PathNetDRP: a novel biomarker discovery framework using pathway and protein-protein interaction networks for immune checkpoint inhibitor response prediction

Dohee Lee, Jaegyoon Ahn, Jonghwan Choi

Abstract: Predicting immune checkpoint inhibitor (ICI) response remains a significant challenge in cancer immunotherapy. Many existing approaches rely on differential gene expression analysis or predefined immune signatures, which may fail to capture the complex regulatory mechanisms underlying immune response. Network-based models attempt to integrate biological interactions, but they often lack a quantitative framework to assess how individual genes contribute within pathways, limiting the specificity and interpretability of biomarkers. Given these limitations, we developed PathNetDRP, a framework that integrates biological pathways, protein-protein interaction networks, and machine learning to identify functionally relevant biomarkers for ICI response prediction.

External IDs:dblp:journals/bmcbi/LeeAC25