bioRxiv2022
Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and NR3C1. Using these features, we designed a prediction model which distinguished NEPC from ARPC in patient plasma samples across three clinical cohorts with 97-100% sensitivity and 85-100% specificity. While phenotype classification is typically assessed by immunohistochemistry or transcriptome profiling, we demonstrate that ctDNA provides comparable results with numerous diagnostic advantages for precision oncology. STATEMENT OF SIGNIFICANCEThis study provides key insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. The new methods established for phenotype classification extend the utility of ctDNA beyond assessments of DNA alterations with important implications for molecular diagnostics and precision oncology.