Skip to main content

NGS-Based Tumor-Informed Analysis of Circulating Tumor DNA

  • Protocol
  • First Online:
Urothelial Carcinoma

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2684))

Abstract

Accurate circulating tumor DNA (ctDNA) detection has an immense biomarker potential in all phases of the cancer disease course. Presence of ctDNA in the blood has been shown to have prognostic value in various cancer types as it may reflect the actual tumor burden. There are two main methods to consider, a tumor-informed and a tumor-agnostic analysis of ctDNA. Both techniques exploit the short half-life of circulating cell-free DNA (cfDNA)/ctDNA for disease monitoring and ultimately future clinical treatment intervention. Urothelial carcinoma is characterized by a high mutation spectrum but very few hotspot mutations. This limits tumor agnostic usability of hotspot mutation or fixed sets of genes for ctDNA detection. Here we focus on a tumor-informed analysis for ultrasensitive patient- and tumor-specific ctDNA detection using personalized mutation panels, probes that bind to specific genomic sequences to enrich for the region of interest. In this chapter, we describe methods for purification of high-quality cfDNA and guidelines for designing tumor-informed customized capture panels for sensitive detection of ctDNA. Furthermore, a detailed protocol for library preparation and panel capture utilizing a double enrichment strategy with low amplification is described.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Thierry AR, El Messaoudi S, Gahan PB et al (2016) Origins, structures, and functions of circulating DNA in oncology. Cancer Metastasis Rev 35:347–376

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kustanovich A, Schwartz R, Peretz T, Grinshpun A (2019) Life and death of circulating cell-free DNA. Cancer Biol Ther 20:1057–1067

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Alcaide M, Cheung M, Hillman J et al (2020) Evaluating the quantity, quality and size distribution of cell-free DNA by multiplex droplet digital PCR. Sci Rep 10:12564

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cristiano S, Leal A, Phallen J et al (2019) Genome-wide cell-free DNA fragmentation in patients with cancer. Nature 570:385–389

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Christensen E, Birkenkamp-Demtröder K, Sethi H et al (2019) Early detection of metastatic relapse and monitoring of therapeutic efficacy by ultra-deep sequencing of plasma cell-free DNA in patients with urothelial bladder carcinoma. J Clin Oncol 37:1547–1557

    Article  CAS  PubMed  Google Scholar 

  6. Sanz-Garcia E, Zhao E, Bratman SV, Siu LL (2022) Monitoring and adapting cancer treatment using circulating tumor DNA kinetics: current research, opportunities, and challenges. Sci Adv 8:eabi8618

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Steensma DP, Bejar R, Jaiswal S et al (2015) Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood 126:9–16

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Newman AM, Lovejoy AF, Klass DM et al (2016) Integrated digital error suppression for improved detection of circulating tumor DNA. Nat Biotechnol 34:547–555

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Schmitt MW, Kennedy SR, Salk JJ et al (2012) Detection of ultra-rare mutations by next-generation sequencing. Proc Natl Acad Sci U S A 109:14508–14513

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Bae JH, Liu R, Nguyen E et al (2021) CODEC enables “single duplex” sequencing. bioRxiv. 2021.06.11.448110

    Google Scholar 

  11. Shendure J, Balasubramanian S, Church GM et al (2017) DNA sequencing at 40: past, present and future. Nature 550:345–353

    Article  CAS  PubMed  Google Scholar 

  12. Gerstung M, Papaemmanuil E, Campbell PJ (2014) Subclonal variant calling with multiple samples and prior knowledge. Bioinformatics 30:1198–1204

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Birkenkamp-Demtröder K, Christensen E, Nordentoft I et al (2018) Monitoring treatment response and metastatic relapse in advanced bladder cancer by liquid biopsy analysis. Eur Urol 73:535–540

    Article  PubMed  Google Scholar 

  14. Pallisgaard N, Spindler K-LG, Andersen RF et al (2015) Controls to validate plasma samples for cell free DNA quantification. Clin Chim Acta 446:141–146

    Article  CAS  PubMed  Google Scholar 

  15. Salk JJ, Schmitt MW, Loeb LA (2018) Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations. Nat Rev Genet 19:269–285

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Gorini F, Scala G, Di Palo G et al (2020) The genomic landscape of 8-oxodG reveals enrichment at specific inherently fragile promoters. Nucleic Acids Res 48:4309–4324

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Brodin J, Mild M, Hedskog C et al (2013) PCR-induced transitions are the major source of error in cleaned ultra-deep pyrosequencing data. PLoS One 8:e70388

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ma X, Shao Y, Tian L et al (2019) Analysis of error profiles in deep next-generation sequencing data. Genome Biol 20:50

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chen L, Liu P, Evans TC Jr, Ettwiller LM (2017) DNA damage is a pervasive cause of sequencing errors, directly confounding variant identification. Science 355:752–756

    Article  CAS  PubMed  Google Scholar 

  20. Tate JG, Bamford S, Jubb HC et al (2019) COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res 47:D941–D947

    Article  CAS  PubMed  Google Scholar 

  21. Chan K, Roberts SA, Klimczak LJ et al (2015) An APOBEC3A hypermutation signature is distinguishable from the signature of background mutagenesis by APOBEC3B in human cancers. Nat Genet 47:1067–1072

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

We thank Mads Heilskov Rasmussen and Amanda Frydendahl Boll Johansen for collaboration on double capture protocol development. We thank Lotte Gernyx for technical assistance during of NGS library preparation and capture protocols development.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iver Nordentoft .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Nordentoft, I., Birkenkamp-Demtröder, K., Dyrskjøt, L. (2023). NGS-Based Tumor-Informed Analysis of Circulating Tumor DNA. In: Hoffmann, M.J., Gaisa, N.T., Nawroth, R., Ecke, T.H. (eds) Urothelial Carcinoma. Methods in Molecular Biology, vol 2684. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3291-8_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-3291-8_11

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3290-1

  • Online ISBN: 978-1-0716-3291-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics