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Mangangcha IR, Malik MZ, Kucuk O, et al. Kinless hubs are potential target genes in prostate cancer network. Genomics. 2020;112(6):5227-5239doi: 10.1016/j.ygeno.2020.09.033.
Mangangcha, I. R., Malik, M. Z., Kucuk, O., Ali, S., & Singh, R. K. B. (2020). Kinless hubs are potential target genes in prostate cancer network. Genomics, 112(6), 5227-5239. https://doi.org/10.1016/j.ygeno.2020.09.033
Mangangcha, Irengbam Rocky, et al. "Kinless hubs are potential target genes in prostate cancer network." Genomics vol. 112,6 (2020): 5227-5239. doi: https://doi.org/10.1016/j.ygeno.2020.09.033
Mangangcha IR, Malik MZ, Kucuk O, Ali S, Singh RKB. Kinless hubs are potential target genes in prostate cancer network. Genomics. 2020 Nov;112(6):5227-5239. doi: 10.1016/j.ygeno.2020.09.033. Epub 2020 Sep 23. PMID: 32976977.
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Genomics. 2020 Nov;112(6):5227-5239. doi: 10.1016/j.ygeno.2020.09.033. Epub 2020 Sep 23.

Kinless hubs are potential target genes in prostate cancer network.

Genomics

Irengbam Rocky Mangangcha, Md Zubbair Malik, Omer Kucuk, Shakir Ali, R K Brojen Singh

Affiliations

  1. School of Interdisciplinary Sciences and Technology, Jamia Hamdard, New Delhi 110062, India; Bioinformatics Infrastructure Facility, BIF & Department of Biochemistry, School of Chemical and Life Sciences Jamia Hamdard, New Delhi 110062, India; Department of Zoology, Deshbandhu College, University of Delhi, New Delhi 110019, India; School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
  2. School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
  3. Winship Cancer Institute of Emory University, 1365 Clifton Road NE, Atlanta, GA 30322, USA.
  4. Bioinformatics Infrastructure Facility, BIF & Department of Biochemistry, School of Chemical and Life Sciences Jamia Hamdard, New Delhi 110062, India.
  5. School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India. Electronic address: [email protected].

PMID: 32976977 DOI: 10.1016/j.ygeno.2020.09.033

Abstract

Complex disease networks can be studied successfully using network theoretical approach which helps in finding key disease genes and associated disease modules. We studied prostate cancer (PCa) protein-protein interaction (PPI) network constructed from patients' gene expression datasets and found that the network exhibits hierarchical scale free topology which lacks centrality lethality rule. Knockout experiments of the sets of leading hubs from the network leads to transition from hierarchical (HN) to scale free (SF) topology affecting network integration and organization. This transition, HN → SF, due to removal of significant number of the highest degree hubs, leads to relatively decrease in information processing efficiency, cost effectiveness of signal propagation, compactness, clustering of nodes and energy distributions. A systematic transition from a diassortative PCa PPI network to assortative networks after the removal of top 50 hubs then again reverting to disassortativity nature on further removal of the hubs was also observed indicating the dominance of the largest hubs in PCa network intergration. Further, functional classification of the hubs done by using within module degrees and participation coefficients for PCa network, and leading hubs knockout experiments indicated that kinless hubs serve as the basis of establishing links among constituting modules and heterogeneous nodes to maintain network stabilization. We, then, checked the essentiality of the hubs in the knockout experiment by performing Fisher's exact test on the hubs, and showed that removal of kinless hubs corresponded to maximum lethality in the network. However, excess removal of these hubs essentially may cause network breakdown.

Copyright © 2020. Published by Elsevier Inc.

Keywords: Centrality lethality rule; Hubs; Key disease genes; Network theory; Prostate Cancer; Systems biology

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