Cancer mRNA vaccines: clinical advances and future opportunities.

mRNA vaccines have been revolutionary in terms of their rapid development and prevention of SARS-CoV-2 infections during the COVID-19 pandemic, and this technology has considerable potential for application to the treatment of cancer. Compared with traditional cancer vaccines based on proteins or peptides, mRNA vaccines reconcile the needs for both personalization and commercialization in a manner that is unique to each patient but not beholden to their HLA haplotype. A further advantage of mRNA vaccines is the availability of engineering strategies to improve their stability while retaining immunogenicity, enabling the induction of complementary innate and adaptive immune responses. Thus far, no mRNA-based cancer vaccines have received regulatory approval, although several phase I-II trials have yielded promising results, including in historically poorly immunogenic tumours. Furthermore, many early phase trials testing a wide range of vaccine designs are currently ongoing. In this Review, we describe the advantages of cancer mRNA vaccines and advances in clinical trials using both cell-based and nanoparticle-based delivery methods, with discussions of future combinations and iterations that might optimize the activity of these agents.

KR158 spheres harboring slow-cycling cells recapitulate GBM features in an immunocompetent system.

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment-resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor-microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM-pathology, and explore specifically the SCC-immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

Expanded specific T cells to hypomutated regions of the SARS-CoV-2 using mRNA electroporated antigen-presenting cells.

The COVID-19 pandemic has caused about seven million deaths worldwide. Preventative vaccines have been developed including Spike gp mRNA-based vaccines that provide protection to immunocompetent patients. However, patients with primary immunodeficiencies, patients with cancer, or hematopoietic stem cell transplant recipients are not able to mount robust immune responses against current vaccine approaches. We propose to target structural SARS-CoV-2 antigens (i.e., Spike gp, Membrane, Nucleocapsid, and Envelope) using circulating human antigen-presenting cells electroporated with full length SARS-CoV-2 structural protein-encoding mRNAs to activate and expand specific T cells. Based on the Th1-type cytokine and cytolytic enzyme secretion upon antigen rechallenge, we were able to generate SARS-CoV-2 specific T cells in up to 70% of unexposed unvaccinated healthy donors (HDs) after 3 subsequent stimulations and in 100% of recovered patients (RPs) after 2 stimulations. By means of SARS-CoV-2 specific TCRß repertoire analysis, T cells specific to Spike gp-derived hypomutated regions were identified in HDs and RPs despite viral genomic evolution. Hence, we demonstrated that SARS-CoV-2 mRNA-loaded antigen-presenting cells are effective activating and expanding COVID19-specific T cells. This approach represents an alternative to patients who are not able to mount adaptive immune responses to current COVID-19 vaccines with potential protection across new variants that have conserved genetic regions.

Comment on Mahajan, S.; Schmidt, M.H.H. Distinct Lineage of Slow-Cycling Cells Amidst the Prevailing Heterogeneity in Glioblastoma. Cancers 2023, 15, 3843.

We greatly appreciate the interest, careful reading, and appraisal by Mahajan and Schmidt [...].

mRNA-based precision targeting of neoantigens and tumor-associated antigens in malignant brain tumors.

BACKGROUND: Despite advancements in the successful use of immunotherapy in treating a variety of solid tumors, applications in treating brain tumors have lagged considerably. This is due, at least in part, to the lack of well-characterized antigens expressed within brain tumors that can mediate tumor rejection; the low mutational burden of these tumors that limits the abundance of targetable neoantigens; and the immunologically "cold" tumor microenvironment that hampers the generation of sustained and productive immunologic responses. The field of mRNA-based therapeutics has experienced a boon following the universal approval of COVID-19 mRNA vaccines. mRNA-based immunotherapeutics have also garnered widespread interest for their potential to revolutionize cancer treatment. In this study, we developed a novel and scalable approach for the production of personalized mRNA-based therapeutics that target multiple tumor rejection antigens in a single therapy for the treatment of refractory brain tumors. METHODS: Tumor-specific neoantigens and aberrantly overexpressed tumor-associated antigens were identified for glioblastoma and medulloblastoma tumors using our cancer immunogenomics pipeline called Open Reading Frame Antigen Network (O.R.A.N). Personalized tumor antigen-specific mRNA vaccine was developed for each individual tumor model using selective gene capture and enrichment strategy. The immunogenicity and efficacy of the personalized mRNA vaccines was evaluated in combination with anti-PD-1 immune checkpoint blockade therapy or adoptive cellular therapy with ex vivo expanded tumor antigen-specific lymphocytes in highly aggressive murine GBM models. RESULTS: Our results demonstrate the effectiveness of the antigen-specific mRNA vaccines in eliciting robust anti-tumor immune responses in GBM hosts. Our findings substantiate an increase in tumor-infiltrating lymphocytes characterized by enhanced effector function, both intratumorally and systemically, after antigen-specific mRNA-directed immunotherapy, resulting in a favorable shift in the tumor microenvironment from immunologically cold to hot. Capacity to generate personalized mRNA vaccines targeting human GBM antigens was also demonstrated. CONCLUSIONS: We have established a personalized and customizable mRNA-therapeutic approach that effectively targets a plurality of tumor antigens and demonstrated potent anti-tumor response in preclinical brain tumor models. This platform mRNA technology uniquely addresses the challenge of tumor heterogeneity and low antigen burden, two key deficiencies in targeting the classically immunotherapy-resistant CNS malignancies, and possibly other cold tumor types.

Developing a computable phenotype for glioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common malignant brain tumor, and thus it is important to be able to identify patients with this diagnosis for population studies. However, this can be challenging as diagnostic codes are non-specific. The aim of this study was to create a computable phenotype (CP) for GBM from structured and unstructured data to identify patients with this condition in a large electronic health record (EHR). METHODS: We used the UF Health Integrated Data Repository, a centralized clinical data warehouse that stores clinical and research data from various sources within the UF Health system, including the EHR system. We performed multiple iterations to refine the GBM-relevant diagnosis codes, procedure codes, medication codes, and keywords through manual chart review of patient data. We then evaluated the performances of various possible proposed CPs constructed from the relevant codes and keywords. RESULTS: We underwent six rounds of manual chart reviews to refine the CP elements. The final CP algorithm for identifying GBM patients was selected based on the best F1-score. Overall, the CP rule "if the patient had at least 1 relevant diagnosis code and at least 1 relevant keyword" demonstrated the highest F1-score using both structured and unstructured data. Thus, it was selected as the best-performing CP rule. CONCLUSIONS: We developed a CP algorithm for identifying patients with GBM using both structured and unstructured EHR data from a large tertiary care center. The final algorithm achieved an F1-score of 0.817, indicating a high performance which minimizes possible biases from misclassification errors.

A study of generative large language model for medical research and healthcare.

There are enormous enthusiasm and concerns in applying large language models (LLMs) to healthcare. Yet current assumptions are based on general-purpose LLMs such as ChatGPT, which are not developed for medical use. This study develops a generative clinical LLM, GatorTronGPT, using 277 billion words of text including (1) 82 billion words of clinical text from 126 clinical departments and approximately 2 million patients at the University of Florida Health and (2) 195 billion words of diverse general English text. We train GatorTronGPT using a GPT-3 architecture with up to 20 billion parameters and evaluate its utility for biomedical natural language processing (NLP) and healthcare text generation. GatorTronGPT improves biomedical natural language processing. We apply GatorTronGPT to generate 20 billion words of synthetic text. Synthetic NLP models trained using synthetic text generated by GatorTronGPT outperform models trained using real-world clinical text. Physicians' Turing test using 1 (worst) to 9 (best) scale shows that there are no significant differences in linguistic readability (p = 0.22; 6.57 of GatorTronGPT compared with 6.93 of human) and clinical relevance (p = 0.91; 7.0 of GatorTronGPT compared with 6.97 of human) and that physicians cannot differentiate them (p < 0.001). This study provides insights into the opportunities and challenges of LLMs for medical research and healthcare.

CXCL9 recombinant adeno-associated virus (AAV) virotherapy sensitizes glioblastoma (GBM) to anti-PD-1 immune checkpoint blockade.

The promise of immunotherapy to induce long-term durable responses in conventionally treatment resistant tumors like glioblastoma (GBM) has given hope for patients with a dismal prognosis. Yet, few patients have demonstrated a significant survival benefit despite multiple clinical trials designed to invigorate immune recognition and tumor eradication. Insights gathered over the last two decades have revealed numerous mechanisms by which glioma cells resist conventional therapy and evade immunological detection, underscoring the need for strategic combinatorial treatments as necessary to achieve appreciable therapeutic effects. However, new combination therapies are inherently difficult to develop as a result of dose-limiting toxicities, the constraints of the blood-brain barrier, and the suppressive nature of the GBM tumor microenvironment (TME). GBM is notoriously devoid of lymphocytes driven in part by a paucity of lymphocyte trafficking factors necessary to prompt their recruitment, infiltration, and activation. We have developed a novel recombinant adeno-associated virus (AAV) gene therapy strategy that enables focal and stable reconstitution of the GBM TME with C-X-C motif ligand 9 (CXCL9), a powerful call-and-receive chemokine for cytotoxic T lymphocytes (CTLs). By precisely manipulating local chemokine directional guidance, AAV-CXCL9 increases tumor infiltration by CD8-postive cytotoxic lymphocytes, sensitizing GBM to anti-PD-1 immune checkpoint blockade (ICB). These effects are accompanied by immunologic signatures evocative of an inflamed and responsive TME. These findings support targeted AAV gene therapy as a promising adjuvant strategy for reconditioning GBM immunogenicity given its excellent safety profile, TME-tropism, modularity, and off-the-shelf capability, where focal delivery bypasses the constrains of the blood-brain barrier, further mitigating risks observed with high-dose systemic therapy.

Patterns and predictors of anxiety and depression symptom trajectories in patients diagnosed with primary brain tumors.

BACKGROUND: Patients with primary brain tumors (pPBTs) often exhibit heightened distress. This study assesses how symptoms of anxiety and depression change over time in pPBTs and identifies factors that may predict patients' symptom trajectories. METHODS: Ninety-nine adult pPBTs completed psychosocial assessments at neuro-oncology appointments over 6-18 months. Quality of life was assessed with the Functional Assessment of Cancer Therapy-Brain; symptoms of anxiety and depression were assessed with the Patient-Reported Outcomes Measurement Information System short forms. The prevalence of patients with clinically elevated symptoms and those who experienced clinically meaningful changes in symptoms throughout follow-up were examined. Linear mixed-effects models evaluated changes in symptoms over time at the group level, and latent class growth analysis (LCGA) evaluated changes in symptoms over time at the individual level. RESULTS: At enrollment, 51.5% and 32.3% of patients exhibited clinically elevated levels of anxiety and depression, respectively. Of patients with follow-up data (n = 74), 54.1% and 50% experienced clinically meaningful increases in anxiety and depression scores, respectively. There were no significant changes in anxiety or depression scores over time, but better physical, functional, and brain-cancer well-being predicted lower levels of anxiety and depression (p < 0.001). Five sub-groups of patients with distinct symptom trajectories emerged via LCGA. CONCLUSIONS: pPBTs commonly experience elevated symptoms of anxiety and depression that may fluctuate in clinically meaningful manners throughout the disease. Routine screening for elevated symptoms is needed to capture clinically meaningful changes and identify factors affecting symptoms to intervene on.

Bioconjugated liquid-like solid enhances characterization of solid tumor - chimeric antigen receptor T cell interactions.

Chimeric antigen receptor (CAR) T cell therapy has demonstrated remarkable success as an immunotherapy for hematological malignancies, and its potential for treating solid tumors is an active area of research. However, limited trafficking and mobility of T cells within the tumor microenvironment (TME) present challenges for CAR T cell therapy in solid tumors. To gain a better understanding of CAR T cell function in solid tumors, we subjected CD70-specific CAR T cells to a challenge by evaluating their immune trafficking and infiltration through a confined 3D microchannel network in a bio-conjugated liquid-like solid (LLS) medium. Our results demonstrated successful CAR T cell migration and anti-tumor activity against CD70-expressing glioblastoma and osteosarcoma tumors. Through comprehensive analysis of cytokines and chemokines, combined with in situ imaging, we elucidated that immune recruitment occurred via chemotaxis, and the effector-to-target ratio plays an important role in overall antitumor function. Furthermore, through single-cell collection and transcriptomic profiling, we identified differential gene expression among the immune subpopulations. Our findings provide valuable insights into the complex dynamics of CAR T cell function in solid tumors, informing future research and development in this promising cancer treatment approach. STATEMENT OF SIGNIFICANCE: The use of specialized immune cells named CAR T cells to combat cancers has demonstrated remarkable success against blood cancers. However, this success is not replicated in solid tumors, such as brain or bone cancers, mainly due to the physical barriers of these solid tumors. Currently, preclinical technologies do not allow for reliable evaluation of tumor-immune cell interactions. To better study these specialized CAR T cells, we have developed an innovative in vitro three-dimensional model that promises to dissect the interactions between tumors and CAR T cells at the single-cell level. Our findings provide valuable insights into the complex dynamics of CAR T cell function in solid tumors, informing future research and development in this promising cancer treatment approach.

Florida-California Cancer Research, Education and Engagement (CaRE2) Health Equity Center: Structure, Innovations, and Initial Outcomes.

INTRODUCTION: The Florida-California Cancer Research, Education, and Engagement (CaRE2) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE2 triad partnership. METHODS: CaRE2 serves diverse populations in Florida and California using a "molecule to the community and back" model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. RESULTS: Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE2-related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. CONCLUSION: The CaRE2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.

Association of Suppressive Myeloid Cell Enrichment with Aggressive Oropharynx Squamous Cell Carcinoma.

BACKGROUND: While immune-cell infiltrated tumors, such as human papillomavirus positive (HPV+) ororpharyngeal squamous cell carcinomas (OPSCC) have been associated with an improved clinical prognosis, there is evidence to suggest that OPSCCs are also subjected to increased immunoregulatory influence. The objective of this study was to assess whether patients with clinically aggressive OPSCC have a distinct immunosuppressive immune signature in the primary tumor. METHODS: This retrospective case-control study analyzed 37 pre-treatment tissue samples from HPV+ and HPV-negative OPSCC patients treated at a single institution. The cases were patients with known disease recurrence and the controls were patients without disease recurrence. An mRNA-expression immune-pathway profiling was performed, and correlated to clinical outcomes. The TCGA head and neck cancer database was utilized to make comparisons with the institutional cohort. RESULTS: In our cohort, HPV-negative and HPV+ patients with known disease recurrence both had significantly increased suppressive monoctyte/macrophage and granulocyte cell-expression-profile enrichment. Similar findings were found in the TCGA cohort when comparing HPV-negative to positive patients. CONCLUSIONS: our study demonstrates that patients with recurrent HPV+ OPSCC had suppressive monocyte/macrophage and granulocyte immune-cell enrichment, similar to those seen in the more aggressive HPV-negative OPSCC.

Three-Dimensional Bioconjugated Liquid-Like Solid (LLS) Enhance Characterization of Solid Tumor - Chimeric Antigen Receptor T cell interactions.

Cancer immunotherapy offers lifesaving treatments for cancers, but the lack of reliable preclinical models that could enable the mechanistic studies of tumor-immune interactions hampers the identification of new therapeutic strategies. We hypothesized 3D confined microchannels, formed by interstitial space between bio-conjugated liquid-like solids (LLS), enable CAR T dynamic locomotion within an immunosuppressive TME to carry out anti-tumor function. Murine CD70-specific CAR T cells cocultured with the CD70-expressing glioblastoma and osteosarcoma demonstrated efficient trafficking, infiltration, and killing of cancer cells. The anti-tumor activity was clearly captured via longterm in situ imaging and supported by upregulation of cytokines and chemokines including IFNg, CXCL9, CXCL10, CCL2, CCL3, and CCL4. Interestingly, target cancer cells, upon an immune attack, initiated an "immune escape" response by frantically invading the surrounding microenvironment. This phenomenon however was not observed for the wild-type tumor samples which remained intact and produced no relevant cytokine response. Single cells collection and transcriptomic profiling of CAR T cells at regions of interest revealed feasibility of identifying differential gene expression amongst the immune subpopulations. Complimentary 3D in vitro platforms are necessary to uncover cancer immune biology mechanisms, as emphasized by the significant roles of the TME and its heterogeneity.

mRNA challenge predicts brain cancer immunogenicity and response to checkpoint inhibitors.

To prospectively determine whether brain tumors will respond to immune checkpoint inhibitors (ICIs), we developed a novel mRNA vaccine as a viral mimic to elucidate cytokine release from brain cancer cells in vitro. Our results indicate that cytokine signatures following mRNA challenge differ substantially from ICI responsive versus non-responsive murine tumors. These findings allow for creation of a diagnostic assay to quickly assess brain tumor immunogenicity, allowing for informed treatment with ICI or lack thereof in poorly immunogenic settings.

mRNA aggregates harness danger response for potent cancer immunotherapy.

Messenger RNA (mRNA) has emerged as a remarkable tool for COVID-19 prevention but its use for induction of therapeutic cancer immunotherapy remains limited by poor antigenicity and a regulatory tumor microenvironment (TME). Herein, we develop a facile approach for substantially enhancing immunogenicity of tumor-derived mRNA in lipid-particle (LP) delivery systems. By using mRNA as a molecular bridge with ultrapure liposomes and foregoing helper lipids, we promote the formation of 'onion-like' multi-lamellar RNA-LP aggregates (LPA). Intravenous administration of RNA-LPAs mimics infectious emboli and elicits massive DC/T cell mobilization into lymphoid tissues provoking cancer immunogenicity and mediating rejection of both early and late-stage murine tumor models. Unlike current mRNA vaccine designs that rely on payload packaging into nanoparticle cores for toll-like receptor engagement, RNA-LPAs stimulate intracellular pathogen recognition receptors (RIG-I) and reprogram the TME thus enabling therapeutic T cell activity. RNA-LPAs were safe in acute/chronic murine GLP toxicology studies and immunologically active in client-owned canines with terminal gliomas. In an early phase first-in-human trial for patients with glioblastoma, we show that RNA-LPAs encoding for tumor-associated antigens elicit rapid induction of pro-inflammatory cytokines, mobilization/activation of monocytes and lymphocytes, and expansion of antigen-specific T cell immunity. These data support the use of RNA-LPAs as novel tools to elicit and sustain immune responses against poorly immunogenic tumors.

Oral IRAK-4 Inhibitor CA-4948 Is Blood-Brain Barrier Penetrant and Has Single-Agent Activity against CNS Lymphoma and Melanoma Brain Metastases.

PURPOSE: An ongoing challenge in cancer is the management of primary and metastatic brain malignancies. This is partly due to restrictions of the blood-brain barrier and their unique microenvironment. These challenges are most evident in cancers such as lymphoma and melanoma, which are typically responsive to treatment in systemic locations but resistant when established in the brain. We propose interleukin-1 receptor-associated kinase-4 (IRAK-4) as a potential target across these diseases and describe the activity and mechanism of oral IRAK-4 inhibitor CA-4948. EXPERIMENTAL DESIGN: Human primary central nervous system lymphoma (PCNSL) and melanoma brain metastases (MBM) samples were analyzed for expression of IRAK-4 and downstream transcription pathways. We next determined the central nervous system (CNS) applicability of CA-4948 in naïve and tumor-bearing mice using models of PCNSL and MBM. The mechanistic effect on tumors and the tumor microenvironment was then analyzed. RESULTS: Human PCNSL and MBM have high expression of IRAK-4, IRAK-1, and nuclear factor kappa B (NF-κB). This increase in inflammation results in reflexive inhibitory signaling. Similar profiles are observed in immunocompetent murine models. Treatment of tumor-bearing animals with CA-4948 results in the downregulation of mitogen-activated protein kinase (MAPK) signaling in addition to decreased NF-κB. These intracellular changes are associated with a survival advantage. CONCLUSIONS: IRAK-4 is an attractive target in PCNSL and MBM. The inhibition of IRAK-4 with CA-4948 downregulates the expression of important transcription factors involved in tumor growth and proliferation. CA-4948 is currently being investigated in clinical trials for relapsed and refractory lymphoma and warrants further translation into PCNSL and MBM.

Immunotherapy reverses glioma-driven dysfunction of immune system homeostasis.

BACKGROUND: Glioma-induced immune dysregulation of the hematopoietic system has been described in a limited number of studies. In this study, our group further demonstrates that gliomas interrupt the cellular differentiation programming and outcomes of hematopoietic stem and progenitor cells (HSPCs) in the bone marrow. HSPCs from glioma-bearing mice are reprogrammed and driven towards expansion of myeloid lineage precursors and myeloid-derived suppressor cells (MDSCs) in secondary lymphoid organs. However, we found this expansion is reversed by immunotherapy. Adoptive cellular therapy (ACT) has been demonstrably efficacious in multiple preclinical models of central nervous system (CNS) malignancies, and here we describe how glioma-induced dysfunction is reversed by this immunotherapeutic platform. METHODS: The impact of orthotopic KR158B-luc glioma on HSPCs was evaluated in an unbiased fashion using single cell RNAseq (scRNAseq) of lineage- cells and phenotypically using flow cytometry. Mature myeloid cell frequencies and function were also evaluated using flow cytometry. Finally, ACT containing total body irradiation, tumor RNA-pulsed dendritic cells, tumor-reactive T cells and HSPCs isolated from glioma-bearing or non-tumor-bearing mice were used to evaluate cell fate differentiation and survival. RESULTS: Using scRNAseq, we observed an altered HSPC landscape in glioma-bearing versus non-tumor-bearing mice . In addition, an expansion of myeloid lineage subsets, including granulocyte macrophage precursors (GMPs) and MDSCs, were observed in glioma-bearing mice relative to non-tumor-bearing controls. Furthermore, MDSCs from glioma-bearing mice demonstrated increased suppressive capacity toward tumor-specific T cells as compared with MDSCs from non-tumor-bearing hosts. Interestingly, treatment with ACT overcame these suppressive properties. When HSPCs from glioma-bearing mice were transferred in the context of ACT, we observed significant survival benefit and long-term cures in orthotopic glioma models compared with mice treated with ACT using non-glioma-bearing HSPCs.

Multimodal In Vivo Tracking of Chimeric Antigen Receptor T Cells in Preclinical Glioblastoma Models.

OBJECTIVES: Iron oxide nanoparticles have been used to track the accumulation of chimeric antigen receptor (CAR) T cells with magnetic resonance imaging (MRI). However, the only nanoparticle available for clinical applications to date, ferumoxytol, has caused rare but severe anaphylactic reactions. MegaPro nanoparticles (MegaPro-NPs) provide an improved safety profile. We evaluated whether MegaPro-NPs can be applied for in vivo tracking of CAR T cells in a mouse model of glioblastoma multiforme. MATERIALS AND METHODS: We labeled tumor-targeted CD70CAR (8R-70CAR) T cells and non-tumor-targeted controls with MegaPro-NPs, followed by inductively coupled plasma optical emission spectroscopy, Prussian blue staining, and cell viability assays. Next, we treated 42 NRG mice bearing U87-MG/eGFP-fLuc glioblastoma multiforme xenografts with MegaPro-NP-labeled/unlabeled CAR T cells or labeled untargeted T cells and performed serial MRI, magnetic particle imaging, and histology studies. The Kruskal-Wallis test was conducted to evaluate overall group differences, and the Mann-Whitney U test was applied to compare the pairs of groups. RESULTS: MegaPro-NP-labeled CAR T cells demonstrated significantly increased iron uptake compared with unlabeled controls ( P < 0.01). Cell viability, activation, and exhaustion markers were not significantly different between the 2 groups ( P > 0.05). In vivo, tumor T2* relaxation times were significantly lower after treatment with MegaPro-NP-labeled CAR T cells compared with untargeted T cells ( P < 0.01). There is no significant difference in tumor growth inhibition between mice injected with labeled and unlabeled CAR T cells. CONCLUSIONS: MegaPro-NPs can be used for in vivo tracking of CAR T cells. Because MegaPro-NPs recently completed phase II clinical trial investigation as an MRI contrast agent, MegaPro-NP is expected to be applied to track CAR T cells in cancer immunotherapy trials in the near future.

Cellular Cancer Immunotherapy Development and Manufacturing in the Clinic.

The transfusion of naturally derived or modified cellular therapies, referred to as adoptive cell therapy (ACT), has demonstrated clinical efficacy in the treatment of hematologic malignancies and metastatic melanoma. In addition, cellular vaccination, such as dendritic cell-based cancer vaccines, continues to be actively explored. The manufacturing of these therapies presents a considerable challenge to expanding the use of ACT as a viable treatment modality, particularly at academic production facilities. Furthermore, the expanding commercial interest in ACT presents new opportunities as well as strategic challenges for the future vision of cellular manufacturing in academic centers. Current trends in the production of ACT at tertiary care centers and prospects for improved manufacturing practices that will foster further clinical benefit are reviewed herein.

A large language model for electronic health records.

There is an increasing interest in developing artificial intelligence (AI) systems to process and interpret electronic health records (EHRs). Natural language processing (NLP) powered by pretrained language models is the key technology for medical AI systems utilizing clinical narratives. However, there are few clinical language models, the largest of which trained in the clinical domain is comparatively small at 110 million parameters (compared with billions of parameters in the general domain). It is not clear how large clinical language models with billions of parameters can help medical AI systems utilize unstructured EHRs. In this study, we develop from scratch a large clinical language model-GatorTron-using >90 billion words of text (including >82 billion words of de-identified clinical text) and systematically evaluate it on five clinical NLP tasks including clinical concept extraction, medical relation extraction, semantic textual similarity, natural language inference (NLI), and medical question answering (MQA). We examine how (1) scaling up the number of parameters and (2) scaling up the size of the training data could benefit these NLP tasks. GatorTron models scale up the clinical language model from 110 million to 8.9 billion parameters and improve five clinical NLP tasks (e.g., 9.6% and 9.5% improvement in accuracy for NLI and MQA), which can be applied to medical AI systems to improve healthcare delivery. The GatorTron models are publicly available at: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/models/gatortron_og .