Multi-omic markers of intraductal papillary mucinous neoplasms progression into pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal and common form of pancreatic cancer, it has no specific symptoms, and most of the patients are diagnosed when the disease is already at an advanced stage. Chemotherapy typically has only a modest effect, making surgery the most effective treatment option. However, only a small percentage of patients are amenable to surgery.

A genome-wide association study identifies eight loci associated with intraductal papillary mucinous neoplasm progression toward malignancy.

Background: Intraductal papillary mucinous neoplasms (IPMNs) are precursors to pancreatic cancer, but not all IPMNs progress to cancer. The objective of this study was to identify the germline genetic variants associated with IPMN clinical progression by conducting the first genome-wide association study (GWAS) and computing a polygenic hazard score (PHS) in 338 patients with IPMN.

Methods: The study population was divided into two subsets, and a Cox analysis adjusted for sex, age, cyst size at diagnosis, and the top 10 principal components was performed.

Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank.

Background: Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramount importance, given its high mortality rate. Current PDAC risk prediction models rely on a limited number of variables, do not include genetics, and have a modest accuracy.

Aim: This study aimed to develop an interpretable PDAC risk prediction model, based on machine learning (ML).