Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas.

ABSTRACT:

Background

Pancreatic adenocarcinomas (PAADs) often exhibit a "cold" or immunosuppressive tumor milieu, which is associated with resistance to immune checkpoint blockade therapy; however, the underlying mechanisms are incompletely understood. Here, we aimed to improve our understanding of the molecular mechanisms occurring in the tumor microenvironment and to identify biomarkers, therapeutic targets, and potential drugs to improve PAAD treatment.

Methods

Patients were categorized according to immunologically hot or cold PAAD subtypes with distinct disease outcomes. Cox regression and weighted correlation network analysis were performed to construct a novel gene signature, referred to as 'Downregulated in hot tumors, Prognostic, and Immune-Related Genes' (DPIRGs), which was u

SUBMITTER: Ge J 

PROVIDER: S-EPMC11328457 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature