Identification of copy number variation-driven molecular subtypes informative for prognosis and treatment in pancreatic adenocarcinoma of a Chinese cohort.

ABSTRACT:

Background

Pancreatic adenocarcinoma (PAAD) is one of the most lethal carcinomas, and the current histopathological classifications are of limited use in clinical decision-making. There is an unmet need to identify new biomarkers for prognosis-informative molecular subtyping and ultimately for precision medicine.

Methods

We profiled genomic alterations for 608 PAAD patients in a Chinese cohort, including somatic mutations, pathogenic germline variants and copy number variations (CNV). Using the CNV information, we performed unsupervised consensus clustering of these patients, differential CNV analysis and functional/pathway enrichment analysis. Cox regression was conducted for progression-free survival analysis, the elastic net algorithm used for prognostic model constructio

SUBMITTER: Zhan Q 

PROVIDER: S-EPMC8628206 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature