Next generation DNA sequencing (NGS) has the power to revolutionize biology and medicine. Determining the sequence of the 3 billion nucleotides in the human genome is no longer a daunting task. However, a major impediment to the full implementation of this technology in the area of cancer detection and research is its high error rate. We have established a method that takes advantage of the complementarity inherent in double-stranded DNA. As a result of sequencing both strands of DNA we can identify true mutations as those present at the same position in both strands. Using this technology we can disregard substitutions due to PCR- amplification since they would only be present in one of the two strands. In addition, we can eliminate most sequencing errors resulting from damage to DNA templates. As a result we have establish a method that is 1000-fold more accurate than standard methods used in next generation DNA sequencing The goal of this application is to validate and further develop the method of Duplex Sequencing. Experiments will be carried out to optimize the recovery of duplex sequences and to probe the exceptional sensitivity of the methodology. To evaluate the utility of duplex DNA sequencing we will analyze hard to sequence segments of the human genome that have been resistant to sequence with accuracy using other approaches. We will also address the question of whether mutations rendering cells resistant to chemotherapeutic agents are preexistent in human cancers prior to the initiation of chemotherapy.

Public Health Relevance

Cancer is a genomic disease, associated with the accumulation of mutations. Recently, DNA sequencing has allowed a scientist to identify mutations that are present in most cells within a tumor. In addition, each tumor cell contains large numbers of random mutations. We have developed an assay to measure random mutations. These random mutations could contribute to how fast tumors grow, metastasize, and for the ability of human tumors to rapidly become resistant to chemotherapy. Thus, an analysis of the frequency of random mutations in tumor cells could be important in formulating treatment and protocols.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
1R33CA181771-01A1
Application #
8735349
Study Section
Special Emphasis Panel (ZCA1-SRLB-Q (M2))
Program Officer
Divi, Rao L
Project Start
2014-09-11
Project End
2017-08-31
Budget Start
2014-09-11
Budget End
2015-08-31
Support Year
1
Fiscal Year
2014
Total Cost
$384,923
Indirect Cost
$135,782
Name
University of Washington
Department
Pathology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Schmitt, Michael W; Pritchard, Justin R; Leighow, Scott M et al. (2018) Single-Molecule Sequencing Reveals Patterns of Preexisting Drug Resistance That Suggest Treatment Strategies in Philadelphia-Positive Leukemias. Clin Cancer Res 24:5321-5334
Salk, Jesse J; Schmitt, Michael W; Loeb, Lawrence A (2018) Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations. Nat Rev Genet 19:269-285
Chawanthayatham, Supawadee; Valentine 3rd, Charles C; Fedeles, Bogdan I et al. (2017) Mutational spectra of aflatoxin B1 in vivo establish biomarkers of exposure for human hepatocellular carcinoma. Proc Natl Acad Sci U S A 114:E3101-E3109
Fox, Edward J; Salk, Jesse J; Loeb, Lawrence A (2016) Exploring the implications of distinct mutational signatures and mutation rates in aging and cancer. Genome Med 8:30
Reid-Bayliss, Kate S; Arron, Sarah T; Loeb, Lawrence A et al. (2016) Why Cockayne syndrome patients do not get cancer despite their DNA repair deficiency. Proc Natl Acad Sci U S A 113:10151-6
Ahn, Eun Hyun; Lee, Seung Hyuk; Kim, Joon Yup et al. (2016) Decreased Mitochondrial Mutagenesis during Transformation of Human Breast Stem Cells into Tumorigenic Cells. Cancer Res 76:4569-78
Loeb, Lawrence A (2016) Human Cancers Express a Mutator Phenotype: Hypothesis, Origin, and Consequences. Cancer Res 76:2057-9
Krimmel, Jeffrey D; Schmitt, Michael W; Harrell, Maria I et al. (2016) Ultra-deep sequencing detects ovarian cancer cells in peritoneal fluid and reveals somatic TP53 mutations in noncancerous tissues. Proc Natl Acad Sci U S A 113:6005-10
Schmitt, Michael W; Loeb, Lawrence A; Salk, Jesse J (2016) The influence of subclonal resistance mutations on targeted cancer therapy. Nat Rev Clin Oncol 13:335-47
Ahn, Eun Hyun; Hirohata, Kensen; Kohrn, Brendan F et al. (2015) Detection of Ultra-Rare Mitochondrial Mutations in Breast Stem Cells by Duplex Sequencing. PLoS One 10:e0136216

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