Construction of a metabolism-related gene prognostic model to predict survival of pancreatic cancer patients

Huimin Huang; Shipeng Zhou; Xingling Zhao; Shitong Wang; Huajun Yu; Linhua Lan; Liyi Li

doi:10.1016/j.heliyon.2022.e12378

Construction of a metabolism-related gene prognostic model to predict survival of pancreatic cancer patients

Heliyon. 2022 Dec 17;9(1):e12378. doi: 10.1016/j.heliyon.2022.e12378. eCollection 2023 Jan.

Authors

Huimin Huang^{1

2}, Shipeng Zhou², Xingling Zhao², Shitong Wang², Huajun Yu³, Linhua Lan², Liyi Li⁴

Affiliations

¹ School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, University Town, Chashan District, Wenzhou, Zhejiang Province, 325000, PR China.
² Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Fanhai West Road, Wenzhou, Zhejiang Province, 325000, PR China.
³ Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Fanhai West Road, Wenzhou, Zhejiang Province, 325000, PR China.
⁴ The general surgery department of second affiliated hospital of Wenzhou medical university, No. 109, College West Road, Wenzhou, Zhejiang Province, 325002, Zhejiang, PR China.

Abstract

Pancreatic cancer (PC) is one of the most fatal malignant tumors, and is commonly diagnosed at an advanced stage with no effective therapy. Metabolism-related genes (MRGs) and immune-related genes (IRGs) play considerable roles in the tumor microenvironment. Therefore, an effective prediction model based on MRGs and IRGs could aid in the prognosis of PC. In this study, differential expression analysis was performed to gain 25 intersectional genes from 857 differentially expressed MRGs (DEMRGs), and 1353 differentially expressed IRGs, from The Cancer Genome Atlas database of PC. Cox and Lasso regression were applied and a five-DEMRGs prognostic model constructed. Survival analysis, ROC values, risk curve and validation analysis showed that the model could independently predict PC prognosis. In addition, the correlation analysis suggested that the five-DEMRGs prognostic model could reflect the status of the immune microenvironment, including Tregs, M1 macrophages and Mast cell resting. Therefore, our study provides new underlying predictive biomarkers and associated immunotherapy targets.

Keywords: Immune-related genes; Metabolism-related genes; Pancreatic cancer; Prognostic model.