Exploring the Metabolic Heterogeneity of Cancers: A Benchmark Study of Context-Specific Models.

ABSTRACT: Metabolic heterogeneity is a hallmark of cancer and can distinguish a normal phenotype from a cancer phenotype. In the systems biology domain, context-specific models facilitate extracting physiologically relevant information from high-quality data. Here, to utilize the heterogeneity of metabolic patterns to discover biomarkers of all cancers, we benchmarked thousands of context-specific models using well-established algorithms for the integration of omics data into the generic human metabolic model Recon3D. By analyzing the active reactions capable of carrying flux and their magnitude through flux balance analysis, we proved that the metabolic pattern of each cancer is unique and could act as a cancer metabolic fingerprint. Subsequently, we searched for proper feature selection methods to

SUBMITTER: Jalili M 

PROVIDER: S-EPMC8229374 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature