Basic Study
Copyright ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 21, 2018; 24(43): 4906-4919
Published online Nov 21, 2018. doi: 10.3748/wjg.v24.i43.4906
Prognostic value of sorting nexin 10 weak expression in stomach adenocarcinoma revealed by weighted gene co-expression network analysis
Jun Zhang, Yue Wu, Hao-Yi Jin, Shuai Guo, Zhe Dong, Zhi-Chao Zheng, Yue Wang, Yan Zhao
Jun Zhang, Shuai Guo, Zhe Dong, Zhi-Chao Zheng, Yue Wang, Yan Zhao, Department of Gastric Cancer, Liaoning Cancer Hospital and Institute (Cancer Hospital of China Medical University), Shenyang 110042, Liaoning Province, China
Yue Wu, Department of Emergency, Sheng Jing Hospital of China Medical University, Shenyang 110042, Liaoning Province, China
Hao-Yi Jin, Pancreatic and Thyroid Surgery Department, Sheng Jing Hospital of China Medical University, Shenyang 110042, Liaoning Province, China
Author contributions: Zhang J performed the majority of experiments and analyzed the data and drafted the manuscript; Zheng ZC, Zhao Y designed the research; Wu Y, Dong Z conducted the immunohistochemistry assays and assisted in writing the manuscript; Guo S, Wang Y collected and analyzed the data; Zhao Y provided critical revision of the manuscript for important intellectual content; Jin HY provided critical revision of the manuscript for important intellectual content.
Supported by Liaoning S&T Project, No. 2015020269.
Institutional review board statement: The study was reviewed and approved by the Faculty of Science Ethics Committee at Liaoning Cancer Hospital and Institute (Cancer Hospital of China Medical University) (20150308-2).
Conflict-of-interest statement: The authors declare that there are no conflicts of interest related to this study.
Data sharing statement: No additional data are available.
ARRIVE guidelines statement: The authors have read the ARRIVE guidelines, and the manuscript was prepared and revised according to the ARRIVE guidelines.
Open-Access: 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/
Correspondence to: Yan Zhao, PhD, Professor, Vice-President, Department of Gastric Cancer, Liaoning Cancer Hospital and Institute (Cancer Hospital of China Medical University), No. 44 Xiaoheyan Road, Dadong District, Shenyang 110042, Liaoning Province, China. zhaoyan@cancerhosp-ln-cmu.com
Telephone: +86-24-31916823 Fax: +86-24-24315679
Received: August 2, 2018
Peer-review started: August 2, 2018
First decision: October 5, 2018
Revised: October 17, 2018
Accepted: October 21, 2018
Article in press: October 21, 2018
Published online: November 21, 2018
Processing time: 111 Days and 22.9 Hours
ARTICLE HIGHLIGHTS
Research background

Stomach adenocarcinoma (SA) is by far the most prevalent pathologic version of gastric cancer, whose prognosis is influenced by the complex gene interactions involved in tumor progression. Guidelines have identified the correlation between clinical prognosis and tumor stage and grade. Detection of significant clusters of co-expressed genes or representative biomarkers associated with tumor stage or grade may prompt to highlight the mechanisms of tumorigenesis and tumor progression, and might be helpful to predict SA patient prognosis.

Research motivation

To detect significant clusters of co-expressed genes associated with tumorigenesis, which may help predict SA patient prognosis. The weighted gene co-expression network analysis (WGCNA) method provided a functional interpretation tool for systems biology and led to new insights into the pathophysiology of SA.

Research objectives

The aim of the present study is to reveal a novel biomarker of SA and evaluate the prognostic value of it in SA.

Research methods

The RNA-seq dataset and clinical dataset of SA in The Cancer Genome Atlas (TCGA) were used in this study. The WGCNA was used to identify meaningful modules and hub genes. A 326 patients database was used to evaluate the clinical significance of hub genes via survival analysis.

Research results

Differentially expressed genes (DEGs) (6231) were obtained through whole genome expression level screening. Gene modules (24) were identified using WGCNA, which were observed to be co-expressed. Pearson’s correlation analysis showed the tan-module to be the most relevant to tumor stages. In addition, we detected SNX10 as the hub gene of the tan-module. SNX10 expression was linked to TNM stage and tumor differentiation. Patients with high SNX10 expression trended to have longer disease-free survival (DFS) and overall survival in univariate analysis. Multivariate analysis also showed that dismal prognosis could be precisely predicted clinicopathologically using SNX10. However, more experiments are needed to validate the clinical and biological functions of SNX10.

Research conclusions

WGCNA as well as other methods were employed to study RNA-seq and the clinical data of SA patients from TCGA. SNX10 was considered as a hub gene associated with tumor grade and acted as an independent prognostic factor in SA patient DFS as well as overall survival. It has the potential to become a novel prognostic indicator, thus contributing to personalized therapy.

Research perspectives

Our research team will explore the molecule function of SNX10 by establishing animal models. We will also explore the mutual regulatory mechanism of SNX10 through mass spectrometry analysis and co-immunoprecipitation.