Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment
Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment
复制标题
宫颈鳞癌免疫微环境中预后相关基因的挖掘
DOI：
10.7717/peerj.9627
复制
发表时间：
2020-08-24
期刊：
影响因子：
2.7
通讯作者：
Zheng，Wei
中科院分区：
文献类型：
--
作者：
Ma，Jiong;Cheng，Pu;Zheng，Wei
目的探索有效的免疫评分方法，挖掘新的、潜在的宫颈鳞癌免疫微环境相关诊断和预后标志物。材料与方法下载癌症基因组图谱（Cancer Genome Atlas，TCGA）数据，采用多种数据分析方法，以ESTIMATE算法为基础，初步寻找免疫相关评分系统。然后，利用加权基因共表达网络分析（WGCNA）和网络拓扑分析，进一步筛选基于ESTIMATE算法的与免疫相关评分相关的基因模块中的代表基因。通过富集分析挖掘基因功能，然后探索这些基因与免疫检查点基因之间的相关性。最后，应用生存分析寻找与总生存率显著相关的基因，并使用外部数据库进行进一步验证。结果基于ESTIMATE算法的免疫相关评分与其他类别评分、HPV感染状况、预后及多个CSCC相关基因（HLA和TP53）突变水平密切相关。最终筛选出18个与患者预后密切相关的新的代表性免疫微环境相关基因，并通过独立数据集GSE 44001进行了进一步验证。结论基于ESTIMATE算法的免疫相关评分有助于筛选新的CSCC免疫相关诊断指标、治疗靶点和预后预测因子。
Purpose The aim of this study was to explore the effective immune scoring method and mine the novel and potential immune microenvironment-related diagnostic and prognostic markers for cervical squamous cell carcinoma (CSSC). Materials and Methods The Cancer Genome Atlas (TCGA) data was downloaded and multiple data analysis approaches were initially used to search for the immune-related scoring system on the basis of Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm. Afterwards, the representative genes in the gene modules correlated with immune-related scores based on ESTIMATE algorithm were further screened using Weighted Gene Co-expression Network Analysis (WGCNA) and network topology analysis. Gene functions were mined through enrichment analysis, followed by exploration of the correlation between these genes and immune checkpoint genes. Finally, survival analysis was applied to search for genes with significant association with overall survival and external database was employed for further validation. Results The immune-related scores based on ESTIMATE algorithm was closely associated with other categories of scores, the HPV infection status, prognosis and the mutation levels of multiple CSCC-related genes (HLA and TP53). Eighteen new representative immune microenvironment-related genes were finally screened closely associated with patient prognosis and were further validated by the independent dataset GSE44001. Conclusion Our present study suggested that the immune-related scores based on ESTIMATE algorithm can help to screen out novel immune-related diagnostic indicators, therapeutic targets and prognostic predictors in CSCC.