Multi-dimensional immunotyping of human NF1-associated peripheral nerve sheath tumors uncovers tumor-associated macrophages as key drivers of immune evasion in the tumor microenvironment.

PURPOSE: Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas and the leading cause of mortality in individuals with neurofibromatosis type 1 (NF1). Despite many clinical trials, outcomes for patients with MPNST have remained stagnant and most succumb to their disease; thus, novel therapeutic approaches are needed. A better understanding of the MPNST immune ecosystem will aid in the development of strategies to activate the immune system against the tumor. Herein, we profile the tumor immune microenvironment (TIME) in NF1-associated peripheral nerve sheath tumors (PNST) to discover insights on the role that tumor-infiltrating immune cells play in malignant transformation. EXPERIMENTAL DESIGN: Utilizing fresh and formalin-fixed, paraffin-embedded tissue from patients diagnosed with NF1-PNST, we dissected the TIME by using immunohistochemistry, multiparameter flow cytometry, and comparative transcriptomic studies. RESULTS: Immunophenotyping confirmed increased immune cells infiltration during malignant progression, with a predominance of infiltrating myeloid cells, particularly CD163+ tumor-associated macrophages (TAM). The T cells within MPNST exhibited signs of tumor activation, characterized by high PD-1 expression. Additionally, MPNST specimens demonstrated elevated levels of immunosuppressive TAM, with heightened PD-L1 expression. The proportion of CD163+ myeloid cells within the TIME correlated with poorer progression free survival. Notably, loss of H3K27 trimethylation correlated with low immune cell infiltration in MPNST. CONCLUSIONS: Malignant transformation of NF1-PNST is characterized by an immunosuppressive microenvironment comprising of TAM with high expression of PD-L1, which are associated with inferior outcomes. These findings suggest a clinical potential of immune modulating therapeutics that can unleash an anti-tumor immune response.

Community assessment of methods to deconvolve cellular composition from bulk gene expression.

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

Obesity-associated microglial inflammatory activation paradoxically improves glucose tolerance.

Hypothalamic gliosis associated with high-fat diet (HFD) feeding increases susceptibility to hyperphagia and weight gain. However, the body-weight-independent contribution of microglia to glucose regulation has not been determined. Here, we show that reducing microglial nuclear factor κB (NF-κB) signaling via cell-specific IKKß deletion exacerbates HFD-induced glucose intolerance despite reducing body weight and adiposity. Conversely, two genetic approaches to increase microglial pro-inflammatory signaling (deletion of an NF-κB pathway inhibitor and chemogenetic activation through a modified Gq-coupled muscarinic receptor) improved glucose tolerance independently of diet in both lean and obese rodents. Microglial regulation of glucose homeostasis involves a tumor necrosis factor alpha (TNF-α)-dependent mechanism that increases activation of pro-opiomelanocortin (POMC) and other hypothalamic glucose-sensing neurons, ultimately leading to a marked amplification of first-phase insulin secretion via a parasympathetic pathway. Overall, these data indicate that microglia regulate glucose homeostasis in a body-weight-independent manner, an unexpected mechanism that limits the deterioration of glucose tolerance associated with obesity.

COVID-19 in people with neurofibromatosis 1, neurofibromatosis 2, or schwannomatosis.

PURPOSE: People with pre-existing conditions may be more susceptible to severe COVID-19 when infected by SARS-CoV-2. The relative risk and severity of SARS-CoV-2 infection in people with rare diseases such as neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), or schwannomatosis (SWN) is unknown. METHODS: We investigated the proportions of people with NF1, NF2, or SWN in the National COVID Cohort Collaborative (N3C) electronic health record data set who had a positive test result for SARS-CoV-2 or COVID-19. RESULTS: The cohort sizes in N3C were 2501 (NF1), 665 (NF2), and 762 (SWN). We compared these with N3C cohorts of patients with other rare diseases (98-9844 individuals) and the general non-NF population of 5.6 million. The site- and age-adjusted proportion of people with NF1, NF2, or SWN who had a positive test result for SARS-CoV-2 or COVID-19 (collectively termed positive cases) was not significantly higher than in individuals without NF or other selected rare diseases. There were no severe outcomes reported in the NF2 or SWN cohorts. The proportion of patients experiencing severe outcomes was no greater for people with NF1 than in cohorts with other rare diseases or the general population. CONCLUSION: Having NF1, NF2, or SWN does not appear to increase the risk of being SARS-CoV-2 positive or of being a patient with COVID-19 or of developing severe complications from SARS-CoV-2.

Centralizing neurofibromatosis experimental tool knowledge with the NF Research Tools Database.

Experimental tools and resources, such as animal models, cell lines, antibodies, genetic reagents and biobanks, are key ingredients in biomedical research. Investigators face multiple challenges when trying to understand the availability, applicability and accessibility of these tools. A major challenge is keeping up with current information about the numerous tools available for a particular research problem. A variety of disease-agnostic projects such as the Mouse Genome Informatics database and the Resource Identification Initiative curate a number of types of research tools. Here, we describe our efforts to build upon these resources to develop a disease-specific research tool resource for the neurofibromatosis (NF) research community. This resource, the NF Research Tools Database, is an open-access database that enables the exploration and discovery of information about NF type 1-relevant animal models, cell lines, antibodies, genetic reagents and biobanks. Users can search and explore tools, obtain detailed information about each tool as well as read and contribute their observations about the performance, reliability and characteristics of tools in the database. NF researchers will be able to use the NF Research Tools Database to promote, discover, share, reuse and characterize research tools, with the goal of advancing NF research. Database URL: https://tools.nf.synapse.org/.

Integrated molecular and clinical analysis of low-grade gliomas in children with neurofibromatosis type 1 (NF1).

Low-grade gliomas (LGGs) are the most common childhood brain tumor in the general population and in individuals with the Neurofibromatosis type 1 (NF1) cancer predisposition syndrome. Surgical biopsy is rarely performed prior to treatment in the setting of NF1, resulting in a paucity of tumor genomic information. To define the molecular landscape of NF1-associated LGGs (NF1-LGG), we integrated clinical data, histological diagnoses, and multi-level genetic/genomic analyses on 70 individuals from 25 centers worldwide. Whereas, most tumors harbored bi-allelic NF1 inactivation as the only genetic abnormality, 11% had additional mutations. Moreover, tumors classified as non-pilocytic astrocytoma based on DNA methylation analysis were significantly more likely to harbor these additional mutations. The most common secondary alteration was FGFR1 mutation, which conferred an additional growth advantage in multiple complementary experimental murine Nf1 models. Taken together, this comprehensive characterization has important implications for the management of children with NF1-LGG, distinct from their sporadic counterparts.

A clinically and genomically annotated nerve sheath tumor biospecimen repository.

Nerve sheath tumors occur as a heterogeneous group of neoplasms in patients with neurofibromatosis type 1 (NF1). The malignant form represents the most common cause of death in people with NF1, and even when benign, these tumors can result in significant disfigurement, neurologic dysfunction, and a range of profound symptoms. Lack of human tissue across the peripheral nerve tumors common in NF1 has been a major limitation in the development of new therapies. To address this unmet need, we have created an annotated collection of patient tumor samples, patient-derived cell lines, and patient-derived xenografts, and carried out high-throughput genomic and transcriptomic characterization to serve as a resource for further biologic and preclinical therapeutic studies. In this work, we release genomic and transcriptomic datasets comprised of 55 tumor samples derived from 23 individuals, complete with clinical annotation. All data are publicly available through the NF Data Portal and at http://synapse.org/jhubiobank.

Integrative Analysis Identifies Candidate Tumor Microenvironment and Intracellular Signaling Pathways that Define Tumor Heterogeneity in NF1.

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40-60% of patients develop plexiform neurofibromas (pNFs), which are deeply embedded in the peripheral nerves. Patients with pNFs have a ~10% lifetime chance of these tumors becoming malignant peripheral nerve sheath tumors (MPNSTs). These tumors have a severe prognosis and few treatment options other than surgery. Given the lack of therapeutic options available to patients with these tumors, identification of druggable pathways or other key molecular features could aid ongoing therapeutic discovery studies. In this work, we used statistical and machine learning methods to analyze 77 NF1 tumors with genomic data to characterize key signaling pathways that distinguish these tumors and identify candidates for drug development. We identified subsets of latent gene expression variables that may be important in the identification and etiology of cNFs, pNFs, other neurofibromas, and MPNSTs. Furthermore, we characterized the association between these latent variables and genetic variants, immune deconvolution predictions, and protein activity predictions.

Wireless control of cellular function by activation of a novel protein responsive to electromagnetic fields.

The Kryptopterus bicirrhis (glass catfish) is known to respond to electromagnetic fields (EMF). Here we tested its avoidance behavior in response to static and alternating magnetic fields stimulation. Using expression cloning we identified an electromagnetic perceptive gene (EPG) from the K. bicirrhis encoding a protein that responds to EMF. This EPG gene was cloned and expressed in mammalian cells, neuronal cultures and in rat's brain. Immunohistochemistry showed that the expression of EPG is confined to the mammalian cell membrane. Calcium imaging in mammalian cells and cultured neurons expressing EPG demonstrated that remote activation by EMF significantly increases intracellular calcium concentrations, indicative of cellular excitability. Moreover, wireless magnetic activation of EPG in rat motor cortex induced motor evoked responses of the contralateral forelimb in vivo. Here we report on the development of a new technology for remote, non-invasive modulation of cell function.