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Record W3094714150 · doi:10.1182/blood-2020-136135

Molecular Response Patterns in Hydroxyurea (HU)-Resistant or Intolerant Polycythemia Vera (PV) during Treatment with Idasanutlin: Results of an Open-Label, Single-Arm Phase 2 Study

2020· article· en· W3094714150 on OpenAlexaff
Francesco Passamonti, Kate Burbury, Tarec Christoffer El‐Galaly, Aaron T. Gerds, Vikas Gupta, Brian Higgins, Ling‐Yuh Huw, Margherita Maffioli, Ruben A. Mesa, Jeanne Palmer, Alessandro Rambaldi, David M. Ross, Alessandro M. Vannucchi, Abdulraheem Yacoub, John Mascarenhas

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsPolycythemia veraMedicineOpen labelInternal medicineGastroenterologyImmunologyClinical trial

Abstract

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Background Activating mutations in JAK2 are the molecular hallmark of PV. However, achieving molecular remission is not a validated endpoint in PV, as its correlation with patient-relevant endpoints, such as thrombotic events or disease progression, is not well established. The expression of MDM2, a negative regulator of wild-type p53, is significantly higher in CD34+ cells from patients with PV vs those from healthy controls. Therefore, MDM2 antagonists such as idasanutlin (idasa) may have selective and potentially disease-modifying effects in PV. This exploratory analysis reports baseline mutational profiling and serial measurements of JAK2 V617F variant allele frequency (VAF) from patients treated with idasa in the Phase II NP39761 study (NCT03287245). Methods Patients with PV, as defined by the 2016 World Health Organization criteria, were eligible for inclusion if their disease was HU resistant/intolerant according to European LeukemiaNet criteria and they were phlebotomy dependent (≥ 1 phlebotomy in the 16-wk period prior to screening). Prior PV therapy with ruxolitinib and/or interferon was allowed. Idasa was given orally once daily on days 1-5 of 28-day cycles for up to 24 mo. The starting dose was 150 mg, but dose increase (to 200 mg) or decrease (to 100 mg) was allowed per protocol-defined criteria. The primary efficacy endpoints were hematocrit control (HTC), defined as maintaining acceptable hematocrit levels with ≤ 1 phlebotomy between cycle 1, day 1 (C1D1) and wk 8 and no phlebotomy after wk 8, and complete hematologic remission (CHR), defined as HTC together with platelets < 400 × 109/L and white blood cell count < 109/L on the day of response assessment (or most recent test). JAK2 V617F VAF was analyzed at screening and at C3D28, C5D28 and wk 32. The JAK2 V617F VAF was determined using quantitative polymerase chain reaction. Baseline blood samples were sequenced using the Foundation Medicine FoundationOne Heme next-generation sequencing panel, which interrogates > 400 DNA-sequenced genes, to explore the genetic landscape of PV beyond JAK2 V617F. Results All 27 patients enrolled in the study harbored JAK2 V617F. Baseline and ≥ 1 later JAK2 VAF measurements were available in 23 patients, allowing for analysis. The median age was 56 y (range, 34-74), and 7 patients (26%) had been previously treated with ruxolitinib. Median treatment duration was 257 days (range, 5-677), and the median number of treatment cycles was 8 (range, 1-22). JAK2 V617F VAFs at baseline were highly variable, ranging from 7% to 96% (median, 66%). A reduction in JAK2 V617F VAF was observed as early as after 3 cycles (median reduction, 39%; n = 19) and was sustained in patients receiving treatment, with a median reduction of 58% at C5D28 (n = 17) and of 76% at wk 32 (n = 13). The median reductions in JAK2 V617F VAF were significantly higher for patients with CHR and HTC than in nonresponders on C3D28 (CHR, P < 0.01; HTC, P = 0.04) and C5D28 (CHR, P < 0.01; HTC, P = 0.03), with a similar trend also at wk 32 (CHR, P = 0.06; HTC, P = 0.19) (Figures). Baseline targeted sequencing (n = 16) identified several additional subclonal mutations. However, no TP53 mutations were detected. Variants in TET2 and ASXL1 were detected in 37% (6 of 16) and 20% (3 of 16) of patients, with VAFs of 2%-51% and 38%-50%, respectively. Notably, 68% of the patients had variants detected in 1 to 3 DNA repair genes, including ATM (VAF, 47%-52%), ATR (VAF, 49%), BRCA2 (VAF, 47%-51%), PARP1 (VAF, 52%), PARP3 (VAF, 48%), FANCM (VAF, 47%-50%), BLM (VAF, 48%) and MSH3 (VAF, 49%). In the absence of sequencing of patient-matched non-hematologic tissue and the VAFs being ≈50%, it is possible some of these variants are germline. Whether such variants predispose to PV is unknown. Conclusions Idasa has relevant clinical activity in patients with PV who are resistant to or intolerant of HU and showed rapid JAK2 V617F VAF reduction in a subset of patients as early as after 3 treatment cycles. The median JAK2 VAF reduction was significantly greater in patients who achieved CHR and HTC after 3 and 5 cycles of idasa treatment, suggesting that early molecular response was associated with higher likelihood of clinical response. Baseline mutations were seen in several genes commonly mutated in PV. A high frequency of variants in DNA repair genes has not previously been reported in PV and may contribute to genomic instability in this disease. Figure Disclosures Passamonti: Roche: Other: Support of parent study and funding of editorial support; BMS: Speakers Bureau; Novartis: Speakers Bureau. El-Galaly:F. Hoffmann-La Roche: Current Employment, Other: Support of parent study and funding of editorial support. Gerds:Celgene: Consultancy, Research Funding; Gilead Sciences: Research Funding; CTI Biopharma: Consultancy, Research Funding; Imago Biosciences: Research Funding; AstraZeneca/MedImmune: Consultancy; Roche/Genentech: Research Funding; Incyte Corporation: Consultancy, Research Funding; Pfizer: Research Funding; Apexx Oncology: Consultancy; Sierra Oncology: Research Funding. Gupta:Incyte: Honoraria, Research Funding; Bristol MyersSquibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy. Higgins:Roche: Current Employment, Current equity holder in publicly-traded company, Other: Support of parent study and funding of editorial support. Huw:Roche: Current Employment, Other: Support of parent study and funding of editorial support. Maffioli:Roche: Other: Support of parent study and funding of editorial support. Mesa:Sierra Oncology: Consultancy; Incyte: Research Funding; Samus Therapeutics: Research Funding; Promedior: Research Funding; Genentech: Research Funding; Novartis: Consultancy; CTI BioPharma: Research Funding; LaJolla Pharmaceutical Company: Consultancy; AbbVie: Research Funding; Bristol Myers Squibb: Research Funding. Rambaldi:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support of parent study and funding of editorial support. Received travel support., Research Funding; Sanofi: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Astellas: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support from Gilead.; BMS/Celgene: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company). Advisory board and speaker fees from Pfizer.; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company). Research grant from Amgen Inc.; Omeros: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); University of Milan: Current Employment. Vannucchi:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees; Blueprint: Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Yacoub:Incyte: Speakers Bureau; Hylapharm: Current equity holder in private company; Cara Therapeutics: Current equity holder in publicly-traded company; Dynavax: Current equity holder in publicly-traded company; Agios: Honoraria, Speakers Bureau; Novartis: Speakers Bureau; Roche: Other: Support of parent study and funding of editorial support; Ardelyx: Current equity holder in publicly-traded company. Mascarenhas:Celgene, Prelude, Galecto, Promedior, Geron, Constellation, and Incyte: Consultancy; Incyte, Kartos, Roche, Promedior, Merck, Merus, Arog, CTI Biopharma, Janssen, and PharmaEssentia: Other: Research funding (institution).

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)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.051
GPT teacher head0.325
Teacher spread0.274 · 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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Citations3
Published2020
Admission routes1
Has abstractyes

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