Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction.

ABSTRACT: Cancer transcriptional patterns reflect both unique features and shared hallmarks across diverse cancer types, but whether differences in these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that these shared transcriptomic signatures reflect repurposed versions of functional tasks performed by normal tissues. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient surv

SUBMITTER: Weistuch C 

PROVIDER: S-EPMC11549333 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature