Basic Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Nov 27, 2020; 12(11): 442-459
Published online Nov 27, 2020. doi: 10.4240/wjgs.v12.i11.442
Identification of key genes controlling cancer stem cell characteristics in gastric cancer
Chao Huang, Ce-Gui Hu, Zhi-Kun Ning, Jun Huang, Zheng-Ming Zhu
Chao Huang, Ce-Gui Hu, Zhi-Kun Ning, Jun Huang, Zheng-Ming Zhu, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
Author contributions: Huang C and Hu CG designed the study and contributed equally to this work; Huang C, Hu CG, and Ning ZK collected the data; Huang C and Huang J analysed the data; Huang C wrote the manuscript with contribution from all authors; and all authors read and approved the final version of the paper.
Supported by the National Natural Science Foundation of China, No. 81560389; and Key Research and Development Program of Jiangxi Province, No. 20181BBG70015.
Institutional review board statement: No human and/or animal subjects were involved in this study.
Conflict-of-interest statement: The authors declare no competing financial interests.
Data sharing statement: RNA sequencing results of 373 tissues and 348 human gastric adenomas and adenocarcinoma samples were obtained from TCGA database (https://portal.gdc.cancer.gov). The RNA-seq results of 30 normal samples and 343 cancer samples were merged into a matrix file using a script in the Perl language (http://www.perl.org/). We then converted the Ensembl ID in the matrix file to the gene name using the Ensembl database (http://www.ensembl.org/index.html) and the Perl language script. In addition, 406 pieces of clinical data were downloaded, and the relevant clinical data were collated and extracted using scripts in the Perl language. The calculation of mRNAsi was performed from the molecular spectrum of normal cells with different degrees of stemness.
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: Zheng-Ming Zhu, MD, Chairman, Surgical Oncologist, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang 330006, Jiangxi Province, China. zzm8654@163.com
Received: July 28, 2020
Peer-review started: July 28, 2020
First decision: August 9, 2020
Revised: August 13, 2020
Accepted: October 12, 2020
Article in press: October 12, 2020
Published online: November 27, 2020
ARTICLE HIGHLIGHTS
Research background

Gastric cancer (GC) stem cells are the primary cause of GC metastasis and drug resistance.

Research motivation

The purpose of this study was to characterize the expression of stem cell-related genes in GC.

Research objectives

Targeting for inhibiting the stemness characteristics of GC cells will become a new treatment for tumors

Research methods

RNA sequencing results and clinical data for gastric adenoma and adeno-carcinoma samples were obtained from The Cancer Genome Atlas (TCGA) database, and the results of the GC mRNA expression-based stemness index (mRNAsi) were analyzed. Weighted gene coexpression network analysis (WGCNA) was then used to find modules of interest and their key genes. Survival analysis of key genes was performed using the online tool Kaplan-Meier Plotter, and the online database Oncomine was used to assess the expression of key genes in GC.

Research results

mRNAsi was significantly upregulated in GC tissues compared to normal gastric tissues (P < 0.0001). A total of 16 modules were obtained from the gene coexpression network; the brown module was most positively correlated with mRNAsi. Sixteen key genes (BUB1, BUB1B, NCAPH, KIF14, RACGAP1, RAD54L, TPX2, KIF15, KIF18B, CENPF, TTK, KIF4A, SGOL2, PLK4, XRCC2, and C1orf112) were identified in the brown module.

Research conclusions

RAD54L, TPX2, and XRCC2 are the most positively correlated with mRNAsi and are the most likely therapeutic targets for inhibiting the stemness characteristics of gastric cancer cells.

Research perspectives

This study aimed to identify key genes related to stemness by combining WGCNA with GC mRNAsi in TCGA, thus providing new ideas for the treatment of GC.