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

Authors :
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 S. Ang
Ilsa M. 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
R. Bruce Montgomery
Eva Corey
Steven Henikoff
Peter S. Nelson
Gavin Ha
Source :
Cancer discovery.
Publication Year :
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. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology. Significance: This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517

Subjects

Subjects :
Oncology

Details

ISSN :
21598290
Database :
OpenAIRE
Journal :
Cancer discovery
Accession number :
edsair.doi.dedup.....cd833af6a03c1560ba09d49700a21b84