S831 CPI‐0610, A BROMODOMAIN AND EXTRATERMINAL DOMAIN (BET) INHIBITOR, REDUCES PRO‐INFLAMMATORY CYTOKINES, BONE MARROW FIBROSIS AND THE NUMBER OF TRANSFUSIONS IN MYELOFIBROSIS PATIENTS
Notice bibliographique
Résumé
Background: Myelofibrosis (MF) is a myeloproliferative neoplasm associated with a cytokine (CK) milieu that leads to bone marrow (BM) fibrosis. Ruxolitinib (RUX) is the only approved therapy for MF, but patients (pts) can eventually relapse/have inadequate response. RUX can also worsen anemia and pts may require transfusions. BET proteins are transcriptional regulators that control key oncogenic pathways, including NF‐κB, MYC, and BCL2 and TGFβ signaling, an important driver of fibrosis. Preclinical studies suggest that a combination of a BET inhibitor (BETi) and RUX results in a synergistic reduction of the hallmarks of MF: splenomegaly, BM fibrosis and the mutant (MUT) allele burden (Kleppe 2018). CPI‐0610 is a selective and potent BETi that impacts megakaryocyte differentiation (unpublished data), cells responsible for pro‐inflammatory CK production and is currently being evaluated in MF, alone or in combination with RUX in a clinical trial with 3 arms: CPI‐0610 alone (Arm 1), CPI‐0610+RUX in pts exposed to RUX/with an inadequate response to RUX (Arm 2), or CPI‐0610+RUX in JAKi naïve pts with anemia (Arm 3). Arm 1 and 2 are stratified between transfusion dependence (TD) and splenomegaly at baseline. Aims: Phase 2 study to assess CPI‐0610 alone or “add‐on” to RUX in MF pts. Primary endpoints: conversion of TD to transfusion independence (TI), spleen volume response, patient reported outcomes, safety and PK. Additional endpoints include: changes in pro‐inflammatory CK levels, BM fibrosis and MUT profiling. Methods: Pt samples were used to analyze CK levels, MUT profiles and BM fibrosis. CK analyses utilized Myriad‐RBM InflammationMAP and CustomMAP and MUT analysis utilized the Rapid Heme Panel (Kluk, 2016). Results: 23 pts were accrued to this multi‐center study, with 18 pts analyzed: MUT profiles which revealed the following MUT: 11 ASXL1 (61%), 10 JAK2 (56%), 6 CALR (33%) and 2 MPL (11%). 10 pts (56%) had at least 3 MUTs and 17 pts (94%) had at least one driver MUT ( JAK2 , CALR or MPL) . 1 pt (6%) was triple negative and 12 pts (67%) had a high MUT profile (HMR). Baseline CK levels were elevated, in pts who failed/inadequate response to RUX. CPI‐0610 at a starting dose of 125 mg QD (days 1–14 of 21‐day cycle) reduced CK levels in both monotherapy and combination arms. Suppression of IL‐18 was observed in all pts analyzed (n = 8) with >50% decrease in 4/8 pts. Trends were also observed for a number of other CK, including IL‐8 and CRP. CK inhibition was sustained over multiple cycles of CPI‐0610 (combination/monotherapy). Best spleen volume reduction ranged from 6–44% in 10 pts. Out of the 4 pts with BM assessments (pre and at least 1 post), 2 were TD at baseline. Three pts had one grade improvement in BM fibrosis (1 at 6 mth, 2 at 1 yr) and had Hgb increases of ≥1.5 g/dL for ≥12 weeks without transfusions. The other pt had a 1 grade improvement in the BM reticulin score (at 6 mth). Moreover, both of the TD pts became TI. Hepcidin levels and PK will be presented. The most common adverse events were Grade 1/2 diarrhea, nausea/vomiting and reversible and non‐cumulative thrombocytopenia. Summary/Conclusion: CPI‐0610 alone or in combination with Rux demonstrates encouraging clinical activity (spleen responses, conversion to TI and improvement in BM fibrosis) with good tolerability. Assessment of CK levels suggest that CPI‐0610 therapy durably reduces pro‐inflammatory CK. Notably, levels of individual CK were reduced to levels observed in normal healthy donors and were maintained during treatment. Genomic profiling data shows that majority of pts had HMR MUT at baseline. Updated data will be presented. image
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 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) | 0,001 | 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 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 ».