Diagnostic Evaluation of t[4;14] in Multiple Myeloma.
Notice bibliographique
Résumé
Abstract The t[4;14] simultaneously deregulates fibroblast growth factor receptor 3 (FGFR3) and MMSET in 15% of patients (pts) with Multiple Myeloma (MM). Although oncogenic, FGFR3 expression is lost in ~25% of t[4;14] pts on gene expression profiling while MMSET is always retained. The t[4;14] is highly associated with poor prognosis, furthermore FGFR3 kinase inhibitors are in Phase I trials, thus detection of t[4;14] pts is increasingly important. The Multiple Myeloma Research Consortium (MMRC) therefore evaluated 4 competing methodologies for the diagnostic detection of t[4;14]. Bone marrow (BM) samples were collected in uniform fashion from 85 pts. FGFR3 immunocytochemistry (ICC) and flow cytometry (FC) were performed at the retrieval site, while split samples were shipped to the MMRC tissue bank and processed under GLP conditions. Processed samples were analyzed by cIg-FISH and quantitative IgH-MMSET RT-PCR (QPCR) on unsorted BM and blood. Of 60 samples with sufficient plasma cells for analysis, 8 were FISH +ve [13.3%]. Low % BM plasma cells prevented successful FISH in 25% of samples reflecting large volume harvests and hemodilution. Analysis was conducted in a blinded fashion. With FISH as the gold standard for detection of t[4;14] the sensitivity and specificity of the other diagnostic tests are: BM QPCR is most sensitive (7 of 8 FISH positive detected) and specific (42/43 negatives correctly identified). QPCR on peripheral blood is ongoing. FC is more sensitive to the detection of FGFR3 protein than ICC. Correlation between FC and ICC was only 0.46. Interestingly, 6 of 7 evaluable pts here and 13/14 (92%) in an expanded analysis of FISH +ve patients also expressed the FGFR3 protein. Given the discrepancy between this finding and previously reported loss of FGFR3 expression in 25% of pts we further explored t[4;14] stability. Clonal selection/heterogeneity was determined by the % plasma cells in each pt. with an unbalanced translocation (loss of one der chromosome). In 42 t[4;14] pts, 13 (31%) had a balanced translocation(>75% of cells with a double fusion), 14 (33%) had an unbalanced translocation (>75% cells with only one signal), and 15 (36%) had a chimeric picture. This heterogeneous pattern is suggestive of an evolution towards an unbalanced translocation. Despite this survival did not differ between pts with balanced or unbalanced translocation. Conclusions: These results indicate that the t[4;14] is highly heterogeneous with respect to balanced versus unbalanced translocations, which likely evolve over time. For detection, cIg-FISH continues to be the gold standard diagnostic methodology but may be limited by low plasma cell numbers in dilute BM or during MM remission. QPCR and FC appear most sensitive and specific for presence of t[4;14] and FGFR3 protein expression respectively. Surprisingly (given prior evidence of loss of FGFR3 expression in 25% of pts) 92% of t[4;14] pts in this series expressed FGFR3 protein. # Analyzed % Positive Sensitivity Specificity FISH 60 13 - - QPCR 65 14 87.5 97.6 Flow 82 15 85.7 91 ICC 85 15 62.5 92
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 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| 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 ».