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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Ulz, P; Perakis, S; Zhou, Q; Moser, T; Belic, J; Lazzeri, I; Wölfler, A; Zebisch, A; Gerger, A; Pristauz, G; Petru, E; White, B; Roberts, CES; John, JS; Schimek, MG; Geigl, JB; Bauernhofer, T; Sill, H; Bock, C; Heitzer, E; Speicher, MR.
Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection.
Nat Commun. 2019; 10(1): 4666-4666. Doi: 10.1038/s41467-019-12714-4 [OPEN ACCESS]
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Führende Autor*innen der Med Uni Graz
Heitzer Ellen
Speicher Michael
Ulz Peter
Co-Autor*innen der Med Uni Graz
Bauernhofer Thomas
Belic Jelena
Geigl Jochen Bernd
Gerger Armin
Hasenleithner Samantha
Lazzeri Isaac
Moser Tina
Petru Edgar
Pristauz-Telsnigg Gunda
Schimek Michael
Sill Heinz
Wölfler Albert
Zebisch Armin
Zhou Qing
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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.

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