Introduction: Gastric cancers (GC) have the high morbidity and mortality rates worldwide . Many efforts in recent years have attempted to find effective proteins in gastric cancer. By using a pervasive list of proteins involved in gastric cancer, scientists were able to retrieve interaction information. The study of protein-protein interaction networks through systems biology based analysis provides appropriate strategies to discover candidate proteins and key biological pathways and in final drug candidate for treatment.
Methods: We explored expression profiles (GSE54129 from NCBI GEO) for gastric cancer (GC) and noncancerous gastric tissue samples. The dataset was generated by Homo sapiens. The dataset includes 132 transcriptomic profiles, 21 from noncancerous gastric tissues and 111 from gastric tumor samples. We directly downloaded the processed expression data and used log Fold change of the expression values for the following analysis. After normalizing the data with p< 0.05, the genes lead to the STRING server to find the connection between the proteins. Then network of connected genes gain by Cytoscape software and centrality parameters including betweenness, degree, and closeness of each topological clusters and expressionally active sub-networks in the resulted network .Interaction information of introduced proteins in literature was gathered from well-known protein-protein interaction databases including Reactome, KEGG, IntAct, and Wiki pathway and in this way method is validated. In the following, drug candidate predict for bcl2 protein by shrodinger software.
Results: The results of functional analysis on gene sets showed that p53 signaling pathway, Hedgehog signaling pathway and Colorectal cancer and HIF-1 signaling pathway excision possess the strongest enrichment signals. According to the computed centrality parameters, BANF1, MALAT1, BCL2 and TP53 manifested as the most significant nodes in the interaction network of the engaged proteins in gastric cancer.
Conclusion: This study also demonstrates pathways and proteins that are applicable as diagnostic markers and therapeutic targets for future attempts to overcome gastric cancer and introduce 10 drug candidate for treatment of gastreic cancer.
Keywords: Gastric cancer- systems biology- 3D-QSAR- network