Based on the Cancer Genome Atlas database development of a prognostic model of RNA binding protein in stomach adenocarcinoma

Sayed Haidar Abbas Raza, Ruimin Zhong, Shen Xing, Xiaoting Yu, Liang Chengcheng, Linsen Zan, Nicola M. Schreurs, Sameer D. Pant, Hongtao Lei

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The purpose of this study was to identify potential RNA binding proteins associated with the survival of gastric adenocarcinoma, as well as the corresponding biological characteristics and signaling pathways of these RNA binding proteins. RNA sequencing and clinical data were obtained from the cancer genome map (N = 32, T = 375) and the comprehensive gene expression database (GSE84437, N = 433). The samples in The Cancer Genome Atlas were randomly divided into a development group and a test group. A total of 1495 RNA binding protein related genes were extracted. Using nonparametric tests to analyze the difference of RNA binding protein related genes, 296 differential RNA binding proteins were obtained, 166 were up-regulated and 130 were down regulated. Twenty prognosis-related RNA binding proteins were screened using Cox regression, including 14 high-risk genes (hazard ratio > 1.0) and 6 low-risk genes (hazard ratio < 1.0). Seven RNA binding protein related genes were screened from the final prognostic model and used to construct a new prognostic model. Using the development group and test group, the model was verified with survival analysis, receiver operating characteristics curves and prognosis analysis curves. A prediction nomogram was finally developed and showed good prediction performance.
Original languageEnglish
Article number107307
Pages (from-to)1-8
Number of pages8
JournalComputers in Biology and Medicine
Volume164
Early online dateJul 2023
DOIs
Publication statusPublished - Sept 2023

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