Preliminary results of 3D telomeres profiling for myeloma MRD and evaluation of concordance between blood and marrow.
Notice bibliographique
Résumé
e19560 Background: Recent meta-analyses have demonstrated the importance of minimal residual disease (MRD) as a prognostic factor in multiple myeloma (MM). As a result, the FDA has approved MRD as an accelerated end point in clinical trials of MM. Current MRD technologies recognized by the International Myeloma Working Group include next generation sequencing and next generation flow cytometry. These technologies are focused on detection and enumeration of MRD. Each of these technologies has its technical limitations that prevent its broader applicability to all MM patients. Furthermore, these technologies are predominantly applicable to bone marrow specimens, which compromises the ability to monitor patients repeatedly over time. Since MM is a patchy disease, sampling of one area of the bone marrow may not detect the true burden of the disease, whereas a blood-based assay may be more representative of the tumor burden. Given the heterogeneity of MM there is a need for technologies that go beyond enumeration to characterize residual MM clones and classify MRD positive cases as aggressive or MGUS-like. Genomic instability (GI) is an accepted sensitive indicator of disease progression in cancer. Telomere dysfunction is an early event in GI. The 3-dimensional (3D) profiling of telomeres was shown to inform on GI and predict disease progression in cancer including hematological disorders. Here we present a comparative analysis of the 3D telomere profiles from blood vs marrow of 8 transplant eligible MM patients enrolled in our MRD clinical trial at baseline. Methods: We developed a technology that allows for enumeration of myeloma MRD cells combined with 3D telomere profiling using the TeloView platform. 3D co-immuno-telomere FISH is conducted on myeloma plasma cells isolated from marrow samples or circulating myeloma plasma cells isolated from blood. MRD enumeration is conducted based on immunophenotyping of the MM plasma cells followed by 3D telomere profiling using TeloView. At least 2 independent samples (from marrow & from blood) were included in the analysis. Statistics was conducted to calculate standard error, standard deviation and co-efficient of variation (CV). Concordance was considered if the CV was less than 20%. Results: The assay was successfully conducted on marrow and blood equally. We report concordance between blood and marrow in 5 out of 6 telomere parameters quantified by TeloView across all 8 patients (>80%), and concordance of all 6 parameters in 6 out of the 8 patients. Conclusions: These results show that at time of diagnosis, the clones in the marrow can be identified in the blood thus allowing for the assessment of GI in the plasma cells which may then predict risk of relapse. As patients will enter MRD negative status, we will demonstrate if this assay compares to the current standard of care assays, and potentially show an assessment of the residual clones in those that remain MRD positive. Clinical trial information: NCT05530096 .
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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 | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».