| Background: Malignant Melanoma(MM)is one of the most aggressive malignant tumors.It has the characteristics of insidious disease,easy metastasis,and poor response to treatment.Its deaths account for 80% of the total deaths from skin tumors.Most patients have distant metastases before they are diagnosed.Due to the limited effective treatments and drugs in the late stage of the disease,the overall survival of the patients with metastases is only about 6-9 months,and the3-year survival rate is less than 15%.The amount of the patients benefited from the latest approved immunotherapy for metastatic melanoma based on therapeutic drugs including molecularly targeted KRAS inhibitors and anti-cytotoxic T lymphocyte antigen(CTLA)-4antibody Ipilimumab is still quite limited,and it is almost impossible to predict the serious side effects of different individuals with treatment.Therefore,it is very important for improving the treatment of MM to identify and screen out markers high-specifically and high-selectively related to the prognosis of patients with metastasis,and to predict the benefit groups for screening new treatment methods accordingly.This is also likely to help discover potential targets for developing new drugs of MM in the future.Objective: Through analyzing and screening out the differentially expressed genes in samples from primary and metastatic cases of MM,to construct a prognostic risk model for MM patients,to explore the impact of prognostic risk model genes on the tumor microenvironment,to analyze the relationship between gene markers and the malignant degree of MM and the complex characteristics of immune tolerance,and to obtain the functional evidence that gene markers affect the malignant behavior of melanoma,thus providing a reference for improving the clinical decision-making in treatment of patients with MM metastasis and developing related new drugs.Methods:(1)To screen out gene signatures:1)The genome expression profile and survival data of MM cases in the TCGA database were downloaded with bioinformatics methods.The inclusion and exclusion criteria were strictly formulated based on the clinical characteristics and treatment interventions of cases to ensure the base data of the primary and the metastasis cases comparable before the differentially expressed genes of the two sets of cases being analyzed.2)The immune-related gene signature(IRGS)was obtained from the base differentially expressed genes being intersected with the immune-related gene data set of the Imm Port database.3)The observed survival interval(OBS,the time interval from TCGA sampling to the death of the patient or the last follow-up)was used instead of the overall survival time(OS)to ensure the accuracy of the prognostic time;in order to exclude the influence of the clinical phenotype and treatment interventions of the included cases on the results,the age,gender,stage,Clark score,and Breslow thickness values of cases were included for univariate and multivariate stepwise Cox risk ratio regression analysis to construct and verify the prognosis predicting model,followed by the included model being verified based on the AUC(area under the curve)of ROC curve,which was constructed through the "survminer" package of R software.4)The relative abundance of immune infiltrating lymphocytes in MM samples was reconstructed by CIBERSORTx deconvolution method,and Spearman correlation analysis was used to determine the correlation between prognostic model genes and immune infiltrating lymphocytes;5)In order to further verify the results of deconvolution calculations,MM single-cell sequencing data has been collected in this study and verified the results of deconvolution calculations.The correlation between metastatic prognostic gene markers and the subgroups of immune infiltrating lymphocytes was analyzed with sc RNA-seq dataset.(2)To verify the gene signatures:1)The characteristics of the gene signatures,including the location of the target protein in the cell,the expression level of tumor tissue and the characteristics of immunohistochemistry were verified by using the human protein atlas(The human protein atlas,HPA)database of human tumor samples immunomics data;the prognostic effects of the gene signature lacking immunohistochemical data on a variety of tumors were verified by meta-analysis of the HR for prognosis of some type cancers use TCGA pan-cancer data;2)Experimental study of CXCR4 gene promoting the invasion and metastasis of A375 cells:the CXCR4 gene was knocked out based on the guide RAN(small guide RNA,sg RNA)with the Cas9 technology to construct melanoma cell line sg-A375 cells model,and the functional evidences of the effect of the CXCR4 on the biological behavior of melanoma cells were obtained through scratch experiment,transwell experiment,and CCK-8 experiment.Results:(1)Through a series of analyses,a gene signature model composed of 6 IRGs(SLPI,S100A7,LYZ,CCL19,CXCR4 and CD79A)that can predict the prognosis of patients with MM metastasis was constructed.This model can distinguish the prognostic risk of patients with metastatic MM between different clinical phenotypes in the training set(TCGA,n = 226,log-rank test,P <0.001);and the 6 IRGs are independent prognostic risk factors of MM,and are not affected by clinical characteristics such as gender,age and pathological stage(HR=20.84,95% CI:5.00 86.93,P <0.001);the validation results in the GEO independent datasets showed that the model can also effectively predict the prognosis of metastatic patients(GSE19234,n = 106,log-rank test,P <0.001,GES53118,n = 79,log-rank test,P < 0.001).The effectiveness of the model was also verified through the ROC curve;the relative abundance of immune infiltrating cells was estimated by CIBERSORTx,and the 6 IRGSs all showed a certain correlation with immune-infiltrating cells and immune-checkpoint genes(ICGs).(2)The sc RNA-seq analysis software and methods were used to analyze the cell characteristics and cluster classification of samples from MM metastatic cases in the GEO(GSE72056)sc RNA-seq dataset.The results showed that the sample cells can be divided into 18 categories after annotation.Among them,tumor cell subsets related to the immune microenvironment included the B cells,DC cells,fibroblasts,granulocyte colony stimulating factor,CD34 hematopoietic stem cells,neuroepithelial cells,neuronal cells,neutrophils,NK cells,precursor CD34 B cells,advanced CD34 B cells,promyelocytic cells,T cells and tissue stem cells.Compared with the tumor microenvironment of samples from the primary case,the abundance of the above-mentioned cells(except NK cells and T cells)in the samples of lymph node metastasis cases have significant differences in the content of immune infiltrating cells(P <0.001).The three gene signatures(CXCR4,LYZ and CD79A)were significantly correlated with the above-mentioned differential cells in single cells dataset(P <0.001).Among them,CXCR4 had a high correlation with a variety of immune infiltrating cells,so CXCR4 was believed the most valuable experimental verification object for later biological experiments to verify its function.(3)Based on the immunohistochemical data of 102 MM samples in the HPA database,the protein expression results of 5 IRGS(SLPI,S100A7,LYZ,CCL19 and CD79A)were verified and analyzed,indicating that LYZ and CD79 A showed low protein expression in malignant melanoma,And the three genes of SLPI,S100A7 and CCL19 all showed clear protein expression.There lacked proteochemistry data of CXCR4 in the HPA database,so the prognostic hazard ratio(HR)of CXCR4 for a variety of tumors other than malignant melanoma were analyzed based on the TCGA pan-cancer data by a meta-analysis.The meta-analysis result showed that CXCR4 had a predictive effect on the overall survival(OS)of gastric cancer,osteosarcoma,ovarian cancer,lung adenocarcinoma,renal clear cell carcinoma,head and neck cancer,esophageal adenocarcinoma,and cervical cancer(P < 0.001),among which,CXCR4 is a protective factor for the prognosis of gastric cancer and renal clear cell carcinoma(HR<1),and a risk factor for other tumors(HR>1).The meta-analysis of CXCR4 on the Relapse-Free Survival(RFS)prognostic HR of patients showed that the high expression of CXCR4 can be ae predictor for the prognosis of gastric cancer,ovarian cancer,lung adenocarcinoma,renal clear cell carcinoma and bladder cancer(P <0.001),among which,it is a protective factor for RFS of patients with gastric cancer,lung adenocarcinoma and renal clear cell carcinoma(HR<1),while a high-risk factor for ovarian cancer and bladder cancer(HR>1).(4)The results of the biological experiments to verify the relationship between CXCR4 and the proliferation and metastasis of MM: The sg-A375 cells were constructed by CXCR4 of A375 cells being knocked out with sg-RNA transfection Cas9 technology.The results of the scratch test and transwell chamber test showed that,compared with A375 cells,the scratch repair ability,migration and invasion capabilities of sg-A375 cells were significantly reduced,indicating that knocking out CXCR4 may inhibit the proliferation,invasion and migration of melanoma and that the high expression of CXCR4 in MM can be associated with poor prognosis of patients.Conclusions:(1)The 6-gene IRGS,SLPI,S100A7,LYZ,CCL19,CXCR4 and CD79 A,obtained through analyzing the differential genes between the primary and the metastatic MM samples and being verified in independent data sets,can be taken as prognostic gene signature for patients with metastatic MM.(2)The results from single-cell analysis indicated that the infiltration of B cells,granulocyte colony stimulating factor,neutrophils and fibroblasts in the metastatic MM samples is related to the prognosis of patients with MM,and the abundance of these infiltrating cells is positively correlated with the expression of immune prognosis related genes.(3)The results of validation of gene signatures with HPA database showed that the protein expressions of the 5 genes,SLPI,S100A7,LYZ,CCL19 and CD79 A can be verified in the database;the meta-analysis results based on the pan-cancer data showed that CXCR4 had a good predictive effect for both OS and RFS of patients with a variety of tumors and played different prognostic role in different tumors.(4)CXCR4 plays an important role in the growth and proliferation of A375 cells.CXCR4 can be closely related to cell migration and invasion behavior,and may change the prognosis of patients by affecting the immune microenvironment. |
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