An ultrasensitive test for profiling circulating tumor DNA using integrated comprehensive droplet digital detection

使用集成式综合液滴数字检测技术对循环肿瘤 DNA 进行分析的超灵敏测试

阅读:7
作者:Chen-Yin Ou, Tam Vu, Jonathan T Grunwald, Michael Toledano, Jan Zimak, Melody Toosky, Byron Shen, Jason A Zell, Enrico Gratton, Timothy J Abram, Weian Zhao

Abstract

Current cancer detection systems lack the required sensitivity to reliably detect minimal residual disease (MRD) and recurrence at the earliest stages when treatment would be most effective. To address this issue, we present a novel liquid biopsy approach that utilizes an integrated comprehensive droplet digital detection (IC3D) digital PCR system which combines microfluidic droplet partitioning, fluorescent multiplex PCR chemistry, and our rapid 3D, large-volume droplet counting technology. The IC3D ddPCR assay can detect cancer-specific, ultra-rare genomic targets due to large sample input and high degree of partitioning. We first demonstrate our droplet digital PCR assay can robustly detect common cancer mutants including KRAS G12D spiked in wild-type genomic background or isolated from patient samples with 100% specificity. We then demonstrate that the IC3D ddPCR system can detect oncogenic KRAS G12D mutant alleles against a background of wild-type genomes at a sensitivity of 0.00125-0.005% with a false positive rate of 0% which is 50 to 1000× more sensitive than existing commercial liquid biopsy ddPCR and qPCR platforms, respectively. In addition, our technology can uniquely enable detection of circulating tumor cells using their genetic markers without a pre-enrichment step, and analysis of total tumor DNA isolated from blood samples, which will increase clinical sensitivity and specificity, and minimize inter-assay variability. Therefore, our technology holds the potential to provide clinicians with a powerful decision-making tool to monitor and treat MRD with unprecedented sensitivity for earlier stage intervention.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。