Abstract PR03: Genome-wide 5-hydroxymethylcytosine profiles in circulating cell-free DNA and survival in patients with multiple myeloma
Notice bibliographique
Résumé
Abstract Background: Biomarkers currently used for prognostic stratification or predicting survival in patients with newly diagnosed multiple myeloma (MM) either lack good sensitivity and specificity or require invasive bone marrow biopsies. Aberrant DNA methylation has been associated with poor prognosis and survival in MM. We recently identified a gene panel modified with 5-hydroxymethylcotosine (5hmC), a mark of gene activation, in circulating cell-free DNA (cfDNA) that is associated with relapse or death in patients with diffuse large B-cell lymphoma, another lymphoproliferative disorder. To date, no study has investigated 5hmC in cfDNA for its prognostic significance in MM. Methods: Starting in 2010, we prospectively enrolled patients who were newly diagnosed with MM at The University of Chicago Medical Center. Blood samples were collected at the time of diagnosis. The current report includes data from 184 MM patients. Mortality was ascertained using medical records and the National Death Index. Follow-up was through December 2017, with an average follow-up length of 41.64 months (deceased, n=31; alive, n=153). We profiled genome-wide 5hmC in cfDNA by first using the nano-hmC-Seal technique to construct DNA libraries, which were subjected to next-generation sequencing, mapped to the human genome, and annotated to ~22,000 gene bodies. Cox proportional hazards model and the elastic net regularization, controlling for age, gender, and population, were used to detect 5hmC marker genes associated with overall survival (OS) after diagnosis. Results: For the 184 patients, median age at diagnosis was 61.7 years and 48% (n=88) were males. The differential 5hmC enrichment levels of a preliminary eight-gene marker panel were used to compute a weighted prognostic score (wp-score). In multivariate Cox models, patients with high wp-score had worse OS (Hazard Ratio [HR] = 8.2; 95% Confidence Interval [CI], 2.9-23.4, p < 0.0001), compared with those in the low risk group. Some of the eight 5hmC-midified marker genes have been previously implicated in MM survival. For example, GTF2I (encoding general transcription factor IIi), a known prosurvival gene in MM, showed a single-gene HR of 0.3 (95% CI, 0.1-0.7, p=0.002). The 5hmC-based wp-score outperformed (sensitivity=0.74, specificity=0.84) standard prognostic indices (e.g., albumin, beta-2 microglobulin, and risk classification by cytogenetics) in predicting patients at risk for inferior survival. We are validating the gene panel in an independent cohort of ~150 MM patients. The results will be presented. Conclusions: These findings suggest that 5hmC in cfDNA at the time of diagnosis correlate with OS and outperform standard clinical prognostic indices. Our novel findings, if confirmed, suggest that a plasma-derived cfDNA 5hmC-modified gene panel holds promise as a noninvasive approach for predicting prognosis in MM and may be integrated in clinical practice to improve precision care of MM. This abstract is also being presented as Poster A40. Citation Format: Brian C.-H. Chiu, Zhou Zhang, Jason Karpus, Benjamin Derman, Chang Zeng, Elizabeth Stepniak, Rudy Chiu, John Spinelli, Andrzej Jakubowiak, Chuan He, Wei Zhang. Genome-wide 5-hydroxymethylcytosine profiles in circulating cell-free DNA and survival in patients with multiple myeloma [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR03.
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 | 0,000 | 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 ».