Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer

doi:10.12998/wjcc.v9.i35.10884

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World Journal of Clinical Cases

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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 by Shanghai 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.

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.