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Cited by 1,495Cancer Genomics and DiagnosticsEpigenetics and DNA MethylationAdvanced biosensing and bioanalysis techniques

Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA

Open access
Liu, M.C., Oxnard, G.R., Klein, E.A., Swanton, C., Seiden, M.V., Liu, Minetta C., Oxnard, Geoffrey R., Klein, Eric A. +149 more·2020·Annals of Oncology
DOI 10.1016/j.annonc.2020.02.011PMC PMC8274402
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Abstract

BACKGROUND: Early cancer detection could identify tumors at a time when outcomes are superior and treatment is less morbid. This prospective case-control sub-study (from NCT02889978 and NCT03085888) assessed the performance of targeted methylation analysis of circulating cell-free DNA (cfDNA) to detect and localize multiple cancer types across all stages at high specificity. PARTICIPANTS AND METHODS: The 6689 participants [2482 cancer (>50 cancer types), 4207 non-cancer] were divided into training and validation sets. Plasma cfDNA underwent bisulfite sequencing targeting a panel of >100 000 informative methylation regions. A classifier was developed and validated for cancer detection and tissue of origin (TOO) localization. RESULTS: Performance was consistent in training and validation sets. In validation, specificity was 99.3% [95% confidence interval (CI): 98.3% to 99.8%; 0.7% false-positive rate (FPR)]. Stage I-III sensitivity was 67.3% (CI: 60.7% to 73.3%) in a pre-specified set of 12 cancer types (anus, bladder, colon/rectum, esophagus, head and neck, liver/bile-duct, lung, lymphoma, ovary, pancreas, plasma cell neoplasm, stomach), which account for ∼63% of US cancer deaths annually, and was 43.9% (CI: 39.4% to 48.5%) in all cancer types. Detection increased with increasing stage: in the pre-specified cancer types sensitivity was 39% (CI: 27% to 52%) in stage I, 69% (CI: 56% to 80%) in stage II, 83% (CI: 75% to 90%) in stage III, and 92% (CI: 86% to 96%) in stage IV. In all cancer types sensitivity was 18% (CI: 13% to 25%) in stage I, 43% (CI: 35% to 51%) in stage II, 81% (CI: 73% to 87%) in stage III, and 93% (CI: 87% to 96%) in stage IV. TOO was predicted in 96% of samples with cancer-like signal; of those, the TOO localization was accurate in 93%. CONCLUSIONS: cfDNA sequencing leveraging informative methylation patterns detected more than 50 cancer types across stages. Considering the potential value of early detection in deadly malignancies, further evaluation of this test is justified in prospective population-level studies.

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  • Perception-based approaches have been used to classify various disease conditions on the basis of patterns in DNA methylation, volatile organic compounds, small metabolites, and imaging data.

    “Perception-based approaches have been used to classify various disease conditions on the basis of different patterns in methylation of DNA sequencing13, volatile organic compounds using electronic noses14, small metabolites using mass spectrometry15, and image analysis of pathology, computerized tomography scans and magnetic resonance imaging data16,17.”

    From Detection of ovarian cancer via the spectral fingerprinting of quantum-defect-modified carbon nanotubes in serum by machine learning (2022) · cites this paper as [13]

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  1. [25]Cohen JD, Li L, Wang Y, Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science. 2018; 359(6378): 926– 930. 29348365 PMC6080308

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Liu, M. C., Oxnard, G. R., Klein, E. A., Swanton, C., Seiden, M. V., Liu, M. C., Oxnard, G. R., Klein, E. A., Smith, D., Richards, D., Yeatman, T. J., Cohn, A. L., Lapham, R., Clement, J., Parker, A. S., Tummala, M. K., McIntyre, K., Sekeres, M. A., Bryce, A. H., Siegel, R., Wang, X., Cosgrove, D. P., Abu-Rustum, N. R., Trent, J., Thiel, D. D., Becerra, C., Agrawal, M., Garbo, L. E., Giguere, J. K., Michels, R. M., Harris, R. P., Richey, S. L., McCarthy, T. A., Waterhouse, D. M., Couch, F. J., Wilks, S. T., Krie, A. K., Balaraman, R., Restrepo, A., Meshad, M. W., Rieger-Christ, K., Sullivan, T., Lee, C. M., Greenwald, D. R., Oh, W., Tsao, C.-K., Fleshner, N., Kennecke, H. F., Khalil, M. F., Spigel, D. R., Manhas, A. P., Ulrich, B. K., Kovoor, P. A., Stokoe, C., Courtright, J. G., Yimer, H. A., Larson, T. G., Swanton, C., Seiden, M. V., Cummings, S. R., Absalan, F., Alexander, G., Allen, B., Amini, H., Aravanis, A. M., Bagaria, S., Bazargan, L., Beausang, J. F., Berman, J., Betts, C., Blocker, A., Bredno, J., Calef, R., Cann, G., Carter, J., Chang, C., Chawla, H., Chen, X., Chien, T. C., Civello, D., Davydov, K., Demas, V., Desai, M., Dong, Z., Fayzullina, S., Fields, A. P., Filippova, D., Freese, P., Fung, E. T., Gnerre, S., Gross, S., Halks-Miller, M., Hall, M. P., Hartman, A.-R., Hou, C., Hubbell, E., Hunkapiller, N., Jagadeesh, K., Jamshidi, A., Jiang, R., Jung, B., Kim, T., Klausner, R. D., Kurtzman, K. N., Lee, M., Lin, W., Lipson, J., Liu, H., Liu, Q., Lopatin, M., Maddala, T., Maher, M. C., Melton, C., Mich, A., Nautiyal, S., Newman, J., Newman, J., Nicula, V., Nicolaou, C., Nikolic, O., Pan, W., Patel, S., Prins, S. A., Rava, R., Ronaghi, N., Sakarya, O., Satya, R. V., Schellenberger, J., Scott, E., Sehnert, A. J., Shaknovich, R., Shanmugam, A., Shashidhar, K. C., Shen, L., Shenoy, A., Shojaee, S., Singh, P., Steffen, K. K., Tang, S., Toung, J. M., Valouev, A., Venn, O., Williams, R. T., Wu, T., Xu, H. H., Yakym, C., Yang, X., Yecies, J., Yip, A. S., Youngren, J., Yue, J., Zhang, J., Zhang, L., Zhang, L. (., Zhang, N., Curtis, C., & Berry, D. A.
Affiliations
  • Compass Oncology (US)
  • Texas Oncology (US)
  • Rocky Mountain Cancer Centers (US)
  • Spartanburg Regional Healthcare System (US)
  • Hartford Hospital (US)
  • Mayo Clinic in Florida (US)
  • Texas Health Dallas (US)
  • Cleveland Clinic (US)
  • Mayo Clinic (US)
  • University of Miami Health System (US)
  • Maryland Oncology Hematology (US)
  • New York Oncology Hematology (US)
  • Prisma Health (US)
  • Virginia Cancer Specialists (US)
  • Oncology Hematology Care (US)
  • Avera Health (US)
  • Lahey Hospital and Medical Center (US)
  • Sansum Medical Clinic (US)
  • Mount Sinai Hospital (US)
  • University of Toronto (CA)
  • Benaroya Research Institute (US)
  • Lehigh Valley Health Network (US)
  • Sarah Cannon (US)
  • Minnesota Oncology (US)
  • Sutter Health (US)
  • Grail (United States) (US)
  • Stanford University (US)
  • The University of Texas MD Anderson Cancer Center (US)
ORCID
Venue
Annals of Oncology
Publisher
Elsevier BV
Published
2020-06
Volume
31
Issue
6
Pages
745-759
ISSN
0923-7534 (ISSN-L)
DOI
10.1016/j.annonc.2020.02.011
PMC
PMC8274402
OpenAlex
W3013924915
Cited by
1,495
References
28
Citations by year
2026: 202 · 2025: 245 · 2024: 253 · 2023: 267 · 2022: 248 · 2021: 205 · 2020: 74
FWCI
70.07
Type
journal article
Language
en
Open access
Licence
Locations
  • Annals of Oncology (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion, cc-by-nc-nd)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by-nc-nd)
Funders
  • GRAIL, Inc
  • Princess Margaret Cancer Centre’s McCain GU BioBank
  • Francis Crick Institute
  • Cancer Research UK (FC001169, FC001202)
  • UK Medical Research Council (FC001169, FC001202)
  • Wellcome Trust (FC001169, FC001202)
  • CRUK Lung Cancer Centre of Excellence
  • Rosetrees Trust
  • Breast Cancer Research Foundation
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
Keywords
multi-cancer early detection, cell-free DNA, DNA methylation signature, liquid biopsy, tumor stage, bisulfite sequencing, false positive rate, early-stage cancer detection, cancer mortality reduction
MeSH terms
Cell-Free Nucleic Acids, DNA, Neoplasm, Female, Humans, Neoplasms, Prospective Studies, Biomarkers, Tumor, DNA Methylation

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