Gastric Cancer Analysis In Data Mining Techniques

Abstract

Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, a case of primary squamous cell carcinoma of the stomach is reported and the previously reported cases are reviewed. We can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published cell expression data and analyzed them with integrative tool combined with pathway and cell ontology enrichment investigation. Considering not only the stage of disease, but also patients’ age and comorbidities. Experimental validation is proposed to further confirm this finding.