Low-level tumor somatic DNA mutations can have profound implications for development of metastasis, prognosis, choice of treatment, follow-up or early cancer detection strategies. Unless they are effectively detected, these low-level mutations can misinform patient management decisions or become missed opportunities for personalized medicine. Next generation sequencing (NGS) technologies can effectively reveal prevalent somatic mutations, yet they 'lose steam' when it comes to detecting low-level DNA mutations in tumors with clonal heterogeneity, or in bodily fluids, and their integration with clinical practice is problematic. For mutations at allelic ratio of ~2-5% or less, NGS generates excessive false positives (?noise?) independent of sequencing depth and hinders personalized clinical decisions based on mutational profiling. Recent adaptations of NGS to detect rare mutations using random barcoding strategies may overcome the noise but invariably diminish its high throughput capability and increase costs. We recently developed NaMe-PrO, a simple and powerful technology to eliminate wild-type sequences from large numbers of targets in genomic DNA. NaME-PrO utilizes a nuclease guided by probes to thousands of DNA targets, to render WT sequences non-amplifiable thereby allowing mutation?containing sequences to amplify and be sequenced as if they were clonal mutations. This R33 proposes to develop quantitative NaME- PrO (qNaME-PrO), which combines NaME-PrO with a novel use of molecular barcoding, to provide strict enumeration of original mutation abundance for all mutant sequences following their enrichment. Thereby converting rare mutations to high abundance mutations, boosting confidence in their detection and circumventing the need for repeated and wasteful sequence reads during NGS. The method creates the potential for massively parallel mutation enrichment prior to sequencing and engenders a new paradigm whereby rare mutations do not require deep sequencing for their detection. The R33 (Aims 1&2) will optimize and develop qNaME-PrO panels to cover all known mutation hotspots and full length exons in tumor suppressor genes and oncogenes relevant to lung cancer.
In Aim 3 the method will be field-tested in a compilation of longitudinally collected plasma samples from patients undergoing radio-chemo-therapy. Being able to extract ?the mutated portion of a large genomic target? from a mixed clinical sample prior to downstream analysis will translate to a major boost in the speed, accuracy and cost of sequencing low- prevalence mutations in heterogeneous tumors and bodily fluids and will accelerate clinical application of NGS for cancer diagnosis, prognosis and management. Therefore relevance to Public Health is high.

Public Health Relevance

Screening of individual patients? tumors for genetic alterations over many genes in a rapid and cost-effective manner is a significant challenge that must be fulfilled in order to realize the promise of individualized cancer treatment. Although major advances have been made, there is still a significant gap in technology that prevents clinical integration of the most powerful platforms for molecular profiling and follow-up of individual patients treatment. We propose an answer to this challenge by combining 2 cutting edge technologies, NaME-PrO and Next Generation Sequencing. The novel combination of these technologies bridges the existing technology gap and enables reliable mutation screening in multiple genes simultaneously, in surgical cancer samples or bodily fluids. In view of the fundamental role of mutations in causing cancer and modulating tumor response to drug treatment this project has significant implications for public health.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants Phase II (R33)
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Special Emphasis Panel (ZCA1)
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Mckee, Tawnya C
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Dana-Farber Cancer Institute
United States
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Fitarelli-Kiehl, Mariana; Yu, Fangyan; Ashtaputre, Ravina et al. (2018) Denaturation-Enhanced Droplet Digital PCR for Liquid Biopsies. Clin Chem 64:1762-1771
Ladas, Ioannis; Fitarelli-Kiehl, Mariana; Song, Chen et al. (2017) Multiplexed Elimination of Wild-Type DNA and High-Resolution Melting Prior to Targeted Resequencing of Liquid Biopsies. Clin Chem 63:1605-1613