An Ngs Workflow To Detect Down To 0.1% Allelic Frequency In Cfdna For Breast And Colon Cancers

Noninvasive detection of rare mutations in blood could allow tumor monitoring for research purposes. Research studies have suggested that cfDNA contains DNA from tumor cells with somatic mutations that could inform on tumor progression and therapeutic resistance. Here, we demonstrate a complete workflow from a single tube of blood through data analysis for research samples down to a 0.1% allelic frequency. The low abundance tumor mutations found in cfDNA requires sensitive and accurate mutation detection. We have developed two panels that utilize an amplification-based assay that generates tagged DNA copies, which allows detection of low abundance tumor mutations found in cfDNA. The two panels allow multiplex interrogation of primary driver and resistance mutations specific to ctDNA from breast and colon cancer. The Oncomine Colon cfDNA panel targets 236 hotspots within 14 genes while the Oncomine Breast cfDNA panel covers 157 hotspot mutations in 10 genes. This workflow was validated from matched single blood tubes, Streck and K2EDTA. Additionally, the utility for cancer research was demonstrated with concordance studies using matched FFPE and plasma from oncology samples. To further characterize these panels we have developed an oncology control for cfDNA with nucleosome fragment sizing and minimal sonication damage. This engineered control contains SNPs and indels at 0.1% allelic frequencies, orthogonally confirmed with TaqMan based Rare Mutation assays. With this control, the Oncomine Breast cfDNA panel had over 81% sensitivity and 99.9% specificity. The Oncomine Colon cfDNA panel had over 85% sensitivity and 100% specificity. The Oncomine Breast cfDNA panel and Oncomine Colon cfDNA panel integrated into a complete workflow starting from a single tube of blood can advance oncology research with the ability to detect blood based cancer biomarkers present at 0.1%. Citation Format: Dalia Dhingra, Richard Chien, Jian Gu, Dumitru Brinza, Ruchi Chaudhary, Kunal Banjara, Yanchun Li, Efren Ballesteros-Villagrana, Kelli Bramlett. An NGS workflow to detect down to 0.1% allelic frequency in cfDNA for breast and colon cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5396. doi:10.1158/1538-7445.AM2017-5396