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Validation Strategy for Ultrasensitive Mutation Detection

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Abstract

Background

Ultrasensitive detection of low-abundance DNA point mutations is a challenging molecular biology problem, because nearly identical mutant and wild-type molecules exhibit crosstalk. Reliable ultrasensitive point mutation detection will facilitate early detection of cancer and therapeutic monitoring of cancer patients.

Objective

The objective of this study was to develop a method to correct errors in low-level cell line mixes.

Materials and Methods

We tested sample mixes with digital-droplet PCR (ddPCR) and next-generation sequencing.

Results

We introduced two corrections: baseline variant allele frequency (VAF) in the parental cell line was used to correct for copy number variation; and haplotype counting was used to correct errors in cell counting and pipetting. We found ddPCR to have better correlation for detecting low-level mutations without applying any correction (R2 = 0.80) and be more linear after introducing both corrections (R2 = 0.99).

Conclusions

The VAF correction was found to be more significant than haplotype correction. It is imperative that various technologies be evaluated against each other and laboratories be provided with defined quality control samples for proficiency testing.

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Acknowledgements

We thank Dr. Zhen Zhang for his insight and expert statistical analysis. We acknowledge Drs. Lori Sokoll, Jun Yu, Maria Bettinotti, Annette Jackson, Bo Song (Bio-Rad), and Kenneth Pienta, in addition to Brian Iglehart and Don Vindivich, for helpful discussions.

Author information

Authors and Affiliations

  1. Department of Pathology, Johns Hopkins University, Johns Hopkins Medical Institutions, Baltimore, MD, USA

    Marija Debeljak, Michael Noë, Stacy L. Riel, Lisa M. Haley, Alexis L. Norris, Derek A. Anderson, Emily M. Adams, Masaya Suenaga, Katie F. Beierl, Ming-Tseh Lin, Michael G. Goggins, Christopher D. Gocke & James R. Eshleman

  2. Department of Oncology, Johns Hopkins University, Johns Hopkins Medical Institutions, Baltimore, MD, USA

    Michael Noë, Michael G. Goggins, Christopher D. Gocke & James R. Eshleman

  3. Department of Medicine, Johns Hopkins University, Johns Hopkins Medical Institutions, Baltimore, MD, USA

    Michael G. Goggins

  4. The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, CRB II, Room 344, 1550 Orleans Street, Baltimore, MD, 21231, USA

    Michael G. Goggins & James R. Eshleman

Authors
  1. Marija Debeljak
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  9. Katie F. Beierl
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  10. Ming-Tseh Lin
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Corresponding author

Correspondence to James R. Eshleman.

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Conflict of interest

Marija Debeljak, Stacy L. Riel, Lisa M. Haley, Alexis L. Norris, Derek A. Anderson, Emily M. Adams, Masaya Suenaga, Katie F. Beierl, Ming-Tseh Lin, Michael G. Goggins, Christopher D. Gocke, James R. Eshleman, and Michael Noë have no conflicts of interest that are directly relevant to the content of this work.

Funding

This work was funded in part by The Sol Goldman Pancreatic Cancer Research Center, the Stringer Foundation, the Michael Rolfe Pancreatic Cancer Foundation, Mary Lou Wootton Pancreatic Cancer Research Fund, and the Institute for Clinical and Translational Research (ICTR) Accelerated Translational Incubator Pilot (ATIP) Program.

Ethical Approval and Informed Consent

No patients were enrolled and nor was protected health information used in this study.

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Debeljak, M., Noë, M., Riel, S.L. et al. Validation Strategy for Ultrasensitive Mutation Detection. Mol Diagn Ther 22, 603–611 (2018). https://doi.org/10.1007/s40291-018-0350-z

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  • DOI: https://doi.org/10.1007/s40291-018-0350-z

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