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宫颈鳞状细胞癌免疫微环境中预后相关基因的挖掘

Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment.

作者信息

Ma Jiong, Cheng Pu, Chen Xuejun, Zhou Chunxia, Zheng Wei

机构信息

Department of Gynecology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hang Zhou, China.

Key Laboratory of Tumor Microenvironment and Immune Therapy of Zhejiang Province, Hang Zhou, China.

出版信息

PeerJ. 2020 Aug 24;8:e9627. doi: 10.7717/peerj.9627. eCollection 2020.

DOI:10.7717/peerj.9627
PMID:32904067
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7450998/
Abstract

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.

摘要

目的

本研究旨在探索有效的免疫评分方法，挖掘子宫颈鳞状细胞癌（CSSC）新的潜在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（TCGA）数据，最初使用多种数据分析方法，基于利用表达数据估计恶性肿瘤组织中的基质和免疫细胞（ESTIMATE）算法搜索免疫相关评分系统。之后，基于ESTIMATE算法，使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与免疫相关评分相关的基因模块中的代表性基因。通过富集分析挖掘基因功能，随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显著相关的基因，并利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感染状态、预后以及多个CSCC相关基因（HLA和TP53）的突变水平密切相关。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GSE44001进行了进一步验证。

结论

我们目前的研究表明，基于ESTIMATE算法的免疫相关评分有助于筛选出CSCC中新的免疫相关诊断指标、治疗靶点和预后预测指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7337/7450998/650a27c478c3/peerj-08-9627-g012.jpg
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