Feature Selection and Network-Driven Analyses to Unveil Common RNA Signatures in Colon and Pancreatic KRAS-Mutant Cancers.

ABSTRACT:

Background

Colon cancer and pancreatic ductal adenocarcinoma are among the most aggressive tumors for which therapeutic options are limited. Both cancers share common features, such as some KRAS pathogenic variants and common epidemiology. The integration of multidimensional datasets by combining machine learning and bioinformatics approaches could provide deeper insights into the intricate KRAS-related networks underlying cancer progression and unveil novel biomarkers and potential therapeutic targets. This study aimed to uncover colon and pancreatic cancers that shared transcriptional changes closely related to KRAS missense mutations.

Methods

Feature Selection (FS) technique and Qiagen's Ingenuity Pathway Analysis (IPA) were used to combine DNA-Seq and RNA-Seq data from m

SUBMITTER: Pane K 

PROVIDER: S-EPMC11865888 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature