ALBERT

Description: Treatment options for relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL) are limited with no standard of care; prognosis is poor, with 4- to 6-month median survival. Avadomide (CC-122) is a cereblon-modulating agent with immunomodulatory and direct antitumor activities. This phase 1 dose expansion study assessed safety and clinical activity of avadomide monotherapy in patients with R/R de novo DLBCL and transformed lymphoma. Additionally, a novel gene expression classifier, which identifies tumors with a high immune cell infiltration, was shown to enrich for response to avadomide in R/R DLBCL. Ninety-seven patients with R/R DLBCL, including 12 transformed lymphoma, received 3 to 5 mg of avadomide administered on continuous or intermittent schedules until unacceptable toxicity, disease progression, or withdrawal. Eighty-two patients (85%) experienced ≥1 grade 3/4 treatment-emergent adverse events (AEs), most commonly neutropenia (51%), infections (24%), anemia (12%), and febrile neutropenia (10%). Discontinuations because of AEs occurred in 10% of patients. Introduction of an intermittent 5/7‑day schedule improved tolerability and reduced frequency and severity of neutropenia, febrile neutropenia, and infections. Among 84 patients with de novo R/R DLBCL, overall response rate (ORR) was 29%, including 11% complete response (CR). Responses were cell-of-origin-independent. Classifier-positive DLBCL patients (de novo) had an ORR of 44%, median progression-free survival (mPFS) of 6 months, and 16% CR versus an ORR of 19%, mPFS of 1.5 months, and 5% CR in classifier-negative patients (P = .0096). Avadomide is being evaluated in combination with other antilymphoma agents. This trial was registered at www.clinicaltrials.gov as #NCT01421524.

Description: Diffuse large B-cell lymphoma is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding two biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies and replicated the subgroups with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and need for a patient selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients demonstrated an enrichment in response rate and progression-free survival of 44% and 6.2 months versus 19% and 1.6 months for classifier-negative patients (HR=0.49 [0.280, 0.86]; P=.0096). The classifier was not prognostic for R-CHOP or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and non-tumor composition and has potential utility to enrich for clinical response to immunomodulatory agents including avadomide.

Description: Background. In addition to clinical considerations (e.g., age, de novo vs secondary disease, comorbidities), therapy selection for AML patients is often based on information considering only cytogenetics and/or molecular aberrations and ignoring other patient-specific omics information that could potentially enable selection of more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification, the current overall outcome of AML patients remains relatively poor. The Cellworks Singula™ report predicts clinical response to physician-prescribed treatments using the novel Cellworks Omics Biology Model (CBM) that simulate in silico downstream molecular effects on cell signaling and survival of drug treatments in patient-specific diseased cells. Methods. The performance of Singula™ was evaluated in a cohort of 474 AML patients aged 2 to 85. The pre-defined Singula™ Classifier utilizes individual patients' next-generation sequencing (NGS) profiles to provide a dichotomous prediction of response or non-response to the physician prescribed treatments. The clinical outcome data for these subjects, i.e., complete response (CR) and overall survival (OS), were obtained from the TCGA and other 144 PubMed publications, each including also information on patients' cytogenetics, targeted gene mutations, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized the cytogenetic and molecular data to generate a Singula™ predicted response (i.e., CR vs non-response) classification for each patient. Statistical analyses, including assessments of accuracy, sensitivity, specificity, and negative (NPV) and positive predictive (PPV) values were performed to compare the Singula™ predicted clinical response to the actual observed clinical response. Kaplan-Meier curves, associated log rank tests and median OS are provided for patients stratified by Singula™ predicted response. Multivariate Cox proportional hazards regression was used to further test the hypothesis that Singula™ is an independent predictor for OS once adjusted for patient age and actual prescribed treatment. Results. Data are summarized in Table 1. The Singula™ classifier had 92.3% (90.6%, 95.3%) accuracy in predicting correctly observed patient complete response to the prescribed treatment. with 97.3% (95.0%, 98.8%) sensitivity. Singula™ had 83.3% (76.1%, 89.1%) specificity for the non-responder patients (n=138; 29.1%). For each of the non-responders, Singula™ provided an alternative treatment therapy predicted to produce clinical response. Assuming at least 2% of the non-responders would have responded to the alternative Singula™ prescribed treatment, Singula™ improves CR rates compared to the original physician prescribed treatment (McNemar's p-value 〈 0.05). Figure 1 provides the Kaplan-Meier curves of Singula-predicted responders vs non-responders for a subset of 292 subjects that had OS data available. In multivariate Cox proportional hazards models, the Singula Classifier remained a significant predictor of overall survival (HR = 2.171, p-value 〈 0.0001) once adjusted for patient age and physician prescribed treatment. Conclusions. Cellworks Singula™ has high accuracy and sensitivity in predicting CR for AML patient. Singula also has high specificity in identifying patients who are unlikely to respond physician and may prescribed potentially effective therapies. The Singula™ predicted responders have a significantly longer OS than the predicted non responders. Thus, Cellworks Singula™ can accurately predict AML response, be used to validate or reject a physician's therapy selection decision and, eventually, provide alternative treatment recommendations. Disclosures Marcucci: Novartis: Speakers Bureau; Abbvie: Speakers Bureau; Iaso Bio: Membership on an entity's Board of Directors or advisory committees; Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial). Watson:Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Amara:Cellworks Research India Private Limited: Current Employment. Pampana:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Stein:Stemline: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau.

Description: Background: Therapy selection for MDS patients is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of MDS patients remains relatively poor. The Cellworks Singula™ report predicts response for physician prescribed treatments using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. Methods: The performance of Singula™ was evaluated in an independent, randomly selected, retrospective cohort of 144 MDS patients aged 28 to 89 years (median 69). The pre-defined Singula™ Classifier utilizes an individual's genomics profile to provide a dichotomous prediction of response or non-responses to a given physician prescribed treatment (PPT). Outcome data for these subjects, including measurement of complete response (CR), were obtained from 42 PubMed publications, each including patient genomics data of either karyotyping, targeted gene panels, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized these data to generate a Singula™ classifier of responder vs non-responder in this MDS cohort. Statistical analyses, including assessments of accuracy, sensitivity, specificity, negative (NPV) and positive predictive (PPV) values were performed on the merged data to compare the Singula™ predicted response with the actual observed CR. Multivariate logistic regression models of complete response were performed incorporating covariates for patient age, PPT, and the Singula™ Classifier. Results: Table 1 reveals that the pre-defined Singula™ classifier had 90.3% (Exact 95% CI: 84.2%, 94.6%) accuracy in predicting observed patient response from the physician prescribed treatment. In this study, Singula™ was able to accurately identify responders with 90.0% (81.2%, 95.6%) sensitivity. Importantly, Singula™ had 90.6% (80.7%, 96.5%) specificity for the subset of 64 patients (44.4%) that had a non-response. For 32% (17/54) of the non-responders patients, Singula™ provided an alternative Standard of Care treatment therapy, as shown in Table 2. The remaining 37 patients were predicted to be non-responders to all remaining Standard of Care options, so did not have alternate treatment predictions. Assuming at least 4% of these non-responding patients would have responded to the alternative Singula™ prescribed therapy, then these data support that Singula™ improves prediction of CR compared to the original PPT (McNemar's p-value 〈 0.05). In multivariate logistic regression models of CR that included patient age and prescribed drug therapy, the Singula™ Classifier remained an independent, significant predictor of CR (OR 〉 100, p-value 〈 0.0001), while both patient age (p = 0.372) and drug therapy (p = 0.720) fell off the model. Conclusions: Cellworks Singula™ has high accuracy and sensitivity in predicting CR for MDS patient response to physician prescribed therapies. Singula™ also has high specificity in identifying patients who are unlikely to respond to physician prescribed therapies and provides alternative treatment recommendations for these patients. The Singula™ Classifier is an independent and superior predictor of CR compared with other clinical (age) or therapeutic (PPT) factors. Figure Disclosures Stein: Amgen: Consultancy, Speakers Bureau; Stemline: Consultancy, Speakers Bureau. Watson:BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Prakash:Cellworks Research India Private Limited: Current Employment. Behura:Cellworks Research India Private Limited: Current Employment. Balakrishnan:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Marcucci:Abbvie: Speakers Bureau; Novartis: Speakers Bureau; Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial); Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Iaso Bio: Membership on an entity's Board of Directors or advisory committees.

Description: Immune thrombocytopenia (ITP) is an acquired autoimmune disorder defined by a platelet count 〈 100 × 109/L without explanation, and an increased risk of bleeding. ITP itself as well as its treatments have multifaceted, often poorly understood impacts on patients' quality of life (QoL). These effects include impact on activities of daily living, emotional health, energy, ability to think well and clearly, and productivity in the workplace. There are limited data on which individual aspects of ITP are perceived both by patients and physicians as having the greatest impact on QoL. Understanding patients' perspectives is vital to optimize their QoL by specifying particular areas in need of therapy. I-WISh 1.0 was an exploratory, cross-sectional survey in which 1507 patients with ITP and 472 physicians across 13 countries completed separate, but related, online surveys that included assessments of ITP signs and symptoms, impact of symptoms, and patient-physician relationships. These findings have been presented at previous ASH and EHA congresses, and manuscripts are currently in preparation. However, although I-WISh 1.0 provided considerable insights into unexplored facets of the effects of ITP, an all-too-large number of gaps in understanding still remain. In response to this, I-WISh 2.0 is currently being developed. The objectives of the I-WISh 2.0 patient and physician cross-sectional surveys include: (1) to further explore the burden of fatigue and how it affects patients' lives, including what makes it better or worse; (2) to assess the emotional impact of living with chronic ITP, especially in relation to depression; (3) to assess how treatments for ITP can impact activities of daily living (positively and negatively); (4) to further relate effects of treatment to patients' QoL; and (5) to explore how telemedicine affects healthcare delivery for patients with ITP. Furthermore, data from subsets of patients will address (6) the impact of COVID-19 in patients with ITP; and (7) special issues affecting ITP in pregnancy. A steering committee of ITP expert physicians and patient advocacy group representatives are designing and will endorse the patient and physician surveys now nearing readiness after several meetings to determine the areas of greatest need of assessment. In addition, a control group will be included. Survey launch and data collection are scheduled to commence in early Q4 2020. Patients and physicians will complete similar online surveys. Both patient and physician surveys include a screener and sections of questions related to the specific objectives of I-WISh 2.0. The surveys include updates to key topics in I-WISh 1.0 (impact of fatigue, impact on daily life, treatment of ITP, emotional impact of ITP); validated patient-reported outcome tools to measure fatigue (MFIS-5), presence and severity of depression (PHQ-9), work-related burden (WPAI), and impact on quality of life (ILQI) tools; and questions related to COVID-19, telemedicine (remote patient monitoring), and pregnancy and ITP. Patients will be recruited to I-WISh 2.0 via treating physicians and patient advocacy groups, and will be included if they are ≥ 18 years of age, diagnosed with ITP, and agree to participate. Participating physicians will be required to be actively managing patients with ITP and have a minimum caseload of 3 ITP patients currently under their care; physicians must also have a primary specialty of hematology or hematology-oncology. Approval will be sought from an independent centralized Institutional Review Board. Data analysis will be primarily descriptive and correlative in nature. Breakdown by country and geographic areas will be included. A global sample is planned from 21 countries across 6 continents, with the aim of surveying more than 2000 patients and 600 physicians. I-WISh 2.0 will be the largest observational global survey ever conducted in ITP. If accepted, preliminary data are planned to be presented at the ASH meeting. I-WISh 2.0 will build on the strengths of I-WISh 1.0, which highlighted areas requiring further assessment and will explore aspects of ITP of great interest that were neither conclusively addressed in the first survey nor well-studied in the past. Disclosures Ghanima: Bristol Myers Squibb:Research Funding;Principia:Honoraria, Speakers Bureau;Pfizer:Honoraria, Research Funding, Speakers Bureau;Amgen:Honoraria, Speakers Bureau;Novartis:Honoraria, Speakers Bureau;Bayer:Research Funding.Provan:ONO Pharmaceutical:Consultancy;MedImmune:Consultancy;UCB:Consultancy;Amgen:Honoraria, Research Funding;Novartis:Honoraria, Research Funding.Cooper:Amgen:Honoraria, Speakers Bureau;Novartis:Honoraria, Speakers Bureau.Matzdorff:Roche Pharma AG:Other: Family stockownership;Amgen GmbH:Consultancy, Other: Honoraria paid to institution;Grifols Deutschland GmbH:Consultancy, Other: Honoraria paid to institution;Swedish Orphan Biovitrium GmbH:Consultancy, Other: Honoraria paid to institution;UCB Biopharma SRL:Consultancy, Other: Honoraria paid to institution;Novartis Oncology:Consultancy, Other: Honoraria paid to institution.Santoro:Novartis:Honoraria, Speakers Bureau;Takeda:Honoraria, Speakers Bureau;Amgen:Honoraria, Speakers Bureau;Novo Nordisk:Honoraria, Speakers Bureau;Bayer:Honoraria, Speakers Bureau;CSL Behring:Honoraria, Speakers Bureau;Roche:Honoraria, Speakers Bureau;Sobi:Honoraria, Speakers Bureau.Morgan:Sobi:Other: Consultancy fees paid to the ITP Support Association;UCB:Other: Consultancy fees paid to the ITP Support Association;Novartis:Other: Consultancy fees paid to the ITP Support Association.Kruse:Principia:Other: Grant paid to PDSA;Pfizer:Other: Grant and consultancy fee, all paid to PDSA;Argenx:Other: Grant paid to PDSA;Novartis:Other: PDSA received payment for recruiting patients to I-WISh and for promoting I-WISh on the globalitp.org website. Grant and consultancy fee, all paid to PDSA outside the submitted work;CSL Behring:Other: Grant paid to PDSA;UCB:Other: Grant and consultancy fee, all paid to PDSA;Rigel:Other: Grant paid to PDSA;Amgen:Other: Grant and honorarium, all paid to PDSA.Zaja:Janssen-Cilag:Honoraria, Speakers Bureau;Takeda:Honoraria, Speakers Bureau;Bristol Myers Squibb:Honoraria, Speakers Bureau;Grifols:Honoraria, Speakers Bureau;Amgen:Honoraria, Speakers Bureau;AbbVie:Honoraria, Speakers Bureau;Kyowa Kirin:Honoraria, Speakers Bureau;Mundipharma:Honoraria, Speakers Bureau;Novartis:Honoraria, Patents & Royalties: Pending patent (No. PAT058521) relating to TAPER trial (NCT03524612), Speakers Bureau;Roche:Honoraria, Speakers Bureau.Lahav:Novartis:Other: Consultancy fees paid to the Israeli ITP Support Association.Tomiyama:Novartis:Consultancy, Honoraria;Kyowa Kirin:Honoraria;Sysmex:Consultancy.Winograd:Novartis:Other: Consultancy fees paid to the Israeli ITP Support Association.Lovrencic:UCB:Other: Consultancy fees paid to AIPIT;Novartis:Other: Honorarium paid to AIPIT.Bailey:Adelphi Real World:Current Employment;Novartis:Other: Employee of Adelphi Real World, which has received consultancy fees from Novartis.Haenig:Novartis:Current Employment.Bussel:Novartis:Consultancy;Argenx:Consultancy;UCB:Consultancy;CSL Behring:Consultancy;Shionogi:Consultancy;Regeneron:Consultancy;3SBios:Consultancy;Dova:Consultancy;Principia:Consultancy;Rigel:Consultancy;Momenta:Consultancy;RallyBio:Consultancy;Amgen:Consultancy.

Description: Background: Monosomy 7/Del 7 (-7) or its long arm (del(7q)) is one of the most common cytogenetic abnormalities in pediatric and adult myeloid malignancies, particularly in adverse-risk acute myeloid leukemias (AMLs). In general, (-7) is associated with poor response to induction chemotherapy (PMID 12393746). At the same time, not all patients fare poorly so the ability to identify responders and non-responders remains a high priority. Aim: To predict the response for induction chemotherapy in AML patients with (-7) and identify novel genomic signatures of response and resistance. Methods: Genomic data from 13 consecutive patients with (-7) were analyzed using the Cellworks Omics Biology Model (CBM) to generate patient-specific protein network models. All data was anonymized, de-identified and exempt from IRB review. For each model, disease simulations were performed and patients were segregated into HOXA-upregulated and HOXA-downregulated cohorts based on the simulation levels of HOXA5 and HOXA9. Digital drug simulations for induction chemotherapy were accomplished by measuring the impact of drug effect on a cell growth score, a composite of cell proliferation, viability and apoptosis indices. Each patient-specific model was analyzed to identify mechanisms underlying treatment outcomes. Results: 7/13 (54%) of (-7) patients failed to achieve remission after induction chemotherapy (Table 1) which highlighted that (-7) alone does not confer resistance to chemotherapy. CBM identified other genomic alterations that determine chemotherapy response, including DNA repair deficiency genes, mismatch repair (MMR), and homologous recombination repair (HRR) genes. DNA methylation and histone methylation (H3K27me) impacting HOXA gene expression, mainly HOXA5 and HOXA9, were identified as upstream regulators of DNA repair genes. Loss or reduced levels of EZH2 is associated with lower H3K27 methylation and thereby higher expression of HOXA5 and HOXA9 gene targets. High active levels of HOXA correlated with low rates of successful remission induction (22%, n=7) and lower activity levels of HOXA correlated with successful induction chemotherapy (100%, n=4) (Table 1). CBM identified that (-7) results in a decreased expression of EZH2, CARD11, EIF3, PMS2, HUS1, KMT2C (MLL3), CDK5 and IKZF1 genes. Since EZH2 abnormalities alone are not implicated in poor prognosis for AML patients, we sought other aberrations that prevent HOXA upregulation. Using CBM, we identified multiple accompanying aberrations which regulate HOXA genes. Deletions of KAT6A, ASXL1, DNMT3B, DNMT3L genes and high KMT2A-partial tandem duplication correspond to HOXA-upregulation whereas EED amplification, gain of function mutations in DNMT3A, mutations in IDH1/2, MYC and KAT6A amplification and KDM4A deletion result in HOXA-downregulation. Conclusion: Alterations of chromatin regulation have consequences for transcription factors that regulate expression of DNA repair genes. Under conditions where DNA repair is enhanced, induction chemotherapy was 78% less likely to effect remission in (-7) AML patients undergoing induction chemotherapy. Loss of H3K27 methylation associated with loss of PRC2 function by any means resulted in HOXA-upregulation and upregulation of DNA repair genes induced resistance to induction therapy. On the other hand, CBM analysis identified genetic signatures associated with a 100% remission rate from AML induction therapy despite the presence of (-7). Generation of H3K27me caused by PRC2 activation resulting from numerous mechanisms led to HOXA-downregulation and 100% response to induction therapy. Stratification of patients harboring (-7) by HOXA biomarker analysis could inform treatment planning, avoid drug-related adverse events and reduce treatment costs after validation with a larger prospective dataset. Disclosures Castro: Cellworks Group Inc: Consultancy. Watson:Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kumar:Cellworks Research India Private Limited: Current Employment. Nair:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Mohapatra:Cellworks Research India Private Limited: Current Employment. G:Cellworks Research India Private Limited: Current Employment. Agarwal:Cellworks Research India Private Limited: Current Employment. Suseela:Cellworks Research India Private Limited: Current Employment. Ganesh:Cellworks Research India Private Limited: Current Employment. Sauban:Cellworks Research India Private Limited: Current Employment. Kumar:Cellworks Research India Private Limited: Current Employment. Raman:Cellworks Research India Private Limited: Current Employment. Singh:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Lunkad:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Howard:Servier: Consultancy, Other: Speaker; Boston Scientific: Consultancy; Sanofi: Consultancy, Other: Speaker; EUSA Pharma: Consultancy; Cellworks: Consultancy.

Description: The tyrosine kinase JAK2 is a critical component of intracellular JAK/STAT cytokine signaling cascades that is prevalent in hematopoietic cells such as hematopoietic stem and progenitor cells (HSPCs), megakaryocytes (MKs), and platelets. Individuals expressing somatic activating JAK2 mutations such as JAK2V617F commonly develop myeloproliferative neoplasms (MPNs) associated with serious complications, including venous and arterial thrombosis, a leading cause of mortality. Here, we investigated the role of JAK2 in hemostasis and thrombosis using Jak2fl/flPf4-Cre (Jak2Plt-/-) mice specifically lacking JAK2 within the platelet lineage. Jak2Plt-/- mice developed severe thrombocytosis with a 5-fold increase in circulating platelet number, MK hyperplasia, and splenomegaly. Jak2Plt-/-platelets were of normal size and the expression of major membrane surface glycoproteins was indistinguishable from controls, except for the integrin β3, which was reduced by 20%. Despite the thrombocytosis, Jak2Plt-/- mice had a severe bleeding diathesis, as evidenced by: 1) prolonged tail bleeding time; 2) failure to occlude in a ferric chloride-induced carotid artery injury model; and 3) failure to form stable thrombi in a laser-induced cremaster muscle injury model. Jak2Plt-/- platelets spread poorly on immobilized collagen or on immobilized fibrinogen following GPVI stimulation with the collagen-related peptide (CRP). Jak2Plt-/- platelets had defective α-granule secretion and integrin αIIbβ3 activation following stimulation with CRP, but not thrombin, and showed aggregation defects with low-doses of CRP. Together, the data support a GPVI-specific impairment in platelets lacking JAK2, a notion that was supported by impaired intracellular signaling following GPVI stimulation, as assessed by protein tyrosine phosphorylation. Jak2Plt-/- platelets adhered poorly to type I collagen under arterial shear rates in whole blood. However, JAK2 deletion in platelets did not alter plasma von Willebrand factor (VWF) levels or botrocetin-mediated binding of plasma VWF to GPIbα. Together, the results underline a critical role for JAK2 in platelet GPVI signaling and hemostatic function, which likely contributes to venous and arterial thrombosis observed in patients with MPNs with the activating JAK2V617F mutation. Disclosures No relevant conflicts of interest to declare.