Fragmentation landscape of cell-free DNA revealed by deconvolutional analysis of end motifs

Author:

Zhou Ze123,Ma Mary-Jane L.123,Chan Rebecca W. Y.123,Lam W. K. Jacky1234,Peng Wenlei123,Gai Wanxia123,Hu Xi123,Ding Spencer C.123,Ji Lu123ORCID,Zhou Qing123ORCID,Cheung Peter P. H.23,Yu Stephanie C. Y.123,Teoh Jeremy Y. C.5,Szeto Cheuk-Chun6,Wong John5ORCID,Wong Vincent W. S.6,Wong Grace L. H.7,Chan Stephen L.48ORCID,Hui Edwin P.48,Ma Brigette B. Y.48,Chan Anthony T. C.48,Chiu Rossa W. K.123ORCID,Chan K. C. Allen1234,Lo Y. M. Dennis1234ORCID,Jiang Peiyong1234ORCID

Affiliation:

1. Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, Hong Kong SAR, China

2. Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

3. Department of Chemical Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

4. State Key Laboratory of Translational Oncology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

5. Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

6. Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

7. Medical Data Analytics Centre, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

8. Department of Clinical Oncology, Sir Y. K. Pao Centre for Cancer, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

Abstract

Cell-free DNA (cfDNA) fragmentation is nonrandom, at least partially mediated by various DNA nucleases, forming characteristic cfDNA end motifs. However, there is a paucity of tools for deciphering the relative contributions of cfDNA cleavage patterns related to underlying fragmentation factors. In this study, through non-negative matrix factorization algorithm, we used 256 5′ 4-mer end motifs to identify distinct types of cfDNA cleavage patterns, referred to as “founder” end-motif profiles (F-profiles). F-profiles were associated with different DNA nucleases based on whether such patterns were disrupted in nuclease-knockout mouse models. Contributions of individual F-profiles in a cfDNA sample could be determined by deconvolutional analysis. We analyzed 93 murine cfDNA samples of different nuclease-deficient mice and identified six types of F-profiles. F-profiles I, II, and III were linked to deoxyribonuclease 1 like 3 (DNASE1L3), deoxyribonuclease 1 (DNASE1), and DNA fragmentation factor subunit beta (DFFB), respectively. We revealed that 42.9% of plasma cfDNA molecules were attributed to DNASE1L3-mediated fragmentation, whereas 43.4% of urinary cfDNA molecules involved DNASE1-mediated fragmentation. We further demonstrated that the relative contributions of F-profiles were useful to inform pathological states, such as autoimmune disorders and cancer. Among the six F-profiles, the use of F-profile I could inform the human patients with systemic lupus erythematosus. F-profile VI could be used to detect individuals with hepatocellular carcinoma, with an area under the receiver operating characteristic curve of 0.97. F-profile VI was more prominent in patients with nasopharyngeal carcinoma undergoing chemoradiotherapy. We proposed that this profile might be related to oxidative stress.

Funder

Innovation and Technology Commission

Li Ka Shing Foundation

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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