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1 februari 2025: Bron: Nature Published: 08 January 2025

De ctDNA bloedtest TriOx gecombineerd met door AI - Kunstmatige Intelligentie gecreeërde TET-Assisted Pyridine Borane Sequencing (TAPS) vond voor 95 procent betrouwbaarheid bij de patiënten met kanker met solide tumoren en zonder kanker.

Onderzoekers aan de universiteit van Oxfort hebben als vervolg op deze studie een nieuwe studie opgezet waarbij twee groepen van mensen werden vergeleken met elkaar. 1 groep bestond uit mensen met bevestigde kanker met solide tumoren. Andere groep bestond uit mensen die op moment van start van de studie geen aantoonbare kanker hadden. Doel was om te kijken of TriOx de mensen met en zonder kanker kon onderscheiden.

Twee derde van de deelnemers waren man en 71% waren 60 jaar of ouder. Voor de mensen die eerder waren gediagnosteerd met kanker was de mediane leeftijd 67,5 jaar.

De ctDNA bloedtest maakte onderscheid tussen mensen met kanker (T = 59) en mensen zonder kanker (T = 9) met een gevoeligheid van 94,9% en een specificiteit van 88,8%. TriOx identificeerde correct acht van de negen kankervrije controles als negatief en 56 van de 59 bevestigde kankergevallen als positief.

Van de patiënten met de diagnose kanker had 8,2% kanker in stadium 1, 32,8% in stadium 2, 57,4% in stadium 3 en 1,6% in stadium 4. Bijna twee derde van alle deelnemers had darmkanker.

Anna Schuh, MD, PhD, hoogleraar moleculaire diagnostiek aan de Universiteit van Oxford en hoofdonderzoeker van deze studie, zei in een persbericht dat TriOx "de potentie heeft om de overlevingskansen van miljoenen mensen wereldwijd te verbeteren door de implementatie van routinematige bloedtesten mogelijk te maken, zodat kanker eerder kan worden opgespoord, wanneer de ziekte nog makkelijker te behandelen is".

Het volledige studierapport is gratis in te zien in Nature, klik op de titel van het abstract:

Article
Open access
Published: 08 January 2025

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

Nature Communications volume 16, Article number: 430 (2025) Cite this article

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Abstract

The analysis of circulating tumour DNA (ctDNA) through minimally invasive liquid biopsies is promising for early multi-cancer detection and monitoring minimal residual disease. Most existing methods focus on targeted deep sequencing, but few integrate multiple data modalities. Here, we develop a methodology for ctDNA detection using deep (80x) whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive approach than bisulphite sequencing, which permits the simultaneous analysis of genomic and methylomic data. We conduct a diagnostic accuracy study across multiple cancer types in symptomatic patients, achieving 94.9% sensitivity and 88.8% specificity. Matched tumour biopsies are used for validation, not for guiding the analysis, imitating an early detection scenario. Furthermore, in silico validation demonstrates strong discrimination (86% AUC) at ctDNA fractions as low as 0.7%. Additionally, we successfully track tumour burden and ctDNA shedding from precancerous lesions post-treatment without requiring matched tumour biopsies. This pipeline is ready for further clinical evaluation to extend cancer screening and improve patient triage and monitoring.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

TAPS data (in the form of BAM files) from 214 samples generated in this study (plasma and matched germline pairs from 91 non-cancer and cancer subjects, matched fresh-frozen tumour biopsies from 16 subjects among these, as well as several follow-up plasma samples from 10 subjects with colorectal cancer) has been deposited in the European Genome-Phenome Archive (EGA) under the study with accession code EGAS50000000715. Source data is provided as a source data file. Source data are provided with this paper.

References

Crosby, D. et al. Early detection of cancer. Science 375, eaay9040 (2022).

Article CAS PubMed MATH Google Scholar
Lennon, A. M. et al. Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention. Science 369, eabb9601 (2020).

Article CAS PubMed PubMed Central MATH Google Scholar
Liu, M. C. et al. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann. Oncol. 31, 745–759 (2020).

Article CAS PubMed MATH Google Scholar
Nadauld, L. D. et al. The PATHFINDER Study: Assessment of the Implementation of an Investigational multi-cancer early detection test into clinical practice. Cancers 13, 3501 (2021).

Article CAS PubMed PubMed Central MATH Google Scholar
Nicholson, B. D. et al. Multi-cancer early detection test in symptomatic patients referred for cancer investigation in England and Wales (SYMPLIFY): a large-scale, observational cohort study. Lancet Oncol. 24, 733–743 (2023).

Article PubMed Google Scholar
Lyratzopoulos, G., Wardle, J. & Rubin, G. Rethinking diagnostic delay in cancer: how difficult is the diagnosis? BMJ 349, g7400 (2014).

Article PubMed MATH Google Scholar
Moore, S. F., Price, S. J., Chowienczyk, S., Bostock, J. & Hamilton, W. The impact of changing risk thresholds on the number of people in England eligible for urgent investigation for possible cancer: an observational cross-sectional study. Br. J. Cancer 125, 1593–1597 (2021).

Article PubMed PubMed Central Google Scholar
CancerData. https://www.cancerdata.nhs.uk/.
Chapman, D. et al. Non-specific symptoms-based pathways for diagnosing less common cancers in primary care: a service evaluation. Br. J. Gen. Pract. 71, e846–e853 (2021).

Article PubMed PubMed Central MATH Google Scholar
Chapman, D. et al. First results from five multidisciplinary diagnostic centre (MDC) projects for non-specific but concerning symptoms, possibly indicative of cancer. Br. J. Cancer 123, 722–729 (2020).

Article CAS PubMed PubMed Central MATH Google Scholar
Jensen, E., Kristensen, J. K., Bjerglund, R. T., Johnsen, S. P. & Thomsen, J. L. The pathway and characteristics of patients with non-specific symptoms of cancer: a systematic review. BMC Cancer 22, 574 (2022).

Article PubMed PubMed Central Google Scholar
Fitzgerald, R. C., Antoniou, A. C., Fruk, L. & Rosenfeld, N. The future of early cancer detection. Nat. Med. 28, 666–677 (2022).

Article CAS PubMed MATH Google Scholar
Hamilton, W., Walter, F. M., Rubin, G. & Neal, R. D. Improving early diagnosis of symptomatic cancer. Nat. Rev. Clin. Oncol. 13, 740–749 (2016).

Article PubMed MATH Google Scholar
Rubin, G. et al. The expanding role of primary care in cancer control. Lancet Oncol. 16, 1231–1272 (2015).

Article PubMed MATH Google Scholar
Nicholson, B. D. & Lyratzopoulos, G. Progress and priorities in reducing the time to cancer diagnosis. Br. J. cancer 128, 468–470 (2023).

Article CAS PubMed Google Scholar
Neal, R. D. et al. Cell-free DNA-based multi-cancer early detection test in an asymptomatic screening population (NHS-Galleri): design of a pragmatic, prospective randomised controlled trial. Cancers 14, 4818 (2022).

Article CAS PubMed PubMed Central MATH Google Scholar
Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359, 926–930 (2018).

Article ADS CAS PubMed PubMed Central MATH Google Scholar
Killcoyne, S. et al. Genomic copy number predicts esophageal cancer years before transformation. Nat. Med. 26, 1726–1732 (2020).

Article CAS PubMed PubMed Central Google Scholar
Cristiano, S. et al. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature 570, 385–389 (2019).

Article ADS CAS PubMed PubMed Central MATH Google Scholar
Bao, H. et al. Letter to the editor: an ultra-sensitive assay using cell-free DNA fragmentomics for multi-cancer early detection. Mol. Cancer 21, 129 (2022).

Article CAS PubMed PubMed Central MATH Google Scholar
Zviran, A. et al. Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring. Nat. Med. 26, 1114–1124 (2020).

Article CAS PubMed PubMed Central Google Scholar
Peneder, P. et al. Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden. Nat. Commun. 12, 3230 (2021).

Article ADS CAS PubMed PubMed Central MATH Google Scholar
Cutts, A. et al. Characterisation of the changing genomic landscape of metastatic melanoma using cell free DNA. NPJ. Genom. Med. 2, 25 (2017).

Google Scholar
Li, Y. et al. Multi-omics integrated circulating cell-free DNA genomic signatures enhanced the diagnostic performance of early-stage lung cancer and postoperative minimal residual disease. EBioMedicine 91, 104553 (2023).

Article CAS PubMed PubMed Central MATH Google Scholar
Ganesamoorthy, D. et al. Whole genome deep sequencing analysis of cell-free DNA in samples with low tumour content. BMC Cancer 22, 85 (2022).

Article MathSciNet CAS PubMed PubMed Central MATH Google Scholar
Widman, A. J. et al. Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment. Nat. Med. 30, 1655–1666 (2024).

Article CAS PubMed PubMed Central MATH Google Scholar
Liu, Y. et al. Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat. Biotechnol. 37, 424–429 (2019).

Article CAS PubMed MATH Google Scholar
Liu, Y. et al. Accurate targeted long-read DNA methylation and hydroxymethylation sequencing with TAPS. Genome Biol. 21, 54 (2020).

Article PubMed PubMed Central MATH Google Scholar
Vaisvila, R. et al. Enzymatic methyl sequencing detects DNA methylation at single-base resolution from picograms of DNA. Genome Res. 31, 1280–1289 (2021).

Article CAS PubMed PubMed Central MATH Google Scholar
Siejka-Zielińska, P. et al. Cell-free DNA TAPS provides multimodal information for early cancer detection. Sci. Adv. 7, eabh0534 (2021).

Article ADS PubMed PubMed Central MATH Google Scholar
Leary, R. J. et al. Detection of chromosomal alterations in the circulation of cancer patients with whole-genome sequencing. Sci. Transl. Med. 4, 162ra154 (2012).

Article PubMed PubMed Central MATH Google Scholar
Adalsteinsson, V. A. et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat. Commun. 8, 1324 (2017).

Article ADS PubMed PubMed Central MATH Google Scholar
Steele, C. D. et al. Signatures of copy number alterations in human cancer. Nature 606, 984–991 (2022).

Article ADS CAS PubMed PubMed Central MATH Google Scholar
Benjamini, Y. & Speed, T. P. Summarizing and correcting the GC content bias in high-throughput sequencing. Nucleic Acids Res. 40, e72 (2012).

Article CAS PubMed PubMed Central MATH Google Scholar
Newman, A. M. et al. Integrated digital error suppression for improved detection of circulating tumor DNA. Nat. Biotechnol. 34, 547–555 (2016).

Article CAS PubMed PubMed Central MATH Google Scholar
Esteller, M. Epigenetics in cancer. N. Engl. J. Med. 358, 1148–1159 (2008).

Article CAS PubMed MATH Google Scholar
Sharma, S., Kelly, T. K. & Jones, P. A. Epigenetics in cancer. Carcinogenesis 31, 27–36 (2010).

Article CAS PubMed MATH Google Scholar
Markowitz, S. D. & Bertagnolli, M. M. Molecular origins of cancer: molecular basis of colorectal cancer. N. Engl. J. Med. 361, 2449–2460 (2009).

Article CAS PubMed PubMed Central MATH Google Scholar
Kang, S. et al. CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA. Genome Biol. 18, 53 (2017).

Article PubMed PubMed Central MATH Google Scholar
Li, W. et al. CancerDetector: ultrasensitive and non-invasive cancer detection at the resolution of individual reads using cell-free DNA methylation sequencing data. Nucleic Acids Res. 46, e89 (2018).

Article PubMed PubMed Central MATH Google Scholar
Choy, L. Y. L. et al. Single-molecule sequencing enables long cell-free DNA detection and direct methylation analysis for cancer patients. Clin. Chem. 68, 1151–1163 (2022).

Article PubMed MATH Google Scholar
Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer. N. Engl. J. Med. 386, 2261–2272 (2022).

Article CAS PubMed PubMed Central MATH Google Scholar
Kotani, D. et al. Molecular residual disease and efficacy of adjuvant chemotherapy in patients with colorectal cancer. Nat. Med. 29, 127–134 (2023).

Article CAS PubMed PubMed Central MATH Google Scholar
Abbosh, C. et al. Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA. Nature 616, 553–562 (2023).

Article ADS CAS PubMed PubMed Central MATH Google Scholar
Killock, D. Early MRD predicts disease recurrence and benefit from adjuvant chemotherapy in CRC. Nat. Rev. Clin. Oncol. 20, 137 (2023).

Article PubMed Google Scholar
Schrag, D. et al. Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study. Lancet 402, 1251–1260 (2023).

Article PubMed PubMed Central MATH Google Scholar
Buchanan, A. H. et al. Multi-year clinical outcomes of cancers diagnosed following detection by a blood-based multi-cancer early detection (MCED) test. Cancer Prev. Res. https://doi.org/10.1158/1940-6207.CAPR-24-0107 (2024).
Hamilton, W., Hajioff, S., Graham, J. & Schmidt-Hansen, M. Suspected cancer (part 2–adults): reference tables from updated NICE guidance. BMJ 350, h3044 (2015).

Article PubMed Google Scholar
Savitzky, A. & Golay, M. J. E. Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36, 1627–1639 (1964).

Article ADS CAS MATH Google Scholar
Mathios, D. et al. Detection and characterization of lung cancer using cell-free DNA fragmentomes. Nat. Commun. 12, 5060 (2021).

Article ADS CAS PubMed PubMed Central MATH Google Scholar
Yu, P. et al. Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer. Genome Med. 16, 79 (2024).

Article CAS PubMed PubMed Central MATH Google Scholar

Download references

Acknowledgements

This research was funded by Innovate UK (Competition: Application of whole genome sequencing approaches to cancer; Project title: Base Genomics: A novel method for single-step, ultra-sensitive, combined DNA methylation and mutation detection of cancer from liquid biopsies using WGS; Grant application: 49382) and the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC4 Cancer theme awarded to AS). We further acknowledge the contribution to this study made by the Oxford Centre for Histopathology Research and the Oxford Radcliffe Biobank, which are supported by the University of Oxford, the Oxford CRUK Cancer Centre and the NIHR Oxford Biomedical Research Centre (Molecular Diagnostics Theme/Multimodal Pathology Subtheme), and the NIHR CRN Thames Valley network. BDN is supported by a National Institute of Health Research Academic Clinical Lectureship, a CRUK Research Careers Committee Postdoctoral Fellowship (RCCPDF\100005), and he is the Early Detection Theme Lead for the CRUK Oxford Cancer Centre (CTRQQR-2021\100002). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

Author information

Authors and Affiliations

Oxford Molecular Diagnostics Centre, Department of Oncology, University of Oxford, Oxford, UK

Dimitrios V. Vavoulis, Anthony Cutts, Arman Ardalan, Kieran Howard, Flavia Matos Santo, Helene Dreau & Anna Schuh
Biomedical Research Centre, Centre for Human Genetics, University of Oxford, Oxford, UK

Dimitrios V. Vavoulis
Exact Sciences Innovation LTD, The Sherard Bldg, Edmund Halley Rd, Littlemore, Oxford, UK

Nishita Thota, Jordan Brown, Robert Sugar, Antonio Rueda, Thippesh Sannasiddappa, Bronwen Miller & Carolyn Tregidgo
Ludwig Institute for Cancer Research, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Stephen Ash & Chun-Xiao Song
College of Chemistry and Molecular Sciences, Wuhan University, Wuhan, China

Yibin Liu
Taikang Centre for Life and Medical Sciences, Wuhan University, Wuhan, China

Yibin Liu
Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Chun-Xiao Song
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Brian D. Nicholson

Contributions

A.S. conceptualised the study, raised funds to implement the study, and directed the study. A.S., D.V.V., A.C., C.T. and H.D. designed the study. C.T., H.D. oversaw laboratory operations. A.C., J.B., F.M.S., T.S., B.M., Y.B.L. and C.X.S. designed and performed experiments. S.A. and B.D.N. provided clinical data and samples; D.V.V., A.A. and K.H. conducted coverage and CNV analysis; D.V.V., J.B., A.A., and A.R. conducted methylation analysis. D.V.V., N.T., R.S. and A.R. conducted somatic SNV analysis. D.V.V. conducted integrative statistical analysis and developed machine learning classifiers. D.V.V., A.S. and B.D.N. interpreted the results and wrote the manuscript with input from all authors.

Corresponding authors

Correspondence to Dimitrios V. Vavoulis or Anna Schuh.

Ethics declarations

Competing interests

A.S. is on the advisory board for Janssen and BeiGene and is the Founder of SERENOx. She also receives research funding from AstraZeneca and Janssen and in-kind contributions from Illumina and Oxford Nanopore Technologies. BDN has received research funding from GRAIL and is an unpaid member of the GRAIL Clinical Advisory Group. D.V.V., A.C. and H.D. own shares in SerenOx. N.T., J.B., R.S., A.R., T.S., B.M., Y.B.L. and C.T. were employees at Exact Sciences Innovation LTD for the duration of the study. The remaining authors declare no competing interests.

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Vavoulis, D.V., Cutts, A., Thota, N. et al. Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals. Nat Commun 16, 430 (2025). https://doi.org/10.1038/s41467-024-55428-y

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Received04 January 2024
Accepted05 December 2024
Published08 January 2025
DOIhttps://doi.org/10.1038/s41467-024-55428-y

Bloedtest, TriOx, kanker met solide tumoren, preventie, AI, Kunstmatige Intelligentie, opsporen van kanker, Universiteit van Oxfort

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