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Enregistrement W2555574679 · doi:10.1182/blood.v114.22.2923.2923

The Percentage of Cytotoxic T-Cells in Mantle Cell Lymphoma (MCL) Biopsies Predicts Response to Rituximab.

2009· article· en· W2555574679 sur OpenAlexaffabout
Stephen Opat, Pedro Farinha, Merrill Boyle, Nathalie A. Johnson, Hilary M O'Leary, James R. Cook, Raymond R. Tubbs, Lin Wang, Ryan Woods, Joseph M. Connors, Randy D. Gascoyne

Notice bibliographique

RevueBlood · 2009
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésMantle cell lymphomaFollicular lymphomaMedicineLymphomaRituximabBiopsyPathologyBone marrowCyclin D1SurvivinCD8Gene signatureImmunophenotypingCancer researchBiologyInternal medicineImmunologyFlow cytometryCancerCell cycleGene expressionImmune system

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 2923 Poster Board II-899 Background: MCL is characterized by the presence of the t(11;14) translocation that juxtaposes the cyclin D1 gene downstream of the immunoglobulin heavy-chain gene promoter resulting in enhanced G1μS phase transition leading to cellular proliferation. Despite the common genetic lesion, patients exhibit considerable heterogeneity in their clinical behavior and response to therapy. The clinical significance of the microenvironment in follicular lymphoma has been highlighted by gene expression studies demonstrating that a T-cell response signature correlates with a superior outcome compared to that seen with a macrophage signature. In contrast, the significance of the non-malignant cellular component in MCL biopsies remains unknown. We report the results of a retrospective study examining flow cytometry (FCM) of MCL diagnostic tissue biopsies, focusing on the non-malignant lymphoid cells. Method: Patients were included in the study if they had MCL diagnosed according to the 2008 WHO criteria, had FCM performed on their diagnostic nodal or tissue biopsy and had adequate clinical information that included baseline clinical characteristics, treatment regimens and clinical outcome. Patients were excluded if they were too frail to receive chemotherapy or if FCM was only performed on peripheral blood or bone marrow. 122 patients met the criteria for inclusion in the study; of which 56 were also assessable by tissue microarray (TMA). FCM data were re-analyzed for expression of CD3, CD4, CD8, CD19, CD20 and kappa and lambda light chains on cells gating on lymphoid populations. Estimates of the non-neoplastic B-cells were derived from total CD19/CD20 positive B cells excluding the light chain restricted population. ‘High' and ‘low' expressers for each marker were determined by examining frequency histograms for a trough. TMAs were prepared from diagnostic paraffin-embedded blocks according to established protocols. Sections were immunostained for CD3, CD4, CD8, CD68, CD34, TIA-1, CD163, FOXP3, PD-1, CD57, CD21, P53 and Ki67. Survival correlates were assessed by Cox regression using SPSS. Results: The median age was 67 y (range 22-94) with 69% being male. 88% had advanced-stage disease with 16% having a high IPI (4/5). 50 (41%) patients received rituximab as part of initial or subsequent therapy. Primary and secondary treatment regimens included: observation (19); single agent alkylators (33); CHOP-like with rituximab (39); CHOP-like without rituximab (32); CVP-like (11); higher intensity regimens (9); fludarabine-based (19); gemcitabine-based (9); bortezimib (4); flavopiridol (2); autologous stem cell transplant (12); allogeneic stem cell transplant (2); radiation (45); and therapeutic splenectomy (6). The median follow up of the living patients was 30 months. The 5-y OS for the group was 21%. FCM median tumor content was high at 84% (range 21-100%) with median CD3, CD4, CD8 and non-tumor CD20 populations of 12%, 7%, 4% and 1%, respectively. Univariate analysis revealed CD8<8% (p=0.009), IPI (p<0.001) and rituximab therapy (p<0.001) as predictive of favorable OS while Cox regression analysis identified only IPI (p<0.001) and rituximab therapy (p<0.001) to be independent predictors of OS. Restricting analysis to those who received rituximab revealed a survival advantage for patients with <8% CD8+ T cells in their biopsies which was independent of the IPI (5-y OS with CD8<8% (37) 49%; CD8≥8% (13) 0%, p=0.023). The number of CD3, CD4 and the non-neoplastic B cells did not appear to significantly predict survival. TMA analysis confirmed the adverse impact of elevated CD8+ lymphocytes (<1% versus ≥1%) in patients who received rituximab (p=0.004) and suggested that many CD8 cells were cytotoxic with increased TIA-1+ expression predicting an inferior outcome (p=0.009). Ki-67 expression >35% was also adversely associated with OS (p=0.028). Conclusion: While the non-neoplastic cellular infiltrate often constitutes only a minor fraction of the tumor mass in MCL, it appears to significantly influence response to rituximab therapy. Further studies are required to validate this observation prospectively and define the mechanism by which the cytotoxic T-cells exert their influence. Disclosures: Connors: Roche Canada: Research Funding. Gascoyne:Roche Canada, Genentech, Lilly, Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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.

Tête enseignante Opus0,008
Tête enseignante GPT0,236
Écart entre enseignants0,228 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2009
Routes d'admission2
Résumé présentoui

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