Integrated network analysis and logistic regression modeling identify stage-specific genes in Oral Squamous Cell Carcinoma.

ABSTRACT:

Background

Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity but, OSCC can be difficult to detect at its earliest stage due to its molecular complexity and clinical behavior. Therefore, identification of key gene signatures at an early stage will be highly helpful.

Methods

The aim of this study was to identify key genes associated with progression of OSCC stages. Gene expression profiles were classified into cancer stage-related modules, i.e., groups of genes that are significantly related to a clinical stage. For prioritizing the candidate genes, analysis was further restricted to genes with high connectivity and a significant association with a stage. To assess predictive power of these genes, a classification model was also develop

SUBMITTER: Randhawa V 

PROVIDER: S-EPMC4502639 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature