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A computational pipeline for deciphering the molecular mechanisms of oral cancer progression

In this work we present a computational pipeline in order to further study the molecular mechanisms underlying the progression of Oral Squamous Cell Carcinoma. Microarray gene expression data of oral cancer patients are exploited aiming to identify the differentially expressed genes between relapse and non-relapse samples. Furthermore, gene ontology analysis of the significant genes is performed and the associated functional groups are annotated. Thus, we are able to interpret the differential expression results in terms of biological processes, molecular functions and cellular components. In addition, pathway enrichment analysis is also considered based on a curated database of molecular pathways. According to our analysis results, genes that exhibit remarkable changes in expression, such as the YES1 oncogene has been predicted to interact closely with genes implicated in oral cancer. Concerning the pathway enrichment analysis, Ribosome and Tyrosine metabolism pathways are identified and should be considered for further analysis.