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A module map showing conditional activity of expression modules in cancer

Nature Genetics volume 36, pages 1090–1098 (2004)Cite this article

Abstract

DNA microarrays are widely used to study changes in gene expression in tumors, but such studies are typically system-specific and do not address the commonalities and variations between different types of tumor. Here we present an integrated analysis of 1,975 published microarrays spanning 22 tumor types. We describe expression profiles in different tumors in terms of the behavior of modules, sets of genes that act in concert to carry out a specific function. Using a simple unified analysis, we extract modules and characterize gene-expression profiles in tumors as a combination of activated and deactivated modules. Activation of some modules is specific to particular types of tumor; for example, a growth-inhibitory module is specifically repressed in acute lymphoblastic leukemias and may underlie the deregulated proliferation in these cancers. Other modules are shared across a diverse set of clinical conditions, suggestive of common tumor progression mechanisms. For example, the bone osteoblastic module spans a variety of tumor types and includes both secreted growth factors and their receptors. Our findings suggest that there is a single mechanism for both primary tumor proliferation and metastasis to bone. Our analysis presents multiple research directions for diagnostic, prognostic and therapeutic studies.

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Figure 1: Overview of the analysis procedure.
Figure 2: The cancer module map: a matrix of modules (rows) versus array clinical conditions (columns), where a red (or green) entry indicates that the arrays in which the corresponding module was significantly induced (or repressed) contained more arrays with the given annotation than would be expected by chance.
Figure 3: Combinatorial signatures in the cancer module map.
Figure 4: Growth inhibitory module (#173), a module that responds significantly to one specific condition: acute leukemia.
Figure 5: Steroid catabolism module (#505), a module that responds significantly to one specific condition: liver tissue and tumor samples.
Figure 6: Bone osteoblastic module (#234), a module that responds significantly to multiple conditions, including breast cancer, lung cancer, HCC and ALL.

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Acknowledgements

We thank J. Effrat, T. Fojo, Y. Friedman, A. Kaushal, W. Lu, T. Pham, M. Tong, and R. Yelensky for technical help with software and visualization and I. Ben-Porath, Y. Dor, L. Garwin, N. Kaminski, D. Pe'er, O. Rando and T. Raveh for comments on previous versions of this manuscript. E.S., N.F. and D.K. were supported by a National Science Foundation grant under the Information Technology Research program. E.S. was also supported by a Stanford Graduate Fellowship. N.F. was also supported by an Alon Fellowship, by the Harry & Abe Sherman Senior Lectureship in Computer Science and by the United States-Israel Bi-National Science Foundation grant. N.F. and A.R. were supported by a Center of Excellence Grant from the National Institute of General Medical Sciences. A.R. was also supported by the Bauer Center for Genomics Research.

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Author notes

  1. Eran Segal

    Present address: Center for Studies in Physics and Biology, The Rockefeller University, New York, New York, 10021, USA

Authors and Affiliations

  1. Computer Science Department, Stanford University, Stanford, 94305, California, USA

    Eran Segal & Daphne Koller

  2. School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel

    Nir Friedman

  3. Bauer Center for Genomics Research, Harvard University, Cambridge, 02138, Massachusetts, USA

    Aviv Regev

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  1. Eran Segal
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Correspondence to Daphne Koller or Aviv Regev.

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Supplementary information

Supplementary Fig. 1

Statistical significance of the procedure for deriving a module from a gene set cluster. (PDF 88 kb)

Supplementary Fig. 2

Distribution of the significant array-gene set pairs by conditions. (PDF 106 kb)

Supplementary Table 1

Microarray data sources for the cancer compendium. (PDF 34 kb)

Supplementary Note (PDF 89 kb)

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Segal, E., Friedman, N., Koller, D. et al. A module map showing conditional activity of expression modules in cancer. Nat Genet 36, 1090–1098 (2004). https://doi.org/10.1038/ng1434

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