基于免疫微环境构建皮肤黑色素瘤的风险预测模型

A risk score model was constructed to predict cutaneous melanoma based on immune microenvironment

目的分析皮肤黑色素瘤(SKCM)免疫微环境相关基因,筛选新的标志物以预测SKCM患者的预后。方法癌症基因组图谱(TCGA)数据库下载SKCM患者的公共测序数据,使用表达数据估计恶性肿瘤中的间质和免疫细胞(ESTIMATE)算法分析SKCM的免疫评分和基质评分,加权基因共表达网络分析(WGCNA)和差异表达分析筛选出与免疫微环境相关的关键基因,单因素和最小绝对收缩和选择算子(LASSO)回归模型用来构建SKCM的风险预测模型。最后,单因素和多因素Cox回归分析评估风险预测模型的独立预后价值。结果本研究通过单因素和LASSO回归分析,从173个免疫微环境相关的基因筛选出的5个(HLA-DRB1、XCL2、CCR1、HLA-DQB2和DERL3)基因,成功的构建了一种新的风险预测模型。基于风险预测模型分组的高危组患者总生存期(OS)显著短于低危组患者(P<0.01)。风险评分模型的独立预后分析证明其是独立预后指标[风险比(HR)=2.823,95%可信区间(CI):1.778~4.481,P<0.01]。结论HLA-DRB1、XCL2、CCR1、HLA-DQB2和DERL3基因构建的风险模型对SKCM具有较好的预后判断价值。

Objective To analyze the immune microenvironment related genes of skin cutaneous melanoma(SKCM)and screen new markers to predict the prognosis of SKCM patients Methods The Cancer Genome Atlas(TCGA)database downloaded public sequencing data from patients with SKCM.The Estimation of STromal and Immune cells in MAlignant Tumours using Expression data(ESTIMATE)algorithm was used to analyze the immune score and matrix score of SKCM.Weighted gene co-expression network analysis(WGCNA)and differential expression analysis were used to screen key genes associated with the immune microenvironment.Univariate and Least Absolute Shrinkage and Selection Operator(LASSO)regression analyses were used to construct a risk model for SKCM.Finally,univariate and multifactorial Cox regression analyses were performed to analyze the independent prognostic value of the risk models.Results In this study,a new risk prediction model was successfully constructed from five(HLA-DRB1,XCL2,CCR1,HLA-DQB2 and DERL3)genes screened from 173 immune microenvironment-related genes by univariate and LASSO regression analysis.The overall survival(OS)of patients in the high-risk group based on the risk prediction model grouping was significantly shorter than that of patients in the low-risk group(P<0.01).Independent prognostic analysis of the risk score model proved to be an independent prognostic indicator[hazard ratio(HR)=2.823,95%confidence interval(CI):1.778 to 4.481,P<0.01].Conclusion The risk model constructed by HLA-DRB1、XCL2、CCR1、HLA-DQB2 and DERL3 genes has prognostic value for SKCM.