Regressions of Clustered Gene Expression Data Manifest Tumor-Specific Genes in Urinary Bladder Cancer

Abstract

Bladder cancer or urinary bladder cancer, is a common neoplasm of the urinary tract, with higher prevalence in men aged 60 to 70 years. In the present work we have used gene expression microarray data both from in-house experimentation, as well as from publicly available microarray data. We have used bioinformatics analyses as well as regression methodologies, in order to find common gene expression profiles with respect to tumor subtypes and differentiation. Our approach included gene clustering with k-means, and gene functional annotation. We have found several gene groups that manifest common expression profiles and also we have identified clusters of genes that manifested an ascending or descending pattern with respect to tumor differentiation and subtype. Such approaches could prove useful to the identification of noel gene targets that could be utilized as prognostic, diagnostic and therapeutic targets.