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  • Inference of transcription ...
    Ulz, Peter; Perakis, Samantha; Zhou, Qing; Moser, Tina; Belic, Jelena; Lazzeri, Isaac; Wölfler, Albert; Zebisch, Armin; Gerger, Armin; Pristauz, Gunda; Petru, Edgar; White, Brandon; Roberts, Charles E S; John, John St; Schimek, Michael G; Geigl, Jochen B; Bauernhofer, Thomas; Sill, Heinz; Bock, Christoph; Heitzer, Ellen; Speicher, Michael R

    Nature communications, 10/2019, Letnik: 10, Številka: 1
    Journal Article

    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.