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Enregistrement W3097378247 · doi:10.1182/blood-2020-136922

Molecular Characterization of Clinical Response and Relapse in Patients with <i>IDH1</i>-Mutant Newly Diagnosed Acute Myeloid Leukemia Treated with Ivosidenib and Azacitidine

2020· article· en· W3097378247 sur OpenAlexaff
Scott R. Daigle, Sung Choe, Courtney D. DiNardo, Anthony S. Stein, Eytan M. Stein, Amir T. Fathi, Olga Frankfurt, Andre C. Schuh, Hartmut Döhner, Giovanni Martinelli, Prapti A. Patel, Emmanuel Raffoux, Peter Tan, Amer M. Zeidan, Stéphane de Botton, Richard M. Stone, Mark G. Frattini, Aleksandra Franovic, Emily Xu, Thomas Winkler, Bin Wu, Paresh Vyas

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMyeloid leukemiaInternal medicineIDH1AzacitidineGastroenterologyIsocitrate dehydrogenaseMyeloidRefractory (planetary science)OncologyBiologyMutant

Résumé

récupéré en direct d'OpenAlex

Background: Acute myeloid leukemia (AML), a hematologic malignancy characterized by clonal expansion of abnormal myeloid progenitors, is a disease exhibiting a dynamic mutational landscape over time. Somatic mutations in isocitrate dehydrogenase 1 (IDH1) are reported in 6-10% of patients (pts) with AML. Ivosidenib (IVO) is an oral, potent, targeted inhibitor of mutant IDH1 (mIDH1) and is FDA-approved for the treatment of mIDH1 relapsed/refractory (R/R) AML and newly diagnosed (ND) AML in adults ≥ 75 years (yrs) of age or with comorbidities precluding intensive induction chemotherapy (IC). In an ongoing phase 1b study (NCT02677922), 23 pts (11 male; median age 76 yrs [range 61-88]) with mIDH1 ND AML received IVO 500 mg daily and subcutaneous azacitidine (AZA) 75 mg/m2 on Days 1-7 in 28-day cycles. As of 19Feb2019, median number of treatment cycles was 15 (range 1-30); 10 pts remained on treatment. Overall response rate (complete remission [CR] + CRi [incomplete neutrophil recovery] + CRp [incomplete platelet recovery] + morphologic leukemia-free state [MLFS]) was 78% (18/23): including CR in 61% (14/23) and CR with partial hematologic recovery (CRh) in 9% (2/23). mIDH1 clearance assessed in bone marrow mononuclear cells (BMMCs) by BEAMing digital PCR (detection limit 0.02-0.04%) was observed in 11/16 pts (69%) with CR/CRh, including 10/14 (71%) with CR. Aim: Characterize clonal evolution and resistance in pts with mIDH1 ND AML treated on study with IVO + AZA. Methods: The secondary efficacy endpoint of CRh was sponsor derived and defined as CR with absolute neutrophil count > 0.5 X 109/L and platelets > 50 X 109/L. Bulk DNA sequencing (DNA-seq, 1400-gene ACE Extended Cancer Panel, 2% variant allele detection limit) was performed on BMMCs and/or peripheral blood mononuclear cells (PBMCs). Single-cell (sc) targeted DNA-seq was performed on PBMCs using a microfluidic platform (Tapestri®) with a 20-gene AML panel capable of detecting rare subclones down to 0.1%. Results: To identify mechanisms of acquired resistance, longitudinal bulk DNA-seq was analyzed for 22/23 pts, including 5 pts with available samples at relapse or disease progression (3 CR and 1 MLFS with morphological relapse; 1 CRh with disease progression). Mutations not detected at baseline but emerging during therapy were categorized into canonical biological pathways (Table). Emerging mutations were observed in 9/22 (41%) pts, including 4 with multiple mutations. 3/22 (14%) pts had emerging IDH2 mutations, with concurrent rise in plasma 2-hydroxyglutarate (2-HG) levels. Within the relapse/progression cases, emerging mutations were observed in 4/5 pts, including 3 where the emerging mutation appeared to be the predominant mutation at relapse/progression (2 CR pts with IDH2 mutations, and 1 CRh pt with a TET2 mutation). To date, from the bulk DNA-seq analysis, no emergence of an IDH1 second-site or receptor tyrosine kinase pathway (FLT3, KRAS, NRAS, PTPN11) mutation has been observed. To further evaluate clonal evolution of clinical response and disease progression, scDNA-seq was performed, with data available for 15 pts (10 CR, 2 CRh, 1 MLFS, and 2 stable disease), including end-of-study time points for 5 relapse/progression pts. In the 2 relapsed pts with an emerging IDH2 mutation observed by bulk DNA-seq, 1 had a minor IDH2 clone present at baseline that expanded independently from IDH1 during therapy (Fig). In a separate case, a subclonal baseline PTPN11 clone evolved to gain both RUNX1 and IDH2 mutations, becoming the predominant clone at relapse. In 2 other cases, scDNA-seq data showed that non-IDH1 clones were selected from baseline clones ancestral (TP53 n = 1) to or emerged separate from mIDH1 (TET2 n = 1). Clonal architecture and evolution from additional pts will be presented. Conclusion: IVO + AZA combination treatment in IC-ineligible ND AML led to deep and durable molecular remissions. Although the dataset is small, IDH2 clones appeared to expand or emerge separate from the IDH1 clone, with no observation of an IDH1 second-site mutation to date. Understanding patterns of emerging mutations/pathways at relapse will allow for comparison with mIDH1 R/R AML and ND AML pts treated with IVO monotherapy. These results underline the importance of mutational testing, particularly at progression to determine optimal salvage therapy. Potential combination or sequential therapies should be evaluated prospectively in future clinical trials. Disclosures Daigle: Agios: Current Employment, Current equity holder in private company. Choe:Agios Pharmaceuticals: Current Employment, Current equity holder in private company. DiNardo:Syros: Honoraria; MedImmune: Honoraria; Notable Labs: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria; Jazz: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria, Research Funding; Novartis: Consultancy; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; ImmuneOnc: Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Calithera: Research Funding. Stein:Stemline: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau. Stein:Astellas Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Agios Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; PTC Therapeutics: 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; Biotheryx: Consultancy; Bayer: Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Syndax: Consultancy, Research Funding; Seattle Genetics: Consultancy; Abbvie: Consultancy; Amgen: Consultancy; Celgene Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Fathi:Amphivena: Consultancy, Honoraria; Agios: Consultancy, Research Funding; Forty Seven: Consultancy; Daiichi Sankyo: Consultancy; Celgene: Consultancy, Research Funding; Astellas: Consultancy; Takeda: Consultancy; PTC Therapeutics: Consultancy; Novartis: Consultancy; NewLink Genetics: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; TrovaGene: Consultancy; Amgen: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Blue Print Oncology: Consultancy; Boston Biomedical: Consultancy; Kura: Consultancy; Pfizer: Consultancy; Seattle Genetics: Consultancy, Research Funding; Trillium: Consultancy; AbbVie: Consultancy. Döhner:Pfizer: Research Funding; Sunesis: Other, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Astex: Consultancy, Honoraria; Jazz: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Arog: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Oxford Biomedicals: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Helsinn: Consultancy, Honoraria; Bristol-Myers Squibb: Research Funding. Martinelli:Celgene: Consultancy, Speakers Bureau; Jazz: Consultancy; Incyte: Consultancy; Pfizer: Consultancy, Research Funding, Speakers Bureau; Daichii Sankyo: Consultancy, Research Funding; Janssen: Consultancy; Amgen: Consultancy; AbbVie: Consultancy, Research Funding; Roche: Consultancy. Patel:France Foundation: Honoraria; DAVA Pharmaceuticals: Honoraria; Celgene: Consultancy, Speakers Bureau; Agios: Consultancy. Tan:AbbVie: Other: Investigator on an AbbVie funded clinical trial; Agios: Research Funding; Janssen: Research Funding; NOHLA Therapeutics: Research Funding; Novartis: Other, Research Funding. Zeidan:Astellas: Consultancy, Honoraria; Taiho: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; BeyondSpring: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria; Ionis: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Trovagene: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Acceleron: Consultancy, Honoraria; Celgene / BMS: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Consultancy, Honoraria; Cardinal Health: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Aprea: Research Funding; MedImmune/Astrazeneca: Research Funding; ADC Therapeutics: Research Funding; Cardiff Oncology: Consultancy, Honoraria, Other; Takeda: Consultancy, Honoraria, Research Funding; Astex: Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Leukemia and Lymphoma Society: Other; CCITLA: Other; Otsuka: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding. De Botton:Forma Therapeutics: Honoraria, Research Funding; Astellas: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Syros: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Agios: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy; Novartis: Consultancy; Pierre Fabre: Consultancy; Janssen: Consultancy, Honoraria; Seattle Genetics: Honoraria; Bayer: Consultancy, Honoraria; Servier: Consultancy. Stone:Syntrix: Consultancy; Macrogenics: Consultancy;

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)0,001
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 enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
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)0,0010,000

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.

Tête enseignante Opus0,012
Tête enseignante GPT0,263
Écart entre enseignants0,251 · 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

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

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