Details

Autor(en) / Beteiligte

• Chan, K. C. Allen
• Jiang, Peiyong
• Chan, Carol W. M.
• Sun, Kun
• Wong, John
• Hui, Edwin P.
• Chan, Stephen L.
• Chan, Wing Cheong
• Hui, David S. C.
• Ng, Simon S. M.
• Chan, Henry L. Y.
• Wong, Cesar S. C.
• Ma, Brigette B. Y.
• Chan, Anthony T. C.
• Lai, Paul B. S.
• Sun, Hao
• Chiu, Rossa W. K.
• Lo, Y. M. Dennis

Titel

Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

Ist Teil von

• Proceedings of the National Academy of Sciences - PNAS, 2013-11, Vol.110 (47), p.18761-18768

Ort / Verlag

United States: National Academy of Sciences

Erscheinungsjahr

2013

Quelle

MEDLINE

Beschreibungen/Notizen

• We explored the detection of genome-wide hypomethylation in plasma using shotgun massively parallel bisulfite sequencing as a marker for cancer. Tumor-associated copy number aberrations (CNAs) could also be observed from the bisulfite DNA sequencing data. Hypomethylation and CNAs were detected in the plasma DNA of patients with hepatocellular carcinoma, breast cancer, lung cancer, nasopharyngeal cancer, smooth muscle sarcoma, and neuroendocrine tumor. For the detection of nonmetastatic cancer cases, plasma hypomethylation gave a sensitivity and specificity of 74% and 94%, respectively, when a mean of 93 million reads per case were obtained. Reducing the sequencing depth to 10 million reads per case was found to have no adverse effect on the sensitivity and specificity for cancer detection, giving respective figures of 68% and 94%. This characteristic thus indicates that analysis of plasma hypomethylation by this sequencing-based method may be a relatively cost-effective approach for cancer detection. We also demonstrated that plasma hypomethylation had utility for monitoring hepatocellular carcinoma patients following tumor resection and for detecting residual disease. Plasma hypomethylation can be combined with plasma CNA analysis for further enhancement of the detection sensitivity or specificity using different diagnostic algorithms. Using the detection of at least one type of aberration to define an abnormality, a sensitivity of 87% could be achieved with a specificity of 88%. These developments have thus expanded the applications of plasma DNA analysis for cancer detection and monitoring.