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Genome-wide cell-free DNA fragmentation in patients with cancer

Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001005339 Illumina HiSeq 2500 537
Publications Citations
Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden.
Nat Commun 12: 2021 3230
61
Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization.
Elife 11: 2022 e71569
3
Genome-wide mutational signatures in low-coverage whole genome sequencing of cell-free DNA.
Nat Commun 13: 2022 4953
6
Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions.
Cell 185: 2022 3789-3806.e17
95
A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA.
Nat Commun 13: 2022 7475
17
Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.
Nat Commun 14: 2023 2017
1