5-hydroxymethylcytosine as a liquid biopsy biomarker in mCRPC.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».