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Do cancer proteins really interact strongly in the human protein-protein interaction network?

Published: 01 June 2011 Publication History

Abstract

Graphical abstractDisplay Omitted Highlights Compared topological properties of four categories of proteins in four interactomes. Cancer proteins interact more strongly than other proteins in four organisms. Strong interaction of cancer proteins is not introduced by data bias. Implication for cancer proteins' biological function in cellular system. Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer.

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Cited By

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  • (2018)A computational approach inspired by simulated annealing to study the stability of protein interaction networks in cancer and neurological disordersData Mining and Knowledge Discovery10.1007/s10618-015-0410-530:1(226-242)Online publication date: 26-Dec-2018

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        Published In

        cover image Computational Biology and Chemistry
        Computational Biology and Chemistry  Volume 35, Issue 3
        June, 2011
        90 pages

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        Elsevier Science Publishers B. V.

        Netherlands

        Publication History

        Published: 01 June 2011

        Author Tags

        1. Cancer genes
        2. Cancer proteins
        3. Global network characteristics
        4. Network topology
        5. Protein interaction network
        6. Protein-protein interactions

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        • (2018)A computational approach inspired by simulated annealing to study the stability of protein interaction networks in cancer and neurological disordersData Mining and Knowledge Discovery10.1007/s10618-015-0410-530:1(226-242)Online publication date: 26-Dec-2018

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