AdaSemb: an adaptive knowledge-driven deep learning framework integrating cancer protein assemblies for predicting PI3Kα inhibitor response and resistance.

ABSTRACT: Protein kinases regulate diverse cellular functions, including cell cycle progression, metabolism, differentiation, and survival, with their dysregulation implicated in multiple carcinogenic processes. Phosphatidylinositol 3-kinase alpha inhibitors (PI3K$ \alpha $is) have revolutionized breast cancer treatment, but acquired resistance remains a major clinical challenge, with around 40% of patients experiencing progression within 4-6 months. Current drug response prediction (DRP) methods typically rely on individual pathways or biomarkers, limiting their ability to capture complex cancer-specific molecular interactions and predict resistance mechanisms. To overcome these limitations, we present AdaSemb, an adaptive, knowledge-driven deep learning framework that uses a multi-protein assembly

SUBMITTER: Li Z 

PROVIDER: S-EPMC12477610 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature