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

循环肿瘤DNA中的核小体模式揭示了晚期前列腺癌表型的转录调控

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