Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

Gabriel Renaud; Maibritt Nørgaard; Johan Lindberg; Henrik Grönberg; Bram De Laere; Jørgen Bjerggaard Jensen; Michael Borre; Claus Lindbjerg Andersen; Karina Dalsgaard Sørensen; Lasse Maretty; Søren Besenbacher

doi:10.7554/ELIFE.71569

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

Gabriel Renaud, Maibritt Nørgaard, Johan Lindberg, Henrik Grönberg, Bram De Laere, Jørgen Bjerggaard Jensen, Michael Borre, Claus Lindbjerg Andersen, Karina Dalsgaard Sørensen, Lasse Maretty, Søren Besenbacher

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

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.

Originalsprog	Engelsk
Artikelnummer	e71569
Tidsskrift	eLife
Vol/bind	11
Antal sider	15
ISSN	2050-084X
DOI	https://doi.org/10.7554/ELIFE.71569
Status	Udgivet - jul. 2022

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10.7554/ELIFE.71569

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title = "Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization",

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.",

keywords = "Biomarkers, Tumor/genetics, Cell-Free Nucleic Acids, Circulating Tumor DNA/genetics, Genomics/methods, Humans, Male, Mutation",

author = "Gabriel Renaud and Maibritt N{\o}rgaard and Johan Lindberg and Henrik Gr{\"o}nberg and {De Laere}, Bram and Jensen, {J{\o}rgen Bjerggaard} and Michael Borre and Andersen, {Claus Lindbjerg} and S{\o}rensen, {Karina Dalsgaard} and Lasse Maretty and S{\o}ren Besenbacher",

note = "{\textcopyright} 2022, Renaud et al.",

year = "2022",

month = jul,

doi = "10.7554/ELIFE.71569",

language = "English",

volume = "11",

journal = "eLife",

issn = "2050-084X",

publisher = "eLife Sciences Publications Ltd.",

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TY - JOUR

T1 - Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

AU - Renaud, Gabriel

AU - Nørgaard, Maibritt

AU - Lindberg, Johan

AU - Grönberg, Henrik

AU - De Laere, Bram

AU - Jensen, Jørgen Bjerggaard

AU - Borre, Michael

AU - Andersen, Claus Lindbjerg

AU - Sørensen, Karina Dalsgaard

AU - Maretty, Lasse

AU - Besenbacher, Søren

PY - 2022/7

Y1 - 2022/7

N2 - 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.

AB - 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.

KW - Biomarkers, Tumor/genetics

KW - Cell-Free Nucleic Acids

KW - Circulating Tumor DNA/genetics

KW - Genomics/methods

KW - Humans

KW - Male

KW - Mutation

U2 - 10.7554/ELIFE.71569

DO - 10.7554/ELIFE.71569

M3 - Journal article

C2 - 35894300

SN - 2050-084X

VL - 11

JO - eLife

JF - eLife

M1 - e71569

ER -

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

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