SMAD2 and p38 MAPK as markers for evaluating effect of immunotherapy on mucosal melanoma

Abstract

The invention relates to the technical field of diagnostic markers, in particular to a marker for evaluating the effect of immunotherapy of mucosal melanoma and application of the marker. Researches show that patients with low scores of the p38MAPK and / or SMAD2 regulators show obviously longer progression-free lifetime (PFS) and overall lifetime (OS) compared with patients with high scores, which indicates that the patients and the SMAD2 regulators can play an important role in prognosis effect evaluation of mucosal melanoma immunotherapy.

Description

Technical Field

[0001] The present invention relates to the technical field of diagnostic markers, and in particular to a marker for evaluating the effect of immunotherapy for mucosal melanoma and its application. Background Art

[0002] According to the site of onset and the degree of sun damage, melanoma can be divided into four subtypes: cutaneous, acral, mucosal, and choroidal. Among them, mucosal melanoma accounts for 22.6% of the incidence in my country. Compared with skin melanoma, mucosal melanoma has significant differences in epidemiology and molecular mechanisms, and progresses rapidly. In recent years, with the advent of immune checkpoint inhibitors, there has been a breakthrough in the treatment of advanced skin melanoma, and the efficacy of PD-1 monoclonal antibody in the first-line treatment of melanoma is as high as 42-45%. The response of mucosal melanoma to PD-1 monoclonal antibody is significantly lower than that of skin melanoma in both Asian and Western Caucasian populations, and the objective response rate is only 13-23%. Although the combination of PD-1 monoclonal antibody and antivascular drugs has increased the response rate of mucosal melanoma to 45-48%, half of mucosal patients still face the dilemma of no cure in clinical practice. On the other hand, immunotherapy is a double-edged sword, often causing varying degrees of side effects, and even life-threatening. However, the commonly used predictive indicators of immunotherapy efficacy, such as the expression level of PD-L1 in tumor cells, the number of tumor-infiltrating lymphocytes, and the tumor mutation load, are not applicable to patients with mucosal melanoma. Therefore, it is of great practical significance to accurately screen the best beneficiary population for the use of PD-1 monoclonal antibody monotherapy and combined therapy in patients with mucosal melanoma, improve the efficacy, and reduce the incidence of treatment side effects. At present, there are few studies on biomarkers for predicting or evaluating the effect of immunotherapy for mucosal melanoma. In view of this, the present invention is proposed. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a marker for evaluating the effect of immunotherapy for mucosal melanoma and its application.

[0004] Specifically, the technical solution of the present invention is as follows:

[0005] In a first aspect, the present invention provides a use of a marker in preparing a product for predicting or evaluating the effect of immunotherapy for mucosal melanoma, wherein the marker comprises SMAD2 and / or p38 MAPK.

[0006] Preferably, the immunotherapy is a combination of immune checkpoint inhibitors and anti-vascular therapy.

[0007] In a second aspect, the present invention provides a product for predicting or evaluating the effect of immunotherapy for mucosal melanoma, wherein the product comprises a reagent or a kit for detecting the expression level of SMAD2.

[0008] Alternatively, the product includes a reagent or kit for detecting the expression level of p38 MAPK.

[0009] Preferably, the product comprises a reagent or a kit for detecting the expression levels of SMAD2 and p38 MAPK.

[0010] In a third aspect, the present invention provides a device for predicting or evaluating the effect of immunotherapy for mucosal melanoma, the device comprising: a detection module, used to detect the content of a marker in a sample to be tested; the marker comprises SMAD2 and / or p38 MAPK; an input module, used to obtain the detection result of the detection module; a judgment module, used to compare the detection result obtained by the input module with the judgment standard to judge the effect of immunotherapy for mucosal melanoma; and an output module, used to output the diagnosis result.

[0011] Preferably, the judgment criteria of the judgment module include: if the level of SMAD2 and / or p38 MAPK is low, it is judged that the effect of immunotherapy for mucosal melanoma or the prognosis is good.

[0012] Preferably, the sample to be tested is tumor tissue.

[0013] Beneficial effects:

[0014] The present invention provides a marker for evaluating the effect of immunotherapy for mucosal melanoma and its application, wherein the marker includes SMAD2 and / or p38 MAPK. The present invention's research shows that patients with lower scores of p38 MAPK and / or SMAD2 regulators show significantly longer progression-free survival (PFS) and overall survival (OS) than patients with higher corresponding scores, indicating that the two can play an important role in the evaluation of the prognostic effect of immunotherapy for mucosal melanoma. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be described below.

[0016] Figure 1 To investigate the differences in factors associated with immunotherapy efficacy among different responders of mucosal melanoma. Figure 1 Figure a in the middle shows the expression differences of the gene set related to immunotherapy efficacy between different response groups of mucosal melanoma. Figure 1 Figure b shows the differences in immunotherapy efficacy-related characteristic scores between different response groups of mucosal melanoma.

[0017] Figure 2 To explore strategies for factors related to the efficacy of immunotherapy for mucosal melanoma. Figure 2Figure a in the middle is a hierarchical clustering diagram of modules divided by weighted gene co-expression network analysis (WGCNA). Figure 2 Figure b in the middle is a correlation heat map, and each cell represents the Pearson correlation coefficient and the corresponding p-value. Figure 2 Figure c in the middle shows pathway enrichment (GO) analysis, showing the top ranked pathways.

[0018] Figure 3 To investigate the correlation between p38 MAPK pathway scores and survival and immune infiltration in mucosal melanoma after immunotherapy. Figure 3 Figure a in the middle shows the Kaplan-Meier survival analysis, which stratifies the patients according to the p38 MAPK pathway expression score to analyze the progression-free survival (PFS). Figure 3 Figure b in the middle is the Kaplan-Meier survival analysis, which stratifies the overall survival (OS) according to the p38 MAPK pathway expression score. Figure 3 Figure c in the middle is the heat map of Stromal Score, Immune Score, ESTIMATEScore and immune infiltrating cells in the p38MAPK high score group and low score group. Figure 3 Figure d in the middle shows the correlation between the tumor "cold" and "hot" scores of patients in the p38 MAPK high score group and the low score group. Figure 3 Figure e in the middle shows the comparison of Stromal Score, Immune Score and ESTIMATE Score between the p38 MAPK high score group and the low score group.

[0019] Figure 4 The expression levels of genes related to co-stimulation and antigen presentation were different between the p38 MAPK high score group and the low score group.

[0020] Figure 5 The differences in immune cell infiltration levels and immunotherapy efficacy-related characteristic scores between the p38 MAPK high score group and the low score group. Figure 5 Figure a in the middle shows the infiltration of CD45+ and cytotoxic cells in the p38 MAPK high score group and low score group analyzed by ssGSEA. Figure 5 Figure b shows the scores of cytotoxicity, IFNγ, myeloid inflammation, and immune response-related features in the p38 MAPK high-score group and the low-score group.

[0021] Figure 6 The difference in methylation levels between immunotherapy responders and non-responders in mucosal melanoma. Figure 6 Figure (a) is an unsupervised hierarchical cluster analysis based on 7710 differentially methylated sites (DMCs), which effectively divides the responder group and the non-responder group into two different clusters. Figure 6 Figure b in the middle shows that the β value of the response group was significantly higher than that of the non-response group. Figure 6 Figure c in the middle shows the DNA methylation pattern and gene expression profile in the integrated patient samples. Red dots represent genes with high methylation and significantly decreased expression in responders, orange dots represent genes with low methylation and significantly increased expression in responders, blue dots represent genes with high methylation but significantly increased expression in responders, and green dots represent genes with low methylation but significantly decreased expression in responders.

[0022] Figure 7 The correlation between SMAD2 and the efficacy of immunotherapy for mucosal melanoma. Figure 7 Figure a in the middle is a heat map of the specific gene regulatory network of the regulatory region analysis of the treatment response group and the non-response group. Figure 7 Figure b compares the SMAD2 regulator scores of responders and non-responders. Figure 7 Figure c in the middle compares the SMAD2 regulator scores of the p38 MAPK high score group and the low score group. Figure 7 Figure d in the middle shows the Kaplan-Meier analysis of the difference in progression-free survival (PFS) between high and low SMAD2 regulator scores. Figure 7 Figure e in the middle shows the Kaplan-Meier analysis of the overall survival (OS) difference between high and low SMAD2 regulator scores. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] The endpoints and any values ​​of the ranges disclosed in this specification are not limited to the precise ranges or values, and these ranges or values ​​should be understood to include values ​​close to these ranges or values. For numerical ranges, the endpoint values ​​of each range, the endpoint values ​​of each range and the individual point values, and the individual point values ​​can be combined with each other to obtain one or more new numerical ranges, which should be considered as specifically disclosed in this article.

[0025] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "specific implementations", or "some specific implementations" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0026] In the examples provided in this specification, if no specific techniques or conditions are specified, the techniques or conditions described in the literature in this field or the product instructions are used. If the manufacturer of the reagents or instruments used is not specified, they are all conventional products that can be purchased through regular channels.

[0027] Example 1

[0028] (1) Experimental procedure.

[0029] Data from patients with unresectable or metastatic mucosal melanoma treated with atezolizumab and bevacizumab. Atezolizumab was administered by intravenous infusion every 3 weeks at a fixed dose of 1200 mg. Bevacizumab was administered by intravenous infusion at a dose of 7.5 mg / kg every 3 weeks. Radiographic evaluation was performed according to Response Evaluation Criteria in Solid Tumors (v1.1), and the evaluation results included complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). The objective response rate (ORR) was the percentage of patients with CR and PR. Patients were divided into two groups according to the degree of response: responder group (CR or PR) and nonresponder group (SD or PD). Progression free survival (PFS) was defined as the duration from the start of treatment to disease progression or the last follow-up. Overall survival (OS) was defined as the duration from the start of treatment to death or the last follow-up.

[0030] Formalin-fixed paraffin-embedded (FFPE) tumor tissue samples were collected for combined DNA and RNA extraction. RNA extracted from tumor samples was reverse transcribed into cDNA using Ribo-SPIA technology, and mRNA libraries were constructed, sequenced, and quality control of FASTQ data was performed. Low-quality reads and reads containing adapter sequences were filtered out. HISAT (v2.0.4) was used to align to the human genome (hg19), and StringTie (v1.2.3) was used for transcriptome assembly to generate a comprehensive gene expression profile. Limma software was used to perform differential expression analysis of genes between different groups. Significantly differentially expressed genes were screened by thresholds of |log2fold-change|>1 and FDR<0.05. Gene set enrichment analysis was performed using the R package clusterProfiler, and the gene sets used included the KEGG, Hallmark, GO, and Reactome collections of the Molecular Signature Database (MSigDB). Pathways with adjusted P values ​​less than 0.05 were considered significant and included in the analysis. The level of immune cell infiltration was evaluated by the single-sample gene set enrichment analysis (ssGSEA) method using the GSVA package in R software. To explore genes associated with the responder and non-responder groups, weighted gene co-expression network analysis (WGCNA) analysis was performed using the R package WGCNA under default parameters. Module genes with significant Spearman correlation with clinical efficacy were selected, and then biological pathway enrichment analysis was performed on the selected modules.

[0031] Methylome detection was performed using targeted bisulfite sequencing (TBS). DNA extracted from FFPE samples was treated with bisulfite and sequencing libraries were constructed. Sequencing was performed on the Illumina HiSeq platform using the Roche SeqCap Epi 4M CpGiant probe. Raw sequencing data were demultiplexed using bcl2fastq and quality controlled using Trimmomatic. PCR duplicates were removed using deduplicate_bismark. High-quality reads were aligned to the human reference genome (hg19) using the Bismark alignment tool. Methylation sites were detected using AsTair software, and the methylation level of each site was quantified using the β value. Differentially methylated sites were analyzed using the methylKit R package, with the screening criteria of methylation level greater than 0.1 and CpG coverage of at least 10. Data were further screened by 2D-KS and Mann-Whitney U tests, with a significance threshold of P < 0.05, and multiple testing correction was performed using the Benjamini-Hochberg method to control the false discovery rate. The distribution of differentially methylated genes on chromosomes was annotated and visualized using the ChIPseeker R package. GO enrichment analysis was performed on hypermethylated and hypomethylated genes using matescape software, with a significance threshold of P value < 0.01. HOMER software and R package RTN were used to construct a transcriptional regulatory network (regulator) associated with clinical response.

[0032] (2) The relationship between p38 MAPK pathway activation and treatment response.

[0033] The present invention explored whether the gene sets previously reported to be associated with the response to immunotherapy of skin melanoma can distinguish between responders and non-responders. However, none of these gene sets could effectively distinguish between the two groups of patients ( Figure 1 In addition, no significant differences were observed between the non-responder and responder groups in terms of feature scores such as T cell toxicity, IFNγ, bone marrow inflammation, and immune response-related features ( Figure 1 Therefore, the present invention performed a weighted gene co-expression network analysis to find factors highly correlated with prognosis. The significant spearman correlations between eigengene values ​​and clinical efficacy were determined and selected for further analysis ( Figure 2 Figures a and b in the middle). Biological pathway enrichment analysis was performed on these selected characteristic genes, and the results showed that genes related to the p38 MAPK pathway were significantly correlated with clinical efficacy ( Figure 2Patients with low p38 MAPK scores showed significantly longer PFS than those with high p38 MAPK scores (median 11.7 months, 95% CI, 8.4 to 16.8 months vs 4.15 months, 95% CI, 2.2 to 12.6 months; HR = 0.41, 95% CI, 0.15 to 1.12; P = 0.024; Figure 3 (a) and OS (median 36.0 months, 95% CI, 28.27 to 43.2 months vs 14.3 months, 95% CI, 8.47 to 23.7 months; HR = 0.16, 95% CI, 0.05 to 0.59; P < 0.001; Figure 3 In addition, the lower the p38MAPK value, the "hotter" the tumor immune microenvironment, the higher the infiltration of activated CD8+T cells, activated DCs, central memory CD8+T cells, and natural killer T cells, and the higher the immune score ( Figure 3 Patients with low p38 MAPK scores had significantly higher levels of genes related to co-stimulation and antigen presentation compared with those with high p38 MAPK scores ( Figure 4 ssGSEA analysis confirmed that the patient group with low p38 MAPK score had higher CD45+ and cytotoxic cell infiltration ( Figure 5 The scores of the above T cell toxicity, IFNγ, myeloid inflammation and immune response-related characteristics were higher in the low p38 MAPK group than in the high p38 MAPK group ( Figure 5 (Fig. b).

[0034] (3) The gene regulatory network revealed by methylation and transcriptome mapping confirmed the relationship between SMAD2 and treatment response.

[0035] The methylation profiles were derived from TBS data of 9 responders and 10 non-responders. Unsupervised hierarchical clustering analysis based on 7710 differentially methylated sites (DMCs) effectively divided the responder and non-responder groups into two different clusters ( Figure 6 The β value of the response group was significantly higher than that of the non-response group ( Figure 6 Figure b, P < 0.001), indicating that the methyl group of the response group is different from that of the non-response group, and the frequency of gene hypermethylation in the response group is higher. In order to explore the significance of DNA methylation in gene expression regulation, the present invention integrated the DNA methylation pattern in patient samples with the gene expression profile. The correlation between 43 DEGs and 103 DMCs is as follows Figure 6 As shown ( Figure 6Figure c, |log2FC|>1, |DMC beta value|>0.1, P<0.05). The present invention uses regulatory region analysis to explore specific gene regulatory networks that may affect treatment response. By comparing the regulator scores, the present invention detected the key regulators of each sample and found that SMAD2, PRDM15, TCF4, TEAD2 and TEAD5 were the most important regulators in the cohort ( Figure 7 The SMAD2 regulator score in the response group was significantly lower than that in the non-response group (P = 0.01, Figure 7 The p38 MAPK low score group was lower than the p38 MAPK high score group (P = 0.005, Figure 7 In addition, patients with lower SMAD2 regulator scores had longer PFS than those with higher SMAD2 regulator scores (median 13.4 months, 95% CI, 9.77 to 16.8 months vs 2.77 months, 95% CI, 2.57 to 8.4 months; HR = 0.46, 95% CI, 0.19 to 1.12; P = 0.043; Figure 7 (middle d panel) and OS (median 31.3, 95% CI, 23.5 to 43.2 months vs 19.5, 11.7 to 34.0 months; HR = 0.48, 95% CI, 0.19 to 1.21; P = .07; Figure 7 (Fig. e).

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. Use of a marker in the preparation of a product for predicting or evaluating the effect of immunotherapy for mucosal melanoma, characterized in that: The markers include SMAD2 and / or p38 MAPK.

2. The use according to claim 1, characterized in that: The immunotherapy is a combination of immune checkpoint inhibitors and anti-vascular therapy.

3. A product for predicting or evaluating the effect of immunotherapy for mucosal melanoma, characterized in that: The product includes a reagent or a kit for detecting the expression level of SMAD2.

4. A product for predicting or evaluating the effect of immunotherapy for mucosal melanoma, characterized in that: The product comprises a reagent or a kit for detecting the expression level of p38MAPK.

5. A product for predicting or evaluating the effect of immunotherapy for mucosal melanoma, characterized in that: The product includes a reagent or a kit for detecting the expression levels of SMAD2 and p38 MAPK.

6. A device for predicting or evaluating the effect of immunotherapy for mucosal melanoma, characterized in that: The device comprises: a detection module, used for detecting the content of a marker in a sample to be tested; the marker comprises SMAD2 and / or p38 MAPK; an input module, used for obtaining the detection result of the detection module; a judgment module, used for comparing the detection result obtained by the input module with the judgment standard to judge the effect of immunotherapy for mucosal melanoma; and an output module, used for outputting the diagnosis result.

7. The device for predicting or evaluating the effect of immunotherapy for mucosal melanoma according to claim 6, characterized in that: The judgment criteria of the judgment module include: if the level of SMAD2 and / or p38MAPK is low, it is judged that the effect of immunotherapy for mucosal melanoma or the prognosis is good.

8. The device for predicting or evaluating the effect of immunotherapy for mucosal melanoma according to claim 7, characterized in that: The sample to be tested is tumor tissue.

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