Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization
- Technical University of Denmark, Denmark
- Aarhus University, Denmark
- Karolinska Institute, Sweden
- Regional Hospital of West Jutland, Denmark
- Aarhus University Hospital, Denmark
Abstract
Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel and completely unsupervised method for studying fragment length patterns in cfDNA. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC=0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.
Data availability
Danish law requires ethical approval of any specific research aim and imposes restrictions on sharing of personal data. This means that the prostate cancer data used in this article cannot be uploaded to international databases. External researchers (academic or commercial) interested in analysing the prostate dataset (including any derivatives of it) will need to contact the Data Access Committee via email to kdso@clin.au.dk. The Data Access Committee is formed of co-authors Karina Dalsgaard Sørensen and Michael Borre, and Ole Halfdan Larsen (Department Head Consultant, Department of Clinical Medicine, Aarhus University). Due to Danish Law, for the authors to be allowed to share the data (pseudonymised) it will require prior approval from The Danish National Committee on Health Research Ethics (or similar) for the specific new research goal. The author (based in Denmark) has to submit the application for ethical approval, with the external researcher(s) as named collaborator(s)). In addition to ethical approval, a Collaboration Agreement and a Data Processing Agreement is required, both of which must be approved by the legal office of the institution of the author (data owner) and the legal office of the institution of the external researcher (data processor). Raw fragment length distributions along with ctDNA% estimates are available in Supplementary File 1.
Article and author information
Author details
Funding
The Independent Research Fund Denmark (Sapere Aude Research Leader)
- Søren Besenbacher
The Danish Cancer Society
- Karina Dalsgaard Sørensen
The Central Denmark Region Health Fund
- Karina Dalsgaard Sørensen
Aarhus Universitet (Graduate School of Health)
- Maibritt Nørgaard
Direktør Emil C. Hertz og Hustru Inger Hertz Fond
- Karina Dalsgaard Sørensen
KV Fonden
- Karina Dalsgaard Sørensen
Raimond og Dagmar Ringgård-Bohns Fond
- Karina Dalsgaard Sørensen
Beckett Fonden
- Karina Dalsgaard Sørensen
Snedkermester Sophus Jacobsen og Hustru Astrid Jacobsens Fond
- Karina Dalsgaard Sørensen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The prostate study was approved by The National Committee on Health Research Ethics (#1901101) and notified to The Danish Data Protection Agency (#1-16-02-366-15). All patients provided written informed consent.
Copyright
© 2022, Renaud et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization
eLife 11:e71569.
https://doi.org/10.7554/eLife.71569
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