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Microarrays 2013, 2(3), 228-242; doi:10.3390/microarrays2030228

Improving Pathological Assessment of Breast Cancer by Employing Array-Based Transcriptome Analysis

1 Deptartment of Pediatrics, Semmelweis University, Budapest H-1083, Hungary 2 Research Laboratory of Pediatrics and Nephrology, Hungarian Academy of Sciences, Budapest H-1083, Hungary
* Author to whom correspondence should be addressed.
Received: 29 July 2013 / Revised: 17 August 2013 / Accepted: 22 August 2013 / Published: 29 August 2013
(This article belongs to the Special Issue Clinical Applications of Microarrays)
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Breast cancer research has paved the way of personalized oncology with the introduction of hormonal therapy and the measurement of estrogen receptor as the first widely accepted clinical biomarker. The expression of another receptor—HER2/ERBB2/neu—was initially a sign of worse prognosis, but targeted therapy has granted improved outcome for these patients so that today HER2 positive patients have better prognosis than HER2 negative patients. Later, the introduction of multigene assays provided the pathologists with an unbiased assessment of the tumors’ molecular fingerprint. The recent FDA approval of complete microarray pipelines has opened new possibilities for the objective classification of breast cancer samples. Here we review the applications of microarrays for determining ER and HER2 status, molecular subtypes as well as predicting prognosis and grade for breast cancer patients. An open question remains the role of single genes within such signatures. Openly available microarray datasets enable the execution of an independent cross-validation of new marker and signature candidates. In summary, we review the current state regarding clinical applications of microarrays in breast cancer molecular pathology.
Keywords: breast cancer; microarray; molecular subtype; prognosis; prediction; biomarker breast cancer; microarray; molecular subtype; prognosis; prediction; biomarker
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Mihály, Z.; Győrffy, B. Improving Pathological Assessment of Breast Cancer by Employing Array-Based Transcriptome Analysis. Microarrays 2013, 2, 228-242.

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