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Article

Malignant Pleural Mesothelioma Interactome with 364 Novel Protein-Protein Interactions

1
Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India
2
Exposure Assessment Branch, National Institute of Occupational Safety and Health, Center for Disease Control, Morgantown, WV 26506, USA
3
Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15206, USA
4
Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA 15213, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Daniel L. Pouliquen and Joanna Kopecka
Cancers 2021, 13(7), 1660; https://doi.org/10.3390/cancers13071660
Received: 28 February 2021 / Revised: 19 March 2021 / Accepted: 22 March 2021 / Published: 1 April 2021
(This article belongs to the Special Issue Malignant Mesothelioma)
Internal organs like the heart and lungs, and body cavities like the thoracic and abdominal cavities, are covered by a thin, slippery layer called the mesothelium. Malignant pleural mesothelioma (MPM) is an aggressive cancer of the lining of the lung, where genetics and asbestos exposure play a role. It is not diagnosable until it becomes invasive, offering only a short survival time to the patient. To help understand the role of the genes that relate to this disease most of which are poorly understood, we constructed the ‘MPM interactome’, including in it the protein-protein interactions that we predicted computationally and those that are previously known in the literature. Five novel protein-protein interactions (PPIs) were tested and validated experimentally. 85.65% of the interactome is supported by genetic variant, transcriptomic, and proteomic evidence. Comparative transcriptome analysis revealed 5 repurposable drugs targeting the interactome proteins. We make the interactome available on a freely accessible web application, Wiki-MPM.
Malignant pleural mesothelioma (MPM) is an aggressive cancer affecting the outer lining of the lung, with a median survival of less than one year. We constructed an ‘MPM interactome’ with over 300 computationally predicted protein-protein interactions (PPIs) and over 2400 known PPIs of 62 literature-curated genes whose activity affects MPM. Known PPIs of the 62 MPM associated genes were derived from Biological General Repository for Interaction Datasets (BioGRID) and Human Protein Reference Database (HPRD). Novel PPIs were predicted by applying the HiPPIP algorithm, which computes features of protein pairs such as cellular localization, molecular function, biological process membership, genomic location of the gene, and gene expression in microarray experiments, and classifies the pairwise features as interacting or non-interacting based on a random forest model. We validated five novel predicted PPIs experimentally. The interactome is significantly enriched with genes differentially ex-pressed in MPM tumors compared with normal pleura and with other thoracic tumors, genes whose high expression has been correlated with unfavorable prognosis in lung cancer, genes differentially expressed on crocidolite exposure, and exosome-derived proteins identified from malignant mesothelioma cell lines. 28 of the interactors of MPM proteins are targets of 147 U.S. Food and Drug Administration (FDA)-approved drugs. By comparing disease-associated versus drug-induced differential expression profiles, we identified five potentially repurposable drugs, namely cabazitaxel, primaquine, pyrimethamine, trimethoprim and gliclazide. Preclinical studies may be con-ducted in vitro to validate these computational results. Interactome analysis of disease-associated genes is a powerful approach with high translational impact. It shows how MPM-associated genes identified by various high throughput studies are functionally linked, leading to clinically translatable results such as repurposed drugs. The PPIs are made available on a webserver with interactive user interface, visualization and advanced search capabilities. View Full-Text
Keywords: malignant mesothelioma; protein-protein interactions; systems biology; network analysis; drug repurposing malignant mesothelioma; protein-protein interactions; systems biology; network analysis; drug repurposing
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MDPI and ACS Style

Karunakaran, K.B.; Yanamala, N.; Boyce, G.; Becich, M.J.; Ganapathiraju, M.K. Malignant Pleural Mesothelioma Interactome with 364 Novel Protein-Protein Interactions. Cancers 2021, 13, 1660. https://doi.org/10.3390/cancers13071660

AMA Style

Karunakaran KB, Yanamala N, Boyce G, Becich MJ, Ganapathiraju MK. Malignant Pleural Mesothelioma Interactome with 364 Novel Protein-Protein Interactions. Cancers. 2021; 13(7):1660. https://doi.org/10.3390/cancers13071660

Chicago/Turabian Style

Karunakaran, Kalyani B.; Yanamala, Naveena; Boyce, Gregory; Becich, Michael J.; Ganapathiraju, Madhavi K. 2021. "Malignant Pleural Mesothelioma Interactome with 364 Novel Protein-Protein Interactions" Cancers 13, no. 7: 1660. https://doi.org/10.3390/cancers13071660

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