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. 2012 Jun 19;14(3):313.
doi: 10.1186/bcr3173.

Prognostic signatures in breast cancer: correlation does not imply causation

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Prognostic signatures in breast cancer: correlation does not imply causation

Charlotte Ng et al. Breast Cancer Res. .

Abstract

Testing the statistical associations between microarray-based gene expression signatures and patient outcome has become a popular approach to infer biological and clinical significance of laboratory observations. Venet and colleagues recently demonstrated that the majority of randomly generated gene signatures are significantly associated with outcome of breast cancer patients, and that this association stems from the fact that a large proportion of the transcriptome is significantly correlated with proliferation, a strong predictor of outcome in breast cancer patients. These findings demonstrate that a statistical association between a gene signature and disease outcome does not necessarily imply biological significance.

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References

    1. Colombo PE, Milanezi F, Weigelt B, Reis-Filho JS. Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction. Breast Cancer Res. 2011;13:212. doi: 10.1186/bcr2890. - DOI - PMC - PubMed
    1. Weigelt B, Pusztai L, Ashworth A, Reis-Filho JS. Challenges translating breast cancer gene signatures into the clinic. Nat Rev Clin Oncol. 2011;9:58–64. doi: 10.1038/nrclinonc.2011.125. - DOI - PubMed
    1. Reis-Filho JS, Pusztai L. Gene expression profiling in breast cancer: classification, prognostication, and prediction. Lancet. 2011;378:1812–1823. doi: 10.1016/S0140-6736(11)61539-0. - DOI - PubMed
    1. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lønning PE, Børresen-Dale AL, Brown PO, Botstein D. Molecular portraits of human breast tumours. Nature. 2000;406:747–752. doi: 10.1038/35021093. - DOI - PubMed
    1. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Lønning PE, Børresen-Dale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001;98:10869–10874. doi: 10.1073/pnas.191367098. - DOI - PMC - PubMed

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