18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is one of the most widely used imaging techniques to detect multiple myeloma (MM). Intracellular FDG uptake depicts in vivo metabolic activity, which can be seen in both malignant and nonmalignant cells, resulting in limited sensitivity and specificity. Our group showed preclinically that tracing MM dissemination using a CD38-directed human antibody, daratumumab, that is radioconjugated with 64Cu via the chelator DOTA (64Cu-daratumumab), led to improved sensitivity and specificity over that of FDG. Here, we report the results of a phase 1 trial designed to (1) assess the safety and feasibility of 64Cu-daratumumab PET/CT and (2) preliminarily evaluate and characterize the ability of 64Cu-daratumumab to accurately detect or exclude MM lesions. A total of 12 daratumumab-naive patients were imaged. Prior to the injection of 15 mCi/5 mg of 64Cu-daratumumab, patients were treated with 0 (n = 3), 10 (n = 3), 45 (n = 3), or 95 mg (n = 3) of unlabeled daratumumab to assess its effect on image quality. No significant adverse events were observed from either unlabeled daratumumab or 64Cu-daratumumab. Of the dose levels tested, 45 mg unlabeled daratumumab was the most optimal in terms of removing background signal without saturating target sites. 64Cu-daratumumab PET/CT provided safe whole-body imaging of MM. A trial comparing the sensitivity and specificity of 64Cu-daratumumab PET/CT with that of FDG PET/CT is planned. This trial was registered at www.clinicaltrials.gov as #NCT03311828.

Chimeric antigen receptor T cell (CAR-T) therapy is an emerging strategy to improve treatment outcomes for recurrent high-grade glioma, a cancer that responds poorly to current therapies. Here we report a completed phase I trial evaluating IL-13Rα2-targeted CAR-T cells in 65 patients with recurrent high-grade glioma, the majority being recurrent glioblastoma (rGBM). Primary objectives were safety and feasibility, maximum tolerated dose/maximum feasible dose and a recommended phase 2 dose plan. Secondary objectives included overall survival, disease response, cytokine dynamics and tumor immune contexture biomarkers. This trial evolved to evaluate three routes of locoregional T cell administration (intratumoral (ICT), intraventricular (ICV) and dual ICT/ICV) and two manufacturing platforms, culminating in arm 5, which utilized dual ICT/ICV delivery and an optimized manufacturing process. Locoregional CAR-T cell administration was feasible and well tolerated, and as there were no dose-limiting toxicities across all arms, a maximum tolerated dose was not determined. Probable treatment-related grade 3+ toxicities were one grade 3 encephalopathy and one grade 3 ataxia. A clinical maximum feasible dose of 200 × 10⁶ CAR-T cells per infusion cycle was achieved for arm 5; however, other arms either did not test or achieve this dose due to manufacturing feasibility. A recommended phase 2 dose will be refined in future studies based on data from this trial. Stable disease or better was achieved in 50% (29/58) of patients, with two partial responses, one complete response and a second complete response after additional CAR-T cycles off protocol. For rGBM, median overall survival for all patients was 7.7 months and for arm 5 was 10.2 months. Central nervous system increases in inflammatory cytokines, including IFNγ, CXCL9 and CXCL10, were associated with CAR-T cell administration and bioactivity. Pretreatment intratumoral CD3 T cell levels were positively associated with survival. These findings demonstrate that locoregional IL-13Rα2-targeted CAR-T therapy is safe with promising clinical activity in a subset of patients. ClinicalTrials.gov Identifier: NCT02208362 .

Objective

Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.

Materials and methods

The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.

Results

Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.

Conclusions

The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.