A pathomics-integrated multimodal model to evaluate chemoimmunotherapy efficacy in unresectable intrahepatic cholangiocarcinoma.

ABSTRACT:

Background & aims

Chemoimmunotherapy has emerged as the first-line therapy for unresectable intrahepatic cholangiocarcinoma (ICC). However, durable clinical responses are observed in less than 30% of patients, necessitating biomarkers of survival benefit. Thus, the aim of this study was to develop and validate a pathomics-based prognostic signature for patients with ICC receiving chemoimmunotherapy.

Methods

This multicenter study included patients with ICC with biopsy samples. Pathomics features were extracted from digital H&E-stained images, and the pathomics signature for ICC (PS-ICC) was developed by machine learning (ML). SHapley Additive exPlanations provided algorithmic explanation, and The Cancer Genome Atlas database supported biological interpretation. We explored t

SUBMITTER: Cao QH 

PROVIDER: S-EPMC12529501 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature