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Record W2905066790 · doi:10.1182/blood-2018-99-116013

Safety, Efficacy, Pharmacokinetic (PK) and Biomarker Analyses of BCL2 Inhibitor Venetoclax (Ven) Plus MDM2 Inhibitor Idasanutlin (idasa) in Patients (pts) with Relapsed or Refractory (R/R) AML: A Phase Ib, Non-Randomized, Open-Label Study

2018· article· en· W2905066790 on OpenAlexaff
Naval Daver, Daniel A. Pollyea, Jacqueline S. Garcia, Brian A. Jonas, Karen Yee, Pierre Fenaux, Sarit Assouline, Norbert Vey, Rebecca L. Olin, Gail J. Roboz, Agostino Tafuri, Giuseppe Visani, Whitney P. Kirschbrown, Cherie Green, Connie Ma, Monique Dail, Jue Wang, Marion Ott, Mehrdad Mobasher, Patrick Phuong, Wan‐Jen Hong, Marina Konopleva, Michael Andreeff

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsJewish General HospitalPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsVenetoclaxMedicineRefractory (planetary science)Internal medicinePharmacokineticsVenOncologyPharmacologyLeukemiaChronic lymphocytic leukemiaBiology

Abstract

fetched live from OpenAlex

Abstract Introduction Effective therapies for R/R AML remain limited. MEK or MDM2 inhibition can downregulate MCL1, overcoming resistance to BCL2 inhibition. Preclinical synergy was seen when combining BCL2 inhibitor Ven with MEK inhibitor cobimetinib (cobi) or MDM2 inhibitor idasa (Han et al. ASH 2016; Pan et al. Cancer Cell 2017), supporting clinical evaluation in AML. Preliminary data in a Phase Ib dose-escalation study (NCT02670044) evaluating Ven+cobi/idasa in R/R AML suggested both combinations were tolerable (Daver et al. ASH 2017). However, Ven+cobi was closed due to limited clinical activity. Here we present data for additional pts, longer follow-up and biomarker analyses for Ven+idasa. Methods This ongoing, open-label, multicenter study evaluates safety, tolerability and efficacy of Ven+idasa in R/R AML or secondary AML previously treated for an antecedent hematologic disease. Pts >60 yrs of age and ineligible for cytotoxic therapy/allogeneic stem cell transplant were enrolled. A 2-dimensional dose escalation was used to establish the maximum tolerated dose: pts received doses of Ven orally (PO) daily (400mg or 600mg) + idasa PO daily on Days 1-5 (150mg, 200mg, or 400mg) in 28-day cycles. Plasma samples were taken for PK analysis at Cycles 1 and 2 Days 1 and 5, and Cycle 4 Day 1. BCL2, BCLxL and MCL1 status and minimal residual disease (MRD) were assayed centrally at Covance Laboratories using multicolor flow cytometry. Mutation (mut) sequencing was performed by Foundation Medicine using FoundationOne Heme at screening and from last bone marrow collected on study. Results As of April 6 2018, 34 pts received Ven+idasa across all dose cohorts (Table 1). Median age: 74 (range 64-93) yrs; median prior therapies: 1 (range 1-4); ECOG performance status 2: 18%; refractory: 56%; secondary AML: 53%; adverse cytogenetics: 27%. Pre-therapy mut data were available for 32 pts; most common muts were RUNX1 14 (41%), ASXL1 11 (32%), SRSF2 11 (32%). Other significant pre-therapy muts: TP53 6 (18%), IDH2 7 (21%), IDH1 1 (3%), FLT3 4 (13%). The most common adverse events (AEs) were diarrhea (88%) and nausea (71%); the most common grade (Gr) ≥3 AEs were neutropenia (32%), febrile neutropenia (32%), thrombocytopenia (29%; Table 2). After 2 cases of Gr 3 diarrhea in the Ven 600mg cohorts, mandatory prophylaxis was implemented; no further cases of Gr ≥3 diarrhea were seen in the following 10 pts. Laboratory tumor lysis syndrome occurred in 3 pts (9%); none required treatment discontinuation. There was no apparent PK drug-drug interaction between Ven and idasa. PK was dose-proportional over the ranges tested for Ven and idasa. The recommended Phase II dose (RP2D) has not been identified yet. Across all dose cohorts, 30/34 pts were response-evaluable; the remaining 4 were still on study treatment without post-baseline response assessment. The anti-leukemic response rate (CR+CRp+CRi+MLFS+PR) was 37% (11/30). Across the 2 Ven 600mg cohorts, which are being considered for RP2D, the anti-leukemic response rate was 9/18 (50%) (Table 1, Figure 1). MRD negativity (<0.1%) was achieved in 43% (3/7) of pts with CR+CRp+CRi (Table 3). The median time to CR+CRp+CRi+PR (all pts) was 1.8 mo (range 0.8-2.7), with median response duration of 8.1 mo (range 0.3-9.7). Median overall survival in all pts and in the Ven 600mg cohorts was 3.9 mo and 5.3 mo (range 0.2-17.6), respectively; median follow-up was 2.9 mo (range 0-18). The anti-leukemic response rate was 86% in pts with IDH2 mut and 57% in pts with a RUNX1 mut, but only 20% in pts with a TP53 mut (Table 4). 8/20 pts with end-of-treatment mut data had either new TP53 muts or an increase in mut TP53 allele frequency (Figure 2). In 14 evaluable pts, those with AML blasts with a high ratio of BCL2:BCLxL or BCL2:MCL1 had a response rate of 100% (5/5) versus 11% (1/9) in pts with low ratios (Table 4). Conclusion Ven+idasa has a tolerable safety profile with appropriate prophylaxis in this R/R AML population. An anti-leukemic response rate of 50% was seen at dose levels being considered for RP2D (Ven 600mg + idasa 150/200mg). Overall, responses appeared deep and durable. Preliminary biomarker data indicate that the relative ratio of BCL2 to BCLxL and MCL1 may be important for Ven+idasa activity, whereas pts with baseline TP53 muts had lower response rates. To confirm the clinical benefit and safety of Ven+idasa, the combination will be further evaluated in an expansion arm, after confirmation of the RP2D. Disclosures Daver: Kiromic: Research Funding; ImmunoGen: Consultancy; Sunesis: Research Funding; Pfizer: Research Funding; Novartis: Research Funding; Novartis: Consultancy; Incyte: Research Funding; Daiichi-Sankyo: Research Funding; Sunesis: Consultancy; Karyopharm: Research Funding; Alexion: Consultancy; Pfizer: Consultancy; ARIAD: Research Funding; BMS: Research Funding; Otsuka: Consultancy; Incyte: Consultancy; Karyopharm: Consultancy. Pollyea:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Curis: Membership on an entity's Board of Directors or advisory committees; Argenx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Research Funding; Gilead: Consultancy; Celyad: Consultancy, Membership on an entity's Board of Directors or advisory committees. Garcia:Celgene: Consultancy. Jonas:Genentech/Roche: Research Funding; AbbVie: Consultancy, Research Funding; Amgen: Consultancy; Glycomimetics: Research Funding; Esanex: Research Funding; Pharmacyclics: Research Funding; Incyte: Research Funding; LP Therapeutics: Research Funding; Tolero: Consultancy; Forma: Research Funding; Celgene: Consultancy, Research Funding; Accelerated Medical Diagnostics: Research Funding; Kalobios: Research Funding; Daiichi Sankyo: Research Funding. Yee:Agensys, Astex, GSK, Onconova, Genentech/Roche: Research Funding; Celgene, Novartis, Otsuka: Membership on an entity's Board of Directors or advisory committees. Fenaux:Otsuka: Honoraria, Research Funding; Roche: Honoraria; Jazz: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Assouline:Roche: Honoraria, Research Funding, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Research Funding, Speakers Bureau; Pfizer: Honoraria, Research Funding, Speakers Bureau; Novartis: Research Funding. Olin:Daiichi Sankyo, Astellas, Genentech: Research Funding. Roboz:Cellectis: Research Funding; Janssen Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy; Daiichi Sankyo: Consultancy; Roche/Genentech: Consultancy; Novartis: Consultancy; Astex Pharmaceuticals: Consultancy; Bayer: Consultancy; Orsenix: Consultancy; Pfizer: Consultancy; Argenx: Consultancy; Otsuka: Consultancy; Bayer: Consultancy; Aphivena Therapeutics: Consultancy; Roche/Genentech: Consultancy; Celgene Corporation: Consultancy; Jazz Pharmaceuticals: Consultancy; Otsuka: Consultancy; Jazz Pharmaceuticals: Consultancy; AbbVie: Consultancy; Novartis: Consultancy; Sandoz: Consultancy; Argenx: Consultancy; Eisai: Consultancy; Aphivena Therapeutics: Consultancy; Celgene Corporation: Consultancy; Orsenix: Consultancy; AbbVie: Consultancy; Astex Pharmaceuticals: Consultancy; Pfizer: Consultancy; Daiichi Sankyo: Consultancy; Eisai: Consultancy; Celltrion: Consultancy; Cellectis: Research Funding; Celltrion: Consultancy; Sandoz: Consultancy. Kirschbrown:Roche: Other: Ownership interests PLC; Genentech: Employment. Green:Genentech: Employment. Ma:Genentech: Employment. Dail:Genentech: Employment, Equity Ownership. Wang:Genentech Inc: Employment; F. Hoffmann-La Roche Ltd: Equity Ownership. Ott:Roche: Other: Ownership interests PLC. Mobasher:Genentech Inc: Employment; F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC. Phuong:Genentech Inc: Employment, Equity Ownership, Other: Ownership interests PLC. Hong:Genentech Inc/Roche: Employment, Other: Ownership interests PLC. Konopleva:Stemline Therapeutics: Research Funding. Andreeff:Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Oncolyze: Equity Ownership; United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; SentiBio: Equity Ownership; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Astra Zeneca: Research Funding; Reata: Equity Ownership; Amgen: Consultancy, Research Funding; Jazz Pharma: Consultancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.392
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations25
Published2018
Admission routes1
Has abstractyes

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