The researchers found that integrating gene expression signatures into clinical risk stratification could refine prognosis for patients in three risk subgroups (low, intermediate, and high) and help predict relapse-free survival and response to chemotherapy.
Pending future prospective clinical validation, these results provide preliminary evidence that the profusion of gene expression signatures in defining breast cancer, if used appropriately, represent less of a paradox and should be viewed as an important complementary approach to current clinicopathological risk stratification systems. Furthermore, knowledge of increased likelihood of sensitivity to specific chemotherapeutic agents from a repertoire of drugs that are commonly used to treat breast cancer is something that could be more immediately used in current clinical practice, once issues regarding cost and accessibility are addressed, in instances wherein multiple chemotherapeutics or chemotherapeutic combinations are Food and Drug Administration approved, as in early stage breast cancer, and are considered the standard of care, the authors conclude.
(JAMA. 2008;299:1574-1587. Available pre-embargo to the media at www.jamamedia.org)
Editors Note: Please see the article for additional information, including other authors, author contributions and affiliations, financial disclosures, funding and support, etc.
Editorial: Use of Gene Signatures to Improve Risk Estimation in Cancer
In an accompanying editorial, Chiang-Ching Huang, Ph.D., and Markus Bredel, M.D., Ph.D., of the Feinberg School of Medicine, Northwestern University, Chicago, write that these findings are promising.
In essence, the study by Acharya et al demonstrates the potential value of using microarray-based gene si
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