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Bioinformatics Advance Access originally published online on August 12, 2004
Bioinformatics 2005 21(2):171-178; doi:10.1093/bioinformatics/bth469
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Bioinformatics vol. 21 issue 2 © Oxford University Press 2005; all rights reserved.

Outcome signature genes in breast cancer: is there a unique set?

Liat Ein-Dor 1,{dagger}, Itai Kela 1,3,{dagger}, Gad Getz 1,{dagger}, David Givol 2 and Eytan Domany 1,*

1 Department of Physics of Complex Systems, Weizmann Institute of Science Rehovot 76100, Israel
2 Department of Molecular Cell Biology, Weizmann Institute of Science Rehovot 76100, Israel
3 Department of Immunology, Weizmann Institute of Science Rehovot 76100, Israel

*To whom correspondence should be addressed.

Motivation: Predicting the metastatic potential of primary malignant tissues has direct bearing on the choice of therapy. Several microarray studies yielded gene sets whose expression profiles successfully predicted survival. Nevertheless, the overlap between these gene sets is almost zero. Such small overlaps were observed also in other complex diseases, and the variables that could account for the differences had evoked a wide interest. One of the main open questions in this context is whether the disparity can be attributed only to trivial reasons such as different technologies, different patients and different types of analyses.

Results: To answer this question, we concentrated on a single breast cancer dataset, and analyzed it by a single method, the one which was used by van't Veer et al. to produce a set of outcome-predictive genes. We showed that, in fact, the resulting set of genes is not unique; it is strongly influenced by the subset of patients used for gene selection. Many equally predictive lists could have been produced from the same analysis. Three main properties of the data explain this sensitivity: (1) many genes are correlated with survival; (2) the differences between these correlations are small; (3) the correlations fluctuate strongly when measured over different subsets of patients. A possible biological explanation for these properties is discussed.

Contact: eytan.domany{at}weizmann.ac.il

Supplementary information: http://www.weizmann.ac.il/physics/complex/compphys/downloads/liate/


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