Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection

Author:

Ulz PeterORCID,Perakis SamanthaORCID,Zhou QingORCID,Moser TinaORCID,Belic JelenaORCID,Lazzeri Isaac,Wölfler Albert,Zebisch ArminORCID,Gerger Armin,Pristauz Gunda,Petru Edgar,White Brandon,Roberts Charles E. S.,John John St.,Schimek Michael G.,Geigl Jochen B.ORCID,Bauernhofer Thomas,Sill Heinz,Bock ChristophORCID,Heitzer EllenORCID,Speicher Michael R.ORCID

Abstract

Abstract Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. Here we develop and validate a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyze whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a 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.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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