IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network.

ABSTRACT:

Introduction

Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cancer types, significantly improving survival rates in patients who respond positively to them. However, only a minority of patients benefit from ICI treatments.

Objectives

Identifying ICI responders before treatment could greatly conserve medical resources, minimize potential drug side effects, and expedite the search for alternative therapies. Our goal is to introduce a novel deep-learning method to predict ICI treatment responses in cancer patients.

Methods

The proposed deep-learning framework leverages graph neural network and biological pathway knowledge. We trained and tested our method using ICI-treated patients' data from several clinical trials covering melanoma, ga

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC12147637 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature