High throughput detection of clinically relevant mutations in archived tumor samples by multiplexed PCR and next-generation sequencing
Bourgon R., Lu, S., Yan, Y. et al.
Tailoring cancer treatment to tumor molecular characteristics promises to make personalized medicine a reality. However, reliable genetic profiling of archived clinical specimens has been hindered by limited sensitivity and high false-positive rates. Here, we describe a novel methodology, MMP-seq, which enables sensitive and specific high-throughput, high-content genetic profiling in archived clinical samples.
We first validated the technical performance of MMP-seq in 66 cancer cell lines and a Latin square cross-dilution of known somatic mutations. We next characterized the performance of MMP-seq in 17 formalin-fixed paraffin-embedded (FFPE) clinical samples using matched fresh-frozen tissue from the same tumors as benchmarks. To demonstrate the potential clinical utility of our methodology, we profiled FFPE tumor samples from 73 patients with endometrial cancer.
We demonstrated that MMP-seq enabled rapid and simultaneous profiling of a panel of 88 cancer genes in 48 samples, and detected variants at frequencies as low as 0.4%. We identified DNA degradation and deamination as the main error sources and developed practical and robust strategies for mitigating these issues, and dramatically reduced the false-positive rate. Applying MMP-seq to a cohort of endometrial tumor samples identified extensive, potentially actionable alterations in the PI3K (phosphoinositide 3-kinase) and RAS pathways, including novel PIK3R1 hotspot mutations that may disrupt negative regulation of PIK3CA.
MMP-seq provides a robust solution for comprehensive, reliable, and high-throughput genetic profiling of clinical tumor samples, paving the way for the incorporation of genomic-based testing into clinical investigation and practice.
Bourgon R., Lu, S., Yan, Y. et al. "High throughput detection of clinically relevant mutations in archived tumor samples by multiplexed PCR and next-generation sequencing" Clinical Cancer Research (2014): 2,080–91