Xu H, Sun J, Zhou L, Du QC, Zhu HY, Chen Y, Wang XY. Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer. World J Clin Cases 2021; 9(35): 10884-10898 [PMID: 35047599 DOI: 10.12998/wjcc.v9.i35.10884]
Corresponding Author of This Article
Xin-Yu Wang, MD, Attending Doctor, General Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, No. 1279 Sanmen Road, Hongkou District, Shanghai 200434, China. wang_xinyuvip@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective 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/
World J Clin Cases. Dec 16, 2021; 9(35): 10884-10898 Published online Dec 16, 2021. doi: 10.12998/wjcc.v9.i35.10884
Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer
Hong Xu, Jian Sun, Ling Zhou, Qian-Cheng Du, Hui-Ying Zhu, Yang Chen, Xin-Yu Wang
Hong Xu, Jian Sun, Ling Zhou, Qian-Cheng Du, Hui-Ying Zhu, Yang Chen, Xin-Yu Wang, General Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai 200434, China
Author contributions: Xu H and Wang XY performed the surgery; Sun J and Zhou L designed the study; Du QC, Zhu HY and Chen Y wrote the paper; Xu H and Wang XY were responsible for analyzing the data; all authors have read and approved the final manuscript.
Supported byShanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine Discipline Boosting Plan, No. SY-XKZT-2019-1006.
Institutional review board statement: The study was reviewed and approved by the Shanghai Fourth People’s Hospital Institutional Review Board (No. 2019057-001).
Conflict-of-interest statement: The authors declare no conflicts 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 noncommercially, and license their derivative works on different terms, provided the original work is properly cited and the use is noncommercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xin-Yu Wang, MD, Attending Doctor, General Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, No. 1279 Sanmen Road, Hongkou District, Shanghai 200434, China. wang_xinyuvip@163.com
Received: June 25, 2021 Peer-review started: June 25, 2021 First decision: August 19, 2021 Revised: September 1, 2021 Accepted: October 27, 2021 Article in press: October 27, 2021 Published online: December 16, 2021 Processing time: 167 Days and 16.5 Hours
ARTICLE HIGHLIGHTS
Research background
Finding specific prognostic markers is important for pancreatic cancer. Understanding the relationship between lipid metabolism-related genes and pancreatic cancer is helpful to improve its prognosis.
Research motivation
To construct a novel model to predict the prognosis of pancreatic cancer.
Research objectives
To investigate the characteristics of lipid metabolites in pancreatic cancer and construct a prognostic polygene signature of differentially expressed genes related to lipid metabolism.
Research methods
Lipid metabolomics analysis was conducted to explore differences in lipid metabolites between pancreatic cancer tissues and paracancerous tissues. A predictive model of lipid metabolism genes associated with pancreatic cancer was established using a cohort from The Cancer Genome Atlas.
Research results
Lipid metabolomics analysis showed that the lipid metabolites phosphatidylcholine, phosphatidyl ethanolamine, phosphatidylethanol, phosphatidylmethanol, phosphatidylserines and diacylglyceryl trimethylhomoserine were significantly higher in cancer tissues. A 4-gene signature model, including GALNT16, FADS3, CERS4 and ABO, was developed to predict the prognosis of pancreatic cancer.
Research conclusions
Differentially expressed genes related to lipid metabolism reflected abnormal lipid metabolism in pancreatic cancer. A novel predictive model of a 4-lipid metabolism-related gene signature contributed to the prediction of pancreatic cancer prognosis.
Research perspectives
New gene markers and models are needed to predict prognosis because of the high heterogeneity of pancreatic cancer.
