Abstract B127: An innovative, ultra-accurate method for cancer mutation detection in cell-free DNA from plasma

Abstract

Abstract The application of cell-free DNA (cfDNA) as a biomarker holds great potential in advancing personalized cancer treatments. However, two major limitations need to be addressed for the development of a practical cfDNA-based cancer diagnostic assay: 1) the low concentration of cfDNA in blood, which presents challenges for detecting mutations at low allele frequency, and 2) the relatively high background noise caused by next generation sequencing (NGS) error, which can mask bona fide cancer mutation signals. Here we introduce an innovative, ultra-accurate, and scalable NGS-based cancer mutation detection system that overcomes these limitations. Our system amplifies nanogram quantities of highly fragmented cfDNA from the whole genome to >1000-fold, and no significant biases were observed. By combining molecular biology techniques with bioinformatics, we reduced the random background error from sequencing to achieve high accuracy (calculated error rate of 10-6), with a detection of 1:10,000 in a cell line gDNA model system, and 1:1000 in cfDNA. We implemented a 127-gene panel with 1 Mb target region, and 2000x-3000x deep sequencing to detect mutations from stage II hepatocellular carcinoma (HCC) cfDNA samples, and 75% of the HCC signature mutations (including those mutations with <1% allele frequencies) were confirmed by tumor gDNA exome sequencing. Furthermore, we developed an algorithm for basic cancer type classification, which in a preliminary study, this algorithm classified our breast and pancreatic cancer cfDNA samples with a sensitivity of 85%, and a specificity of 100%. In summary, this unbiased cfDNA amplification and highly accurate mutation detection system serves as a first step toward developing a reliable, non-invasive cancer genome analysis, which will dramatically enhance options for personalizing cancer treatments and ultimately screening high risk populations. Citation Format: Grace Zhao, Paul Tang, Johnny Sun, Shengrong Lin. An innovative, ultra-accurate method for cancer mutation detection in cell-free DNA from plasma. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr B127.