A Novel Approach to Quantify Heterogeneity of Intrahepatic Cholangiocarcinoma: The Hidden-Genome Classifier.

ABSTRACT:

Purpose

Intrahepatic cholangiocarcinoma (IHC) is a heterogeneous tumor. The hidden-genome classifier, a supervised machine learning-based algorithm, was used to quantify tumor heterogeneity and improve classification.

Experimental design

A retrospective review of 1,370 patients with IHC, extrahepatic cholangiocarcinoma (EHC), gallbladder cancer (GBC), hepatocellular carcinoma (HCC), or biphenotypic tumors was conducted. A hidden-genome model classified 527 IHC based on genetic similarity to EHC/GBC or HCC. Genetic, histologic, and clinical data were correlated.

Results

In this study, 410 IHC (78%) had >50% genetic homology with EHC/GBC; 122 (23%) had >90% homology ("biliary class"), characterized by alterations of KRAS, SMAD4, and CDKN2A loss; 117 IHC (22%) had >50% g

SUBMITTER: Song Y 

PROVIDER: S-EPMC11326964 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature