Study
Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection
Study ID | Alternative Stable ID | Type |
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EGAS00001003206 | Other |
Study Description
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.
Study Datasets 1 dataset.
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 |
random whole-genome shotgun sequencing of cfDNA in control samples (NPH*) and late-stage cancer samples. First letter denotes primary cancer tissue (C: Colon, B: Breast, P: Prostate)
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Illumina NovaSeq 6000,NextSeq 550 | 41 |
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