Nucleosome patterns in circulating tumor DNA reveal transcriptional regulation of advanced prostate cancer phenotypes

Navonil De Sarkar*, Robert D. Patton*, Anna-Lisa Doebley, Brian Hanratty, Mohamed Adil, Adam J. Kreitzman, Jay F. Sarthy, Minjeong Ko, Sandipan Brahma, Michael P. Meers, Derek H. Janssens, Lisa A. Ang, Ilsa Coleman, Arnab Bose, Ruth F. Dumpit, Jared M. Lucas, Talina A. Nunez, Holly M. Nguyen, Heather M. McClure, Colin C. Pritchard, Michael T. Schweizer, Colm Morrissey, Atish D. Choudhury, Sylvan C. Baca, Jacob E. Berchuck, Matthew L. Freedman, Kami Ahmad, Michael C. Haffner, Bruce Montgomery, Eva Corey, Steven Henikoff, Peter S. Nelson+, Gavin Ha+.
Cancer Discovery , CD-22-0692 (2022).

Abstract

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 GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. While phenotype classification is typically assessed by immunohistochemistry or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology.