Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes

表型 生物 表观遗传学 前列腺癌 染色质 核小体 组蛋白 转录组 转录因子 癌症研究 计算生物学 基因 遗传学 癌症 基因表达
作者
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
出处
期刊:Cancer Discovery [American Association for Cancer Research]
卷期号:13 (3): 632-653 被引量:56
标识
DOI:10.1158/2159-8290.cd-22-0692
摘要

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
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