Diabetes-associated metabolic-immune signature stratifies survival and immunotherapy response in pancreatic adenocarcinoma through multi-omics integration

Abstract

Objective

Pancreatic adenocarcinoma (PAAD) poses a significant threat, especially to patients with diabetes mellitus (DM). While numerous studies have explored prognostic factors for pancreatic cancer, research specifically focusing on PAAD patients with DM remains scarce. This study aims to address this gap by identifying differentially expressed genes (DEGs) between DM and non-DM individuals and developing a reliable prognostic model to predict overall survival (OS) in PAAD patients with DM.

Methods

PAAD patients with DM were divided into a training group (70%) and a test group (30%). Univariate COX analysis was used to screen genes associated with OS. A 10-gene risk model (ACACA, ATG7, DEFB123, FSTL3, NIPSNAP3B, RASSF1, RBPJ, SLC35F2, SLC37A1 and ZC3H12D) was constructed via LASSO-penalized COX regression combined with ten-fold cross-validation. Additionally, multi-omics findings were integrated, and in vitro functional studies were conducted to validate the oncogenic roles of key metabolic regulators (ACACA and ATG7) under high-glucose conditions.

Results

The constructed model demonstrated strong predictive ability, with a C-index of 0.83 in the training group and 0.76 in the test group, indicating good performance across both cohorts. Further analysis revealed that the high-risk group exhibited a tumor-growth and angiogenic phenotype (which may drive rapid tumor progression), while the low-risk group showed an immune-active phenotype (suggesting a favorable immunological microenvironment).

Conclusions

This prognostic model can predict the OS of PAAD patients with DM. Low-risk patients may be suitable candidates for immunotherapy, whereas high-risk patients may benefit from alternative strategies such as anti-angiogenic therapy.