Citations

Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. Methods: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record–derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier; NCT03394859.

Abstract This international guideline proposes improving clozapine package inserts worldwide by using ancestry-based dosing and titration. Adverse drug reaction (ADR) databases suggest that clozapine is the third most toxic drug in the United States (US), and it produces four times higher worldwide pneumonia mortality than that by agranulocytosis or myocarditis. For trough steady-state clozapine serum concentrations, the therapeutic reference range is narrow, from 350 to 600 ng/mL with the potential for toxicity and ADRs as concentrations increase. Clozapine is mainly metabolized by CYP1A2 (female non-smokers, the lowest dose; male smokers, the highest dose). Poor metabolizer status through phenotypic conversion is associated with co-prescription of inhibitors (including oral contraceptives and valproate), obesity, or inflammation with C-reactive protein (CRP) elevations. The Asian population (Pakistan to Japan) or the Americas’ original inhabitants have lower CYP1A2 activity and require lower clozapine doses to reach concentrations of 350 ng/mL. In the US, daily doses of 300–600 mg/day are recommended. Slow personalized titration may prevent early ADRs (including syncope, myocarditis, and pneumonia). This guideline defines six personalized titration schedules for inpatients: 1) ancestry from Asia or the original people from the Americas with lower metabolism (obesity or valproate) needing minimum therapeutic dosages of 75–150 mg/day, 2) ancestry from Asia or the original people from the Americas with average metabolism needing 175–300 mg/day, 3) European/Western Asian ancestry with lower metabolism (obesity or valproate) needing 100–200 mg/day, 4) European/Western Asian ancestry with average metabolism needing 250–400 mg/day, 5) in the US with ancestries other than from Asia or the original people from the Americas with lower clozapine metabolism (obesity or valproate) needing 150–300 mg/day, and 6) in the US with ancestries other than from Asia or the original people from the Americas with average clozapine metabolism needing 300–600 mg/day. Baseline and weekly CRP monitoring for at least four weeks is required to identify any inflammation, including inflammation secondary to clozapine rapid titration.

Shared decision making (SDM) has been advocated to improve patient care, patient decision acceptance, patient-provider communication, patient motivation, adherence, and patient reported outcomes. Documentation of SDM is endorsed in several society guidelines and is a condition of reimbursement for selected cardiovascular and cardiac arrhythmia procedures. However, many clinicians argue that SDM already occurs with clinical encounter discussions or the process of obtaining informed consent and note the additional imposed workload of using and documenting decision aids without validated tools or evidence that they improve clinical outcomes. In reality, SDM is a process and can be done without decision tools, although the process may be variable. Also, SDM advocates counter that the low-risk process of SDM need not be held to the high bar of demonstrating clinical benefit and that increasing the quality of decision making should be sufficient. Our review leverages a multidisciplinary group of experts in cardiology, cardiac electrophysiology, epidemiology, and SDM, as well as a patient advocate. Our goal is to examine and assess SDM methodology, tools, and available evidence on outcomes in patients with heart rhythm disorders to help determine the value of SDM, assess its possible impact on electrophysiological procedures and cardiac arrhythmia management, better inform regulatory requirements, and identify gaps in knowledge and future needs.

On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton‐density fat fraction, and cardiacT1. These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.

Abstract Introduction Several studies reported that AML patients who remain in long-term remission after allogeneic transplant (allo-HCT) or autologous transplant (auto-HCT) have a shorter life expectancy, compared to the general population. However, little is known about the life expectancy of adult long-term survivors of AML who were treated with chemotherapy without HCT and, there have been no comparisons with survival among the general population. The current study reports on the life expectancy of AML patients who survived 3 years in complete remission (CR) after treatment without HCT, and compared this to the gender- and age-matched normal population. At 3 years in CR, the incidence of recurrence is exceedingly low (3%; Watts JM, Leuk Res 2014) minimizing the impact of relapse on the long-term survival. Methods Between 1984 and 2008, 3,012 patients, aged 15 years and older, with untreated AML entered 9 consecutive, phase II and III, ECOG-ACRIN trials (E3483, PC486, E3489, E1490, E3993, E4995, E3997, E3999, E1900). Patients in CR and relapse-free at 3 years are included in the analysis . Minimal cytogenetic information was available in the early protocols (E1490, E3483, PC486). A Kaplan-Meier plot was generated for the three groups, allo, auto and no HCT, censoring for patients alive at last contact. Univariate and multivariate cox proportional hazard regression models were generated, considering death as an event. For comparison of long-term outcomes, patients were grouped together by age and matched to a normative population mortality rate. Subjects were also grouped by gender and treatment allowing for separate analysis of these groups with the no HCT group as the main group of interest. The normative population comparator of expected deaths was derived using mortality rates from United State CDC life table data. The median year was derived by calculating the person-years for each calendar year that patients were followed. To calculate the expected deaths for each age group, person-years was calculated by tabulating the years lived in each age group for all subjects. Each year of follow-up for AML patient was counted as one person year, and the tabulated bin corresponded with their age at the time. Person-years was then multiplied by the matching mortality rate. Chi-square statistics were derived using expected and observed deaths and then summed for each gender and treatment. The final comparison was of mortality rates since diagnosis in the 3-year alive and relapse-free AML patient population vs the normative population. To produce plots of mortality from diagnosis, person-years was tabulated for every year since diagnosis by treatment. The person-years were tabulated into 2-year bins. The US life tables from the CDC were used to generate a population mortality rate from diagnosis. Results A total of 503 adult AML patients in 3 year CR with a mean age of 42.9 years (15-79) were identified; 78 underwent allo, 110 auto and 315 did not undergo transplantation. The patients in the groups differed in age (p<.001) and cytogenetics (p=.01). The multivariate model showed equivalent hazards of death to the 3 groups. Observed deaths and person-years were given by age group, gender, and treatment group and each were matched to a mortality rate from the United State CDC life table data that matched the median year of each treatment group. A chi square test for each group compared the derived expected to observed deaths. In every treatment group, patients had a shorter survival compared to their age- and gender- matched general population (p-value of 0.004 for the auto-HCT and <0.001 for both allo-HSCT and no transplant groups). Table 1, selected only for the no HCT group, demonstrates the mortality rates by age and gender. Figure 1 indicates that AML patients who have survived relapse-free for at least 3 years continue to have higher mortality rates compared to the normative population for up to 14 years. This finding is not altered even if the very small number of patients who die from late relapse (>3 years from diagnosis) are removed from the analysis (data not shown) Conclusions Patients with AML who remain in CR at 3 years, do not have a normal life expectancy, even if they do not undergo HCT. The shorter life expectancy observed following an HCT may, at least in part, be related to the prior intensive therapy or other predisposing factors (e.g. CHIP) of the leukemia, rather than the transplant procedure itself. Figure 1 Figure 1. Disclosures Luger: Syros: Honoraria; Agios: Honoraria; Daiichi Sankyo: Honoraria; Jazz Pharmaceuticals: Honoraria; Brystol Myers Squibb: Honoraria; Acceleron: Honoraria; Astellas: Honoraria; Pfizer: Honoraria; Onconova: Research Funding; Celgene: Research Funding; Biosight: Research Funding; Hoffman LaRoche: Research Funding; Kura: Research Funding. Lazarus: Bristol Myer Squibb: Membership on an entity's Board of Directors or advisory committees. Douer: Amgen: Consultancy, Speakers Bureau; Servier: Consultancy, Speakers Bureau; Adaptive: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company, Speakers Bureau; Jazz: Consultancy. Tallman: Syros: Membership on an entity's Board of Directors or advisory committees; Kura: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Biosight: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Orsenix: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Rafael Pharmaceuticals: Research Funding; Glycomimetics: Research Funding; Biosight: Research Funding; Orsenix: Research Funding; Abbvie: Research Funding; NYU Grand Rounds: Honoraria; Mayo Clinic: Honoraria; UC DAVIS: Honoraria; Northwell Grand Rounds: Honoraria; NYU Grand Rounds: Honoraria; Danbury Hospital Tumor Board: Honoraria; Acute Leukemia Forum: Honoraria; Miami Leukemia Symposium: Honoraria; New Orleans Cancer Symposium: Honoraria; ASH: Honoraria; NCCN: Honoraria. Litzow: Pluristem: Research Funding; Biosight: Other: Data monitoring committee; AbbVie: Research Funding; Actinium: Research Funding; Astellas: Research Funding; Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Amgen: Research Funding.

Abstract Background Several therapies are recommended by NCCN/ESMO guidelines for autologous stem cell transplant (ASCT)-ineligible patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL). In the single-arm, Phase II L-MIND study (NCT02399085), the chemotherapy-free regimen tafasitamab + lenalidomide (LEN) demonstrated efficacy for this patient population. In the absence of randomized clinical trial data, RE-MIND2 (NCT04697160), an observational, retrospective cohort study, compared patient outcomes from L-MIND with matched patient populations treated with NCCN/ESMO recommended therapies for ASCT-ineligible patients with R/R DLBCL. Methods Data were retrospectively collected between 1 April and 13 November 2020 from academic and public hospitals, as well as private practices in North America, Europe and Asia Pacific. To ensure consistency with L-MIND I/E criteria, patients aged ≥18 years with histologically confirmed DLBCL and who had received ≥2 systemic therapies for DLBCL (including ≥1 anti-CD20 therapy) were enrolled. For the main analysis, patients from the L-MIND tafasitamab + LEN cohort were matched with patients from the RE-MIND2 observational cohort using estimated propensity score-based 1:1 nearest neighbor matching, balanced for six baseline characteristics: age (<70 vs ≥70 years), refractoriness to last line of therapy (yes vs no), number of prior lines of therapy (1 vs 2/3), history of primary refractoriness (yes vs no), prior ASCT (yes vs no), and Eastern Cooperative Oncology Group performance status (0-1 vs ≥2). A sensitivity analysis was performed using an inverse probability of treatment weighting method calculating the average effect of the treatment on the treated, to generate balanced cohorts based on nine baseline characteristics: age, refractoriness to last line of therapy, number of previous lines of therapy, history of primary refractoriness, prior ASCT, Ann Arbor Stage (I/II vs III/IV), elevated LDH (yes vs no), neutropenia (yes vs no), and anemia (yes vs no). Additional sensitivity analyses accounting for missing baseline characteristics using multiple imputation technique were performed. Data are presented for tafasitamab + LEN versus polatuzumab vedotin + bendamustine + rituximab (pola-BR), rituximab + LEN (R2), and CD19 CAR-T therapies (CAR-T). The primary endpoint was overall survival (OS). Secondary endpoints included objective response rate (ORR), complete response rate, progression-free survival and duration of response. Results Of 3,454 patients enrolled from 200 sites, 106, 106, and 149 patients were treated with pola-BR, R2, and CAR-T, respectively. For the comparative analysis, matched patient pairs were created using 1:1 nearest neighbor matching with a caliper. Matched pairs consisted of: tafasitamab + LEN vs pola-BR, n=24 pairs; vs R2, n=33 pairs; and vs CAR-T, n=37 pairs. A significant OS benefit was associated with tafasitamab + LEN compared to pola-BR (HR: 0.44, 95% confidence interval [CI]: 0.20-0.96; p=0.038) and R2 (HR=0.44, 95% CI: 0.22-0.84; p=0.014) (Figure 1A-B). There was no significant difference in OS benefit between tafasitamab + LEN and CAR-T (HR=0.95, 95% CI: 0.47-1.91; p=0.891) (Figure 1C). ORR was 62.5% (15/24) for tafasitamab + LEN vs 58.3% (14/24) for pola-BR (p=1.000), 63.6% (21/33) vs 30.3% (10/33) for R2 (p=0.013), and 59.5% (22/37) vs 75.7% (28/37) for CAR-T (p=0.214). Improved outcomes were also observed with tafasitamab + LEN for other secondary endpoints (Table 1). Results are consistent with those obtained in the sensitivity analyses. Conclusions The results of this retrospective cohort analysis suggest that the novel tafasitamab + LEN combination may significantly improve health outcomes, with a prolonged survival benefit for ASCT-ineligible R/R DLBCL patients, relative to NCCN/ESMO recommended therapies. Tafasitamab + LEN improved survival outcomes compared with pola-BR and R2 in closely matched patient populations. Comparable outcomes were observed for tafasitamab + LEN vs CAR-T. Although based on limited patient numbers, these data may be clinically relevant in the context of emerging therapies for R/R DLBCL. While this study design does not replace randomized data, it remains more rigorous than inter-trial comparison. The limitations of comparing clinical trial and matched retrospective real-world data will be discussed. Funding: MorphoSys AG. Figure 1 Figure 1. Disclosures Nowakowski: Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding. Joffe: AstraZeneca. Epizyme: Consultancy. Fleury: Abbvie, Astrazeneca, BMS, Celgene, Janssen, Kite-Gilead, Merck, Novartis, Roche, Seattle Genetics: Other: conference and advisory role. Peters: AbbVie, Incyte: Consultancy, Honoraria. Greil: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; AstraZeneca: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; MSD: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Daiichi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Sankyo: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Other: Travel, Accommodations, Expenses, Research Funding; Sandoz: Honoraria, Research Funding. Ku: Roche: Consultancy; Antegene: Consultancy; Genor Biopharma: Consultancy. Marks: Kite/Gilead: Membership on an entity's Board of Directors or advisory committees; AbbVie: Other: Meeting attendance; Kite/Gilead: Honoraria; Merck: Consultancy. Kim: AstraZeneca: Research Funding. Zinzani: BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; EUSA Pharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; ADC Therapeutics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Merck Sharp & Dohme: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celltrion: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kyowa Kirin: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Verastem: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; TG Therapeutics Inc: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; ImmuneDesign: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Portola: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Trotman: Beigene: Research Funding; Celgene: Research Funding; Bristol Myers Squibb: Research Funding; Roche: Research Funding; Janssen: Research Funding; PCYC Pharmacyclics: Research Funding. Sabatelli: Incyte: Current Employment, Current equity holder in publicly-traded company. Huang: MorphoSys: Current Employment. Waltl: MorphoSys: Current Employment. Winderlich: MorphoSys: Current Employment, Current equity holder in publicly-traded company. Ambarkhane: MorphoSys: Current Employment, Other: Support for attending meetings/travel. Kurukulasuriya: MorphoSys: Current Employment, Current equity holder in publicly-traded company, Other: Support for attending meetings/travel. Cordoba: Pfizer: Research Funding; Kyowa-Kirin: Membership on an entity's Board of Directors or advisory committees; Roche: 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; ADCTherapeutics: Membership on an entity's Board of Directors or advisory committees; BMS: 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; Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Hess: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead/Kite: Research Funding; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genmab: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; EUSA: Honoraria, Membership on an entity's Board of Directors or advisory committees. Salles: Miltneiy: Consultancy; Novartis: Consultancy; Morphosys: Consultancy, Honoraria; Janssen: Consultancy; Genentech/Roche: Consultancy; Kite/Gilead: Consultancy; Regeneron: Consultancy, Honoraria; Velosbio: Consultancy; Takeda: Consultancy; Allogene: Consultancy; Ipsen: Consultancy; Loxo: Consultancy; Rapt: Consultancy; Genmab: Consultancy; Incyte: Consultancy; Epizyme: Consultancy, Honoraria; Debiopharm: Consultancy; BMS/Celgene: Consultancy; Beigene: Consultancy; Abbvie: Consultancy, Honoraria; Bayer: Honoraria.

Abstract Interferon-alpha (IFN), the first approved immunotherapy for cancer, remains an effective therapy for patients with myeloproliferative neoplasms (MPN). The mechanisms of action of IFN on MPN cells are poorly understood, particularly in patients with CALR mutated (MUT) MPNs, who often exhibit clinical but not molecular responses. Previously, by developing Genotyping of Transcriptomes (GoT) that captures mutation status and single-cell RNA-seq (scRNA-seq) in high-throughput, we observed that CALR mutations led to cell identity-dependent effects on CD34 + cells, including a strong megakaryocytic progenitor (MkP) differentiation bias and fitness. We hypothesized that the IFN effects may be cell identity and mutation status dependent; thus we applied GoT to serial bone marrow aspirates (BM) from 5 patients with CALRmutated ET treated with pegylated-IFN-alfa2a who participated in MPD-RC-111/112 clinical trials. To capture the transcriptional impact of IFN, we removed experimental batch effects with Cell Hashing, in which CD34 + cells from serial BM were uniquely labeled and combined for the same GoT experiment (Fig. 1A). Cell clustering based on transcriptomic data alone revealed that the cells on active treatment clustered based on cell identity and IFN effects (Fig. 1B). When off therapy for 3 weeks, the strong transcriptional effects of IFN were largely lost (Fig. 1B). Next, we batch corrected and integrated across time points for each BM sample (Fig. 1C). We observed that IFN caused large shifts in the composition of wildtype (WT) and MUT cell subsets (Fig. 1D). IFN resulted in a dramatic expansion of WT lymphoid progenitors with a corresponding diminution of other progenitors (Fig. 1E). MUT cells at baseline were enriched for MkPs, compared to WT cells; after treatment, we observed an expansion of the immature myeloid (IMP) and neutrophil progenitors, with a less striking expansion of lymphoid progenitors (Fig. 1E). As IFN has been reported to induce cell cycling of murine hematopoietic progenitor cells, we examined whether a differential increase in proliferation by IFN underlies the differentiation shifts in WT and MUT cells. Cell cycle gene expression of ProB cells increased after treatment similarly in MUT and WT cells, while cell cycle expression of IMPs was increased to a greater extent in MUT cells (Fig. 1F), consistent with the differential shifts in populations. Next, we performed differential expression analysis between baseline and treated WT and MUT cells, respectively. We observed enrichment of the IFN pathways post-therapy, whereas TNF-a signaling was downregulated (Fig. 1G). Uniquely in the MUT cells, TGF-b signaling was downregulated, which may underlie improvements in marrow fibrosis following IFN therapy (Fig. 1G). Finally, as the differentiation biases of IFN persisted after discontinuation, we hypothesized that IFN results in chromatin remodeling of the earliest hematopoietic stem progenitor cells (HSPCs), with respect to transcription factor (TF) accessibility. We leveraged single nuclei chromatin accessibility (snATAC-seq) as a powerful measure of TF regulatory activities. We developed GoT-ATAC, an adaptation of the Multiome platform (10x Genomics), to capture snRNA-seq, snATAC-seq and somatic genotyping within the same cells in high-throughput (Fig. 1H). We applied GoT-ATAC to CD34 + cells from the same clinical trial cohorts (Fig. 1I, n = 3 patients: 3 baseline, 2 treated) and identified the expected enrichment of IRFs and STAT2 in treated HSPCs (Fig. 1J). Accessibility of BCL11A, critical for early lymphoid development, was increased in treated MUT and WT HSPCs. We also identified enhanced motif accessibility of PU.1 which can associate with IRF and is essential for myeloid and lymphoid differentiation. Uniquely within the treated MUT cells, we observed enhanced CEBPA motif enrichment, which regulates myeloid differentiation, together with PU.1. In conclusion, GoT revealed that IFN reshapes the differentiation landscape by promoting early lymphoid development and, uniquely in MUT cells, myeloid differentiation, providing a novel mechanism of actions underlying the effects of IFN in MPN patients. Downregulations of TNF-a and TGF-b signaling were other key molecular consequences of IFN. Lastly, GoT-ATAC demonstrated that IFN governs master regulators of hematopoietic differentiation as a function of the underlying mutational status. Figure 1 Figure 1. Disclosures Mimitou: Immunai: Current Employment. Smibert: Immunai: Current Employment. Hoffman: AbbVie Inc.: Other: Data Safety Monitoring Board, Research Funding; Novartis: Other: Data Safety Monitoring Board, Research Funding; Protagonist Therapeutics, Inc.: Consultancy; Kartos Therapeutics, Inc.: Research Funding.

Abstract Background: Sickle cell disease (SCD) is a group of genetic disorders in which sickle hemoglobin polymerizes under deoxygenation, altering red blood cell (RBC) morphology and behavior. The properties of sickle RBCs contribute to increased viscosity of blood and occurrence of vaso-occlusions, a major aspect of SCD pathophysiology. Voxelotor is a novel FDA-approved treatment for SCD which modulates hemoglobin O 2 affinity, and while its known mechanism inhibits sickle polymerization, the impact on other aspects of SCD pathophysiology remain unknown. Thus, despite the new treatment option, highly variable clinical manifestation continues to be a hallmark of sickle cell and there is consequently a need to optimize the use of current therapies based on patient-specific factors. In this work, we leverage datasets generated from a unique microfluidic assay that measures blood flow behavior under varying oxygen tension in conjunction with novel statistical approaches to model and assess sources of variability in sickle blood flow response to voxelotor. Methods: RBCs from patients with SCD (n=28) were treated with voxelotor at 500 uM concentration. Treated samples and untreated controls were perfused through a microfluidic platform that dynamically modulates oxygen tension and measures flow velocity (Wood et al, 2012; Valdez et al, 2019). The area between curves (ABC) of the normalized velocity across the range of oxygen tension between treated and control conditions was calculated to quantify the effect of voxelotor for each sample (figure 1). A paired t-test was used to assess the difference in response between treated and untreated samples. Where available, clinical data including the hemoglobin fractions and complete blood count (CBC) were collected for each sample as predictor variables, and partial least squares regression (PLSR) modeling was used to assess the correlation of predictors and responses. Results: Voxelotor increased the velocity ABC from untreated to treated conditions (p<.0001). We observed that there were differences in response for velocity ABC between sickle cell genotypes (figure 2). Thus, generating separate PLSR models for distinct SCD genotypes revealed differences in sets of clinical factors that explained the most variance in response to voxelotor treatment. A 2-component model was constructed for the HbSC samples (n=6) that best explained variance in the data and had good predictive abilities (R 2X=.69, R 2Y=.97, Q 2=.74). Within this subset, clustering of variables related to hemolysis and inflammation were observed (figure 3). An equivalent model constructed for the HbSS samples (n=15) characterized the predictor variables but lacked predictive power of the response (R 2X=.74, R 2Y=.25, Q 2=.-0.21). Response to voxelotor for this model was most strongly correlated with HbA. Due to low sample size (n=2 samples with full set of predictors), predictive modeling was not performed for HbSβ 0 samples, however, these samples responded the least to voxelotor treatment. Conclusions: Our analysis quantified patient-specific differences in the blood flow response to voxelotor, showing a wide variability in response despite treatment by the same drug concentration. Genotype-specific multivariable models that take into account easily measurable clinical variables such as the CBC have the potential to explain the variability in patient response to voxelotor treatment. In HbSC samples, the WBC, platelet, and reticulocyte counts were highly correlated and strong predictors of response to voxelotor, which may point to markers of hemolysis and inflammation being useful in determining patients that can be optimally treated with this drug. In HbSS, response to voxelotor was mainly inversely correlated with HbA levels, which is a surrogate marker for blood transfusions, indicating that the effect of voxelotor is lessened for patients who are receiving transfusions. However, the low R2Y of this model highlights the clinical variability in this SCD genotype and consequent need for additional biomarkers of disease severity. In conclusion, our hybrid experimental-computational approach is able to identify clinical factors that highly impact the response of patient blood samples to treatment with voxelotor for HbSC patients, and highlights the need for precision therapy recommendations in SCD. Figure 1 Figure 1. Disclosures Lam: Sanguina, Inc.: Current holder of individual stocks in a privately-held company. Kemp: Parthenon Therapeutics: Membership on an entity's Board of Directors or advisory committees.