Dataset Information

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

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.

SUBMITTER: De Sarkar N

PROVIDER: S-EPMC9976992 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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

De Sarkar Navonil N Patton Robert D RD Doebley Anna-Lisa AL Hanratty Brian B Adil Mohamed M Kreitzman Adam J AJ Sarthy Jay F JF Ko Minjeong M Brahma Sandipan S Meers Michael P MP Janssens Derek H DH Ang Lisa S LS Coleman Ilsa M IM Bose Arnab A Dumpit Ruth F RF Lucas Jared M JM Nunez Talina A TA Nguyen Holly M HM McClure Heather M HM Pritchard Colin C CC Schweizer Michael T MT Morrissey Colm C Choudhury Atish D AD Baca Sylvan C SC Berchuck Jacob E JE Freedman Matthew L ML Ahmad Kami K Haffner Michael C MC Montgomery R Bruce RB Corey Eva E Henikoff Steven S Nelson Peter S PS Ha Gavin G

Cancer discovery 20230301 3

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 transcripti ...[more]

PMID: 36399432

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Project description:BackgroundTreatment response biomarkers are urgently needed for castration-resistant prostate cancer (CRPC). Baseline and post-treatment circulating tumor cell (CTC) counts of ≥5 cells/7.5ml are associated with poor CRPC outcome.ObjectiveTo determine the value of a ≥30% CTC decline as a treatment response indicator.Design, setting, and participantsWe identified patients with a baseline CTC count ≥5 cells/7.5ml and evaluable post-treatment CTC counts in two prospective trials.InterventionPatients were treated in the COU-AA-301 (abiraterone after chemotherapy) and IMMC-38 (chemotherapy) trials.Outcome measures and statistical analysisThe association between a ≥30% CTC decline after treatment and survival was evaluated using univariable and multivariable Cox regression models at three landmark time points (4, 8, and 12 wk). Model performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC) and c-indices.ResultsOverall 486 patients (122 in IMMC-38 and 364 in COU-AA-301) had a CTC count ≥5 cells/7.5ml at baseline, with 440, 380, and 351 patients evaluable at 4, 8, and 12 wk, respectively. A 30% CTC decline was associated with increased survival at 4 wk (hazard ratio [HR] 0.45, 95% confidence interval [CI] 0.36-0.56; p<0.001), 8 wk (HR 0.41, 95% CI 0.33-0.53; p<0.001), and 12 wk (HR 0.39, 95% CI 0.3-0.5; p<0.001) in univariable and multivariable analyses. Stable CTC count (<30% fall or <30% increase) was not associated with a survival benefit when compared with increased CTC count. The association between a 30% CTC decline after treatment and survival was independent of baseline CTC count. CTC declines significantly improved the AUC at all time-points. Finally, in the COU-AA-301 trial, patients with CTC ≥5 cells/7.5ml and a 30% CTC decline had similar overall survival in both arms.ConclusionsA 30% CTC decline after treatment from an initial count ≥5 cells/7.5ml is independently associated with CRPC overall survival following abiraterone and chemotherapy, improving the performance of a multivariable model as early as 4 wk after treatment. This potential surrogate must now be prospectively evaluated.Patient summaryCirculating tumor cells (CTCs) are cancer cells that can be detected in the blood of prostate cancer patients. We analyzed changes in CTCs after treatment with abiraterone and chemotherapy in two large clinical trials, and found that patients who have a decline in CTC count have a better survival outcome.

Project description:BackgroundSomatic alterations in circulating tumor DNA (ctDNA) may be associated with treatment response or prognosis in prostate cancer (PCa). The goal was to characterize androgen receptor gene (AR) amplifications and mutations detected in ctDNA from patients with PCa and to further understand the somatic genetic heterogeneity of advanced prostate cancer.Patients and methodsThis study included a heterogeneous group of 892 patients with advanced PCa (predominantly castrate-resistant prostate cancer) with AR alterations detected in ctDNA that underwent next-generation sequencing of 54 to 73 genes via Guardant360 testing (Guardant Health, Inc., Redwood City, CA). Distribution and summary of AR alterations detected, the association of AR alterations with other genes, and a pathway analysis are reported.ResultsThe median absolute plasma copy number of AR amplifications was 3.3 (range, 1.2-165.2). Many patients had multiple AR mutations; a total of 112 unique mutations were identified in AR, including L702H (25%), T878A (14%), H875Y (11%), W742C (8%), W742L (4%), F877L (2%), and T878S (2%). Other ctDNA gene alterations in the Guardant assays included TP53 (50%), MYC (34%), BRAF (32%), PIK3CA (29%), MET (25%), CDK6 (26%), EGFR (24%), FGFR1 (21%), and APC (12%). Many of these non-AR alterations are not tissue verified in other studies. AR amplification cosegregated with alterations in MYC (p < .001), BRAF (p < .001), PIK3CA (p < .001), MET (p < .001), CDK6 (p < .001), EGFR (p < .001), FGFR1 (p = .391), and more. Alterations in APC were significantly associated with mutations in AR (p < .001).ConclusionSeveral AR alterations and concomitant non-AR alterations that associate with drug resistance were detected. These findings provide additional insights into the heterogeneity of advanced prostate cancer.Implications for practiceThe goal was to characterize androgen receptor gene (AR) amplifications and mutations detected in circulating tumor DNA (ctDNA) from patients with prostate cancer in relation to non-AR gene alterations detected in the ctDNA landscape. The study included 892 patients with prostate cancer with AR alterations in ctDNA. AR alterations were significantly associated with other gene alterations detected in ctDNA. The common AR mutations found are linked to resistance to abiraterone, enzalutamide, or bicalutamide. Characterization of the circulating AR landscape and gene alterations provides potential additional insight into the somatic genetic heterogeneity of advanced prostate cancer.

Dataset Information

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

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Publications

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

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