5-hydroxymethylcytosine as a liquid biopsy biomarker in mCRPC.
Bibliographic record
Abstract
148 Background: 5-hydroxymethylcytosine (5hmC) is an epigenetic modification which regulates gene expression and is associated with active transcription. The optimization of 5hmC sequencing in cell-free DNA (cfDNA) could therefore enable assessment of gene activity through a liquid biopsy. We aimed to investigate the 5hmC landscape of metastatic castration-resistant prostate cancer (mCRPC) and to evaluate the potential of 5hmC modifications in cfDNA as biomarkers of outcome in mCRPC patients. Methods: Genome-wide 5hmC modifications were analyzed with a low-input whole-genome 5hmC sequencing method based on selective chemical labeling in DNA from 93 mCRPC tissue biopsies previously profiled with whole-genome sequencing (WGS), RNA-sequencing and whole-genome bisulfite sequencing (WGBS). In addition, we analyzed 64 cell-free DNA (cfDNA) samples, from men with mCRPC before first-line abiraterone or enzalutamide, with both 5hmC sequencing and a conventional targeted ctDNA panel assessing common genomic alterations. Results: In mCRPC tissue samples, 5hmC enrichment was more strongly associated with gene expression than promoter methylation or copy number. Among cancer hallmark pathways, the androgen response genes had the strongest association between 5hmC and gene expression, suggesting a disease specific marking of gene activation. 5hmC patterns in cfDNA could be used to estimate the circulating tumor DNA fraction (ct-fraction), which was prognostic for overall survival (tertiles of ct-fraction, HR = 1.6 95%CI 1.1-2.3, p = 0.007). Further, 5hmC levels were indicative of gain of oncogene activity (such as AR, MYC, and PIK3CA) and loss of tumor suppressor gene activity (such as RB1, TP53 and BRCA2). The number of alterations, by 5hmC levels, of common drivers of mCRPC was prognostic for overall survival, also after adjusting for ct-fraction (adjusted p = 0.00001), and the prognostic value of common alterations detected by 5hmC sequencing versus conventional targeted ctDNA sequencing was similar. Finally, 5hmC levels in cfDNA of genes not significantly altered by copy number gain or loss (and thus not routinely included in targeted ctDNA sequencing assays), such as TOP2A and EZH2, identified a high-risk subgroup of mCRPC, which was highly prognostic for overall survival independent of ct-fraction (adjusted HR = 1.8 95%CI 1.2-2.8, p = 0.007). Conclusions: 5hmC in mCRPC tissue demonstrated an association with gene expression that was highest for prostate cancer driver genes, highlighting the ability to track disease-specific biology. 5hmC in cfDNA from men with mCRPC can be used to estimate the ct-fraction of the sample, infer activity gain and loss of common drivers of mCRPC, and identify high-risk groups of mCRPC based on alterations not commonly detected with conventional ctDNA sequencing, showing its potential as a liquid biomarker. Further studies are aimed at optimizing and validating 5hmC-based biomarkers in larger cohorts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".