Novel Single Panel Method for Minimal Residual Disease Detection for Plasma Cells By Flow Cytometry
Notice bibliographique
Résumé
Introduction: Advancement in myeloma therapy has significantly improved outcomes including minimal residual disease (MRD) negativity that may be a surrogate for overall survival. We describe an assay using a single 10-colour panel to detect minimal residual disease (MRD) in plasma cell neoplasms to a level < 10-5. Methodology: Bone marrow aspirate specimens for this MRD assay must be from the first pull of 1.0 to 1.5 mL of bone marrow. A 1 in 10 dilution of the bone marrow is prepared and run on the instrument using a WBC count from the following calculation to determine the volume of specimen to process: For the MRD method, a corrective factor of 4 has been empirically determined to provide a sufficient number of cells to achieve the goal of 10-13 million viable cells during analysis. The required volume of bone marrow is added directly to Versalyse (Beckman Coulter) with 10% bovine serum albumin (BSA) in a bulk RBC lysis step. The cells are incubated for 15 minutes at room temperature while rocking. The cells are centrifuged and the following antibodies are added (Table 1): The cells and surface antibodies are incubated for a total of 20 minutes, specimen is gently vortexed at 10 minutes. Intracellular staining is achieved using the IntraPrep Kit (Beckman Coulter) using our standardized laboratory process. Cells are suspended in approximately 2mL of RPMI 1640 with 10% FCS. The specimen is loaded on to the Navios EX flow cytometer (Beckman Coulter)and data is acquired at approximately 5000 to 10000 events per second. The Navios EX is not capable of collecting more 1 700 000 events at acquisition when all 10 fluorescent detectors are in use plus light scatter detectors, so the specimen is repeatedly reloaded a total of 7 or 8 times. All data files are opened in Kaluza (Beckman Coulter) and merged in to a single file. This large data file is then imported in to the analysis template and analyzed for plasma cells. Analysis: A pilot of 20 specimens from patients with varying plasma cell disorders have been analyzed. Half of these specimens contained populations of monoclonal plasma cells. Ranked in order of smallest to largest (Figure 1): The smallest clone detected at 10x10E-4 is comprised of 1311 events. If a theoretical lower limit of quantitation of 50 events or 5x10E-6 in 10 000 000 total cells analyzed is required, this method will meet this criteria .Notably, all bone marrow specimens of adequate quality (not clotted, non-hemodilute) required less than 1.5mL of bone marrow to achieve > 10 000 000 nucleated cells in the final analysis. Analysis is complex using several dozen plots. Plasma cells are identified using CD38 and CD138. Gated plasma cells are analyzed for the immunophenotype of CD56, CD117, CD27, CD45, CD81 and cytoplasmic light chains simultaneously using n-dimensional radar plots (Figures 2, 3a, 3b): Qualitative results can be calculated from adjusted gates (Table 2): Conclusion: This rapid, high-sensitivity assay for immunophenotypically abnormal and clonal plasma cells requires low volumes of bone marrow. Results are ready in approximately 4 hours which is a distinct advantage and sensitivity can be shown to reach 5 X10-6. Disclosures Foley: Amgen,CelgeneJanssen: Honoraria. Mian:Takeda: Consultancy, Honoraria; Sanofi: Consultancy; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy.
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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,005 |
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 ».