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The role of protein interaction domains in the human cancer network

By Shady S. Ibrahim, Maha AR. Eldeeb and et al. Mona AH. Rady

Abstract

Protein-protein interaction networks provide a global picture of cellular function and biological processes. Proteins interact largely through specific domains which constitute the main building blocks of an interaction network. Perturbed or dysfunctional protein interactions are linked to many diseases, including cancer. In this study we describe the major pathways and connections within the human cancer network by a novel approach in which we overlay the human cancer network with all protein interaction domain (PID) superfamilies. Based on 38,777 experimentally derived interactions, we constructed a cancer network with 8 different levels and identified all major protein hubs within this cancer interactome. Only one percent of the cancer genes constitute over 50 percent of all interactions within the network. In addition, we mapped 56 PID superfamilies onto the cancer network, and discovered that over 10% of protein interaction domains are overrepresented within the cancer interactome when compared to the normal protein network. We present here a comprehensive list of all PIDs in the cancer network, identify the most important hubs within it and discover several individual genes which had previously not been linked to cancer. These proteins constitute excellent targets for the development of novel cancer therapeutics. Our results further hint to a partial molecular commonality between cancer and neurodegenerative diseases such as Alzheimer's and Huntington's

Topics: protein domain, interaction network, PDZ domain, systems biology, cancer, tumour, superfamily, metastasis, interactome, p53, signaling, protein binding, neurodegenerative disease, Alzheimer, Huntington, NMDAR, Biology (General), QH301-705.5, Science, Q, DOAJ:Biology, DOAJ:Biology and Life Sciences
Publisher: International Academy of Ecology and Environmental Sciences
Year: 2011
OAI identifier: oai:doaj.org/article:e159dca2040741ff989d5c187d775c6e
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