Rna-Seq Data Analysis To Identify Enriched Metabolic Pathways And A Prognostic Signature In Squamous Cell Lung Cancer.

e24288Background: Abnormal changes in the metabolism are cancer hallmarks and can be used as therapeutic targets. Our study aim was to identify enriched metabolic pathways in patients (pts) with squamous cell lung cancer (SQLC). Methods: We evaluated RNA-Seq data (RPKM) of Normal lung tissues and SQLC from GTEx (n = 320) and TCGA (n = 215), respectively. Genes in KEGG metabolism pathways were manually curated. Highly stable genes in the GTEx data was used to normalization. Overall, 2819 genes were evaluated in a Gene Set Enrichment Analysis (GSEA). The TCGA data was randomly divided in training (n = 150) and validation (n = 65) sets. The prognostic value for overall survival (OS) of the top 100 enriched genes (50 for each controls and pts) were assessed in the training group and a prognostic signature was developed then tested in the validation group and in two additional datasets profiled with microarrays (GSE30219 and GSE37745). Results: Eleven metabolic processes were enriched (FDR u003c 25%, p u003c 0.05): Py...