Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers.

ABSTRACT: To date, microarray analyses have led to the discovery of numerous individual 'molecular signatures' associated with specific cancers. However, there are serious limitations for the adoption of these multi-gene signatures in the clinical environment for diagnostic or prognostic testing as studies with more power need to be carried out. This may involve larger richer cohorts and more advanced analyses. In this study, we conduct analyses-based on gene regulatory network-to reveal distinct and common biomarkers across cancer types. Using microarray data of triple-negative and medullary breast, ovarian and lung cancers applied to a combination of glasso and Bayesian networks (BNs), we derived a unique network-containing genes that are uniquely involved: small proline-rich protein 1A (SPRR1A),

SUBMITTER: Chudasama D 

PROVIDER: S-EPMC5862298 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature