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Fragmentomic analysis of circulating tumor DNA-targeted cancer panels.

Publication ,  Journal Article
Helzer, KT; Sharifi, MN; Sperger, JM; Shi, Y; Annala, M; Bootsma, ML; Reese, SR; Taylor, A; Kaufmann, KR; Krause, HK; Schehr, JL; Sethakorn, N ...
Published in: Ann Oncol
September 2023

BACKGROUND: The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner. PATIENTS AND METHODS: We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n = 320). Each cohort was split 70%/30% into training and validation sets. RESULTS: In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99. CONCLUSIONS: To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.

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Published In

Ann Oncol

DOI

EISSN

1569-8041

Publication Date

September 2023

Volume

34

Issue

9

Start / End Page

813 / 825

Location

England

Related Subject Headings

  • Prostatic Neoplasms
  • Oncology & Carcinogenesis
  • Mutation
  • Male
  • Humans
  • Gene Expression Profiling
  • Circulating Tumor DNA
  • Cell-Free Nucleic Acids
  • Biomarkers, Tumor
  • 3211 Oncology and carcinogenesis
 

Citation

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Helzer, K. T., Sharifi, M. N., Sperger, J. M., Shi, Y., Annala, M., Bootsma, M. L., … Zhao, S. G. (2023). Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Ann Oncol, 34(9), 813–825. https://doi.org/10.1016/j.annonc.2023.06.001
Helzer, K. T., M. N. Sharifi, J. M. Sperger, Y. Shi, M. Annala, M. L. Bootsma, S. R. Reese, et al. “Fragmentomic analysis of circulating tumor DNA-targeted cancer panels.Ann Oncol 34, no. 9 (September 2023): 813–25. https://doi.org/10.1016/j.annonc.2023.06.001.
Helzer KT, Sharifi MN, Sperger JM, Shi Y, Annala M, Bootsma ML, et al. Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Ann Oncol. 2023 Sep;34(9):813–25.
Helzer, K. T., et al. “Fragmentomic analysis of circulating tumor DNA-targeted cancer panels.Ann Oncol, vol. 34, no. 9, Sept. 2023, pp. 813–25. Pubmed, doi:10.1016/j.annonc.2023.06.001.
Helzer KT, Sharifi MN, Sperger JM, Shi Y, Annala M, Bootsma ML, Reese SR, Taylor A, Kaufmann KR, Krause HK, Schehr JL, Sethakorn N, Kosoff D, Kyriakopoulos C, Burkard ME, Rydzewski NR, Yu M, Harari PM, Bassetti M, Blitzer G, Floberg J, Sjöström M, Quigley DA, Dehm SM, Armstrong AJ, Beltran H, McKay RR, Feng FY, O’Regan R, Wisinski KB, Emamekhoo H, Wyatt AW, Lang JM, Zhao SG. Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Ann Oncol. 2023 Sep;34(9):813–825.
Journal cover image

Published In

Ann Oncol

DOI

EISSN

1569-8041

Publication Date

September 2023

Volume

34

Issue

9

Start / End Page

813 / 825

Location

England

Related Subject Headings

  • Prostatic Neoplasms
  • Oncology & Carcinogenesis
  • Mutation
  • Male
  • Humans
  • Gene Expression Profiling
  • Circulating Tumor DNA
  • Cell-Free Nucleic Acids
  • Biomarkers, Tumor
  • 3211 Oncology and carcinogenesis