Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection
Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. We Here we developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.
- Type: Other
- Archiver: European Genome-Phenome Archive (EGA)
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 |
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EGAD00001005343 | Illumina NovaSeq 6000 NextSeq 550 | 41 |
Publications | Citations |
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Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection.
Nat Commun 10: 2019 4666 |
108 |
Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden.
Nat Commun 12: 2021 3230 |
74 |
Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes.
Cancer Discov 13: 2023 632-653 |
16 |