DNA methylation-based classifier differentiates intrahepatic pancreato-biliary tumours.

ABSTRACT:

Background

Differentiating intrahepatic cholangiocarcinomas (iCCA) from hepatic metastases of pancreatic ductal adenocarcinoma (PAAD) is challenging. Both tumours have similar morphological and immunohistochemical pattern and share multiple driver mutations. We hypothesised that DNA methylation-based machine-learning algorithms may help perform this task.

Methods

We assembled genome-wide DNA methylation data for iCCA (n = 259), PAAD (n = 431), and normal bile duct (n = 70) from publicly available sources. We split this cohort into a reference (n = 399) and a validation set (n = 361). Using the reference cohort, we trained three machine learning models to differentiate between these entities. Furthermore, we validated the classifiers on the technical validation set and used a

SUBMITTER: Dragomir MP 

PROVIDER: S-EPMC10333440 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature