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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.

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
EGAD00001005343 Illumina NovaSeq 6000 NextSeq 550 41
Publications Citations
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