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International Journal of Cancer Research
Year: 2017  |  Volume: 13  |  Issue: 2  |  Page No.: 51 - 58

Identification of Target Genes in Breast Cancer Pathway using Protein-Protein Interaction Network

Divya Bafna and Arnold Emerson Isaac    

Abstract: Background and Objective: The emergence of cancer genomics has expanded the background of protein-protein interaction network applications for identification of protein targets for drug development. The objective of the present study was to analyse breast cancer pathway genes to determine the potential drug targets. Methodology: In this study, breast cancer subnetwork was constructed from the pathway genes and potential targets in breast cancer pathway were identified using node or gene deletion analysis. The most popular centrality measures, such as betweenness and closeness centrality play a major role in the network robustness. Deleting the genes with the highest centrality values may result in significant destruction of the network. The significantly mutated values of the genes involved assists in selecting a precise target were determined using z-score. Results: On deleting the top 10 genes with highest betweenness centrality, significant (p<0.05) changes were observed in both shortest path length (L) and clustering coefficient (c) values as compared to breast cancer subnetwork. Out of these top 10 genes two of them had positive significant mutation values. Conclusion: These genes were identified to be NOTCH 1 (NOTCH family of proteins) and epidermal growth factor receptor (EGFR family) and therefore, these genes are possible target for drug therapy.

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