OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer.

ABSTRACT:

Background

Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies.

Methods

We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis. We integrated multi-dataset analyses, single-cell transcriptomic data, and functional experiments to explore the role of OSBPL3 in pancreatic cancer.

Results

Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. Notably, the "rf" algorithm model showed

SUBMITTER: Sun Q 

PROVIDER: S-EPMC11716069 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature