Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Abstract 2395: Direct assessment of sequence heterogeneity in human cancers by Duplex Sequencing

Authors: Jesse J. Salk; Justin R. Pritchard; Lawrence A. Loeb; Michael W. Schmitt; J. Graeme Hodgson; Victor M. Rivera; Jerald P. Radich; +2 Authors

Abstract 2395: Direct assessment of sequence heterogeneity in human cancers by Duplex Sequencing

Abstract

Abstract The extent of heterogeneity in DNA sequence within human cancers has been difficult to fully assess, due to the absence of methods with sufficient sensitivity to detect minority variants. For example, next-generation sequencing could in principle detect sub-clonal mutations at any genomic position; however due to amplification errors and inaccuracies in the sequencing platform itself, such approaches are limited to detection of mutations present in >1% of cells. We have overcome this limitation by developing an approach, Duplex Sequencing, which improves the accuracy of next-generation sequencing by >100,000 fold. Duplex Sequencing is based upon separately tagging and sequencing the two strands of single molecules of duplex DNA. True mutations are present at the same position in both DNA strands and are complementary, whereas artifacts arising from amplification or sequencing errors are seen in only one strand. The calculated error rate of our approach is less than one artifactual mutation per billion nucleotides sequenced (ref. 1). We have also developed an enrichment approach based on sequential rounds of hybridization to biotinylated probes which enables efficient sequencing of targeted regions of the genome (ref. 2). Duplex Sequencing thereby enables exceptionally sensitive detection of sequence heterogeneity within any set of genes. We have now applied Duplex Sequencing to study of sequence heterogeneity in both normal and malignant samples. In acute myeloid leukemia (AML), we find multiple sub-clonal mutations which fall below the detection limit of conventional approaches, some of which encode mutations that can drive chemotherapy resistance and cancer progression. Our results indicate that prior studies have under-estimated the burden of sub-clonal mutations in AML by more than 1,000-fold. We have additionally studied chronic myeloid leukemia (CML); treatment of CML with inhibitors directed against the Abl kinase represents the prototypical targeted cancer therapy. With Duplex Sequencing, we find that Abl mutations are extremely uncommon at the time of CML diagnosis. In contrast, refractory patients who fail therapy frequently possess multiple sub-clonal mutations within the Abl kinase, most of which are below the resolution of conventional approaches but are readily detected with our method. In ongoing work, we have found multiple sub-clonal mutations within human prostate cancer and colon cancer, suggestive of widespread intratumor heterogeneity that may limit the efficacy of single-agent therapy in these diseases. References: 1. Schmitt MW, Kennedy SR, Salk JJ, Fox EJ, Hiatt JB, Loeb LA (2012). Detection of ultra-rare mutations by next-generation sequencing. Proceedings of the National Academy of Sciences USA. 109(36):14508-13. 2. Schmitt MW, Fox EJ, Prindle MJ, Reid-Bayliss KS, True LD, Radich JP, Loeb LA (2015). Sequencing small genomic targets with high efficiency and extreme accuracy. Nature Methods. 12(5):423-5. Citation Format: Michael W. Schmitt, Jesse J. Salk, Edward J. Fox, Justin R. Pritchard, J Graeme Hodgson, Victor M. Rivera, Pamela S. Becker, Jerald P. Radich, Lawrence A. Loeb. Direct assessment of sequence heterogeneity in human cancers by Duplex Sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2395.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average