Combined assessment of circulating tumor cells (CTCs) and measurable residual disease (MRD) for dynamic risk assessment of patients (Pts) with multiple myeloma (MM)
Notice bibliographique
Résumé
Abstract Background: CTCs and MRD are rare tumor cell populations that respectively disseminate MM and drive relapse after treatment. If its combined assessment improves patients' prognostication, and if CTCs and MRD are genetically related, remains unknown. Aim: Analyze the complementary prognostic value and the genomic profiles of patient-paired CTCs and MRD. Methods: The European CTC consortium is composed of five collaborative groups (Czech Republic, Greece, Italy, HOVON/Netherlands-Belgium, PETHEMA/Spain) that ensembled patient-level data from 2,466 pts with newly diagnosed MM. Of these, 971 had CTC enumeration performed at diagnosis and MRD assessment throughout treatment with EuroFlow (71%) or other flow cytometry methods (29%). Up to 86% of pts were enrolled in clinical trials (GEM-CLARIDEX, CASSIOPEIA, HOVON-143, FORTE, GEM2012MENOS65) while 14% were treated in routine practice (Czech Republic, Greece). Median age was 59 (IQR 52-64); 83% of pts were transplant-eligible and 17% ineligible. Induction treatment included doublet (13%), triplet (77%) and quadruplet (9%) regimens. Progression-free (PFS) was landmarked at the time of MRD assessment. Median follow up was 6 years. Genomic data from tripartite bone marrow (BM) tumor cells and CTCs at diagnosis plus MRD at different time points of treatment was available in 29 MM pts enrolled in the GEM2012MENOS65 and GEM-CLARIDEX clinical trials. BM tumor cells at relapse were available in 3 of the 29 pts. All tumor cell populations were isolated based on patient-specific aberrant phenotypes by FACS. Whole exome sequencing was performed in 144 samples including peripheral blood T cells as germline control. Results: Overall, 641 of the 971 (66%) pts in the European pooled analysis achieved MRD negativity, whereas 330 (34%) remained MRD positive. Median PFS of MRD positive pts was gradually inferior in those with <0.001%, 0.001–0.01%, 0.01–0.1%, 0.1–1% and ≥1% CTCs at diagnosis (65, 38, 29, 30 and 16 months, respectively, p=.001). Of note, these inferior outcomes were not because of progressively higher MRD levels since the respective percentages were 0.01%, 0.02%, 0.04%, 0.01% and 0.01%. MRD negative rates were 76%, 58%, 67%, 61% and 63% in pts with <0.001%, 0.001–0.01%, 0.01–0.1%, 0.1–1% and ≥1% CTCs at diagnosis. Median PFS of MRD negative pts was gradually inferior in those with <0.001%, 0.001–0.01%, 0.01–0.1%, 0.1–1% and ≥1% CTCs: not reached, not reached, 85, 72 and 76 months (p<.001). The most significant differences in PFS were observed when MRD negative pts were stratified according to <0.01% vs ≥0.01% CTCs at diagnosis (median not reached vs 81 months, p<.001). In multivariate analysis of PFS adjusted for transplant-eligibility, induction regimen, R-ISS and 1q gain/amplification, CTC log levels and MRD status showed independent prognostic value. The hazard ratio (HR) of progression and/or death was 1.4 (95% CI 1 – 2, p=.03) in pts with 0.01–0.1% CTCs, 1.8 (95% CI 1.2 – 2.6, p=.003) if 0.1–1% CTCs, and 2.3 (95% CI 1.4 – 3.6, p=.001) if ≥1% CTCs at diagnosis. The HR of progression and/or death in pts with positive MRD was 2.9 (95% CI 2.3 – 3.7, p<.001). Genomic profiles of tripartite BM tumor cells, CTCs and MRD from 29 MM pts uncovered that 36% of single-nucleotide and copy number variants were concordant between CTCs and MRD cells. The Jaccard index of similarity was the lowest between CTCs and MRD (0.36) when compared to the indexes between BM tumor cells at diagnosis and MRD (0.40), or between BM tumor cells and CTCs at diagnosis (0.45). Individual-patient-level observations suggested progressive genomic diversity between CTCs and MRD cells prior to relapse. For example, one patient exhibited mutations in BRAF and DIS3 and del(13q) at diagnosis in BM tumor cells and CTCs, which persisted in MRD. After induction, de novo mutations in NEK11 and SLAMF7 emerged, followed by the appearance of subclonal copy number variants after HDT/ASCT contributing to resistance. Conclusions: While achieving MRD negativity was paramount to ameliorate the poor prognosis of pts with high CTCs, their PFS was not superimposable to those with low CTCs. These results support the integration of CTC levels at diagnosis in clinical-decision making about treatment adaptation in MRD negative pts. Genomic profiles of CTCs and MRD cells show considerable divergency. These results may help explaining why the assessment of CTCs and MRD is independently associated with clinical outcomes.
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 | 0,001 | 0,002 |
| 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 | 0,001 | 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 ».