Construction of a microenvironment immune gene model for predicting the prognosis of endometrial cancer.
Construction of a microenvironment immune gene model for predicting the prognosis of endometrial cancer.
复制标题
预测子宫内膜癌预后的微环境免疫基因模型的构建
DOI：
10.1186/s12885-021-08935-w
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发表时间：
2021-11-11
期刊：
影响因子：
3.8
通讯作者：
Liu Q
中科院分区：
文献类型：
--
作者：
Wang Y;Zhang J;Zhou Y;Li Z;Lv D;Liu Q
研究背景浸润免疫细胞和基质细胞是子宫内膜癌（EC）微环境的重要组成部分，对子宫内膜癌的生物学行为具有显着影响，提示独特的免疫相关基因可能与子宫内膜癌的预后相关。然而，免疫相关基因与 EC 预后的关系尚未阐明。我们试图利用癌症基因组图谱数据库以及免疫微环境与EC之间的关系来识别EC中具有潜在预后价值的免疫相关基因。方法我们分析了TCGA数据库中的578个EC样本，并使用加权基因共表达网络分析来筛选免疫相关基因。我们构建了蛋白质-蛋白质相互作用网络，并使用 STRING 和 Cytoscape 对其进行了分析。通过联合Cox回归和随机森林算法分析免疫相关基因，以确定多基因预测模型，并对EC患者的低风险和高风险群体进行分层。基于这些数据，我们构建了列线图预测模型以改进预后评估。对这些组应用免疫学评估、基因突变和基因富集分析来量化额外的差异。结果使用联合Cox回归和随机森林算法，我们发现TRBC2、TRAC、LPXN和ARHGAP30与EC的预后相关，并构建了四种总体生存的基因风险模型和一致的列线图。时间依赖性受试者工作特征曲线分析显示，1 年、3 年和 5 年总生存率的曲线下面积分别为 0.687、0.699 和 0.76。这些结果通过验证队列进行了验证。免疫相关通路大多富集于低风险组，具有较高的免疫浸润水平和免疫状态。结论我们的研究为EC中的新型生物标志物和免疫治疗靶点提供了新的见解。
BackgroundInfiltrating immune and stromal cells are important components of the endometrial cancer (EC) microenvironment, which has a significant effect on the biological behavior of EC, suggesting that unique immune-related genes may be associated with the prognosis of EC. However, the association of immune-related genes with the prognosis of EC has not been elucidated. We attempted to identify immune-related genes with potentially prognostic value in EC using The Cancer Genome Atlas database and the relationship between immune microenvironment and EC.MethodsWe analyzed 578 EC samples from TCGA database and used weighted gene co-expression network analysis to screen out immune-related genes. We constructed a protein–protein interaction network and analyzed it using STRING and Cytoscape. Immune-related genes were analyzed through conjoint Cox regression and random forest algorithm analysis were to identify a multi-gene prediction model and stratify low-risk and high-risk groups of EC patients. Based on these data, we constructed a nomogram prediction model to improve prognosis assessment. Evaluation of Immunological, gene mutations and gene enrichment analysis were applied on these groups to quantify additional differences.ResultsUsing conjoint Cox regression and random forest algorithm, we found that TRBC2, TRAC, LPXN, and ARHGAP30 were associated with the prognosis of EC and constructed four gene risk models for overall survival and a consistent nomogram. The time-dependent receiver operating characteristic curve analysis revealed that the area under the curve for 1-, 3-, and 5-y overall survival was 0.687, 0.699, and 0.76, respectively. These results were validated using a validation cohort. Immune-related pathways were mostly enriched in the low-risk group, which had higher levels of immune infiltration and immune status.ConclusionOur study provides new insights for novel biomarkers and immunotherapy targets in 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
DOI：
10.1073/pnas.1806838116
发表时间：
2019-02-26
影响因子：
11.1
作者：
Monsivais, Diana;Peng, Jia;Matzuk, Martin M.
通讯作者：
Matzuk, Martin M.
DOI：
10.2174/1386207323999200729113641
发表时间：
2021-01-01
影响因子：
1.8
作者：
Li, Nan;Yu, Kai;Zeng, Dingyuan
通讯作者：
Zeng, Dingyuan
影响因子：
30.8
作者：
Paloneva, J;Kestilä, M;Peltonen, L
通讯作者：
Peltonen, L
影响因子：
9.8
作者：
Schmandt RE;Iglesias DA;Co NN;Lu KH
通讯作者：
Lu KH