Abstract 1985: 5hmC-sequencing of matched cfDNA and tissue from men with mCRPC is concordant and identifies loss of AR signaling in NEPC and DNPC
Bibliographic record
Abstract
Abstract Purpose: In this study, we aimed to study whether 5-hydroxymethylcytosine sequencing (5hmC-seq) of circulating cell-free DNA (cfDNA) predicts gene expression in tumor tissue and can distinguish tumor subtypes defined in tissue in metastatic castration-resistant prostate cancer (mCRPC). Methods: We performed 5hmC-seq on cfDNA samples from 86 mCRPC patients with matched tumor tissue profiled with 5hmC-seq (N=49) and RNA-sequencing (N=86) and we compared cfDNA 5hmC levels with matched tissue 5hmC levels and tissue gene expression. We developed a 5hmC-seq-based circulating tumor-DNA fraction (ctDNA-fraction) classifier and assessed if gene-level and pathway-level differences between mCRPC subtypes could be detected in cfDNA using a differential 5hmC-analysis adjusting for ctDNA-fraction. Results: Patients with androgen receptor (AR)-positive prostate cancer (ARPC) exhibited lower ctDNA-fraction, whereas patients with neuroendocrine (NE) prostate cancer (NEPC) and double-negative prostate cancer (DNPC) tumors displayed higher ctDNA-fraction (median ctDNA-fraction across subtypes 0.09 [95% confidence interval (CI), 0.04-0.14] (ARPC), 0.41 [95% CI, 0.18-0.64] (NEPC) and 0.37 [95% CI, 0.30-0.44] (DNPC), pairwise t-test P = 5.5 x 10-2 (ARPC vs. NEPC) and P = 8.8 x 10-4 (ARPC vs. DNPC) respectively). Nearly 30% of all protein-coding genes showed significant concordance between cfDNA 5hmC and tissue RNA-seq, after adjusting for ctDNA-fraction (adjusted p<0.05 in linear model), which were enriched in the androgen response, EGFR, and ERBB signaling pathways. Compared to ARPC, NEPC displayed upregulated 5hmC enrichment in NE-related genes, and downregulated androgen response and MYC target pathways in cfDNA. As expected, an NE pathway score calculated from cfDNA 5hmC was significantly different between tissue-confirmed ARPC and NEPC (p=0.03). Double-negative prostate cancer (DNPC) showed downregulated androgen response and MYC targets and upregulated epithelial cell pathways compared to ARPC in cfDNA. Furthermore, DNPC indicated an aggressive phenotype with cell proliferation pathways even more upregulated when compared to NEPC. Conclusions: We created a cohort of 86 matched tissue and cfDNA samples and demonstrated concordance for a significant number of transcribed protein-coding genes. Expected biological differences previously seen in tissue between NEPC and ARPC were readily detected via 5hmC profiles in cfDNA. Furthermore, DNPC showed a clear downregulation of androgen response signaling in cfDNA, indicating the possibility to identify a group of patients in addition to classical NEPC that may have reduced response to standard androgen-targeting agents. Future work will aim to develop single-sample multi-class subtype classifiers and evaluate differences in prognosis and treatment response based on cfDNA-based subtyping. Citation Format: Rensheng Wan, Raunak Shrestha, Gulfem Guler, Yuhong Ning, Aishwarya Subramanian, Adam Foye, Meng Zhang, Xiaolin Zhu, Thaidy Moreno-Rodriguez, Haolong Li, Shuang G. Zhao, SU2C/PCF West Coast Prostate Cancer Dream Team, Joshi J. Alumkal, Rahul Aggarwal, Alexander W. Wyatt, David Quigley, Samuel Levy, Eric Small, Felix Feng, Martin Sjöström. 5hmC-sequencing of matched cfDNA and tissue from men with mCRPC is concordant and identifies loss of AR signaling in NEPC and DNPC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1985.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".