Yao Yong, Liu Kangping, Wu Yuxuan, Zhou Jieyu, Jin Heyue, Zhang Yimin, Zhu Yumin
Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
MOE Key Laboratory of Population Health Across Life Cycle, Hefei, Anhui, China.
Front Mol Biosci. 2022 Oct 3;9:962412. doi: 10.3389/fmolb.2022.962412. eCollection 2022.
The dysregulation of RNA binding proteins (RBPs) is involved in tumorigenesis and progression. However, information on the overall function of RNA binding proteins in Uterine Corpus Endometrial Carcinoma (UCEC) remains to be studied. This study aimed to explore Uterine Corpus Endometrial Carcinoma-associated molecular mechanisms and develop an RNA-binding protein-associated prognostic model. Differently expressed RNA binding proteins were identified between Uterine Corpus Endometrial Carcinoma tumor tissues and normal tissues by R packages (DESeq2, edgeR) from The Cancer Genome Atlas (TCGA) database. Hub RBPs were subsequently identified by univariate and multivariate Cox regression analyses. The cBioPortal platform, R packages (ggplot2), Human Protein Atlas (HPA), and TIMER online database were used to explore the molecular mechanisms of Uterine Corpus Endometrial Carcinoma. Kaplan-Meier (K-M), Area Under Curve (AUC), and the consistency index (c-index) were used to test the performance of our model. We identified 128 differently expressed RNA binding proteins between Uterine Corpus Endometrial Carcinoma tumor tissues and normal tissues. Seven RNA binding proteins genes (, , , , , , ) were screened as prognostic hub genes and used to construct a prognostic model. Such a model may be able to predict patient prognosis and acquire the best possible treatment. Further analysis indicated that, based on our model, the patients in the high-risk subgroup had poor overall survival (OS) compared to those in the low-risk subgroup. We also established a nomogram based on seven RNA binding proteins. This nomogram could inform individualized diagnostic and therapeutic strategies for Uterine Corpus Endometrial Carcinoma. Our work focused on systematically analyzing a large cohort of Uterine Corpus Endometrial Carcinoma patients in the The Cancer Genome Atlas database. We subsequently constructed a robust prognostic model based on seven RNA binding proteins that may soon inform individualized diagnosis and treatment.
RNA结合蛋白(RBPs)的失调与肿瘤发生和进展有关。然而,关于RNA结合蛋白在子宫内膜癌(UCEC)中的整体功能信息仍有待研究。本研究旨在探索子宫内膜癌相关的分子机制,并建立一个与RNA结合蛋白相关的预后模型。通过来自癌症基因组图谱(TCGA)数据库的R包(DESeq2、edgeR),鉴定子宫内膜癌肿瘤组织和正常组织之间差异表达的RNA结合蛋白。随后通过单变量和多变量Cox回归分析鉴定枢纽RBPs。利用cBioPortal平台、R包(ggplot2)、人类蛋白质图谱(HPA)和TIMER在线数据库探索子宫内膜癌的分子机制。采用Kaplan-Meier(K-M)法、曲线下面积(AUC)和一致性指数(c-index)来检验我们模型的性能。我们鉴定出子宫内膜癌肿瘤组织和正常组织之间有128种差异表达的RNA结合蛋白。筛选出7个RNA结合蛋白基因(,,,,,,)作为预后枢纽基因,并用于构建预后模型。这样的模型或许能够预测患者的预后并获得最佳治疗方案。进一步分析表明,基于我们的模型,高危亚组患者的总生存期(OS)低于低危亚组。我们还基于7个RNA结合蛋白建立了一个列线图。该列线图可为子宫内膜癌的个体化诊断和治疗策略提供参考。我们的工作重点是系统分析癌症基因组图谱数据库中的一大群子宫内膜癌患者。随后,我们基于7个RNA结合蛋白构建了一个强大的预后模型,该模型可能很快为个体化诊断和治疗提供参考。