Abstract LB-220: An automated breast cancer detection assay for screening in the developing world
Authors: Bradley M. Downs, Mary Jo Fackler, Claudia Mercado-Rodriguez, Ashley Cimino-Mathews, Chuang Chen, Jing-Ping Yuan, Eunice van den Berg, Leslie M. Cope, Susan C. Harvey, Syed Z. Ali, Suzana Tulac, Kriszten J. Kocmond, Edwin W. Lai, Brian Rhees, Mike Bates, Saraswati Sukumar
Journal: Cancer Research (2018)

Abstract Introduction: Breast cancer incidence is rapidly increasing globally with 1.7 million new cases and 600,000 deaths due to the disease annually. Death due to breast cancer is four to six times more frequent in the developing world compared to the USA due to lack of early detection, definitive diagnosis, and limited access to treatment. Ultrasound imaging for early detection and ultrasound guided fine needle aspiration (FNA) of suspicious lesions followed by an automated, cartridge-based analysis of methylated genes could triage malignancies for faster pathology assessment and treatment, thus enabling better use of scarce resources. Experimental Procedures: To identify a panel of methylated DNA markers to enable sensitive and specific detection of malignant breast lesions, we screened 24 methylated genes (known to be frequently methylated in malignant breast tissue and unmethylated in normal breast tissue) by Quantitative Multiplex Methylation-Specific PCR (QM-MSP) analysis. Formalin-fixed paraffin-embedded (FFPE) sections of biopsies of both benign and malignant breast lesions from the USA, China and South Africa were analyzed. Samples were divided into Training and Test sets. The Training set consisted of 206 tissues [66 invasive ductal carcinoma (IDC), 30 ductal carcinoma in situ (DCIS), 99 benign breast disease (BBD) and 11 normal breast (NB)]. The gene panel selected in the Training set was examined in an independent Test set of tissues (n=204) [65 IDC, 29 DCIS, 99 BBD and 11 NB]. Further, we optimized the technical performance of an automated, prototype breast cancer detection cartridge system for quantitative assessment of gene methylation and tested it in pilot study using FNA samples from breast cancers. Results: Analysis of the tissues in the Training set (n=206) led to the selection of a panel of 10 genes highly methylated in malignant lesions with little or no methylation in benign lesions. For the 10-gene panel to achieve a sensitivity greater than 90%, a laboratory cutoff of 14.5 cumulative methylation (CM) units (out of a possible 10,000 units) was set. In the Training set, the 10-gene panel achieved a sensitivity of 90% and a specificity of 85% with receiver operating characteristic (ROC) statistics: ROC, AUC= 0.947. In a blinded Test set of tissue samples (n=204), with a laboratory cutoff of 14.5 CM units, the 10-gene panel achieved a sensitivity of 87% and a specificity of 89%, with ROC statistics: p&amp;lt;0.001, AUC= 0.936, and provided significant accuracy for breast cancers from three countries and all molecular subtypes. In a pilot study of FNA samples using the cartridge system, robust methylation in all ten genes was detected in malignant tumors. Conclusions: QM-MSP of breast lesions led to the selection of a panel of 10 genes methylated for detection of breast cancer. We have validated the technical performance of an automated, prototype cartridge system. The study reveals the potential of methylation markers to provide fast, accurate and automated cancer detection at a low cost in developing regions globally. Research Use Only. Not for diagnostic tests. A sponsored research agreement from Cepheid to Dr. Sukumar's Lab at Johns Hopkins University. Citation Format: Bradley M. Downs, Mary Jo Fackler, Claudia Mercado-Rodriguez, Ashley Cimino-Mathews, Chuang Chen, Jing-Ping Yuan, Eunice van den Berg, Leslie M. Cope, Susan C. Harvey, Syed Z. Ali, Suzana Tulac, Kriszten J. Kocmond, Edwin W. Lai, Brian Rhees, Mike Bates, Saraswati Sukumar. An automated breast cancer detection assay for screening in the developing world [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-220.