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Cancer Gene Discovery by Network Analysis of Somatic Mutations Using the MUFFINN Server

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Cancer Driver Genes

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1907))

Abstract

Identifying genes that are capable of inducing tumorigenesis has been a major challenge in cancer research. In many cases, such genes frequently show somatic mutations in tumor samples; thus various computational methods for predicting cancer genes have been developed based on “significantly mutated genes.” However, this approach is intrinsically limited by the fact that there are many cancer genes infrequently mutated in cancer genomes. Therefore, we recently developed MUFFINN (Mutations For Functional Impact on Network Neighbors), a method for cancer gene prediction based not only on mutation occurrences in each gene but also those of neighbors in functional networks. This enables the identification of cancer genes with infrequent mutation occurrence. We demonstrated that MUFFINN could retrieve known cancer genes more efficiently than gene-based methods and predicted cancer genes with low mutation occurrences in tumor samples. Users can freely access a web server (http://www.inetbio.org/muffinn) and run predictions with either public or private data of cancer somatic mutations. For given information of mutation occurrence profiles, the MUFFINN server returns lists of candidate cancer genes by four distinct predictions with different combinations between gene networks and scoring algorithms. Stand-alone software is also available, which allows MUFFINN to be run on local machines with a custom gene network. Here, we present an overall guideline for using the MUFFINN web server and stand-alone software for the discovery of novel cancer genes.

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Authors and Affiliations

  1. Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, South Korea

    Heonjong Han & Insuk Lee

  2. EMBL-CRG Systems Biology Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain

    Ben Lehner

Authors
  1. Heonjong Han
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  2. Ben Lehner
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  3. Insuk Lee
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Corresponding author

Correspondence to Insuk Lee .

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Editors and Affiliations

  1. Masonic Cancer Center, University of Minnesota Medical School, Minneapolis, MN, USA

    Timothy K. Starr

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Han, H., Lehner, B., Lee, I. (2019). Cancer Gene Discovery by Network Analysis of Somatic Mutations Using the MUFFINN Server. In: Starr, T. (eds) Cancer Driver Genes. Methods in Molecular Biology, vol 1907. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8967-6_3

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  • DOI: https://doi.org/10.1007/978-1-4939-8967-6_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8966-9

  • Online ISBN: 978-1-4939-8967-6

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