Introducing crucial protein panel of gastric adenocarcinoma disease

AIM

Since interactome analysis of diseases can provide candidate biomarker panel related to the diseases, in this research, protein-protein interaction (PPI) network analysis is used to introduce the involved crucial proteins in Gastric adenocarcinoma (GA).

BACKGROUND

Gastric adenocarcinoma (GA) is the most common type of stomach cancer. There is no efficient diagnostic molecular method for GA.

METHOD

Applying Cytoscape software 3.4.0 and String Database, the PPI network was constructed for 200 genes. Based on centrality parameters, the critical nodes were screened. Gene ontology of the key proteins for pathway analysis and molecular function processing were done and the highlighted pathways and activities were discussed.

RESULTS

Among 200 initial genes, 141 genes were included in a main connected network. Seven crucial proteins, including tumor protein p53, epidermal growth factor receptor, albumin, v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian), v-akt murine thymoma viral oncogene homolog 1, v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) and catenin (cadherin-associated protein), beta 1, 88kDa, and Myogenic differentiation 1, were introduced as key nodes of the network. These identified proteins are mostly involved in pathways and activities related to cancer.

CONCLUSION

In conclusion, the finding is corresponding to the significant roles of these introduced proteins in GA disease. This protein panel may be a useful probe in the management of GA.

Evaluation of involved proteins in colon adenocarcinoma: an interactome analysis

AIM

Assessment of related genes to colon cancer to introduce crucial ones, was the aim of this research.

BACKGROUND

Colon cancer is one of the invasive colorectal diseases. This disease is preventable and manageable if it be diagnosed in early stage. The aggressive tools for its detection imply more investigation for new molecular diagnostic methods.

METHODS

Numbers of 300 genes from String database (SD) are analyzed via constructed Protein-protein interaction (PPI) network by Cytoscape software 3.4.0. Based on centrality parameters the main connected component of network was analyzed and the crucial genes were introduced. Cluster analysis of the network and gene ontology for the nodes of the main cluster revealed more details about the role of the key proteins related to colon cancer disease.

RESULTS

The constructed network was consisted of 300 genes which among them 68 genes were isolated and the 232 other genes formed the main connected component. Ten crucial genes related to colon adenocarcinoma were introduced that presented in cluster 1. Gene ontology analysis showed that cluster 1 is involved in 226 biological processes which are classified in 25 groups.

CONCLUSION

In conclusion, results indicate that the identified key proteins play significant roles in colon adenocarcinoma. It may be possible to introduce a few diagnostic biomarker candidates for colon cancer disease.