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Bayesian Network to Infer Drug-Induced Apoptosis Circuits from Connectivity Map Data

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Gene Expression Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1783))

Abstract

The Connectivity Map (CMAP) project profiled human cancer cell lines exposed to a library of anticancer compounds with the goal of connecting cancer with underlying genes and potential treatments. As most targeted anticancer therapeutics aim to induce tumor-selective apoptosis, it is critical to understand the specific cell death pathways triggered by drugs. This can help to better understand the mechanism of how cancer cells respond to chemical stimulations and improve the treatment of human tumors. In this study, using Connectivity MAP microarray-based gene expression data, we applied a Bayesian network modeling approach and identified apoptosis as a major drug-induced cellular pathway. We focused on 13 apoptotic genes that showed significant differential expression across all drug-perturbed samples to reconstruct the apoptosis network. In our predicted subnetwork, 9 out of 15 high-confidence interactions were validated in literature, and our inferred network captured two major cell death pathways by identifying BCL2L11 and PMAIP1 as key interacting players for the intrinsic apoptosis pathway, and TAXBP1 and TNFAIP3 for the extrinsic apoptosis pathway. Our inferred apoptosis network also suggested the role of BCL2L11 and TNFAIP3 as “gateway” genes in the drug-induced intrinsic and extrinsic apoptosis pathways.

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Author information

Authors and Affiliations

  1. Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Jiyang Yu

  2. Department of Pathology, Icahn School of Medicine at Mount Sinai, The Mount Sinai Hospital, New York, NY, USA

    Jose M. Silva

Authors
  1. Jiyang Yu
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  2. Jose M. Silva
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Corresponding author

Correspondence to Jiyang Yu .

Editor information

Editors and Affiliations

  1. Division of Geriatrics and Clinical Gerontology, National Institute on Aging, Bethesda, Maryland, USA

    Nalini Raghavachari

  2. Environmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, Mississippi, USA

    Natàlia Garcia-Reyero

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Yu, J., Silva, J.M. (2018). Bayesian Network to Infer Drug-Induced Apoptosis Circuits from Connectivity Map Data. In: Raghavachari, N., Garcia-Reyero, N. (eds) Gene Expression Analysis. Methods in Molecular Biology, vol 1783. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7834-2_18

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  • DOI: https://doi.org/10.1007/978-1-4939-7834-2_18

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7833-5

  • Online ISBN: 978-1-4939-7834-2

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