Multi-omics data integration and modeling unravels new mechanisms for pancreatic cancer and improves prognostic prediction.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC), has recently been found to be a heterogeneous disease, although the extension of its diversity remains to be fully understood. Here, we harmonize transcriptomic profiles derived from both PDAC epithelial and microenvironment cells to develop a Master Regulators (MR)-Gradient model that allows important inferences on transcriptional networks, epigenomic states, and metabolomics pathways that underlies this disease heterogeneity. This gradient model was generated by applying a blind source separation based on independent components analysis and robust principal component analyses (RPCA), following regulatory network inference. The result of these analyses reveals that PDAC prognosis strongly associates with the tumor epithelial cell phenotype and the

SUBMITTER: Fraunhoffer NA 

PROVIDER: S-EPMC9385633 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature