Analysis of recurrently protected genomic regions in cell-free DNA found in urine
Science Translational Medicine • 17 Feb 2021 • Vol 13, Issue 581 • DOI: 10.1126/scitranslmed.aaz3088
Detecting cancer by urine cell-free DNA
Detection of cell-free DNA (cfDNA) in urine could be a noninvasive approach to diagnose cancer. However, urine cfDNA is very fragmented, making it difficult to use. Markus et al. analyzed fragmentation patterns in urine and plasma cfDNA using whole-genome sequencing in healthy individuals and those with cancer. Compared to cfDNA from healthy individuals, tumor-derived fragmentation patterns ending within recurrently protected regions occurred more frequently in urine. By comparing genome-wide differences in urine cfDNA fragmentation patterns, the authors could distinguish cancer samples from controls, suggesting that this approach might complement plasma cfDNA as a cancer diagnostic.
Abstract
Cell-free DNA (cfDNA) in urine is a promising analyte for noninvasive diagnostics. However, urine cfDNA is highly fragmented. Whether characteristics of these fragments reflect underlying genomic architecture is unknown. Here, we characterized fragmentation patterns in urine cfDNA using whole-genome sequencing. Size distribution of urine cfDNA fragments showed multiple strong peaks between 40 and 120 base pairs (bp) with a modal size of 81- and sharp 10-bp periodicity, suggesting transient protection from complete degradation. These properties were robust to preanalytical perturbations, such as at-home collection and delay in processing. Genome-wide sequencing coverage of urine cfDNA fragments revealed recurrently protected regions (RPRs) conserved across individuals, with partial overlap with nucleosome positioning maps inferred from plasma cfDNA. The ends of cfDNA fragments clustered upstream and downstream of RPRs, and nucleotide frequencies of fragment ends indicated enzymatic digestion of urine cfDNA. Compared to plasma, fragmentation patterns in urine cfDNA showed greater correlation with gene expression and chromatin accessibility in epithelial cells of the urinary tract. We determined that tumor-derived urine cfDNA exhibits a higher frequency of aberrant fragments that end within RPRs. By comparing the fraction of aberrant fragments and nucleotide frequencies of fragment ends, we identified urine samples from cancer patients with an area under the curve of 0.89. Our results revealed nonrandom genomic positioning of urine cfDNA fragments and suggested that analysis of fragmentation patterns across recurrently protected genomic loci may serve as a cancer diagnostic.
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Supplementary Material
Summary
Fig. S1. Fragment size distribution of cfDNA from individual healthy plasma samples.
Fig. S2. Fragment size distribution of cfDNA from individual healthy urine samples.
Fig. S3. Comparison of raw sequencing coverage between plasma and urine.
Fig. S4. Distribution of RPR widths across multiple genome-wide RPR maps.
Fig. S5. Comparison of overlapping and nonoverlapping RPR call confidence scores.
Fig. S6. Comparison of fragment size in urine cfDNA between open and closed chromatin regions, using bins of 50, 500, and 1000 kb.
Fig. S7. Cosine similarity between cfDNA fragment sizes and DHS sites.
Fig. S8. Mean pooled plasma and urine cfDNA sequencing depth at the TSS of genes grouped according to their expression.
Fig. S9. Spearman’s rank correlation coefficients for cfDNA sequencing coverage at NDR coverage and gene expression.
Fig. S10. Changes in rank based on the correlation between NDR coverage and gene expression between plasma and urine.
Fig. S11. Nucleotide frequencies at fragment start sites in plasma samples.
Fig. S12. Nucleotide frequencies at fragment end sites in plasma samples.
Fig. S13. Nucleotide frequencies at fragment start sites in urine samples.
Fig. S14. Nucleotide frequencies at fragment end sites in urine samples.
Fig. S15. Nucleotide frequencies at fragment start and end sites across fragment size bins in plasma and urine cfDNA.
Fig. S16. Fragment size distribution in individual urine samples from patients with cancer.
Fig. S17. Effect of changing maximum distance from RPR center on fraction of fragments with ends within RPRs in urine samples from healthy controls and patients with cancer.
Fig. S18. Nucleotide frequencies at fragment start sites in urine samples from patients with cancer.
Fig. S19. Nucleotide frequencies at fragment end sites in urine samples from patients with cancer.
Fig. S20. ROC analysis for classifying control and cancer samples by cancer type.
Fig. S21. Aberrant fragments across copy number changes in sample 36.
Fig. S22. Aberrant fragments across copy number changes in sample 37.
Fig. S23. Aberrant fragments across copy number changes in sample 34.
Fig. S24. Aberrant fragments across copy number changes in sample 43.
Fig. S25. Aberrant fragments across copy number changes in sample 33.
Fig. S26. Comparison of fragment size distributions between multiple urine samples collected from five healthy individuals.
Table S1. Histone proteins identified in urine using mass spectrometry.
Table S2. Clinical characteristics of patients with cancer.
Data file S1. Quantile normalized cosine similarity between DHS sites and cfDNA fragment size.
Data file S2. Quantile normalized Spearman’s rank correlation coefficients between gene expression and NDR coverage.
Data file S3. Rank changes in Spearman’s rank correlation coefficients across pooled plasma and urine.
Data file S4. FAF and multidimensional scaled dimensions 1 to 4 of FEMs in urine samples.
Resources
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Information & Authors
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Published In
Science Translational Medicine
Volume 13 | Issue 581
February 2021
February 2021
Copyright
Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
This is an article distributed under the terms of the Science Journals Default License.
Submission history
Received: 29 August 2019
Accepted: 28 January 2021
Acknowledgments
We would like to thank C. Sinclair, D. Metz, and S. Buchholtz at TGen, L. Keller at Phoenix Children’s Hospital, and the volunteers and patients who participated in this study. Editorial services were provided by N. R. Gough (BioSerendipity, LLC, Elkridge, MD). Funding: This work was supported by funding from Ben and Catherine Ivy Foundation to M. Murtaza and S.C., from the National Cancer Institute (NCI) of the NIH under award numbers 1U01CA243078-01A1 to M. Murtaza and 1R01CA223481-01 to M. Murtaza; from Science Foundation Arizona under award number BSP-0542-13 to M. Murtaza, from Arizona Women’s Board to P.P. and M. Murtaza; from Phoenix Children’s Hospital to J.Z. and P.H.; and from Baylor Scott and White Research Institute to S.C., C.B., A.G., and M.M. Author contributions: H.M. and M. Murtaza conceptualized and designed the study. H.M., J.Z., T.C.-C., E.R., A.O.-B., P.P., K.V.K.-J., and M. Murtaza developed methods. J.Z., M.D.S., M.C.M., C.B., S.A.C., A.G., D.D.V.H., and P.H. designed and conducted prospective clinical studies. T.C.-C., M.D.S., E.R., A.O.-B., S.C., B.M., E.H., and M. McGilvrey generated data. H.M., E.H., and B.R.M. analyzed sequencing data. H.M., E.R., P.P., and M. Murtaza interpreted data. H.M. and M. Murtaza wrote the paper with assistance from J.Z., T.C.-C., E.R., D.D.V.H., S.A.C., P.H., and P.P. All authors approved the final manuscript. Competing interests: H.M., B.R.M., and M. Murtaza are inventors on patent applications covering technologies described here including patent application number PCT/US20/41469, titled “Methods of detecting disease and treatment response in cfDNA.” M. Murtaza consults for AstraZeneca and Bristol Myers Squibb. All other authors declare that they have no competing interests. Data and materials availability: Urine and plasma sequencing data from controls, urine sequencing data, and tumor/germline exome sequencing data from patients with pediatric cancer are available in dbGaP through dbGaP accession number phs002273.v1.p1. Deidentified tumor/germline sequencing data and urine sequencing data from patients with pancreatic cancer will be made available to academic researchers upon request to M. Murtaza under a data transfer agreement. All other data associated with this study are present in the paper or the Supplementary Materials.
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Funding Information
National Cancer Institute: U01CA243078
National Cancer Institute: R01CA223481
Science Foundation Arizona: BSP-0542-13
Arizona Women’s Board
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