Extended Follow-up and Resistance Mutations in CLL Patients Treated with Acalabrutinib
Notice bibliographique
Résumé
Background: Covalent Bruton tyrosine kinase inhibitor (cBTKi) is a standard treatment for chronic lymphocytic leukemia (CLL). Understanding of acquired resistance to cBTKi therapy has largely come from data on patients (pts) treated with the first-in-class cBTKi ibrutinib. Mutations in BTK C481 and to a lesser extent PLCG2 are frequently detected in ibrutinib-treated pts at the time of progressive disease (PD). In contrast, much less is known about genetic mechanisms of drug resistance in pts treated with next generation cBTKi acalabrutinib and zanubrutinib. A recent study identified 3 pts with BTK C481 mutations and no pts with PLCG2 mutations among 8 acalabrutinib-treated pts with progressive disease (PD) (Black, et al. Blood 2022). A second study found a kinase-dead BTK L528W mutation in 7/13 zanubrutinib-treated pts (Blombery, et al. Blood Adv 2022). Although cBTKi share the same mechanism of action by binding to BTK C481, the latter report discloses differences in clonal selection and underscores the need for further investigation in pts treated with next generation cBTKi. In a phase 2 study of acalabrutinib in pts with treatment naïve (TN) CLL or small lymphocytic lymphoma (SLL) with 17p deletion, or TP53 or NOTCH1 mutation, or relapsed/refractory (R/R) CLL/SLL regardless of cytogenetics or somatic mutations (Sun, et al. Blood 2020), we sought to understand clonal evolution during treatment. Methods: Peripheral blood mononuclear cells (PBMCs) were collected from 48 pts at baseline, after 6 months, then annually on treatment until PD. Current analysis includes 14 PD pts [excluding 3 Richter transformation (RT) pts] comprising 10 R/R and 4 TN CLL pts. Additionally, paired baseline and PD bone marrow (BM) from 6 pts and lymph node (LN) samples from 2 pts were included. Targeted next-generation sequencing of ~700 recurrently mutated genes in hematological malignancies (Collins, et al. Leuk Lymphoma. 2021) was performed using DNA isolated from CD19 + enriched cryopreserved PBMCs and BM aspirates, as well as fresh-frozen core LN biopsies. Filtered variants in putative CLL driver genes (Knisbacher, et al. Nat Genet. 2022) with variant allele frequencies (VAF) ≥1% for BTK and PLCG2, ≥5% for variants with known oncological significance, and ≥7.5% for all other variants were included in downstream analysis. Results: After a median follow-up of 6.5 years (IQR 2.9-6.3), 23/48 (48%) pts developed PD (20 CLL, 3 RT). PD occurred in 17/32 (53%) R/R pts and 6/16 (38%) TN pts. Median progression-free survival was reached at 6.0 years. Best response was complete remission in 2/20 (10%) pts and partial remission in 18/20 (90%) pts with CLL PD. IGHV was unmutated in all but one PD patient. At baseline, 34 CLL driver genes were mutated in 41/45 pts (91%; excluding 3 RT pts) with most mutations in NOTCH1, TP53, ATM, SF3B1, BIRC3, and NFKBIE. During acalabrutinib treatment but before PD, 14/45 pts (31%; 8 R/R and 6 TN) acquired mutations in 11 driver genes, most commonly in BRAF (n=4), CREBBP (n=4), and KMT2D (n=2). At the time of PD, 11/14 pts (79%) had newly acquired mutations in 4 genes, predominantly BTK (n=6) and PLCG2 (n=4). BTK C481 mutations (VAF 2-42%) were detected in 6/14 (43%; 4 R/R and 2 TN) pts and T474I mutation (VAF 4-46%) in 3/14 (21%; 1 R/R and 2 TN) pts. Paired BM samples in 2 pts and LN samples in 2 pts showed the same BTK mutations as PBMCs with similar VAFs. PLCG2 mutations (VAF 1-8%) were found in 4/14 (29%; 2 R/R and 2 TN) pts. BTK C481 co-occurred with BTK T474I in 3 pts, but on different sequencing reads suggesting independent subclones, and with a PLCG2 mutation in 1 pt. There have been no pts with BTK L528 mutations. In conclusion, mutations in BTK and PLCG2 are the predominant resistance mechanism to acalabrutinib. Among BTK mutations, C481 was the most common. All T474I mutations co-occurred with C481.
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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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,000 |
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 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 ».