ArticleCancer discovery2023
Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes.
Article in Cancer discovery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed, 63 citations in OpenAlex.
- Article
- Integration of breaking-point transition probabilities and specific open chromatin region features for early cancer detection.Cell communication and signaling : CCS · 2026Article
- Decoding DNA metabolism and its clinical relevance through the lens of high-throughput sequencing assays.Medical review (2021) · 2026Review
- Circulating Tumor DNA as Emerging Predictive and Prognostic Biomarker in Prostate Cancer.Cancers · 2026Review
- Correlative Biomarker Analysis of PSMA Expression on CTCs and PSMA Imaging in a Phase I Study of PSMA-Targeted Tubulysin Conjugate EC1169.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Multi-modal circulating cell-free DNA profiling to predict response to docetaxel in metastatic castration-resistant prostate cancer.NPJ precision oncology · 2026Article
- Nucleosome spacing across cell types, diseases, and ages.Nucleic acids research · 2026Review
- Deep learning-based non-invasive profiling of tumor transcriptomes from cell-free DNA for precision oncology.bioRxiv : the preprint server for biology · 2026Article
- Integrative dual ctDNA 5mC/5hmC methylomics and clonal reconstruction infer tumor transcription and resistance phenotypes in metastatic prostate cancer.Research square · 2026Article
- Mechanisms and implications of epithelial cell plasticity in the bladder.Nature reviews. Urology · 2026Review
- Epigenomics-guided precision oncology: Chromatin variants in prostate tumor evolution.International journal of cancer · 2026Review
- Advances in understanding the tumor microenvironment of neuroendocrine prostate cancer.Frontiers in oncology · 2026Review
- Cell-Free DNA (cfDNA), Its Applications in Cancer Diagnosis and Monitoring, and Its Potential Role in Regulating Cancer Metabolism.Advances in experimental medicine and biology · 2026Review
- The Quartet of Core Oncogenic Drivers in Neuroendocrine Prostate Cancer: Multi-Omics Dataset Integration to Forge a Translational Link Between Biology and Precision Therapy.International journal of biological sciences · 2026Review
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
- Liquid biopsy in genitourinary cancers: Diagnostic and prognostic implications.World journal of clinical oncology · 2025Review
- Simulating cell-free chromatin using preclinical cancer models for liquid biopsy applications.iScience · 2025Article
- Review
- Cross-dataset pan-cancer detection by correlating cell-free DNA fragment coverage with open chromatin sites across cell types.Nature communications · 2025Article
- cfOncoXpress: Tumor gene expression prediction from cell-free DNA whole-genome sequences.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
33 authors at 5 institutions in 2 countries.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.