD-L1 in tumor tissues is not stable enough. It is affected by many molecular signals and will change dynamically, resulting in the possibility that the results of the samples taken at that time may not represent the PD-L1 expression level of the whole tumor tissue. Predicting immunotherapy through the expression level of PD-L1 is theoretically feasible, but in practice, due to the above reasons, there are often deviations in the prediction results. Summary of the Invention

[0005] The present invention discovers that by quantitatively calculating the aggregation abundance of M1 macrophages, CD8 + T cells and NKT cells in the body of a patient or in their tumor tissues, the treatment effect of tumor patients after receiving treatment can be well predicted. On this basis, the present invention is completed.

[0006] In a first aspect, the present invention provides a set of biomarkers for evaluating the treatment effect of tumor patients after receiving treatment, and the biomarkers are M1 macrophages, CD8 +One or more of T cells and NKT cells, and the biomarker is achieved by calculating the cell aggregation abundance; the cell aggregation abundance refers to the abundance of M1 macrophages, CD8 + T cells and NKT cells aggregating, that is, MT 2 abundance; when the MT 2 abundance in the patient's body is high, it indicates that the patient has a better prognosis or a better response to immunotherapy.

[0007] Furthermore, the aggregation abundance of the M1 macrophages is detected by CD68 and CD86 or CD68 and CD80, and the aggregation abundance of the CD8 + T cells is detected by CD3 and CD8, and the aggregation abundance of the NKT cells is detected by CD3 and CD56.

[0008] Furthermore, the patient's body herein refers to within the patient's tumor tissue.

[0009] Preferably, the tumor tissue is selected from areas without necrosis and bleeding.

[0010] Furthermore, the tumors include but are not limited to small cell lung cancer (SCLC), renal cell carcinoma (RCC), colorectal cancer (CRC), gastric cancer (GC), melanoma, non-small cell lung cancer (NSCLC), glioblastoma, and any other type of solid tumor.

[0011] Furthermore, the treatment methods include one or more of immunotherapy, chemotherapy, and / or surgical resection.

[0012] In a second aspect, the present invention provides an application of a biomarker in the preparation of a reagent for evaluating the treatment effect of a tumor patient after treatment, the biomarker being M1 macrophages, CD8 + T cells and NKT cells, and the reagent being a reagent containing the ability to detect the aggregation abundance of M1 macrophages, CD8 + T cells and NKT cells in a biological sample of a patient.

[0013] Furthermore, the cell aggregation abundance refers to the abundance of M1 macrophages, CD8 + T cells and NKT cells aggregating, that is, MT 2 abundance.

[0014] Furthermore, the biomarker functions by quantitatively calculating the MT 2 abundance. When the MT 2 abundance in the patient's body is high, it indicates that the patient has a better prognosis or a better response to immunotherapy.

[0015] Furthermore, the reagent for detecting the cell aggregation abundance refers to a reagent that can be used to label and localize M1 macrophages, CD8+ Reagents for T cells and NKT cells.

[0016] Furthermore, the detection reagent includes one or more of anti-CD68 antibody, anti-CD86 antibody, anti-CD80 antibody, anti-CD3 antibody, anti-CD8 antibody, and / or anti-CD56 antibody.

[0017] Preferably, the detection reagent includes anti-CD68 antibody, anti-CD86 antibody, anti-CD3 antibody, anti-CD8 antibody, and anti-CD56 antibody.

[0018] Further, the aggregation abundance of M1 macrophages is detected by CD68 and CD86 or CD68 and CD80, and the aggregation abundance of CD8 + T cells is detected by CD3 and CD8, and the aggregation abundance of NKT cells is detected by CD3 and CD56.

[0019] Further, the patient biological sample is derived from tumor tissue.

[0020] Preferably, the tumor tissue is selected from areas without necrosis and bleeding.

[0021] Further, the tumors include but are not limited to small cell lung cancer (SCLC), renal cell carcinoma (RCC), colorectal cancer (CRC), gastric cancer (GC), melanoma, non-small cell lung cancer (NSCLC), glioblastoma, and any other type of solid tumor.

[0022] Further, the treatment method includes one or more of immunotherapy, chemotherapy, and / or surgical resection.

[0023] In a third aspect, the present invention provides a kit for evaluating the treatment effect of a tumor patient after treatment, and the kit contains reagents for detecting the aggregation abundance of M1 macrophages, CD8 + T cells, and NKT cells in a patient biological sample.

[0024] Further, the cell aggregation abundance refers to the aggregation abundance of M1 macrophages, CD8 + T cells, and NKT cells, that is, the MT 2 abundance.

[0025] Further, the biomarker functions by quantitatively calculating the MT 2 abundance. When the MT 2 abundance in the patient's body is high, it indicates that the patient has a better prognosis or a better response to immunotherapy.

[0026] Further, the reagent for detecting the cell aggregation abundance refers to a reagent that can be used to label and localize M1 macrophages, CD8 +Reagents for T cells and NKT cells.

[0027] Furthermore, the detection reagent includes one or more of anti-CD68 antibody, anti-CD86 antibody, anti-CD80 antibody, anti-CD3 antibody, anti-CD8 antibody, and / or anti-CD56 antibody.

[0028] Preferably, the detection reagent includes anti-CD68 antibody, anti-CD86 antibody, anti-CD3 antibody, anti-CD8 antibody, and anti-CD56 antibody.

[0029] Further, the aggregation abundance of the M1 macrophages is detected by CD68 and CD86 or CD68 and CD80, and the aggregation abundance of the CD8 + T cells is detected by CD3 and CD8, and the aggregation abundance of the NKT cells is detected by CD3 and CD56.

[0030] Further, the patient biological sample is derived from tumor tissue.

[0031] Preferably, the tumor tissue is selected from areas without necrosis and hemorrhage.

[0032] Further, the kit can be one or more of an ELISA detection kit, a colloidal gold detection kit, an immunohistochemistry kit, an immunofluorescence kit, and / or an in situ hybridization staining kit.

[0033] Furthermore, the diagnostic method of the kit includes one or more of the direct method, the indirect method, the double antibody sandwich method, and / or the competitive method.

[0034] Further, the tumors include but are not limited to small cell lung cancer (SCLC), renal cell carcinoma (RCC), colorectal cancer (CRC), gastric cancer (GC), melanoma, non-small cell lung cancer (NSCLC), glioblastoma, and any other type of solid tumor.

[0035] Further, the kit also includes software for calculating the aggregation abundance, and the aggregation abundance can be obtained by calculating the overlapping area according to the specific cell type, relative position, and influence range detected.

[0036] In a fourth aspect, the present invention provides a method for calculating the aggregation abundance of a biomarker, where the biomarker is one or more of M1 macrophages, CD8 + T cells, and NKT cells; wherein, the aggregation abundance of the biomarker is to quantitatively calculate the aggregation abundance of M1 macrophages, CD8 + T cells, and NKT cells, that is, the MT 2 abundance; the aggregation abundance of the M1 macrophages is detected by CD68 and CD86 or CD68 and CD80, and the CD8+ The aggregation abundance of T cells is detected by CD3 and CD8, and the aggregation abundance of NKT cells is detected by CD3 and CD56. The method comprises the following steps:

[0037] 1) Obtain cell positions: Determine the positions of each CD8 + T cell, NKT cell and M1 macrophage on the material to be detected;

[0038] 2) Define the influence range: For each cell at the determined position, define its influence range with a radius of 1 - 100 μm;

[0039] 3) Measure the overlapping area: Measure the overlapping area of the influence ranges of all CD8 + T cells and NKT cells with the influence ranges of all M1 macrophages;

[0040] 4) Calculate the aggregation abundance: Divide the overlapping area by the total tissue area or tumor tissue area on the section, which is the MT 2 abundance described in the present invention.

[0041] Furthermore, in step 1), the method for obtaining cell positions includes immunohistochemical staining of cells or other methods capable of localizing cell positions.

[0042] Moreover, the method of immunohistochemical staining of cells includes, but is not limited to, direct immunohistochemical staining, indirect immunohistochemical staining, and multiplex immunofluorescence, etc.

[0043] Moreover, the immunohistochemical staining of cells refers to using corresponding antibodies to label and stain M1 macrophages indicated by CD68 and CD86 or CD68 and CD80, CD8 + T cells indicated by CD3 and CD8, and NKT cells indicated by CD3 and CD56.

[0044] Furthermore, the other methods capable of localizing cell positions include, but are not limited to, super-resolution spatial omics technology, in-situ RNA analysis technology, and protein spatial distribution analysis technology, etc.

[0045] Furthermore, in step 1), the material to be detected refers to a tumor tissue section.

[0046] Furthermore, in step 2), the lower limit of the radius is 1 - 20 μm, preferably 1, 5, 10, 12, 14, 15, 16, 18, 20 μm.

[0047] Furthermore, in step 2), the upper limit of the radius is 40 - 95 μm, preferably 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90 or 95 μm.

[0048] Beneficial effects

[0049] 1. Based on considering the synergistic effect of immune cells, the present invention predicts the treatment effect of a patient after receiving treatment, and helps to determine the clinical diagnosis and treatment plan.

[0050] 2. The present invention innovatively discovers that by quantitatively calculating the aggregation abundance (MT + abundance) of M1 macrophages, CD8 2 T cells, and NKT cells in the patient's body or in their tumor tissue, the effect of a cancer patient after receiving treatment can be well predicted. Among them, patients with a high MT 2 abundance in the tumor tissue have a better treatment effect after receiving treatment and a longer survival period after treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 For a section with a high MT 2 abundance (left) and a section with a lower MT 2 abundance (right).

[0052] Figure 2 For the MT 2 abundance distribution diagram of 44 patients with small cell lung cancer.

[0053] Figure 3 For 44 patients with small cell lung cancer, the survival curves of patients in the high MT 2 abundance group and the low MT 2 abundance group.

[0054] Figure 4 For the MT 2 abundance distribution diagram of 85 patients with small cell lung cancer.

[0055] Figure 5 For 85 patients with small cell lung cancer, the survival curves of patients in the high MT 2 abundance group and the low MT 2 abundance group.

[0056] Figure 6 For the verification set ROC curve of 85 patients with small cell lung cancer.

[0057] Figure 7 For 23 patients with small cell lung cancer who received immunotherapy, the survival curves of patients in the high MT 2 abundance group and the low MT 2 abundance group. DETAILED DESCRIPTION OF THE INVENTION

[0058] The following further describes the specific embodiments of the present invention. It should be noted here that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation on the present invention. In addition, the technical features involved in the following described embodiments can be combined with each other as long as they do not conflict with each other.

[0059] The experimental methods in the following embodiments are all conventional methods unless otherwise specified. The test materials used in the following embodiments are all available through conventional commercial channels unless otherwise specified.

[0060] Both CD8+ T cells and NKT cells in the present invention can obtain the presented antigen from M1 macrophages and both have cell killing functions. The present invention discovers that if the first two types of cells (CD8+ T cells and NKT cells) and M1 macrophages can be located and aggregated together in tumors, it can well indicate the treatment effect of tumor patients.

[0061] The "cell aggregation abundance" described in the present invention refers to the degree of aggregation of different types of cells in the same region or position within the tissue. A high aggregation abundance means that different types of cells to be measured are more concentrated together, showing an aggregation effect on the tissue section, and the overlapping area between different types of cell regions can be used to represent it. Since the sizes of the tissues taken in the sections are different, the overlapping area can be compared with the total section tissue area (or the tumor tissue area in the section), so as to standardize the measured value of the overlapping area and more accurately reflect the aggregation degree of cells inside the tissue.

[0062] The "MT 2 abundance" described in the present invention refers to the aggregation abundance of M1 macrophages, CD8 + T cells and NKT cells. Relying on the generally recognized immunological principles, M1 macrophages mainly show a pro-inflammatory phenotype and at the same time have a strong antigen presentation function. On the one hand, CD8+ T cells and NKT themselves have cell killing effects, and on the other hand, they can specifically recognize tumor cells through the tumor antigens presented by M1 macrophages. The two aspects are combined to form a complete positive cycle of tumor antigen processing - specific recognition of cytotoxic immune cells - killing tumor cells. Therefore, the three types of cells are divided into two groups. NKT cells and CD8+ T cells form the cytotoxic cell group, and M1 macrophages form the antigen presentation group. The influence ranges are respectively delimited by all the cells within each group with a certain distance as the radius. The one delimited by the cytotoxic cell group is called the cell killing region, and the one delimited by the antigen presentation group is called the antigen presentation region. The overlapping area between the cell killing region and the antigen presentation region in the section is the MT 2 abundance.

[0063] The "M1 macrophages" described in the present invention refer to classically activated macrophages, which are mainly responsible for regulating T cell antigen expression, promoting inflammatory responses and Th1 cell functions. Their characteristic cell surface markers are CD68 and CD86, or alternatively, CD68 and CD80.

[0064] The "CD8+ T cells" described in the present invention refer to cytotoxic T cells, and their characteristic cell surface markers are CD3 and CD8.

[0065] The "NKT cells" described in the present invention refer to natural killer T cells, which are a type of T cells that also have some characteristics of NK cells. Their characteristic cell surface markers are CD3 and CD56.

[0066] The surface markers of the various types of cells described above are currently recognized markers in immunology. Those skilled in the art are familiar with the method of using corresponding antibodies for immunohistochemical staining to stain and label the corresponding cells, so as to obtain their localization information in tissues. The same type of cells can also be stained with different other known surface markers, and the types of markers used are not limited herein.

[0067] Example 1

[0068] MT 2 The staining and calculation method for abundance is as follows:

[0069] 1. Obtain tumor tissue sample sections from tumor patients after surgery. Identify suitable dense cancer regions for staining on slides stained with hematoxylin and eosin (H&E) by thoracic pathologists (design punching holes in areas where tumor cells are relatively dense in the section (such as cancer nests) to capture as much microenvironment information in the tumor dense area as possible). Generate a tissue microarray (TMA) block with a tumor core by removing and processing the marked area. Section the TMA tissue block and transfer it to a slide for fluorescence staining.

[0070] 2. Place the slide in a container and cover it with a bleaching solution. Clamp the container between two LED lights and place it at room temperature for 45 min.

[0071] 3. Wash the tissue 4 times with 1X PBS, 5 min each time, and dry it after washing.

[0072] 4. Cover the tissue with staining buffer and let the tissue equilibrate at room temperature for 30 min.

[0073] 5. Stain the tissue by adding the prepared specific antibody to the tissue.

[0074] 6. After antibody incubation, wash the tissue in staining buffer.

[0075] 7. Subsequently, tissue fixation is carried out. The tissue is placed in the post-staining fixation solution and incubated at room temperature for 10 min, and then the tissue is rinsed with PBS.

[0076] 8. For the second fixation, the slides are transferred to a container filled with pre-cooled methanol. Incubate for 5 min, then transfer back to PBS and rinse with PBS.

[0077] 9. For the third and final fixation, the final fixation solution is added to the slides and incubated in a humidity chamber at room temperature for 20 min, and the tissue is rinsed with PBS.

[0078] 10. Transfer the slides to the imaging device and then dry for 15 min, and perform cyclic image acquisition.

[0079] 11. Staining is performed using antibodies such as CD3, CD8, CD56, CD68, and CD86. Three antibodies are added in each round of staining. After staining, fixation, and elution, the fluorescence of the three antibodies is photographed and recorded. After rinsing, after multiple rounds of staining, the finally photographed multi-round fluorescence images will be corrected and aligned on the original tissue image.

[0080] 12. Use Qupath software for cell segmentation and identification of the images to obtain cell types and their spatial localization.

[0081] 13. Use the colony recognition algorithm to calculate the MT 2 abundance, and the calculation method is as follows:

[0082] 1) Obtain cell positions: Determine the positions of CD8+ T cells, NKT cells, and M1 macrophages after staining on the sections (wherein, the aggregation abundance of CD8+ T cells is detected by CD3 and CD8, the aggregation abundance of NKT cells is detected by CD3 and CD56, and the aggregation abundance of M1 macrophages is detected by CD68 and CD86);

[0083] 2) Define the influence range: For each cell at the determined position, a circle with a radius of 30 μm is drawn to define its influence range;

[0084] 3) Measure the overlapping area: Measure the overlapping area of the influence ranges of all CD8+ T cells and NKT cells (killer cell group) and all M1 macrophages (antigen-presenting group);

[0085] 4) Calculate the aggregation abundance: The ratio of the overlapping area to the total tissue area or tumor tissue area on the section is the MT 2 abundance.

[0086] Figure 1 shows the MT 2 abundance staining results of different tumor tissue sections after being processed by the above method. The left figure shows high MT2 Tumor tissue section with MT abundance of 0.0275; the right figure shows a tumor tissue section with low MT abundance 2 Tumor tissue section with MT abundance of 0.0275; the right figure shows a tumor tissue section with low MT abundance 2 Tumor tissue section with MT abundance of 0.0275; the right figure shows a tumor tissue section with low MT abundance 2 Tumor tissue section with MT abundance of 0.0099.

[0087] Example 2

[0088] Using the method of Example 1, paraffin sections of tumor samples from 44 patients with resected primary small cell lung cancer diagnosed between 2010 and 2021 were subjected to detection and calculation of MT abundance. The samples were from tumor tissues after surgical resection, and the samples were then made into paraffin blocks and stored in the sample library. 2 Using the method of Example 1, paraffin sections of tumor samples from 44 patients with resected primary small cell lung cancer diagnosed between 2010 and 2021 were subjected to detection and calculation of MT abundance. The samples were from tumor tissues after surgical resection, and the samples were then made into paraffin blocks and stored in the sample library.

[0089] Figure 2 Shows the distribution of MT abundance in this batch of samples, with a median MT abundance value of 0.0218. 2 Shows the distribution of MT abundance in this batch of samples, with a median MT abundance value of 0.0218. 2 Shows the distribution of MT abundance in this batch of samples, with a median MT abundance value of 0.0218.

[0090] According to the median value of MT abundance in this batch of samples, the corresponding patients were divided into a high MT abundance group and a low MT abundance group. Combining with information such as the clinical prognosis of the patients stored in the hospital, survival curves of the two groups of patients were made, as shown. 2 According to the median value of MT abundance in this batch of samples, the corresponding patients were divided into a high MT abundance group and a low MT abundance group. Combining with information such as the clinical prognosis of the patients stored in the hospital, survival curves of the two groups of patients were made, as shown. 2 According to the median value of MT abundance in this batch of samples, the corresponding patients were divided into a high MT abundance group and a low MT abundance group. Combining with information such as the clinical prognosis of the patients stored in the hospital, survival curves of the two groups of patients were made, as shown. 2 According to the median value of MT abundance in this batch of samples, the corresponding patients were divided into a high MT abundance group and a low MT abundance group. Combining with information such as the clinical prognosis of the patients stored in the hospital, survival curves of the two groups of patients were made, as shown. Figure 3 Shown.

[0091] Figure 3 The results showed that the survival period of patients in the high MT abundance group was significantly higher than that in the low MT abundance group (P < 0.00001). This indicates that patients with high MT abundance have better treatment effects and longer survival times after treatment. 2 The results showed that the survival period of patients in the high MT abundance group was significantly higher than that in the low MT abundance group (P < 0.00001). This indicates that patients with high MT abundance have better treatment effects and longer survival times after treatment. 2 The results showed that the survival period of patients in the high MT abundance group was significantly higher than that in the low MT abundance group (P < 0.00001). This indicates that patients with high MT abundance have better treatment effects and longer survival times after treatment. 2 The results showed that the survival period of patients in the high MT abundance group was significantly higher than that in the low MT abundance group (P < 0.00001). This indicates that patients with high MT abundance have better treatment effects and longer survival times after treatment.

[0092] Example 3

[0093] Based on the results found in Example 2, a further validation was carried out on an independent cohort of 85 patients. The sample sources were the same as in Example 2, and the enrolled patients all received chemotherapy after surgery. Using the method described in Example 1, the tumor tissue samples were stained and the MT abundance in each section was calculated. 2 Based on the results found in Example 2, a further validation was carried out on an independent cohort of 85 patients. The sample sources were the same as in Example 2, and the enrolled patients all received chemotherapy after surgery. Using the method described in Example 1, the tumor tissue samples were stained and the MT abundance in each section was calculated.

[0094] Figure 4 Shows the distribution of MT abundance in the samples of this example, with a median MT abundance value of 0.0116. 2 Shows the distribution of MT abundance in the samples of this example, with a median MT abundance value of 0.0116. 2 Shows the distribution of MT abundance in the samples of this example, with a median MT abundance value of 0.0116.

[0095] According to the MT abundance in this batch of samples 2The median abundance value was used to divide the corresponding patients into a high MT 2 abundance group and a low MT 2 abundance group. Combining with the information such as the clinical prognosis of the patients stored in the hospital, survival curves of the two groups of patients were made, as Figure 5 shown. The results showed that the survival rate of the group with high MT 2 abundance was significantly higher than that of the group with low MT 2 abundance (P = 0.031). It was proved that MT 2 abundance could indicate the prognosis of patients, and high MT 2 abundance indicated good prognosis of patients.

[0096] Furthermore, the predictive effect of MT 2 abundance was analyzed by ROC curve. The results showed that its AUC value was 0.7 ( Figure 6 ), indicating that MT 2 abundance had a high predictive effect.

[0097] Example 4

[0098] In another cohort of small cell lung cancer patients (23 cases) receiving PD-L1 monoclonal antibody immunotherapy, the predictive situation of MT 2 abundance on the treatment effect was verified.

[0099] All enrolled patients received surgical treatment. The subsequent immunotherapy regimen was 1200 mg of atezolizumab every three weeks or 1500 mg of durvalumab every three weeks, combined with chemotherapy. The preservation and sampling of tumor tissue samples were the same as those described in Example 2.

[0100] In this example, multiplex acquisition immunofluorescence (mIF) was used for cell staining in tissues. The specific experimental steps were as follows:

[0101] Multiplex immunohistochemistry (mIHC) was performed by sequentially staining 4-μm thick formalin-fixed and paraffin-embedded whole tissue sections with standard primary antibodies, and paired with a TSA7-color kit (abs50037-100T, Absinbio, Shanghai).

[0102] 2. Then stain with DAPI. Incubate the deaffinity slide with anti-IL-10RA antibody (#ab225820, Abcam) for 30 minutes, and then treat with anti-rabbit / mouse horseradish peroxidase-conjugated (HRP) secondary antibody (abs50015-02, Absinbio, Shanghai) for 10 min.

[0103] 3. According to the manufacturer's instructions, use TSA520 to perform labeling within 10 min under strict compliance.

[0104] 4. The glass slides are washed in TBST buffer, then transferred to a preheated citrate solution (90 °C), and then heat-treated with microwave at 20% of the maximum power for 15 min. The glass slides are cooled to room temperature in the same solution.

[0105] 5. Between all steps, the glass slides are washed with Tris buffer. The same procedure is repeated for the following antibody / fluorescent dyes in the order of: anti-CD3 / TSA570, anti-CD8 / TSA620, anti-CD68 / TSA670. Then each glass slide is treated with 2 drops of DAPI (abs47047616, Absinbio, Shanghai), washed in distilled water, and manually covered with a coverslip.

[0106] 6. The glass slides are air-dried and photographed with PhenoImager HT (Akoya Biosciences, USA).

[0107] 7. The images are analyzed using Halo software (Indica Labs, USA) to identify the type of each cell and export the corresponding spatial location.

[0108] After obtaining the spatial location of each cell, the MT 2 abundance is calculated using the method described in Example 1.

[0109] Using the method in the aforementioned Example 2, based on the high or low MT 2 abundance, the 23 patients in this example are grouped, and combined with the statistical information such as the clinical prognosis of the patients stored in the hospital, the survival curves of the two groups of patients are made ( Figure 7 ).

[0110] The results show that the overall survival time of the group of patients with high MT 2 abundance is significantly higher than that of the group of patients with low MT 2 abundance (P = 0.0128), suggesting that MT 2 abundance can significantly indicate the response degree and treatment effect of patients to immunotherapy, and can be used to guide the use of immunotherapy drugs.

Claims

1. A set of biomarkers for evaluating the treatment effect of tumor patients after treatment, the biomarkers being one or more of M1 macrophages, CD8 + T cells and NKT cells, and the biomarkers are achieved by calculating the cell aggregation abundance; the cell aggregation abundance refers to the abundance of M1 macrophages, CD8 + T cells and NKT cells aggregating, that is, the MT 2 abundance; when the MT 2 abundance in the patient's body is high, it indicates that the patient has a better prognosis or a better response to immunotherapy.

2. The biomarker according to claim 1, wherein the aggregation abundance of M1 macrophages is detected by CD68 and CD86 or CD68 and CD80, and the CD8 + The aggregation abundance of T cells is detected by CD3 and CD8, and the aggregation abundance of NKT cells is detected by CD3 and CD56.

3. The biomarker according to any one of claims 1 or 2, wherein the tumor includes but is not limited to small cell lung cancer (SCLC), renal cell carcinoma (RCC), colorectal cancer (CRC), gastric cancer (GC), melanoma, non-small cell lung cancer (NSCLC), glioblastoma, and any other type of solid tumor.

4. The biomarker according to any one of claims 1-3, wherein the treatment method includes one or more of immunotherapy, chemotherapy, and / or surgical resection.

5. Use of a biomarker in the preparation of a reagent for evaluating the therapeutic effect of a tumor patient after treatment, wherein the biomarker is M1 macrophage, CD8 + T cell and NKT cell, and the reagent is a reagent containing the ability to detect the aggregation abundance of M1 macrophage, CD8 + T cell and NKT cell in a biological sample of a patient.

6. A kit for evaluating the treatment effect of tumor patients after treatment, the kit comprising reagents for detecting the aggregation abundances of M1 macrophages, CD8 + T cells and NKT cells in a biological sample of the patient.

7. The kit according to claim 6, wherein the kit further comprises software for calculating the aggregation abundance, and the aggregation abundance can be obtained by calculating according to the overlapping area according to the detected cell type and location.

8. A method for calculating the aggregation abundance of biomarkers, wherein the biomarkers are one or more of M1 macrophages, CD8 + T cells, and NKT cells; wherein, The biomarker aggregation abundance is the abundance of M1 macrophages, CD8 + T cells, and NKT cells, that is, the MT 2 abundance; the aggregation abundance of M1 macrophages is detected by CD68 and CD86 or CD68 and CD80, and the aggregation abundance of the CD8 + T cells is detected by CD3 and CD8, and the aggregation abundance of NKT cells is detected by CD3 and CD56. The method includes the following steps: 1) Obtain cell positions: Determine the positions of each CD8 + T cell, NKT cell, and M1 macrophage on the material to be detected; 2) Define the influence range: For each cell at a determined position, define its influence range with a radius of 1-100 μm. 3) Measure the overlapping area: Measure the area of the overlapping region between the affected ranges of all CD8 + T cells and NKT cells and the affected range of all M1 macrophages; 4) Calculate the aggregation abundance: Divide the area of the overlapping region by the total tissue area or the tumor tissue area on the section, which is the MT abundance described in the present invention. 2 Abundance.

9. The method according to claim 8, wherein in step 1), the method for obtaining the cell position includes cell immunohistochemical staining or other methods capable of localizing the cell position.

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