Prognostic biomarkers for PD1 / PD-L1 tumor treatment and application thereof

Abstract

The invention relates to the technical field of molecular diagnosis, in particular to a group of PD1 / PD-L1 prognostic biomarkers for tumor treatment and application of the PD1 / PD-L1 prognostic biomarkers. The biomarker disclosed by the invention is simple and convenient to sample, high in accuracy and quick in result reporting. When the expression level of Pseudomonas viridiflava is up-regulated, the prognosis of PD1 / PD-L1 in treating tumors is good, the AUC value (threshold value 0.04386) for predicting the curative effect of immunotherapy in a screening set is 0.9063, and the AUC value (threshold value 0.05311) for predicting the curative effect of immunotherapy in a verification set is 0.8056. When the expression level of Rothiia mucilaginosa is reduced, the prognosis of the PD1 / PD-L1 for treating the tumor is poor. The AUC value for predicting the curative effect of the immunotherapy in the screening set is 0.8563 (the threshold value is 0.06214), and the AUC value for predicting the curative effect of the immunotherapy in the verification set is 0.7111 (the threshold value is 0.06690). The method has important scientific significance and clinical value in improving individualized precise treatment application of immunotherapy, provides an effective molecular target for individualized precise treatment of lung cancer patients, provides a basis for a new intervention strategy, and provides more reliable lung cancer diagnosis and prognosis prediction.

Description

Technical Field

[0001] The present invention relates to the field of molecular diagnostic technology, and in particular to a group of PD1 / PD-L1 biomarkers for tumor prognosis and their applications. Background Art

[0002] Lung cancer is a highly prevalent cancer worldwide, of which non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer, accounting for approximately 85% of lung cancer patients (Lin Q, Wang X, Hu Y. The opportunities and challenges in immunotherapy: Insights from the regulation of PD-L1 in cancer cells. Cancer Lett 2023, 569: 216318.). Immunotherapy has shown increasingly powerful therapeutic efficacy in the evolution of tumor treatment, including cytokine therapy, tumor vaccines, immune checkpoint blockade therapy, and adoptive cell therapy. Although immunotherapy based on PD-1 immune checkpoint blockers has significant efficacy in patients with non-small cell lung cancer, its drug resistance and adverse events remain a fundamental challenge that has not yet been resolved.

[0003] Metabolites produced by microorganisms have a regulatory effect on the host epigenome, leading to carcinogenesis (Paul B, Barnes S, Demark-Wahnefried W, Morrow C, Salvador C, Skibola C, Tollefsbol TO. Influences of diet and the gut microbiome on epigenetic modulation incancer and other diseases. Clin Epigenetics 2015, 7: 112). Multiple studies have shown that different cancer subtypes have different microbial compositions. Mechanistic studies have shown that intratumoral bacteria may promote the occurrence and development of cancer through DNA damage, epigenetic modification, inflammatory response, host immune regulation and activation of oncogenes or oncogenic pathways (Wang G, He X, Wang Q. Intratumoral bacteria are an important "accomplice" in tumor development and metastasis. Biochim Biophys Acta Rev Cancer 2023, 1878 (1): 188846.). There is evidence that certain microbial agents, such as Helicobacter pylori, Porphyromonas gingivalis, Fusobacterium nucleatum, Streptococcus bovis, Chlamydia pneumoniae, Campylobacter rectum, Epstein-Barr virus, hepatitis virus, human tumor virus, polyoma virus, can cause host epigenetic changes and are often associated with carcinogenesis (Oka T, Sato H, Ouchida M, Utsunomiya A, Yoshino T. Cumulative Epigenetic Abnormalities in Host Genes with Viral and Microbial Infection during Initiation and Progression of Malignant Lymphoma / Leukemia. Cancers (Basel) 2011, 3(1): 568-581.). Metabolites released by certain intestinal flora have regulatory effects that induce epigenetic modifications, thereby affecting gene expression.Although it is not clear how these metabolites alter host gene expression, metabolites produced by the gut microbiota, including biotin, short-chain fatty acids (SCFAs), amino acids, etc., are associated with these changes (Mathebela P, Damane BP, Mulaudzi TV, Mkhize-Khwitshana ZL, Gaudji GR, Dlamini Z. Influence of the Microbiome Metagenomics and Epigenomics on Gastric Cancer. Int J Mol Sci 2022, 23(22).).

[0004] Bacterial therapy uses inactivated, attenuated, or killed bacteria to stimulate the immune system through a variety of mechanisms and pathways and has long been used to fight cancer. One of the main advantages of bacterial therapy is that it can effectively stimulate anti-tumor immune responses through a variety of immunomodulatory mechanisms (Wang Y. Bacterial therapy: a promising strategy for cancer immunotherapy. Cancer Biol Med 2023, 20 (11): 795-798.). Bacterial vaccination has long been used to treat certain cancers; for example, non-muscle invasive bladder cancer can be successfully treated with Bacillus Calmette-Guérin (BCG). Recent studies have shown that the microbiome can determine the success of checkpoint inhibitor immunotherapy, and in-depth research is underway to use bacteria as immunotherapy tools because they have the ability to activate the immune system, which will be the basis for improving tumor immunotherapy (Osuna-Pérez J, García-Ferreras R, Veiga E. Fromcellular microbiology tobacteria-based next generations of cancer immunotherapies. Cell Microbiol 2020, 22 (4): e13187.). Studies have shown that the fungus Pseudomonas has antitumor activity against tumors (Chai X, Wang J, LiH, Gao C, Li S, Wei C, Huang J, TianY, Yuan J, Lu J, Gao D, Zheng Y, Huang C, Zhou J, ShiG, Ke A, Liu F, Fan J, Cai J. Intratumor microbiome features revealantitumorpotentials of intrahepatic cholangiocarcinoma. Gut Microbes 2023, 15(1): 2156255.).

[0005] Recent studies have extended the concept of DNA methylation epigenetic regulation to bacteria, showing that DNA methylation can also epigenetically control bacterial phenotypes (Rolando M, Silvestre CD, Gomez-Valero L, Buchrieser C. Bacterial methyltransferases: from targeting bacterial genomes to host epigenetics. Microlife 2022, 3: uqac014.). Epigenetic modification enzymes require appropriate substrates to catalyze changes in chromatin, and microbiota can synthesize a large number of biological compounds, including several compounds that serve as epigenetic substrates, cofactors, or regulators of epigenetic enzyme activity (Miro-Blanch J, Yanes O. Epigenetic Regulation at the Interplay Between Gut Microbiota and Host Metabolism. Front Genet 2019, 10: 638.; Shock T, Badang L, Ferguson B, Martinez-Guryn K. The interplay between diet, gut microbes, and host epigenetics in health and disease. J Nutr Biochem 2021, 95: 108631.). Changes in bacterial composition can affect the availability of SAM and, accordingly, alter the DNA or histone methylation status in the host (Woo V, Alenghat T. Epigenetic regulation by gut microbiota. Gut Microbes 2022, 14(1): 2022407.). Some intracellular pathogens are able to circumvent defense mechanisms that lead to epigenetic modifications in the host. These changes trigger alterations in chromatin structure and transcription levels of genes involved in the pathogenesis of many bacterial diseases. In this way, a better understanding of the epigenetic consequences of bacterial infection could open new avenues for therapeutic efficacy (Fol M, M, Druszczyńska M.Host Epigenetics in Intracellular Pathogen Infections. Int J Mol Sci 2020, 21(13).). DNA methylation can stabilize bacterial evolution. DNA methyltransferase plays a conservative function in maintaining the bacterial genome during bacterial evolution. In addition, the bacterial type II restriction modification (RM) system can distinguish methylation modifications between self-DNA and exogenous DNA, thereby preventing horizontal gene transfer (HGT) (Gao Q, LuS, WangY, He L, Wang M, Jia R, Chen S, Zhu D, Liu M, Zhao X, Yang Q, WuY, Zhang S, HuangJ, Mao S, Ou X, Sun D, Tian B, Cheng A. Bacterial DNA methyltransferase: A key to the epigenetic world with lessons learned from proteobacteria. Front Microbiol2023, 14: 1129437.).

[0006] In the colonic mucosa of colorectal cancer patients carrying phylotype A Gram-positive anaerobic cocci, DNA methylation changes and significant enrichment of differentially expressed genes in pathways involved in inflammation, cell adhesion and actin cytoskeleton regulation were found, providing evidence for a possible carcinogenic role of Pseudomonas micra (Bergsten E, Mestivier D, Donnadieu F, Pedron T, Barau C, Meda LT, Mettouchi A, Lemichez E, Gorgette O, Chamaillard M, Vaysse A, Volant S, Doukani A, Sansonetti PJ, Sobhani I, NigroG. Parvimonas micra, an oral pathobiont associated with colorectal cancer, epigenetically reprograms human colonocytes. Gut Microbes 2023, 15(2): 2265138.). In one study, quantitative PCR results showed that exposure of EBV-infected gastric cells (NC1-N87) to H. pylori for 48 hours increased the proliferation of EBV-infected cells and the expression level of DNA methyltransferase (MT), thereby silencing tumor suppressor genes (TSGs) that control many gastric cancer-related pathways (cell cycle, apoptosis, and DNA repair). Many host genes targeted by H. pylori remain methylated after eradication. In addition to H. pylori, several other bacteria also manipulate their hosts epigenetically (Capparelli R, Iannelli D. Epigenetics and Helicobacter pylori. Int J Mol Sci 2022, 23(3).). Genomic methylation in bacteria has broad effects on phage resistance, replication, genomic diversity through replication fidelity, response to stress, gene expression regulation and virulence (Chen P, Bandoy DJD, Weimer BC. Bacterial Epigenomics: Epigenetics in the Age of Population Genomics. In: Tettelin H, Medini D (eds). The Pangenome: Diversity, Dynamics and Evolution of Genomes. Springer Copyright 2020, The Author (s). Cham (CH), 2020, pp 233-252.).By studying the above-mentioned microbial action links and mechanisms, epigenetic regulation can be modified, thereby affecting the tumor treatment efficacy of immunotherapy and PD-1 inhibitors. Summary of the Invention

[0007] The present invention was completed based on the discovery that the therapeutic effect of tumor PD1 / PD-L1 inhibitors is correlated with the expression levels of the patient's microbial compositions Pseudomonas viridiflava and Rothia mucilaginosa.

[0008] In a first aspect, the present invention provides a group of biomarkers for predicting the prognostic effect of PD1 / PD-L1 in treating tumors, wherein the biomarkers include Pseudomonas viridiflava and / or Rothia mucilaginosa.

[0009] Furthermore, when the expression level of Pseudomonas viridiflava in the subject's biological sample is upregulated, that is, the expression level is ≥0.05311, the subject's tumor prognosis is good after PD1 / PD-L1 treatment.

[0010] Furthermore, when the expression level of Rothia mucilaginosa in the subject's biological sample is downregulated, that is, the expression level is ≤0.06214, the subject's tumor prognosis is poor after PD1 / PD-L1 treatment.

[0011] Furthermore, the biological sample of the subject is tissue.

[0012] Furthermore, the subject is a patient receiving PD1 / PD-L1 treatment for tumors.

[0013] Furthermore, the microorganism is an intratumoral bacterium.

[0014] In a second aspect, the present invention provides a method for preparing a reagent for predicting the prognostic effect of PD1 / PD-L1 in treating tumors, wherein the biomarker comprises Pseudomonas viridiflava and / or Rothiamucilaginosa.

[0015] Furthermore, when the expression level of Pseudomonas viridiflava in the subject's biological sample is upregulated, that is, the expression level is ≥0.05311, the subject's tumor prognosis is good after PD1 / PD-L1 treatment.

[0016] Furthermore, when the expression level of Rothia mucilaginosa in the subject's biological sample is downregulated, that is, the expression level is ≤0.06214, the subject's tumor prognosis is poor after PD1 / PD-L1 treatment.

[0017] Furthermore, the biological sample of the subject is tissue.

[0018] Furthermore, the subject is a patient receiving PD1 / PD-L1 treatment for tumors.

[0019] Furthermore, the microorganism is an intratumoral bacterium.

[0020] In a third aspect, the present invention provides a kit for predicting the prognostic effect of PD1 / PD-L1 in treating tumors, wherein the kit contains reagents for detecting the expression level of the markers described in the first aspect, and the biomarkers include Pseudomonas viridiflava and / or Rothia mucilaginosa.

[0021] Furthermore, when the expression level of Pseudomonas viridiflava in the subject's biological sample is upregulated, that is, the expression level is ≥0.05311, the subject's tumor prognosis is good after PD1 / PD-L1 treatment.

[0022] Furthermore, when the expression level of Rothia mucilaginosa in the subject's biological sample is downregulated, that is, the expression level is ≤0.06214, the subject's tumor prognosis is poor after PD1 / PD-L1 treatment.

[0023] Furthermore, the biological sample of the subject is tissue.

[0024] Furthermore, the subject is a patient receiving PD1 / PD-L1 treatment for tumors.

[0025] Furthermore, the microorganism is an intratumoral bacterium.

[0026] Furthermore, the kit may be one or more of a nucleic acid detection kit, an immunofluorescence kit, a gene chip detection kit, a molecular hybridization kit and / or an in situ hybridization staining kit.

[0027] Furthermore, the diagnostic method of the kit includes one or more of PCR method / qPCR method, linear probe method, high-resolution melting curve method and / or gene chip method.

[0028] Beneficial effects

[0029] The biomarkers applied for in the present invention are easy to sample and report results quickly. The biomarkers applied for in the present invention are highly accurate: the content of Pseudomonas viridiflava is low in the BT group and IMPD group, and high in the CP group and IMSD group. The ROC curve results show that the AUC value of Pseudomonas viridiflava for predicting the efficacy of immunotherapy in the screening set is 0.9063 (threshold 0.04386), and the AUC value for predicting the efficacy of immunotherapy in the validation set is 0.8056 (threshold 0.05311). The content of Rothia mucilaginosa is high in the BT group and IMPD group, and low in the CP group and IMSD group. The ROC curve results show that the AUC value of Pseudomonas viridiflava for predicting the efficacy of immunotherapy in the screening set is 0.8563 (threshold 0.06214), and the AUC value for predicting the efficacy of immunotherapy in the validation set is 0.7111 (threshold 0.06690). It has important scientific significance and clinical value in improving the personalized precision treatment application of immunotherapy, providing effective molecular targets for the personalized precision treatment of lung cancer patients, providing a basis for new intervention strategies, and providing more reliable lung cancer diagnosis and prognosis prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 To investigate the relationship between microbial abundance and PD-1 / PD-L1 efficacy in patients with lung cancer receiving immunotherapy.

[0031] Figure 2 To investigate the relationship between Pseudomonas viridiflava and Rothia mucilaginosa and PD-1 / PD-L1 efficacy in an expanded sample cohort of lung cancer patients receiving immunotherapy using qPCR.

[0032] Note: A is a screening study. The left figure shows the relative quantification results of Pseudomonas viridiflava and Rothia mucilaginosa by qPCR, and the right figure shows the corresponding receiver operating characteristic curve (ROC curve); B is a validation study. The left figure shows the relative quantification results of Pseudomonas viridiflava and Rothia mucilaginosa by qPCR, and the right figure shows the corresponding receiver operating characteristic curve (ROC curve).

[0033] Figure 3 The purpose of this study was to detect the relationship between Pseudomonas viridiflava and Rothia mucilaginosa and PD-1 / PD-L1 efficacy in patients with lung cancer treated with immunotherapy using multicolor immunohistochemistry + FISH probes.

[0034] Note: The left image is a representative picture, and the right image is the mean fluorescence quantitative density percentage of the corresponding samples. DETAILED DESCRIPTION

[0035] The following is a further description of specific embodiments of the present invention. It should be noted that the description of these embodiments is intended to facilitate understanding of the present invention and does not constitute a limitation of the present invention. In addition, the technical features involved in the embodiments described below may be combined with each other as long as they do not conflict with each other.

[0036] The experimental methods in the following examples are conventional methods unless otherwise specified, and the experimental materials used in the following examples are commercially available unless otherwise specified.

[0037] Explanation of terms

[0038] Post-treatment progression refers to changes in tissue structure, function, or pathological characteristics after treatment due to changes in the disease or pathological state. This phenomenon can occur across a variety of diseases and treatments, including cancer, inflammatory diseases, and complications after organ transplantation. In cancer treatment, post-treatment progression often manifests as tumor recurrence or metastasis.

[0039] Example 1 Relationship between microbial abundance and PD-1 / PD-L1 efficacy in immunotherapy of lung cancer patients

[0040] Fresh tissue for testing:

[0041] A total of 84 tissues were collected, including 22 adjacent normal tissues (NC group), 35 untreated tumor tissues (BT group), 9 stable tissues after treatment (IMSD group), and 18 progressive tissues after treatment (IMPD group).

[0042] A. Test Method

[0043] (1) DNA extraction and PCR amplification: After the genomic DNA extraction is completed, the extracted genomic DNA is detected by agarose gel electrophoresis;

[0044] (2) Fluorescence quantification: PCR products are quantified based on the preliminary electrophoresis results, and then mixed in appropriate proportions according to the sequencing requirements of each sample;

[0045] (3) Library construction and sequencing: Add the adapter sequence to the outer end of the target region through PCR; cut the gel to recover the PCR product,

[0046] Synthesize the target DNA fragment on the chip; calculate the fluorescence signal results to obtain the sequence of the template DNA fragment;

[0047] (4) Bioinformatics analysis: After the PEreads obtained by sequencing are sample split, the paired-end reads are first quality controlled and filtered according to the sequencing quality. At the same time, they are spliced according to the overlap relationship between the paired-end reads to obtain the optimized data after quality control splicing; the optimized data are processed to obtain ASV (Amplicon Sequence Variant) representing the sequence and abundance information.

[0048] B. Test Results

[0049] To eliminate the interference of contaminating bacteria introduced during the experimental operation, negative controls were used during DNA extraction and PCR amplification. By analyzing 16S rRNA sequencing data, DecontamCitation19 was used to remove contaminating bacteria in the operating environment and to determine the specific microbial composition of tissues from immunotherapy patients.

[0050] like Figure 1 As shown in A, after removing contaminating bacteria from the negative control and filtering out a single low-quality sample, the taxonomic classification level corresponded to 266 species, 602 genera, 282 families, 160 orders, 98 classes, 33 phyla, and 1 kingdom. Calculation of the spectral diversity index showed that the alpha diversity of the bacterial microbiota was much higher in the NC and IMSD groups than in the BT and IMPD groups.

[0051] Beta diversity of community species was calculated using PCoA1 and NMDS analysis (non-metric multidimensional scaling) methods, which characterize the similarity or difference in community composition between different subpopulations. Figure 1 As shown in B and 1C, there were significant differences in beta diversity between the NC and IMSD groups, and between the BT and IMPD groups. However, there was more overlap between the NC and IMSD groups, and between the BT and IMPD groups. The bacteria with high abundance in each group included Firmicute, Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacieria, and Cyanobaderia. The results of the study showed that the microbial composition patterns between the tissues were generally similar, but the microbial composition differences between the IMPD and IMSD groups were greater ( Figure 1 D). It was further found that the abundance of Pseudomonas viridiflava increased significantly in the NC and IMSD groups, while the abundance of Rothia mucilaginosa increased significantly in the BT and IMPD groups ( Figure 1 E and F). and are associated with metabolic pathways ( Figure 1 G).

[0052] Example 2 Relationship between Pseudomonas viridiflava and Rothia mucilaginosa and the efficacy of immunotherapy in patients with lung cancer treated with immunotherapy

[0053] A. Screening Test

[0054] A total of 20 cases of adjacent normal tissues (CP group), 31 cases of untreated tumor tissues (BT group), 24 cases of stable tissues after treatment (IMSD group), and 20 cases of progressive tissues after treatment (IMPD group) were selected.

[0055] (1) Test method

[0056] Extract DNA from tissues, measure concentration and store. Design qPCR primer sequences, amplify, collect fluorescence and make melting curves. -ΔCt The data were analyzed by the method, and the melting curve ensured the specificity of the product.

[0057] The qPCR primer sequences are as follows:

[0058] Primer pair 1: Pseudomonas viridiflava specific recognition primers.

[0059] Upstream primer: 5′-GAGAAGCTTGCTTCTCTTGA-3′;

[0060] Downstream primer: 5′-GGTCCCCTGCTTTCTCCCGT-3′.

[0061] Primer pair 2: Rothia mucilaginosa specific recognition primers.

[0062] Upstream primer: 5′-TAGCAGGGAAGAAGAGAGAT-3′;

[0063] Downstream primer: 5′-CCCGTACCCACTGCAATACA-3′.

[0064] Wherein, the internal reference primer used for normalization is a primer using Albumin as an internal reference,

[0065] Upstream primer: 5′-TGTTGCATGAGAAAACGCCA-3′;

[0066] Downstream primer: 5′-GTCGCCTGTTCAACCAAGGAT-3′.

[0067] The qPCR amplification reaction system is as follows:

[0068]

[0069]

[0070] (2) Test results

[0071] like Figure 2 As shown in A, the content of Pseudomonas viridiflava in the screening set was low in the BT and IMPD groups, but high in the CP and IMSD groups. The ROC curve results showed that the AUC value of Pseudomonas viridiflava for predicting immunotherapy efficacy in the screening set was 0.9063 (threshold value 0.04386). The content of Rothia mucilaginosa was high in the BT and IMPD groups, but low in the CP and IMSD groups. The ROC curve results showed that the AUC value of Rothia mucilaginosa for predicting immunotherapy efficacy in the screening set was 0.8563 (threshold value 0.06214).

[0072] B. Verification test

[0073] Thirty cases of adjacent normal tissues (CP group), 48 cases of untreated tumor tissues (BT group), 36 cases of stable tissues after treatment (IMSD group), and 30 cases of progressive tissues after treatment (IMPD group) were selected.

[0074] (1) Test method

[0075] Extract DNA from tissues, measure concentration and store. Design qPCR primer sequences, amplify, collect fluorescence and make melting curves. -ΔCt The data were analyzed by the method, and the melting curve ensured the specificity of the product.

[0076] The qPCR primer sequences are as follows:

[0077] Primer pair 1: Pseudomonas viridiflava specific recognition primers.

[0078] Upstream primer: 5′-GAGAAGCTTGCTTCTCTTGA-3′;

[0079] Downstream primer: 5′-GGTCCCCTGCTTTCTCCCGT-3′.

[0080] Primer pair 2: Rothia mucilaginosa specific recognition primers.

[0081] Upstream primer: 5′-TAGCAGGGAAGAAGAGAGAT-3′;

[0082] Downstream primer: 5′-CCCGTACCCACTGCAATACA-3′.

[0083] Wherein, the internal reference primer used for normalization is a primer using Albumin as an internal reference,

[0084] Upstream primer: 5′-TGTTGCATGAGAAAACGCCA-3′;

[0085] Downstream primer: 5′-GTCGCCTGTTCAACCAAGGAT-3′.

[0086] The qPCR amplification reaction system is as follows:

[0087]

[0088]

[0089] (2) Test results

[0090] like Figure 2 As shown in Figure B, in the screening set, Pseudomonas viridiflava levels were low in the BT and IMPD groups and high in the CP and IMSD groups. The ROC curve showed that the AUC value of Pseudomonas viridiflava for predicting immunotherapy efficacy in the validation set was 0.8056 (threshold value 0.05311). Rothia mucilaginosa levels were high in the BT and IMPD groups and low in the CP and IMSD groups. The ROC curve showed that the AUC value of Rothia mucilaginosa for predicting immunotherapy efficacy in the validation set was 0.7111 (threshold value 0.06690).

[0091] Example 3 Multicolor immunohistochemistry + FISH probe detection of Pseudomonas viridiflava and Rothia mucilaginosa in patients with immunotherapy for lung cancer and their relationship with immunotherapy efficacy

[0092] Twenty patients who received immunotherapy were selected, including 11 patients with stable tissue after treatment (IMSD group) and 9 patients with progressive tissue after treatment (IMPD group).

[0093] A. Test Method

[0094] (1) Multicolor immunohistochemical staining

[0095] Perform multicolor immunohistochemical analysis on tissue using a fluorescent immunohistochemistry kit. 4 μm tissue sections were then baked, dewaxed, hydrated, fixed, incubated, and blocked. Incubate with the primary antibody: CK antibody; add the secondary antibody and continue incubation.

[0096] (2) FISH in situ hybridization

[0097] Tissues were analyzed using a fluorescent in situ hybridization kit for DNA-FISH. Following RNase treatment, aging, digestion, probe and sample denaturation, hybridization, washing, and nuclear staining with DAPI, the tissues were observed under a fluorescence microscope.

[0098] The FISH-specific probe sequences are as follows:

[0099] Probe 1: Pseudomonas viridiflava specific recognition probe:

[0100] 5'-FITC GTCAACTTAATGCGTTAGCTGCGCCACTAAAATCTCA-3';

[0101] Probe 2: Rothia mucilaginosa specific recognition probe:

[0102] Upstream primer: 5'-CY3 CGCTTTCCACCAACACCCCATGCGGAGATTGGTCGTAT-3'; B. Experimental results

[0103] FISH in situ hybridization was used to detect the relative contents of Pseudomonas viridiflava and Rothia mucilaginosa in 20 patients who received immunotherapy, including 11 cases of stable tissues after treatment (SD group) and 9 cases of progressive tissues after treatment (IMPD group), and their relationship with the efficacy of immunotherapy. Figure 3 As shown, in the tumor tissue area, the content of Pseudomonas viridiflava in lung cancer cells of patients who progressed after treatment showed a down-regulation pattern (the difference in mean density ± standard deviation was -1.182 ± 0.5794, p = 0.0563). The content of Rothia mucilaginosa in lung cancer cells of patients who progressed after treatment showed an up-regulation pattern (the difference in mean density ± standard deviation was 0.4980 ± 0.1576, p = 0.0054).

Claims

1. A group of biomarkers for predicting the prognostic effect of PD1 / PD-L1 treatment of tumors, wherein the biomarkers include Pseudomonas viridiflava and / or Rothia mucilaginosa.

2. The biomarker of claim 1, wherein when the expression level of Pseudomonas viridiflava in the biological sample of the subject is upregulated, i.e., the expression level is ≥0.05311, the subject has a good prognosis for PD1 / PD-L1 treatment of the tumor.

3. The biomarker of claim 1, wherein when the expression level of Rothia mucilaginosa in the biological sample of the subject is downregulated, i.e., the expression level is ≤0.06214, the subject has a poor prognosis for PD1 / PD-L1 treatment of the tumor. The biomarker according to any one of claims 2 and 3, wherein the biological sample of the subject is a tissue.

5. Use of the marker according to claim 1 in the preparation of a reagent for predicting the prognostic effect of PD1 / PD-L1 in treating tumors, wherein the biomarker comprises Pseudomonas viridiflava and / or Rothia mucilaginosa.

6. The reagent according to claim 5, wherein when the expression level of Pseudomonas viridiflava in the biological sample of the subject is upregulated, that is, the expression level is ≥0.05311, the subject has a good prognosis for PD1 / PD-L1 treatment of the tumor.

7. The reagent of claim 5, wherein when the expression level of Rothia mucilaginosa in the biological sample of the subject is downregulated, i.e., the expression level is ≤0.06214, the prognosis of the subject's tumor after PD1 / PD-L1 treatment is poor.

8. A kit for predicting the prognostic effect of PD1 / PD-L1 in treating tumors, the kit comprising reagents for detecting the expression level of the markers according to claim 1, wherein the biomarkers include Pseudomonas viridiflava and / or Rothiamucilaginosa.

9. The kit according to claim 8, wherein the kit is selected from one or more of a nucleic acid detection kit, an immunofluorescence kit, a gene chip detection kit, a molecular hybridization kit and / or an in situ hybridization staining kit.

10. The kit according to claim 8, wherein the diagnostic method of the kit comprises one or more of PCR / qPCR, line probe, high-resolution melting curve and / or gene chip methods.

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