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.
| Original language | English |
|---|---|
| Pages (from-to) | 1090-1098 |
| Number of pages | 9 |
| Journal | Nature Genetics |
| Volume | 36 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2004 |
Bibliographical note
Funding Information: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.
