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PathMEx: Pathway-Based Mutual Exclusivity for Discovering Rare Cancer Driver Mutations

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Computational Science – ICCS 2021 (ICCS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12743))

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Abstract

The genetic material we carry today is different from that we were born with: our DNA is prone to mutations. Some of these mutations can make a cell divide without control, resulting in a growing tumor. Typically, in a cancer sample from a patient, a large number of mutations can be detected, and only a few of those are drivers - mutations that positively contribute to tumor growth. The majority are passenger mutations that either accumulated before the onset of the disease but did not cause it, or are byproducts of the genetic instability of cancer cells. One of the key questions in understanding the process of cancer development is which mutations are drivers, and should be analyzed as potential diagnostic markers or targets for therapeutics, and which are passengers. We propose PathMEx, a novel method based on simultaneous optimization of patient coverage, mutation mutual exclusivity, and pathway overlap among putative cancer driver genes. Compared to state-of-the-art method Dendrix, the proposed algorithm finds sets of putative driver genes of higher quality in three sets of cancer samples: brain, lung, and breast tumors. The genes in the solutions belong to pathways with known associations with cancer. The results show that PathMEx is a tool that should be part of a state-of-the-art toolbox in the driver gene discovery pipeline. It can help detect low-frequency driver genes that can be missed by existing methods.

Supported by NSF grant IIS-1453658.

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Acknowledgements

TA is supported by NSF grant IIS-1453658.

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Authors and Affiliations

  1. Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia

    Yahya Bokhari

  2. Department of Computer Science, Virginia Commonwealth University, Richmond, VA, 23284, USA

    Tomasz Arodz

Authors
  1. Yahya Bokhari
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  2. Tomasz Arodz
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Correspondence to Tomasz Arodz .

Editor information

Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Dieter Kranzlmüller

  3. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  4. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  5. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Bokhari, Y., Arodz, T. (2021). PathMEx: Pathway-Based Mutual Exclusivity for Discovering Rare Cancer Driver Mutations. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12743. Springer, Cham. https://doi.org/10.1007/978-3-030-77964-1_43

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  • DOI: https://doi.org/10.1007/978-3-030-77964-1_43

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