Identification and Characterization of Optimal Gene Expression Markers for Detection of Breast Cancer Metastasis
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Date
2005-08
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Authors
Backus, John
Laughlin, Todd
Wang, Yixin
Belly, Robert
White, Robert
Baden, Jon
Min, C. Justus
Mannie, Ann
Tafra, Lorraine
Atkins, David
Journal Title
Journal ISSN
Volume Title
Publisher
East Carolina University
Abstract
Sentinel lymph node (SLN) status is highly predictive of
overall axillary lymph node involvement in breast cancer.
Historically, SLN-positive patients have undergone
axillary lymph node dissection in a second surgery.
Intraoperative SLN analysis could reduce the cost and
complications of a second surgery; however, existing
histopathological methods lack standardization and exhibit
poor sensitivity. Rapid molecular methods may
lead to improved intraoperative diagnosis of SLN metastasis.
In this study,we used a genome-wide gene expression
analysis of breast and other tissues to identify
seven putative markers for detecting breast cancer metastasis.
We assessed the utility of these markers for
identifying clinically actionable metastases in lymph
nodes through reverse transcriptase-polymerase chain
reaction analysis of SLNs from 254 breast cancer patients.
Polymerase chain reaction signals were compared
to pathology on a per-patient basis. The optimal
two-gene combination, mammaglobin and cytokeratin
19, detected clinically actionable metastasis in breast
SLNs with 90% sensitivity and 94% specificity. Application
of stringent criteria for identifying presumptive
hematoxylin- and eosin-positive samples increased sensitivity
and specificity to 91 and 97%, respectively. This
study represents the first comprehensive demonstration
of the utility of gene expression markers for detecting
clinically actionable breast metastases. An intraoperative
molecular assay using these markers has the
potential to significantly reduce second surgeries for
patients undergoing SLN dissection. Originally published Journal of Molecular Diagnostics, Vol. 7, No. 3, Aug 2005
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Citation
Journal of Molecular Diagnostics; 7:3 p. 327-336
DOI
10.1016/S1525-1578(10)60561-2