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Imaging, Diagnosis, Prognosis |
Authors' Affiliations: Departments of 1 Oncology and 2 Surgery, Johns Hopkins University School of Medicine, Baltimore Maryland and Departments of 3 Surgery and 4 Pathology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Requests for reprints: Saraswati Sukumar, Breast Cancer Program, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Room 410, Bunting/Blaustein Building, 1650 Orleans Street, Baltimore, MD 21231-1000. Phone: 410-614-2479; Fax: 410-614-4073; E-mail: saras{at}jhmi.edu.
Purpose: The challenges of cytology for accurate diagnosis of breast cancer are well recognized. We previously showed that normal and tumor tissue can be distinguished using a technique called quantitative multiplex methylation-specific PCR (QM-MSP). We hypothesized that quantitative analysis of methylated genes will provide enhanced detection of cancer cells present in cytologic specimens.
Experimental Design: QM-MSP was done on ductal lavage cells from a set of 37 ductal lavage samples from women undergoing mastectomy (27 with cancer and 3 without). Duct histology information was available for each lavaged duct. QM-MSP data was assessed by measuring cumulative methylation index and by receiver operating characteristic threshold analysis. To determine the baseline level of methylation for each gene in this population, cells from 60 ducts of women at high risk of developing breast cancer were analyzed.
Results: QM-MSP findings on a panel of nine genes were correlated to duct histology and ductal lavage cytology. Cytology detected cancer in 33% (7 of 21 ducts) with a specificity of 99% (92 of 93). QM-MSP detected cancer as calculated by cumulative methylation index with a sensitivity of 62% (13 of 21) and specificity of 82% (62 of 76) and by receiver operating characteristic threshold analysis with a sensitivity of 71% (15 of 21) and specificity of 83% (63 of 76).
Conclusions: Compared with cytology, QM-MSP doubled the sensitivity of detection of cancer. This study provides proof of principle by showing the advantages of using methylation analyses to query cytologic specimens and indicates its potential use in diagnosis and in stratifying risk.
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