Bioinformatic profiling identifies prognosis-related genes in the immune microenvironment of endometrial carcinoma.
Bioinformatic profiling identifies prognosis-related genes in the immune microenvironment of endometrial carcinoma.
复制标题
生物信息分析鉴定子宫内膜癌免疫微环境中与预后相关的基因
DOI：
10.1038/s41598-021-92091-5
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发表时间：
2021-06-15
影响因子：
4.6
通讯作者：
Chen X
中科院分区：
文献类型：
--
作者：
Cheng P;Ma J;Zheng X;Zhou C;Chen X
子宫内膜癌（endometrialcarcinoma，EC）是女性生殖系统常见的恶性肿瘤，具有独特的免疫学特征。定量检测EC的免疫模式是预测预后和治疗效果的一个很有前途的策略。在这里，我们试图确定可能的免疫微环境相关的预后指标EC。我们从TCGA数据库中获得了EC的RNA测序和相应的临床资料。然后，计算基于使用表达数据（ESTIMATE）算法的恶性肿瘤组织中的Stromal和免疫细胞的估计的3个免疫评分。进一步分析上述ESTIMATE评分与其他免疫相关评分、分子亚型、预后、基因突变状态（包括BRCA和TP53）的相关性。然后，通过系统聚类分析和加权基因共表达网络分析（WGCNA）筛选出与ESTIMATE评分相关的基因模块。进行差异表达分析，找出最相关模块共有的基因。通过KEGG途径富集分析，探讨这些基因的生物学功能。通过生存分析确定预后免疫相关基因，并进一步使用GSE17025数据库来确认免疫相关基因与ImmuneScore的相关性。基于ESTIMATE算法的免疫相关评分与EC的免疫微环境密切相关。获得了与3个ESTIMATE评分相关性最密切的3个基因模块。初步发现109个免疫相关基因，29条通路显著富集，其中大部分与免疫应答相关。单因素生存分析显示，有14个基因与OS和PFS呈正相关。其中，11个基因与GSE17025数据库中的ImmuneScore值显著相关。我们目前的研究概述了免疫状态，并确定了14个新的免疫相关的预后生物标志物EC。我们的研究结果可能有助于研究复杂的肿瘤微环境，并开发新的个体化治疗EC的靶点。
Endometrial carcinoma (EC) is a common malignancy of female genital system which exhibits a unique immune profile. It is a promising strategy to quantify immune patterns of EC for predicting prognosis and therapeutic efficiency. Here, we attempted to identify the possible immune microenvironment-related prognostic markers of EC. We obtained the RNA sequencing and corresponding clinical data of EC from TCGA database. Then, 3 immune scores based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm were computed. Correlation between above ESTIMATE scores and other immune-related scores, molecular subtypes, prognosis, and gene mutation status (including BRCA and TP53) were further analyzed. Afterwards, gene modules associated with the ESTIMATE scores were screened out through hierarchical clustering analysis and weighted gene co-expression network analysis (WGCNA). Differentially expressed analysis was performed and genes shared by the most relevant modules were found out. KEGG pathway enrichment analysis was conducted to explore the biological functions of those genes. Survival analysis was carried out to identify prognostic immune-related genes and GSE17025 database was further used to confirm the correlation between immune-related genes and the ImmuneScore. The immune-related scores based on ESTIMATE algorithm was closely related to the immune microenvironment of EC. 3 gene modules that had the closest correlations with 3 ESTIMATE scores were obtained. 109 immune-related genes were preliminarily found out and 29 pathways were significantly enriched, most of which were associated with immune response. Univariate survival analysis revealed that there were 14 genes positively associated with both OS and PFS. Among which, 11 genes showed marked correlations with ImmuneScore values in GSE17025 database. Our current study profiled the immune status and identified 14 novel immune-related prognostic biomarkers for EC. Our findings may help to investigate the complicated tumor microenvironment and develop novel individualized therapeutic targets for EC.
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WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
64.8
作者：
通讯作者：
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影响因子：
3
作者：
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通讯作者：
Holzinger A
影响因子：
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作者：
Liu, Yuexin
通讯作者：
Liu, Yuexin
影响因子：
3.9
作者：
Jiang X;Tang H;Chen T
通讯作者：
Chen T