Published online before print October 1, 2009

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Copyright © 2009 American Society for Investigative Pathology
Journal of Molecular Diagnostics, doi:10.2353/jmoldx.2009.090037

Accepted for publication May 1, 2009.

Article

A Quantitative Reverse Transcription-PCR Assay for Rapid, Automated Analysis of Breast Cancer Sentinel Lymph Nodes

Steven J. Hughes^*@, Liqiang Xi, William E. Gooding, David J. Cole, Michael Mitas, John Metcalf^¶, Rohit Bhargava^||, David Dabbs^||, Jesus Ching^**, Lynn Kozma^**, William McMillan^**, and Tony E. Godfrey

From the Departments of Surgery* and Pathology,^|| University of Pittsburgh Medical Cancer, Pittsburgh, Pennsylvania; Department of Pathology, Mount Sinai School of Medicine, New York, New York; Biostatistics Facility, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania; Department of Surgery and Pathology,^¶ Medical University of South Carolina, Charleston, South Carolina; and Cepheid,** Sunnyvale, California

^@ To whom correspondence should be addressed. E-mail: hughess2{at}upmc.edu.

	Abstract

We have previously reported that a quantitative reverse transcription (QRT)-PCR assay accurately analyzes sentinel lymph nodes (SLNs) from breast cancer patients. The aim of this study was to assess a completely automated, cartridge-based version of the assay for accuracy, predictive value, and reproducibility. The triplex (two markers + control) QRT-PCR assay was incorporated into a single-use cartridge for point-of-care use on the GeneXpert system. Three academic centers participated equally. Twenty-nine positive lymph nodes and 30 negative lymph nodes were analyzed to establish classification rules. SLNs from 120 patients were subsequently analyzed by QRT-PCR and histology (including immunohistochemistry), and the predetermined decision rules were used to classify the SLNs; 112 SLN specimens produced an informative result by both QRT-PCR and histology. By histological analysis, 21 SLNs were positive and 91 SLNs were negative for metastasis. QRT-PCR characterization produced a classification with 100% sensitivity, 97.8% specificity, and 98.2% accuracy compared with histology (91.3% positive predictive value and 100% negative predictive value). Interlaboratory reproducibility analyses demonstrated that a 95% prediction interval for a new measurement (Ct) ranged between 0.403 and 0.956. This fully automated QRT-PCR assay accurately characterizes breast cancer SLNs for the presence of metastasis. Furthermore, the assay is not dependent on subjective interpretation, is reproducible across three clinical environments, and is rapid enough to allow intraoperative decision making.