IDENTIFYING MUTATIONS ENRICHED IN RELAPSED‐REFRACTORY DLBCL TO DERIVE GENETIC FACTORS UNDERLYING TREATMENT RESISTANCE
Notice bibliographique
Résumé
Introduction: Diffuse Large B-cell Lymphoma (DLBCL) the most common subtype of Non-Hodgkin Lymphoma and is characterized by genetic and clinical heterogeneity. In relapsed/refractory DLBCL (rrDLBCL) cases, where frontline treatment is unsuccessful, patient prognosis is extremely poor, with 2-year overall survival of 20-40%. While numerous treatments are under investigation to improve patient outcomes, their success has been limited as the genetic mechanisms underpinning treatment resistance are largely unknown. Identifying genomic alterations associated with relapse may open new treatment avenues and allow the stratification of patients into subgroups based upon relevant mutations. Methods: We have collected samples from 134 patients enrolled in three clinical trials (LY17, Obinituzumab-GDP, QCROC2) exploring candidate treatment options for rrDLBCL. For each patient enrolled, blood plasma samples were collected prior to and at several time points following candidate treatment. A combination of exome sequencing and target panel sequencing of lymphoma-associated genes was performed on cell-free DNA extracted from plasma samples and tissue biopsies (where available) obtained upon trial enrollment (relapse). Somatic mutations were identified using Strelka2, and clonal population structure was inferred using PyClone. Mutation prevalence was compared to a large unselected cohort of diagnostic DLBCLs to identify genes enriched for mutations. Results: Patients with rrDLBCL were enriched for mutations in 5 genes; TP53 (Q=6.74x10-5), IL4R (Q=0.00391), HVCN1(Q=0.0729), RB1 (Q=0.0127) and MS4A1 (Q=0.0522), with TP53 mutations previously associated with rrDLBCL. Mutations in IL4Rmay lead to constitutively active JAK/STAT signalling and inferior overall survival in DLBCL. HVCN1 encodes a voltage-gated proton channel which modulates the B-Cell Receptor (BCR), and truncated HVCN1 isoforms have been shown to enhance BCR signaling. MS4A1 encodes CD20, the target of the monoclonal antibody Rituximab, a cornerstone of frontline DLBCL treatment. In several patients, clonal subpopulations with MS4A1 mutations underwent clonal selection following treatment. These mutations are predicted to either truncate CD20, or destabilize a common transmembrane helix, with 4/15 patients containing mutations affecting Tyrosine 86. We also observed recurrent in-frame deletions targeting S1680 of CREBBP, and although CREBBP mutations are associated with treatment resistance in other cancers, the functional effect of this deletion has not been characterized. Conclusions: DLBCL patients with mutations in relapse-enriched genes are at a higher risk of treatment failure. Mutations in these genes, specifically hotspot deletions, may have power as biomarkers to identify patients at a high risk of relapse and could inform on the mechanism of acquired resistance to components of R-CHOP. Keywords: CD20; diffuse large B-cell lymphoma (DLBCL); R-CHOP. Disclosures: Michaud, N: Employment Leadership Position: Epizyme. Daigle, S: Employment Leadership Position: Epizyme.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».