Identification and Characterization of Optimal Gene Expression Markers for Detection of Breast Cancer Metastasis

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