An international learning collaborative phase 2 trial for haploidentical bone marrow transplant in sickle cell disease.

ABSTRACT: In the setting of a learning collaborative, we conducted an international multicenter phase 2 clinical trial testing the hypothesis that nonmyeloablative-related haploidentical bone marrow transplant (BMT) with thiotepa and posttransplant cyclophosphamide (PTCy) will result in 2-year event-free survival (no graft failure or death) of at least 80%. A total of 70 participants were evaluable based on the conditioning protocol. Graft failure occurred in 8 of 70 (11.4%) and only in participants aged <18 years; all had autologous reconstitution. After a median follow-up of 2.4 years, the 2-year Kaplan-Meier-based probability of event-free survival was 82.6%. The 2-year overall survival was 94.1%, with no difference between children and adult participants. After excluding participants with graft failure (n = 8), participants with engraftment had median whole blood donor chimerism values at days +180 and +365 after transplant of 100% (n = 58), respectively, and 96.6% (57/59) were off immunosuppression 1 year after transplant. The 1-year grade 3 to 4 acute graft-versus-host disease (GVHD) rate was 10%, and the 2-year moderate-severe chronic GVHD rate was 10%. Five participants (7.1%) died from infectious complications. We demonstrate that nonmyeloablative haploidentical BMT with thiotepa and PTCy is a readily available curative therapy for most adults, even those with organ damage, compared to the more expensive myeloablative gene therapy and gene editing. Additional strategies are required for children to decrease graft failure rates. The trial was registered at www.clinicaltrials.gov as #NCT01850108.

Velociraptor: Cross-Platform Quantitative Search Using Hallmark Cell Features.

A key challenge for single cell discovery analysis is to identify new cell types, describe them quantitatively, and seek these novel cells in new studies often using a different platform. Over the last decade, tools were developed to address identification and quantitative description of cells in human tissues and tumors. However, automated validation of populations at the single cell level has struggled due to the cytometry field's reliance on hierarchical, ordered use of features and on platform-specific rules for data processing and analysis. Here we present Velociraptor, a workflow that implements Marker Enrichment Modeling in three cross-platform modules: 1) identification of cells specific to disease states, 2) description of hallmark features for each cell and population, and 3) searching for cells matching one or more hallmark feature sets in a new dataset. A key advance is that Velociraptor registers cells between datasets, including between flow cytometry and quantitative imaging using different, overlapping feature sets. Four datasets were used to challenge Velociraptor and reveal new biological insights. Working at the individual sample level, Velociraptor tracked the abundance of clinically significant glioblastoma brain tumor cell subsets and characterized the cells that predominate in recurrent tumors as a close match for rare, negative prognostic cells originally observed in matched pre-treatment tumors. In patients with inborn errors of immunity, Velociraptor identified genotype-specific cells associated with GATA2 haploinsufficiency. Finally, in cross-platform analysis of immune cells in multiplex imaging of breast cancer, Velociraptor sought and correctly identified memory T cell subsets in tumors. Different phenotypic descriptions generated by algorithms or humans were shown to be effective as search inputs, indicating that cell identity need not be described in terms of per-feature cutoffs or strict hierarchical analyses. Velociraptor thus identifies cells based on hallmark feature sets, such as protein expression signatures, and works effectively with data from multiple sources, including suspension flow cytometry, imaging, and search text based on known or theoretical cell features.

An AI-based novel system for predicting respiratory support in COVID-19 patients through CT imaging analysis.

The proposed AI-based diagnostic system aims to predict the respiratory support required for COVID-19 patients by analyzing the correlation between COVID-19 lesions and the level of respiratory support provided to the patients. Computed tomography (CT) imaging will be used to analyze the three levels of respiratory support received by the patient: Level 0 (minimum support), Level 1 (non-invasive support such as soft oxygen), and Level 2 (invasive support such as mechanical ventilation). The system will begin by segmenting the COVID-19 lesions from the CT images and creating an appearance model for each lesion using a 2D, rotation-invariant, Markov-Gibbs random field (MGRF) model. Three MGRF-based models will be created, one for each level of respiratory support. This suggests that the system will be able to differentiate between different levels of severity in COVID-19 patients. The system will decide for each patient using a neural network-based fusion system, which combines the estimates of the Gibbs energy from the three MGRF-based models. The proposed system were assessed using 307 COVID-19-infected patients, achieving an accuracy of [Formula: see text], a sensitivity of [Formula: see text], and a specificity of [Formula: see text], indicating a high level of prediction accuracy.

Diagnostics, treatment and outcomes of cardiac sarcoidosis in a Norwegian cohort.

BACKGROUND: Evidence-based guidelines for cardiac sarcoidosis (CS) regarding use of second- and third-line agents, treatment duration, surveillance and prognostic factors are lacking. OBJECTIVE: To analyze the clinical presentation, diagnostics, treatment, monitoring and clinical outcomes in a Norwegian cohort. METHODS: Using discharge diagnoses between 2017 through 2020 from a large tertiary center, we identified 52 patients with CS. We performed a systematic chart review following a pre-specified checklist. The primary outcome of major cardiovascular events (MACE) was defined as a composite of cardiovascular hospitalization, defibrillator therapy, cardiac transplantation, or death. RESULTS: 18-fluorodeoxyglucose positron emission tomography (FDG-PET) showed pathological tracer uptake in 35/36 (97%) of immunosuppression-naïve patients. Immunosuppressive treatment was administered to 49/52 patients (94%) for a median of 43 (IQR 34) months; 69% were treated with second-line (methotrexate, azathioprine, mycophenolate mofetil) and 25% with third-line (rituximab, infliximab) agents, respectively. Rituximab reduced inflammation as assessed by interval FDG-PET imaging and was overall well tolerated. Median duration to first MACE was 6 (IQR 10) months and 17/23 patients (74%) experienced a MACE within 12 months from CS diagnosis. No mortality was recorded and 20% achieved full remission. Age below the median of 53 years at time of diagnosis was associated with an increased risk of a MACE. CONCLUSION: Long-term immunosuppression including a liberal use of non-steroidal agents, appeared essential in treating CS. Although the burden of cardiovascular events was substantial, the survival was excellent in this contemporary cohort. Prospective randomized studies are urgently needed to define the best therapy for these patients.

Peripheral T Cell Development and Immunophenotyping of Twins with Heterozygous FOXN1 Mutations.

The transcription factor FOXN1 plays an established role in thymic epithelial development to mediate selection of maturing thymocytes. Patients with heterozygous loss-of-function FOXN1 variants are associated with T cell lymphopenia at birth and low TCR excision circles that can ultimately recover. Although CD4+ T cell reconstitution in these patients is not completely understood, a lower proportion of naive T cells in adults has suggested a role for homeostatic proliferation. In this study, we present an immunophenotyping study of fraternal twins with low TCR excision circles at birth. Targeted primary immunodeficiency testing revealed a heterozygous variant of uncertain significance in FOXN1 (c.1205del, p.Pro402Leufs*148). We present the immune phenotypes of these two patients, as well as their father who carries the same FOXN1 variant, to demonstrate an evolving immune environment over time. While FOXN1 haploinsufficiency may contribute to thymic defects and T cell lymphopenia, we characterized the transcriptional activity and DNA binding of the heterozygous FOXN1 variant in 293T cells and found the FOXN1 variant to have different effects across several target genes. These data suggest multiple mechanisms for similar FOXN1 variants pathogenicity that may be mutation specific. Increased understanding of how these variants drive transcriptional regulation to impact immune cell populations will guide the potential need for therapeutics, risk for infection or autoimmunity over time, and help inform clinical decisions for other variants that might arise.