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Review
. 2011 Dec 6;9(1):48-57.
doi: 10.1038/nrclinonc.2011.178.

Practical implications of gene-expression-based assays for breast oncologists

Aleix Prat  1 , Matthew J Ellis, Charles M Perou
Affiliations
Review

Practical implications of gene-expression-based assays for breast oncologists

Aleix Prat et al. Nat Rev Clin Oncol. .

Abstract

Gene-expression profiling has had a considerable impact on our understanding of breast cancer biology, and more recently on clinical care. Two statistical approaches underlie these advancements. Supervised analyses have led to the development of gene-expression signatures designed to predict survival and/or treatment response, which has resulted in the development of new clinical assays. Unsupervised analyses have identified numerous biological signatures including signatures of cell type of origin, signaling pathways, and of cellular proliferation. Included within these biological signatures are the molecular subtypes known as the 'intrinsic' subtypes of breast cancer. This classification has expanded our appreciation of the heterogeneity of breast cancer and has provided a way to sub-classify the disease in a manner that might have clinical utility. In this Review, we discuss the clinical utility of gene-expression-based assays and their technical potential as clinical tools vis-a-vis the performance of breast cancer biomarkers that are the current standard of care.

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Conflict of interest statement

Competing interests

M. J. Ellis and C. M. Perou declare associations with the following company: BioClassifier. See the article online for full details of the relationship. A. Prat declares no competing interests.

Figures

Figure 1
Figure 1
Identification of tumor individuality using global gene-expression analyses. a | Supervised hierarchical clustering of breast cancer data from Harrell et al. of 367 breast samples using 1,900 intrinsic genes. Paired tumor samples are highlighted by the red lines in the array tree, with 41 out of 43 possible pairs being paired. The two paired samples that did not pair together are shown in green and light blue color. Note that one of each paired sample was a primary tumor sample that was present within the normal-like cluster, which suggests that both were highly contaminated with true normal breast tissue. b | A subset of the basal-like array tree showing the different array names. Note that some tumors had more than two samples, and in all cases, these were all grouped together. Abbreviations: INT, second partner of an intrinsic pair (that is, two distinct pieces of the same primary tumor); LN, lymph-node metastasis; Met, distant metastasis; Meta, metaplastic.
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References

    1. Jemal A, Siegel R, Xu J, Ward E. Cancer Statistics, 2010. CA Cancer J Clin. 2010;60:277–300. - PubMed
    1. NCCM Clinical Practicce Guidelines in Oncology. Breast Cancer. 2011 [online], http://www.nccn.org/professionals/physician_gls/pdf/breast.pdf.
    1. Harris L, et al. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol. 2007;25:5287–5312. - PubMed
    1. Goldhirsch A, et al. Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol. 2011;22:1736–1747. - PMC - PubMed
    1. Wirapati P, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10:R65. - PMC - PubMed

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