Effects of Hypoxia in Pancreatic Cancer on Immune Cell Behavior in the Tumor Microenvironment

Abstract

Hypoxia serves as a fundamental component of the tumor microenvironment, exerting a crucial influence on tumor advancement. Nonetheless, a comprehensive examination of a prognostic signature linked to hypoxia in pancreatic cancer is notably absent, presenting an urgent necessity. Therefore, our objective was to create and authenticate a robust prognostic signature capable of predicting outcomes for pancreatic cancer.

Initially, the Gene Set Enrichment Analysis (GSEA) database was used to obtain hypoxia-related genes, and prognostic genes were analyzed. Following this, we utilized the Lasso Cox regression model to construct the hypoxia risk score model. Pancreatic cancer patients were subsequently categorized into high- and low-risk groups according to the median risk score. Finally, the CIBERSORT technique was used to assess immune cell infiltration while examining the relationship between hypoxia and immune-related genes.

Applying the Lasso Cox regression model, we pinpointed 2 significant genes, GYS1 and ALDOB. Following this, patients were categorized into hypoxia high-risk and low-risk groups. Notably, the low-risk cohort demonstrated a substantially heightened survival rate relative to the high-risk group. Further investigation into the immune microenvironment unveiled a greater prevalence of resting mast cells, monocytes, plasma cells, and naive CD4⁺ T cells in the low-risk category. In addition, we detected differences in the expression of 39 immune-related genes between the 2 groups.

In summary, our study has established a predictive signature comprising molecular markers for forecasting the prognosis of pancreatic cancer patients.