Using MEMo to Discover Mutual Exclusivity Modules in Cancer

Giovanni Ciriello1, Ethan Cerami1, Bulent Arman Aksoy1, Chris Sander1, Nikolaus Schultz1

1 Computational Biology Center, Memorial Sloan‐Kettering Cancer Center, New York, New York
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 8.17
DOI:  10.1002/0471250953.bi0817s41
Online Posting Date:  March, 2013
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Although individual tumors show surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co‐occur in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in Cancer (MEMo). The method searches and identifies modules characterized by three properties: (1) member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. MEMo integrates multiple data types and maps genomic alterations to biological pathways. MEMo's mutual exclusivity uses a statistical model that preserves the number of alterations per gene and per sample. The MEMo software, source code and sample data sets are available for download at: Curr. Protoc. Bioinform. 41:8.17.1‐8.17.12. © 2013 by John Wiley & Sons, Inc.

Keywords: mutual exclusivity; network modules; cancer genomics

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Table of Contents

  • Introduction
  • Basic Protocol 1: Running MEMo on Template Data
  • Basic Protocol 2: Running MEMo Integrating Copy‐Number Alterations and Somatic Mutations
  • Basic Protocol 3: Running MEMo with Customized Alterations
  • Support Protocol 1: Setting Up MEMo on Linux or MAC OS
  • Support Protocol 2: Setting Up MEMo on Windows
  • Support Protocol 3: Compile MEMo from Source Code
  • Guidelines for Understanding Results
  • Commentary
  • Literature Cited
  • Figures
  • Tables
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Literature Cited

   Bell, D., Berchuck, A., Birrer, M., Chien, J., Cramer, D.W., Dao, F., Dhir, R., DiSaia, P., Gabra, H., Glenn, P., et al. 2011. Integrated genomic analyses of ovarian carcinoma. Nature 474:609‐615.
   Beroukhim, R., Getz, G., Nghiemphu, L., Barretina, J., Hsueh, T., Linhart, D., Vivanco, I., Lee, J.C., Huang, J.H., Alexander, S., Du, J., Kau, T., Thomas, R.K., Shah, K., Soto, H., Perner, S., Prensner, J., Debiasi, R.M., Demichelis, F., Hatton, C., Rubin, M.A., Garraway, L.A., Nelson, S.F., Liau, L., Mischel, P.S., Cloughesy, T.F., Meyerson, M., Golub, T.A., Lander, E.S., Mellinghoff, I.K., and Sellers, W.R. 2007. Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma. Proc. Natl. Acad. Sci. U.S.A. 104:20007‐20012.
   Ciriello, G., Cerami, E., Sander, C., and Schultz, N. 2012. Mutual exclusivity analysis identifies oncogenic network modules. Genome Res. 22:398‐406.
   Dees, N.D., Zhang, Q., Kandoth, C., Wendl, M.C., Schierding, W., Koboldt, D.C., Mooney, T.B., Callaway, M.B., Dooling, D., Mardis, E.R., Wilson, R.K., and Ding, L. 2012. MuSiC: Identifying mutational significance in cancer genomes. Genome Res. 22:1589‐1598.
   Getz, G., Hofling, H., Mesirov, J.P., Golub, T.R., Meyerson, M., Tibshirani, R., and Lander, E.S. 2007. Comment on “The consensus coding sequences of human breast and colorectal cancers”. Science 317:1500.
   Taylor, B.S., Barretina, J., Socci, N.D., Decarolis, P., Ladanyi, M., Meyerson, M., Singer, S., and Sander, C. 2008. Functional copy‐number alterations in cancer. PLoS One 3:e3179.
   TCGA. 2008. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455:1061‐1068.
   TCGA. 2011. Integrated genomic analyses of ovarian carcinoma. Nature 474:609‐615.
   TCGA. 2012a. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487:330‐337.
   TCGA. 2012b. Comprehensive molecular portraits of human breast tumours. Nature 490:61‐70.
Internet Resources
  MEMo source code, required libraries, and sample data.‐portal/
  Constantly updated background networks in simple interaction format (SIF) are available through the cBio Cancer Genomics Portal (Cerami et al., 2012) by clicking on the Networks tab.‐+v2.2
  Details on the Mutation Annotation Format (MAF).
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