A curated target gene pool assisting disease prediction and patient-specific biomarker selection for lung squamous cell carcinoma.

ABSTRACT: There have been hundreds of genes demonstrated to be associated with lung squamous cell carcinoma (LSCC), presenting various degrees of association with this disease. In the present study, gene vectors were investigated as genetic biomarkers for the diagnosis and personalized treatment of LSCC. A LSCC genetic database (LSCC_GD) was developed through literature-associated data analysis, where 260 LSCC target genes were curated. Subsequently, numerous associations between these genes and LSCC were studied. Following this, a sparse representation-based variable selection (SRVS) was employed for gene selection from two LSCC gene expression datasets, followed by a case/control classification. Results were compared using analysis of variance (ANOVA)-based gene selection approaches. Using SRVS, a

SUBMITTER: Huang B 

PROVIDER: S-EPMC6126348 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature