Abstract P4-01-25: Blood-based DNA methylation as epigenetic biomarkers for non-invasive detection of breast cancer

Abstract

Abstract Background: DNA methylation significantly contributes to all hallmarks of cancer. In particular, promoter hypermethylation has been identified as a potential marker for early detection of cancer, therapy monitoring, assessment of prognosis or prediction of therapy response. Here, we identified and validated breast cancer-specific methylation markers for diagnosis of the disease with high sensitivity and specificity. Methods: 151 bio-banked samples were obtained for a randomized blind study; 65 subjects diagnosed with breast cancer (Stage I to IV), 15 subjects with benign breast disease, 32 subjects diagnosed with other cancer types (11 colorectal, 9 liver and 12 lung cancer), and 39 healthy donor samples. Cell-free DNA was then extracted from the samples, bisulfite converted, and DNA methylation was quantified by using the IvyGene Platform. Finally, the raw data were collected and analyzed to evaluate the test performance. Results: A total of 53 of the 65 breast cancer samples were correctly identified for an overall calculated sensitivity of 89% with little difference between the sensitivity of detecting Stage I to Stage IV breast cancer (range 88% to 94%). The breast cancer subjects were correctly identified with 96% specificity. Additionally, 28 of 32 samples drawn from healthy donor subjects (specificity 95%) and all 15 samples drawn from subjects diagnosed with benign breast disease (specificity 100%) were also correctly identified. Of the samples drawn from subjects with cancer other than breast cancer, over 96% of lung cancer, colorectal cancer and liver cancer samples were correctly identified as not breast cancer. Conclusion: The results demonstrate the high diagnostic potential of ctDNA methylation markers in the blood for the detection of breast cancer. In addition, a quantitative analysis of ctDNA provides an opportunity for non-invasive detection of cancer and it's benefits can be anticipated to improve patient management and healthcare quality.