Chromosome 9p24.1/PD-L1/PD-L2Alterations and PD-L1 Expression and Treatment Outcomes in Patients with Classical Hodgkin Lymphoma Treated with Nivolumab (PD-1 Blockade)
Notice bibliographique
Résumé
Abstract Classical Hodgkin lymphomas (cHLs) include infrequent malignant Hodgkin Reed-Sternberg (HRS) cells within an extensive but ineffective inflammatory/immune cell infiltrate. HRS cells exhibit frequent copy number alterations (CNAs) of 9p24.1/CD274 (PD-L1)/PDCD1LG2(PD-L2), ranging from low-level polysomy to relative copy gain and high-level amplification, all associated with increased expression of programmed death receptor-1 (PD-1) ligands on the tumor cell. PD-1 ligands engage the PD-1 receptor on T cells, inhibiting T cell activation and anti-tumor immune responses. cHL patients (pts) with the highest-level 9p24.1 alterations, PD-L1/PD-L2 amplification, have inferior progression-free survival (PFS) after standard primary chemotherapy (Roemer et al. J Clin Oncol 2016). Given the demonstrated responsiveness of cHL to PD-1 blockade, we examined the prevalence and type of 9p24.1 genetic alterations, PD-L1 expression, and association of these alterations with clinical outcome in pts receiving nivolumab (nivo; anti-PD-1) for relapsed/refractory (R/R) cHL. CheckMate205 is a multicenter, multicohort, phase 2 trial of nivo in R/R cHL. This analysis focused on 2 cohorts: pts with recurrent cHL following autologous stem cell transplantation (ASCT) and subsequent brentuximab vedotin (BV) (cohort B), and pts with R/R cHL following ASCT and BV given pre- or post-ASCT (cohort C). Pts received nivo 3 mg/kg every 2 weeks. Best overall response (BOR) and PFS were assessed by an independent radiological review committee (IRRC). In pts with available tumor biopsies, 9p24.1 genetic alterations were evaluated via fluorescence in situ hybridization (FISH) assay; probes encompassed CD274 (PD-L1, red) or PDCD1LG2 (PD-L2, green)and included a centromeric control (aqua).Dual immunohistochemical staining of PD-L1/PAX5 was performed to delineate PD-L1 expression in PAX5dim+ HRS cells and PAX5- cells in the tumor microenvironment. A modified PD-L1 H-score (range 0-300) was calculated by multiplying the percentage of PAX5+ (malignant) or PAX5- (non-malignant) cells with positive staining (0-100%) and the average intensity of positive staining (1-3+; ≥50 RS cells counted). All p-values are nominal. 96 pts had evaluable baseline tumor biopsy specimens; all 96 had detectable 9p24.1 alterations: polysomy in 10/96 (10%), copy gain in 56/96 (58%), amplification in 28/96 (29%), and presumptive rearrangement (split-apart FISH signal) in 2/96 (2%) (Figure). There was a significant association between PD-L1 protein expression (H-score) and the level of 9p24.1 alterations in HRS cells (p=0.002) (Figure). We next evaluated the association between BOR and defined 9p24.1 alterations and PD-L1 H-scores. The level of 9p24.1 CNAs was significantly associated with BOR (p=0.01); no pts with progressive disease (PD) had genomic amplification and no pts with complete response (CR) had polysomy. Similarly, there was significant association between PD-L1 H-score in HRS cells and BOR (p=0.02); all pts with PD had PD-L1 H-scores in quartiles (Q) 1/2, whereas most pts with CR had PD-L1 H-scores in Q4. We also assessed the association of PFS with 9p24.1 status and PD-L1 H-scores. The level of 9p24.1 alterations was associated with PFS; pts with 9p24.1 amplification had the most favorable PFS with nivo. HRS cell PD-L1 H-score (by quartiles) was also significantly associated with PFS (p=0.048), as pts with PD-L1 H-scores in Q1/Q2 had significantly shorter PFS than those with scores in Q3/Q4 (p=0.01). In contrast, there was no association between PD-L1 expression on non-malignant cells in the tumor microenvironment and PFS (p=0.43). In conclusion, all evaluable pts in this study had genetic alterations of 9p24.1/PD-L1/PD-L2 and copy number-dependent increased expression of PD-L1 in HRS cells. Although high-level alterations of 9p24.1 and increased PD-L1 expression were previously linked with inferior response to standard primary chemotherapy, we now associate these parameters with more favorable outcomes to targeted PD-1 blockade. These analyses also highlight the importance of quantifying and delineating PD-L1 expression in HRS cells and non-malignant cells in the tumor microenvironment in cHL biopsy evaluation. While further research is needed to guide possible use in clinical practice, these data advance understanding of 9p24.1 alterations and PD-L1 expression as prognostic biomarkers in cHL. Disclosures Engert: Takeda, BMS: Consultancy, Honoraria, Research Funding. Zinzani:Abbvie: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Celegene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Timmerman:Bristol-Myers Squibb, Kite Pharma, Valor Biopharmaceuticals, Janssen: Research Funding; Seattle Genetics, Genmab, Celgene: Consultancy, Honoraria. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding. Armand:Bristol-Myers Squibb: Consultancy, Research Funding; Pfizer: Research Funding; Sequenta Inc: Research Funding; Roche: Research Funding; Merck: Consultancy, Research Funding; Infinity Pharmaceuticals: Consultancy. Kuruvilla:BMS: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Amgen: Honoraria; Celgene: Consultancy, Honoraria; Merck: Honoraria; Roche Canada: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Lundbeck: Honoraria. Cohen:Bristol-Myers Squibb: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Collins:Takeda: Consultancy, Honoraria, Speakers Bureau. Trneny:Roche, Celgene, Takeda, Janssen, Gilead, Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche, Celgene: Research Funding. Farsaci:Bristol-Myers Squibb: Employment. Kato:Bristol-Myers Squibb: Employment. Sumbul:Bristol-Myers Squibb: Employment. Rodig:Bristol-Myers Squibb: Honoraria, Research Funding; Perkin Elmer: Membership on an entity's Board of Directors or advisory committees. Shipp:Bayer: Research Funding; Merck, Gilead, Takeda: Other: Scientific Advisory Board; Cell Signaling: Honoraria; Bristol-Myers Squibb: Consultancy, 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 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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 |
| 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 ».