A rapid, fully automated, molecular-based assay accurately analyzes sentinel lymph nodes for the presence of metastatic breast cancer.
OBJECTIVE
To develop a fully automated, rapid, molecular-based assay that accurately and objectively evaluates sentinel lymph nodes (SLN) from breast cancer patients.


BACKGROUND
Intraoperative analysis for the presence of metastatic cancer in SLNs from breast cancer patients lacks sensitivity. Even with immunohistochemical staining (IHC) and time-consuming review, alarming discordance in the interpretation of SLN has been observed.


METHODS
A total of 43 potential markers were evaluated for the ability to accurately characterize lymph node specimens from breast cancer patients as compared with complete histologic analysis including IHC. Selected markers then underwent external validation on 90 independent SLN specimens using rapid, multiplex quantitative reverse transcription-polymerase chain reaction (QRT-PCR) assays. Finally, 18 SLNs were analyzed using a completely automated RNA isolation, reverse transcription, and quantitative PCR instrument (GeneXpert).


RESULTS
: Following analysis of potential markers, promising markers were evaluated to establish relative level of expression cutoff values that maximized classification accuracy. A validation set of 90 SLNs from breast cancer patients was prospectively characterized using 4 markers individually or in combinations, and the results compared with histologic analysis. A 2-marker assay was found to be 97.8% accurate (94% sensitive, 100% specific) compared with histologic analysis. The fully automated GeneXpert instrument produced comparable and reproducible results in less than 35 minutes.


CONCLUSIONS
A rapid, fully automated QRT-PCR assay definitively characterizes breast cancer SLN with accuracy equal to conventional pathology. This approach is superior to intraoperative SLN analysis and can provide standardized, objective results to assist in pathologic diagnosis.
Department of Surgery, Medical University of South Carolina, Charleston, USA.
Steven J
SJ
Hughes
Liqiang
L
Xi
Siva
S
Raja
William
W
Gooding
David J
DJ
Cole
William E
WE
Gillanders
Keidi
K
Mikhitarian
Kenneth
K
McCarty
Susan
S
Silver
Jesus
J
Ching
William
W
McMillan
James D
JD
Luketich
Tony E
TE
Godfrey
D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D001943:Breast Neoplasms / Q000378:metabolism* / Q000473:pathology; D005260:Female; D006801:Humans; D008198:Lymph Nodes / Q000378:metabolism*; D008207:Lymphatic Metastasis; D011379:Prognosis; D011446:Prospective Studies; D012334:RNA, Neoplasm / Q000032:analysis*; D015203:Reproducibility of Results; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012680:Sensitivity and Specificity
D014408:Biomarkers, Tumor; D012334:RNA, Neoplasm