Interpreting the distinct and shared genetic characteristics between Epstein-Barr virus associated and non-associated...

Gastric carcinoma is one of the major causes of cancer mortality worldwide. There is a better prognosis for patients with Epstein-Barr virus (EBV)-associated gastric carcinoma (EBVaGC) compared with those with EBV negative gastric carcinoma (EBVnGC). It is partly due to the fact that EBV infection recruits lymphocytes infiltrating the tumor. It has been reported that this infection indeed resulted in the changes in immune response genes and thus preventing the development of tumor. It is worthwhile to do a systematic study of EBVaGC and EBVnGC based on genetic characteristics and pathways. In this study, we investigated the information of gene ontology (GO) and KEGG pathway annotations to characterize EBVaGC and EBVnGC-related genes. By applying minimum redundancy maximum relevance (mRMR) algorithm, we provided an optimal set of features for identifying the EBVaGC and EBVnGC. We also employed the shortest path algorithm to probe the novel EBVaGC- and EBVnGC-related genes based on the interaction network of genes that differently expressed in them respectively. We obtained 1039 and 1003 features to identify these two types of gastric carcinoma respectively. Based on the optimal features of classification, we predicted 1881 and 2475 novel genes as additional candidates to support clinical research respectively for these two types of gastric cancers. We compared the differences and similarities of molecular traits between EBVaGC and EBVnGC, which would facilitate the understanding of gastric cancer and its therapy and was thus clinically relevant.