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

Abstract

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 patientspecific 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.

Androgen receptor enhancer usage and the chromatin regulatory landscape in human prostate cancers

“…Another interesting approach, applicable for patients with large burden of ctDNA, could be identification of nucleosome footprints in ctDNA. Analysis of two plasma samples taken 12 months apart, during which the prostate adenocarcinoma transdifferentiated to a treatmentemergent small-cell neuroendocrine prostate carcinoma (t-SCNC, AR-independent disease state), showed no longer accessibility of AR-binding sites during the disease course (Ulz et al 2018). Given the paucity of serial sample collections at different points during the disease course, alternative models such as patient-derived xenografts (PDX), ex vivo cultures and/or cell lines are required to monitor therapy effect on transcription factor dynamics.…”

Towards systematic nomenclature for cell-free DNA

“…This knowledge will not only aid in the identification of more disease-specific cfDNA features, but also inform the development of strategies that maximize the chances of detecting target cfDNA molecules, thereby increasing the diagnostic sensitivity and specificity of clinical assays, such as; the selection of patient conditions that either favor the release of target molecules or limit the release of background molecules into the body fluids in question prior to sampling; optimization of preanalytical procedures that preserve target molecules and limit the incidence of contaminating DNA; tailoring or development of extraction procedures that are either biased towards the capture of specific cfDNA molecules or the elimination of non-specific DNA molecules. Therefore, in keeping with these recent important findings, it may in the near-future become necessary to devise nomenclature for distinguishing between (i) cytoplasmic vs. cell-surface bound cfDNA (Tamkovich and Laktionov 2019 ), (ii) cfDNA fragments that possess different epigenetic signatures (e.g., unique DNA fragmentation patterns and endpoint motifs, methylation patterns, nucleosome positioning and transcription factor binding sites) (Sanchez et al 2018 ; Snyder et al 2016 ; Sun et al 2018 ; Ulz et al 2019a ), (iii) cfDNA fragments that exhibit different sizes, (iv) cfDNA fragments that originate from somatic cells vs. germline cells, which may be termed cell-free somatic DNA (cf-somDNA) and cell-free germline DNA (cf-germDNA), respectively, (v) cfDNA complexed or associated with different proteins and other subcellular components—for example, studies have shown significant portions of cfDNA to be associated with (a) histone proteins in nucleosomal structures, which may be termed cell-free nucleosomes (cfNucs), (b) extracellular vesicles, which may be termed extracellular vesicle associated DNA (evDNA), (c) specific extracellular vesicles such as exosomes, which may be termed exosome associated DNA (exoDNA), (d) small lipoprotein complexes, (e) fragments of cellular membranes, and (f) neutrophil extracellular traps (NETs) released from polymorphonuclear neutrophils, which are structures composed of DNA, histones, granules and enzymes (Aucamp et al 2018 ; Thierry et al 2016 ).…”