TY - JOUR T1 - Inference of tumor cell-specific transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection of cancer JF - bioRxiv DO - 10.1101/456681 SP - 456681 AU - Peter Ulz AU - Samantha Perakis AU - Qing Zhou AU - Tina Moser AU - Jelena Belic AU - Isaac Lazzeri AU - Albert Wölfler AU - Armin Zebisch AU - Armin Gerger AU - Gunda Pristauz AU - Edgar Petru AU - Brandon White AU - Charles E.S. Roberts AU - John St. John AU - Michael G. Schimek AU - Jochen B. Geigl AU - Thomas Bauernhofer AU - Heinz Sill AU - Christoph Bock AU - Ellen Heitzer AU - Michael R. Speicher Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/03/31/456681.abstract N2 - Deregulation of transcription factors (TFs) is an important driver of tumorigenesis. 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 that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observed 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 early detection of 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. ER -