CanSeer: a translational methodology for developing personalized cancer models and therapeutics.

ABSTRACT: Computational modeling and analysis of biomolecular network models annotated with omics data are emerging as a versatile tool for designing personalized therapies. Current endeavors aimed at employing in silico models towards personalized cancer therapeutics remain limited in providing all-in-one approach that ascertains actionable targets, re-positions FDA (Food and Drug Administration) approved drugs, furnishes quantitative cues on therapy responses such as efficacy and cytotoxic effect, and identifies novel drug combinations. Here we propose "CanSeer"-a methodology for developing personalized therapeutics. CanSeer employs patient-specific genetic alterations and RNA-seq data to annotate in silico models followed by dynamical network analyses towards assessment of treatment responses. To

SUBMITTER: Butt RN 

PROVIDER: S-EPMC12041273 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature