AUTHOR=Yao Yong , Liu Kangping , Wu Yuxuan , Zhou Jieyu , Jin Heyue , Zhang Yimin , Zhu Yumin 

TITLE=Comprehensive landscape of the functions and prognostic value of RNA binding proteins in uterine corpus endometrial carcinoma

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.962412

DOI=10.3389/fmolb.2022.962412

ISSN=2296-889X

ABSTRACT=Abstract
Background
The dysregulation of RNA binding proteins (RBPs) is involved in tumorigenesis and progression. However, information on the overall function of RBPs in Uterine Corpus Endometrial Carcinoma (UCEC) remains to be studied. The aims of this study were to explore the associated molecular mechanisms and to develop an RNA binding protein-associated prognostic model for UCEC.
Methods
Based on The Cancer Genome Atlas (TCGA) database, differently expressed RBPs were identified between UCEC tumor tissues and normal tissues by R packages (DESeq2, edgeR). Hub RBPs were then found by univariate and multivariate Cox regression analysis. The cBioPortal platform, R packages (ggplot2), the Human Protein Atlas (HPA) and TIMER online database were used to explore the molecular mechanisms of UCEC. Kaplan-Meier (K-M), Area Under Curve (AUC), and the consistency index (c-index) were used to test the performance of our model.
Results
In total, 128 differently expressed RBPs between UCEC tumor tissues and normal tissues were identified. Seven RBP genes (NOP10, RBPMS, ATXN1, SBDS, POP5, CD3EAP, ZC3H12C) were screened as prognostic hub genes and used to construct a prognostic model, which are particularly important to prospectively predict patient prognosis and help them get treatment accordingly. Further analysis indicated that the patients in the high-risk subgroup had poor overall survival (OS) compared to those in low-risk subgroup based on the model. We also established a nomogram based on seven RBPs, which potentially improved individualized diagnostic and therapeutic strategies for UCEC.
Conclusion
Our work focused on the systematic analysis of a large cohort of UCEC patients in the TCGA database, which allowed us to construct a robust prognostic model based on seven RBPs, that may be of great value in clinical applications.