Wu KZ, Xu XH, Zhan CP, Li J, Jiang JL. Identification of a nine-gene prognostic signature for gastric carcinoma using integrated bioinformatics analyses. World J Gastrointest Oncol 2020; 12(9): 975-991 [PMID: 33005292 DOI: 10.4251/wjgo.v12.i9.975]
Corresponding Author of This Article
Jin-Lan Jiang, PhD, Professor, Research Scientist, Scientific Research Center, China-Japan Union Hospital of Jilin University, No. 126 Xiantai Street, Changchun 130000, Jilin Province, China. jiangjinlan@jlu.edu.cn
Research Domain of This Article
Oncology
Article-Type of This Article
Basic Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Kun-Zhe Wu, Jin-Lan Jiang, Scientific Research Center, China-Japan Union Hospital of Jilin University, Changchun 130000, Jilin Province, China
Xiao-Hua Xu, Jing Li, Department of Nephrology, China-Japan Union Hospital of Jilin University, Changchun 130000, Jilin Province, China
Cui-Ping Zhan, Department of Ultrasound, China-Japan Union Hospital of Jilin University, Changchun 130000, Jilin Province, China
Author contributions: Jiang JL designed this study; Li J and Zhan CP conducted the data analysis; Xu XH reviewed the article; Wu KZ wrote the article.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of China-Japan Union Hospital of Jilin University.
Conflict-of-interest statement: All the authors declare no conflict of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Jin-Lan Jiang, PhD, Professor, Research Scientist, Scientific Research Center, China-Japan Union Hospital of Jilin University, No. 126 Xiantai Street, Changchun 130000, Jilin Province, China. jiangjinlan@jlu.edu.cn
Received: May 21, 2020 Peer-review started: April 5, 2020 First decision: May 15, 2020 Revised: May 15, 2020 Accepted: August 1, 2020 Article in press: August 1, 2020 Published online: September 15, 2020
Core Tip
Core Tip: A total of 95 differentially expressed genes were found by mining the datasets of Gene Expression Omnibus and the Cancer Genome Atlas databases. Overlapping differentially expressed genes were analyzed using univariate and multivariate Cox regression analyses. Receiver operating characteristic curve performance in the training and validation datasets demonstrated a robust prognostic value of the risk score model. Multiple database analyses for each gene provided evidence to further understand the nine-gene signature. Gene set enrichment analysis showed that the high-risk group was enriched in multiple cancer-related pathways. Moreover, several new small molecule drugs for potential treatment of gastric carcinoma (GC) were identified. A nine-gene signature was identified to predict GC prognosis and prove potentially useful for guiding therapeutic strategies for GC patients.
