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Background: Zanubrutinib is a next-generation, selective Bruton tyrosine kinase inhibitor with efficacy in relapsed chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL). We compared zanubrutinib with bendamustine-rituximab to determine its effectiveness as frontline therapy in patients with CLL or SLL., Methods: We conducted an open-label, multicentre, phase 3 study at 153 academic or community hospitals in 14 countries and regions. Eligible patients had untreated CLL or SLL requiring treatment as per International Workshop on CLL criteria; were aged 65 years or older, or 18 years or older and had comorbidities; and had an Eastern Cooperative Oncology Group performance status score of 0-2. A central interactive web response system randomly assigned patients without del(17)(p13·1) to zanubrutinib (group A) or bendamustine-rituximab (group B) by sequential block method (permutated blocks with a random block size of four). Patients with del(17)(p13·1) were enrolled in group C and received zanubrutinib. Zanubrutinib was administered orally at 160 mg twice per day (28-day cycles); bendamustine at 90 mg/m 2 of body surface area on days 1 and 2 for six cycles plus rituximab at 375 mg/m 2 of body surface area the day before or on day 1 of cycle 1, and 500 mg/m 2 of body surface area on day 1 of cycles 2-6, were administered intravenously. The primary endpoint was progression-free survival per independent review committee in the intention-to-treat population in groups A and B, with minimum two-sided α of 0·05 for superiority. Safety was analysed in all patients who received at least one dose of study treatment. The study is registered with ClinicalTrials.gov, NCT03336333, and is closed to recruitment., Findings: Between Oct 31, 2017, and July 22, 2019, 590 patients were enrolled; patients without del(17)(p13·1) were randomly assigned to zanubrutinib (group A; n=241) or bendamustine-rituximab (group B; n=238). At median follow-up of 26·2 months (IQR 23·7-29·6), median progression-free survival per independent review committee was not reached in either group (group A 95% CI not estimable [NE] to NE; group B 28·1 months to NE). Progression-free survival was significantly improved in group A versus group B (HR 0·42 [95% CI 0·28 to 0·63]; two-sided p<0·0001). The most common grade 3 or worse adverse event was neutropenia (27 [11%] of 240 patients in group A, 116 [51%] of 227 in group B, and 17 [15%] of 111 patients in group C). Serious adverse events occurred in 88 (37%) of 240 patients in group A, 113 (50%) of 227 patients in group B, and 45 (41%) of 111 patients in group C. Adverse events leading to death occurred in 11 (5%) of 240 patients in group A, 12 (5%) of 227 patients in group B, and three (3%) of 111 patients in group C, most commonly due to COVID-19 (four [2%] of 240 patients in group A), diarrhoea, and aspiration pneumonia (two each [1%] of 227 patients in group B)., Interpretation: Zanubrutinib significantly improved progression-free survival versus bendamustine-rituximab, with an acceptable safety profile consistent with previous studies. These data support zanubrutinib as a potential new treatment option for untreated CLL and SLL., Funding: BeiGene., Competing Interests: Declaration of interests CST reports receiving funding from AbbVie and Janssen; and honoraria from AbbVie, BeiGene, Janssen, Novartis, and Roche, outside the submitted work. JRB reports receiving funding from Gilead, Lilly–LOXO, TG Therapeutics, Verastem–SecuraBio, and Sun; consulting fees from AbbVie, Acerta–AstraZeneca, BeiGene, Bristol Myers Squibb–Juno–Celgene, Catapult Therapeutics, Dynamo Therapeutics, Eli Lilly, Genentech/Roche, Gilead, Janssen, Kite, LOXO, MEI Pharma, MorphoSys, Nextcea, Novartis, Octapharma, Pfizer, Pharmacyclics, Rigel, Sunesis, TG Therapeutics, and Verastem; honoraria from Janssen; and participation on an advisory board for Invectys and MorphoSys, outside of the submitted work. BSK reports receiving funding from BeiGene paid to Washington University School of Medicine (St Louis, MO, USA), and receiving consulting fees from AbbVie, AstraZeneca, BeiGene, Janssen, and Pharmacyclics, outside the submitted work. PG reports receiving funding from BeiGene with regards to the submitted work; funding from AbbVie, AstraZeneca, Janssen, Gilead, Novartis, and Sunesis; consulting fees from and participating on an advisory board for AbbVie, AstraZeneca, ArQule–MSD, Celgene–Juno–Bristol Myers Squibb, Janssen, Lilly–LOXO, and Roche; and receiving honoraria from AbbVie, AstraZeneca, Janssen, and MSD, outside the submitted work. KG reports receiving consulting fees and honoraria from BeiGene, with regards to the submitted work; funding from AbbVie, Amgen, AstraZeneca, Janssen, Novartis, Roche, Sanofi-Genzyme, and Takeda and paid to the Next Generation Hematology Association; receiving consulting fees from GSK and Sandoz; receiving honoraria from AbbVie, Amgen, AstraZeneca, BeiGene, Gilead, GSK, Janssen, Karyopharm, Novartis, Pfizer, Roche, Sandoz, Takeda, and Teva; receiving financial support for attending meetings or travel, or both, from Janssen, Roche, and Sanofi-Genzyme; participating on an advisory board for AbbVie, Amgen, AstraZeneca, Gilead, GSK, Janssen, Novartis, Roche, Sandoz, and Takeda; and a leadership role at the Next Generation Hematology Association, outside the submitted work. WJ reports receiving funding from BeiGene and Janssen, with regards to the submitted work, and funding from AstraZeneca and TG Therapeutics, outside the submitted work. MŠ reports receiving consulting fees from AbbVie and AstraZeneca; receiving honoraria from AbbVie and Janssen-Cilag; participating on an advisory board for AbbVie, AstraZeneca, and Janssen-Cilag; and stock or stock options, or both, from AbbVie, AstraZeneca, Eli Lilly, Johnson & Johnson, and Merck, outside the submitted work. MS reports receiving funding from BeiGene paid to Fred Hutchinson Cancer Research Center and the University of Washington (Seattle, WA, USA), with regards to the submitted work; funding from AbbVie, AstraZeneca, Atara Biotherapeutics, BeiGene, GenMab, Genentech, Gilead, Mustang Bio, Bristol Myers Squibb, Celgene, Pharmacyclics, Sunesis, and TG Therapeutics; and receiving consulting fees from AbbVie, Adaptimmune, Adaptive Biotechnologies, AstraZeneca, Atara Biotherapeutics, BeiGene, Bristol Myers Squibb, Eli Lilly, Epizyme, Genentech, InnatePharma, Kite Pharma, MorphoSys, Mustang Bio, Pharmacyclics, Sound Biologics, and TG Therapeutics, outside the submitted work. PW reports receiving consulting fees from Acerta and BeiGene, outside the submitted work. SO reports receiving funding from BeiGene paid to Monash University (Clayton, VIC, Australia), with regards to the submitted work; and honoraria and participating on an advisory board for BeiGene, outside the submitted work. HCh reports receiving financial support for attending meetings or travel, or both, from Celgene and Janssen, and participating on an advisory board for AbbVie, Eusa, and Janssen, outside the submitted work. RG reports receiving consulting fees from AbbVie, AstraZeneca, Bristol Myers Squibb, Celgene, Daiichi Sankyo, Gilead, Janssen, Merck, MSD, Novartis, Roche, and Takeda; honoraria from AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Celgene, Daiichi Sankyo, Gilead, Merck, MSD, Novartis, Roche, Takeda, and Sandoz; financial support for attending meetings or travel, or both, from AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Celgene, Daiichi Sankyo, Gilead, Janssen, MSD, Novartis, and Roche; and participating on an advisory board for AbbVie, AstraZeneca, Bristol Myers Squibb, Celgene, Daiichi Sankyo, Gilead, Janssen, Merck, MSD, Novartis, Roche, and Takeda, outside the submitted work. MTr reports receiving consulting fees from AbbVie, Amgen, Janssen, Bristol Myers Squibb, Gilead Sciences, Incyte, MorphoSys, Novartis, Roche, Takeda; receiving honoraria from AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Gilead Sciences, Incyte, Janssen, Roche, MorphoSys, Novartis, Portolla, and Takeda; receiving financial support for attending meetings or travel, or both, from AbbVie, Bristol Myers Squibb, Gilead, Janssen, Roche, and Takeda; participating on an advisory board for AbbVie, Bristol Myers Squibb, Incyte, Janssen, MorphoSys, Novartis, Portolla, Roche, and Takeda; and employment at Charles University General Hospital in Prague, outside the submitted work. DMB reports receiving funding from AbbVie, ArQule, Ascentage, AstraZeneca, BeiGene, DTRM, Genetech, Juno–Celgene–Bristol Myers Squibb, LOXO, MEI Pharma, Novaris, Pharmacyclics, and TG Therapeutics; receiving consulting fees from AbbVie, Genentech, Pharmacyclics, Pfizer, TG Therapeutics, and Verastem; participating on an advisory board for AbbVie, Genentech, Novartis, Pharmacyclics, Pfizer, TG Therapeutics, and Verastem; and a leadership role with NCCN (panel member), informCLL registry (steering committee; AbbVie), and Biosimilars outcomes research panel (Pfizer), outside the submitted work. IWF reports receiving funding from AbbVie, Acerta Pharma, Agios, ArQule, AstraZeneca, BeiGene, Calithera Biosciences, Celgene, Constellation Pharmaceuticals, Curis, Forma Therapeutics, Forty Seven, Genentech, Gilead Sciences, IGM Biosciences, Incyte, Infinity Pharmaceuticals, Janssen, Juno Therapeutics, Karyopharm Therapeutics, Kite Pharma, LOXO, Merck, MorphoSys, Novartis, Pfizer, Pharmacyclics, Portola Pharmaceuticals, Rhizen Pharmaceuticals, Roche, Seattle Genetics, Takeda, Teva, TG Therapeutics, Trillium Therapeutics, Triphase Research & Development, Unum Therapeutics, and Verastem, paid to the Sarah Cannon Research Institute; and consulting fees from AbbVie, AstraZeneca, BeiGene, Century Therapeutics, Genentech, Gilead Sciences, Great Point Partners, Hutchison MediPharma, Iksuda Therapeutics, Janssen, Juno Therapeutics, Kite Pharma, MorphoSys, Novartis, Nurix Therapeutics, Pharmacyclics, Roche, Seattle Genetics, Servier Pharmaceuticals, Takeda, TG Therapeutics, Unum Therapeutics, Verastem, Vincerx Pharma, and Yingli Pharmaceuticals, paid to the Sarah Cannon Research Institute, outside the submitted work. AT reports receiving consulting fees from AbbVie, AstraZeneca, BeiGene, and Janssen; and honoraria from AbbVie, AstraZeneca, BeiGene, and Janssen, outside the submitted work. TT, LZ, CM, JCP, and AC are employees of BeiGene, with regards to the submitted work, and report stocks or stock options, or both, from BeiGene, outside the submitted work. JH is an employee of BeiGene, with regards to the submitted work; reports receiving royalties from BeiGene; receiving financial support for attending meetings or travel, or both, from BeiGene and Protara; patents with BeiGene; a leadership role with BeiGene and Protara; and stock or stock options, or both, from BeiGene and Protara, outside the submitted work. TR reports receiving funding from BeiGene, with regards to the submitted work; receiving funding from AbbVie, AstraZeneca, Janssen, and Roche; and participating on an advisory board for AbbVie, AstraZeneca, BeiGene, Janssen, and Roche. PH reports receiving funding from AbbVie, Gilead, Janssen, Pharmacyclics, and Roche; honoraria from AbbVie, AstraZeneca, BeiGene, Janssen, Pharmacyclics, and SOBI; and financial support for attending meetings or travel, or both, from AbbVie and Janssen, outside the submitted work. All other authors declare no competing interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: Ibrutinib, a first-in-class, once-daily inhibitor of Bruton's tyrosine kinase (BTK), is approved in the US and EU for the treatment of various B-cell malignancies. In clinical studies, BTK inhibitors have been associated with increased bleeding risk, which may result from BTK inhibition in platelets. Methods: To better understand the mechanism of ibrutinib in bleeding events, we isolated platelet-rich plasma from healthy donors ( n  = 8) and donors with conditions associated with impaired platelet function or with potentially increased bleeding risk (on hemodialysis, taking aspirin, or taking warfarin; n  = 8 each cohort) and used light transmission aggregometry to assess platelet aggregation in vitro after exposure to escalating concentrations of ibrutinib, spanning and exceeding the pharmacologic range of clinical exposure. Results: Platelet aggregation was induced by agonists of 5 major platelet receptors: adenosine diphosphate (ADP), thrombin receptor-activating peptide 6 (TRAP6), ristocetin, collagen, or arachidonic acid (AA). Platelet aggregation induced by ADP, TRAP6, ristocetin, and AA was not meaningfully inhibited by the maximal concentrations of ibrutinib (10 µM). In contrast, collagen-induced platelet aggregation was dose-dependently inhibited by ibrutinib in all donor cohorts (maximum aggregation % with 10 μM ibrutinib, -64% to -83% of agonist activity compared to control agonist samples but without ibrutinib). Conclusion: These results confirm prior reports and support a mechanistic role for the inhibition of collagen-induced platelet aggregation in bleeding events among susceptible individuals receiving ibrutinib therapy.

Single-cell network profiling (SCNP) data generated from multi-parametric flow cytometry analysis of bone marrow (BM) and peripheral blood (PB) samples collected from patients >55 years old with non-M3 AML were used to train and validate a diagnostic classifier (DXSCNP) for predicting response to standard induction chemotherapy (complete response [CR] or CR with incomplete hematologic recovery [CRi] versus resistant disease [RD]). SCNP-evaluable patients from four SWOG AML trials were randomized between Training (N = 74 patients with CR, CRi or RD; BM set = 43; PB set = 57) and Validation Analysis Sets (N = 71; BM set = 42, PB set = 53). Cell survival, differentiation, and apoptosis pathway signaling were used as potential inputs for DXSCNP. Five DXSCNP classifiers were developed on the SWOG Training set and tested for prediction accuracy in an independent BM verification sample set (N = 24) from ECOG AML trials to select the final classifier, which was a significant predictor of CR/CRi (area under the receiver operating characteristic curve AUROC = 0.76, p = 0.01). The selected classifier was then validated in the SWOG BM Validation Set (AUROC = 0.72, p = 0.02). Importantly, a classifier developed using only clinical and molecular inputs from the same sample set (DXCLINICAL2) lacked prediction accuracy: AUROC = 0.61 (p = 0.18) in the BM Verification Set and 0.53 (p = 0.38) in the BM Validation Set. Notably, the DXSCNP classifier was still significant in predicting response in the BM Validation Analysis Set after controlling for DXCLINICAL2 (p = 0.03), showing that DXSCNP provides information that is independent from that provided by currently used prognostic markers. Taken together, these data show that the proteomic classifier may provide prognostic information relevant to treatment planning beyond genetic mutations and traditional prognostic factors in elderly AML.

The aim of this study was to assess the feasibility of applying the single cell network profiling (SCNP) assay to the examination of signaling networks in epithelial cancer cells, using bladder washings from 29 bladder cancer (BC) and 15 nonbladder cancer (NC) subjects. This report describes the methods we developed to detect rare epithelial cells (within the cells we collected from bladder washings), distinguish cancer cells from normal epithelial cells, and reproducibly quantify signaling within these low frequency cancer cells. Specifically, antibodies against CD45, cytokeratin, EpCAM, and cleaved-PARP (cPARP) were used to differentiate nonapoptotic epithelial cells from leukocytes, while measurements of DNA content to determine aneuploidy (DAPI stain) allowed for distinction between tumor and normal epithelial cells. Signaling activity in the PI3K and MAPK pathways was assessed by measuring intracellular levels of p-AKT and p-ERK at baseline and in response to pathway modulation; 66% (N = 19) of BC samples and 27% (N = 4) of NC samples met the "evaluable" criteria, i.e., at least 400,000 total cells available upon sample receipt with >2% of cells showing an epithelial phenotype. The majority of epithelial cells detected in BC samples were nonapoptotic and all signaling data were generated from identified cPARP negative cells. In four of 19 BC samples but in none of the NC specimens, SCNP assay identified epithelial cancer cells with a quantifiable increase in epidermal growth factor-induced p-AKT and p-ERK levels. Furthermore, preincubation with the PI3K inhibitor GDC-0941 reduced or completely inhibited basal and epidermal growth factor-induced p-AKT but, as expected, had no effect on p-ERK levels. This study demonstrates the feasibility of applying SCNP assay using multiparametric flow cytometry to the functional characterization of rare, bladder cancer cells collected from bladder washing. Following assay standardization, this method could potentially serve as a tool for disease characterization and drug development in bladder cancer and other solid tumors., (Copyright © 2013 International Society for Advancement of Cytometry.)