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基于肿瘤微环境相关基因和临床因素的子宫内膜癌总生存预测列线图的构建与验证

Development and validation of nomogram with tumor microenvironment-related genes and clinical factors for predicting overall survival of endometrial cancer.

作者信息

Chen Qian, Wang Shu, Lang Jing-He

机构信息

Department of Gynecology and Obstetrics, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases. Beijing, P.R, China.

出版信息

J Cancer. 2021 Apr 23;12(12):3530-3538. doi: 10.7150/jca.51493. eCollection 2021.

Abstract

Tumor microenvironment (TME) has attracted lots of attention with its important role in the tumor development. This study aimed to explore TME- related genes of prognostic value in patients with endometrial cancer (EC) and establish a prediction model for EC. The RNA-Seq data and clinicopathological characteristics of 521 subjects were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were identified based on the immune and stromal scores, which were calculated by the ESTIMATE algorithm. Hub genes were initially screened using the Cytoscape and further selected through Cox regression. Gene correlation analysis was performed in TIMER database. A nomogram was constructed integrating prognosis-related hub genes and clinical factors and validated in the validation group. Risk stratification was performed based on the nomogram. Three TME-related hub genes (, and ) were found with significant prognostic value for EC patients. The expression of , and were significantly correlated with various immune cells infiltration. Based on the Cox regression, a nomogram was constructed by integrating five predictors (stage, grade, immune score, expression of , and ), with a C-index of 0.765. Discrimination of the model was confirmed in the validation group (C-index: 0.716). The calibration curves for the 3- and 5- year survival indicated good calibration. Patients in high- and low- risk groups presented significantly different survival outcomes (P<0.001) in both discovery and validation group. TME-related hub genes of prognostic value identified in our study may provide references for the mechanisms underlying EC development and the immunotherapy for EC. The prediction model may help assess the prognosis of EC patients.

摘要

肿瘤微环境(TME)因其在肿瘤发展中的重要作用而备受关注。本研究旨在探索子宫内膜癌(EC)患者中具有预后价值的TME相关基因,并建立EC的预测模型。从癌症基因组图谱(TCGA)数据库中获取了521名受试者的RNA测序数据和临床病理特征。基于通过ESTIMATE算法计算的免疫和基质评分来鉴定差异表达基因(DEG)。首先使用Cytoscape筛选枢纽基因,然后通过Cox回归进一步选择。在TIMER数据库中进行基因相关性分析。构建了一个整合预后相关枢纽基因和临床因素的列线图,并在验证组中进行了验证。基于列线图进行风险分层。发现三个TME相关枢纽基因(、和)对EC患者具有显著的预后价值。、和的表达与各种免疫细胞浸润显著相关。基于Cox回归,通过整合五个预测因子(分期、分级、免疫评分、的表达和)构建了一个列线图,C指数为0.765。在验证组中证实了该模型的辨别力(C指数:0.716)。3年和5年生存的校准曲线显示校准良好。在发现组和验证组中,高风险和低风险组的患者生存结果存在显著差异(P<0.001)。我们研究中鉴定出的具有预后价值的TME相关枢纽基因可能为EC发展的潜在机制和EC的免疫治疗提供参考。该预测模型可能有助于评估EC患者的预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34d2/8120177/c79b7e4fed58/jcav12p3530g001.jpg

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