Monie, Dileep D.

TRAIL is a TNF family ligand that trimerizes TRAIL-R1 (DR4) or TRAIL-R2 (DR5) to induce apoptosis, necroptosis, and/or NF-κB activation in receptor-bearing cells. We previously identified TRAILshort as a splice variant of TRAIL that lacks cysteine 230, cannot trimerize, and acts as a dominant-negative ligand that blocks TRAIL-mediated apoptosis. TRAILshort is expressed on cell surfaces and within extracellular vesicles, enabling it to confer TRAIL resistance to both producing and bystander cells. In this study, we showed that elevated TRAILshort levels were associated with chronic viral infections, cancer, and autoimmune diseases, suggesting a link to impaired immune regulation. Using unbiased phosphoproteomics and mechanistic studies, we demonstrated that TRAILshort binding to DR5 recruited and activated the phosphatase Src homology region 2 domain–containing phosphatase 1 (SHP-1), leading to zeta-chain-associated protein kinase 70 (ZAP-70) dephosphorylation, disruption of ZAP-70–CD3ζ interactions, and impaired T cell receptor signaling, thereby reducing T cell activation, proliferation, and cytokine production in response to antigen or CD3/CD28 ligation. Genetic or pharmacologic SHP-1 inhibition reverses these effects. In humanized mouse models, TRAILshort promoted the persistence of transformed mouse embryonic fibroblasts (MEFs) and L428 and antagonized CD19-directed CAR T cell activity, revealing TRAILshort as an immunomodulator of T cell function with therapeutic implications, including blocking TRAILshort to restore T cell immunity or delivering TRAILshort to enforce tolerance. TRAILshort, a variant of TRAIL, suppresses T cell function and immune responses in cancer and infectious diseases, highlighting its potential as a therapeutic target.

Abstract Glioblastoma is the most common and lethal primary brain tumor in adults, with a median survival less than 15 months despite current standard of care. Oncolytic immunovirotherapies (OVs) have shown promise in early clinical trials. OVs are engineered to specifically target cancer cells, trigger autophagic programmed cell death, and release tumor antigens in the context of T-cell activating cytokines. Cellular communication network factor 1 (CCN1) is an extracellular matrix protein expressed in 70% of glioblastomas that has been shown to drastically reduce OV efficacy, particularly herpes simplex virus type 1 (HSV-1). Our objectives were to decode protein-protein interaction (PPI) networks activated by CCN1, identify critical nodes in resistance networks, and use this analysis to design OVs that overcome CCN1-mediated resistance. We used NetDecoder to elucidate phenotype-specific PPI subnetworks in LN229 human glioblastoma cells with tetracycline-inducible CCN1 expression. Publicly available microarray data on CCN1-induced and control samples established differentially expressed genes, which served as sources in our PPI network to derive prioritized context-specific subnetworks. We found that 11 source genes collaborate via 39 deep nodes to confer OV resistance to CCN1-expressing glioblastomas. Of these, a router (IKBKE) and a sink (YBX1) have been previously implicated in glioblastoma pathogenesis. We conclude that autophagy regulator HSP90AA1, a critical node, may be targeted to improve OV efficacy in CCN1-expressing glioblastomas. Furthermore, WebGestalt overrepresentation analysis of subnetwork nodes suggests that oncolytic adenovirus may be more effective than HSV-1 as a synthetic biology chassis.

OBJECTIVE Glioblastoma (GBM) is a devasting primary brain tumor with less than a 5% 5-year survival. Treatment response assessment can be challenging because of inflammatory pseudoprogression that mimics true tumor progression clinically and on imaging. Developing additional noninvasive assays is critical. In this article, the authors review various biomarkers that could be used in developing liquid biopsies for GBM, along with strengths, limitations, and future applications. In addition, they present a potential liquid biopsy design based on the use of an extracellular vesicle–based liquid biopsy targeting nonneoplastic extracellular vesicles. METHODS The authors conducted a current literature review of liquid biopsy in GBM by searching the PubMed, Scopus, and Google Scholar databases. Articles were assessed for type of biomarker, isolation methodology, analytical techniques, and clinical relevance. RESULTS Recent work has shown that liquid biopsies of plasma, blood, and/or CSF hold promise as noninvasive clinical tools that can be used to diagnose recurrence, assess treatment response, and predict patient outcomes in GBM. Liquid biopsy in GBM has focused primarily on extracellular vesicles, cell-free tumor nucleic acids, and whole-cell isolates as focal biomarkers. GBM tumor signatures have been generated via analysis of tumor gene mutations, unique RNA expression, and metabolic and proteomic alterations. Liquid biopsies capture tumor heterogeneity, identifying alterations in GBM tumors that may be undetectable via surgical biopsy specimens. Finally, biomarker burden can be used to assess treatment response and recurrence in GBM. CONCLUSIONS Liquid biopsy offers a promising avenue for monitoring treatment response and recurrence in GBM without invasive procedures. Although additional steps must be taken to bring liquid biopsy into the clinic, proof-of-principle studies and isolation methodologies are promising. Ultimately, CSF and/or plasma-based liquid biopsy is likely to be a powerful tool in the neurosurgeon’s arsenal in the near future for the treatment and management of GBM patients.

Neuroimmunology plays a critical role in our understanding of the pathophysiological processes that underlie a variety of diseases treated by neurosurgeons, including degenerative disc disease (DDD), glioblastoma (GBM), aneurysmal subarachnoid hemorrhage (aSAH), and others. Compared with traditional methods in neuroimmunology, which study one pathway or gene at a time, emerging multiomics methodologies allow for holistic interrogation of multiple immune-signaling pathways to test hypotheses and the effects of therapeutics at a systems level. In this review, the authors summarize key concepts for gathering and analyzing multiomics data so that neurosurgeons can contribute to the emerging field of systems neuroimmunology. Additionally, they describe 3 use cases, based on original research published by their group and others, that utilize transcriptomic, metabolomic, and proteomic analyses to study immune-signaling pathways in DDD, aSAH, and GBM. Through these use cases, techniques for performing machine learning and network-based analyses to generate new clinical insights from multiomics data are shared. The authors hope that neurosurgeons might use this review as a summary of common tools and principles in systems immunology to better engage in creating the immunotherapies of tomorrow.

Abstract Cytotoxic CD8+ T cells (CTL) are a crucial component of the immune system notable for their ability to eliminate rapidly proliferating malignant cells. However, the T-cell intrinsic factors required for human CTLs to accomplish highly efficient antitumor cytotoxicity are not well defined. By evaluating human CD8+ T cells from responders versus nonresponders to treatment with immune checkpoint inhibitors, we sought to identify key factors associated with effective CTL function. Single-cell RNA-sequencing analysis of peripheral CD8+ T cells from patients treated with anti–PD-1 therapy showed that cells from nonresponders exhibited decreased expression of the cytolytic granule-associated molecule natural killer cell granule protein-7 (NKG7). Functional assays revealed that reduced NKG7 expression altered cytolytic granule number, trafficking, and calcium release, resulting in decreased CD8+ T-cell–mediated killing of tumor cells. Transfection of T cells with NKG7 mRNA was sufficient to improve the tumor-cell killing ability of human T cells isolated from nonresponders and increase their response to anti–PD-1 or anti–PD-L1 therapy in vitro. NKG7 mRNA therapy also improved the antitumor activity of murine tumor antigen–specific CD8+ T cells in an in vivo model of adoptive cell therapy. Finally, we showed that the transcription factor ETS1 played a role in regulating NKG7 expression. Together, our results identify NKG7 as a necessary component for the cytotoxic function of CD8+ T cells and establish NKG7 as a T-cell–intrinsic therapeutic target for enhancing cancer immunotherapy. See related article by Li et al., p. 154.

Abstract Glioblastoma multiforme (GBM) is a particularly aggressive primary brain tumor that is relatively common in adults. The disease comes with a dismal prognosis, often with expected survival just over a year when treated with surgery, chemotherapy, and radiation. A promising addition to our GBM treatment arsenal are oncolytic viruses (OVs), a class of immunotherapy now in clinical trials. The most effective OVs home in on tumor cells, killing them and releasing tumor-associated antigens that elicit antitumor immunity. This effectiveness, however, varies depending on the cell state—a property that may be influenced by the composition of the extracellular matrix (ECM) of GBM. Cellular communication network factor 1 (CCN1) is found in the ECM of the majority of GBMs and is predictive of resistance to OVs, particularly those derived from herpes simplex virus type 1 (HSV-1). In this study, our aim is to understand how extracellular CCN1 alters the GBM intracellular state in a manner that confers resistance to OVs. We began by using our NetDecoder platform to build CCN1-specific prioritized protein-protein interaction (PPI) networks from published LN229 human GBM transcriptomic datasets. From this network, we identified 12 PPI edges that dominate the network flow in CCN1-high LN229 cells when compared to CCN1-low controls. The 21 unique nodes that comprise these binary PPI edges were extracted and subjected to downstream biological process overrepresentation analyses using Gene Ontology. We found that the cytokine-mediated signaling pathway (FDR = 4.2 x 10-11; enrichment ratio = 15.8) and the cellular response to cytokine stimulus (FDR = 3.1 x 10-9; enrichment ratio = 10.9) were highly enriched when mapped to these nodes. We conclude that CCN1, acting as a paracrine signal in the GBM tumor microenvironment, primes the cell to inhibit HSV-1 and other candidate OV replication prior to any virus interactions, thus contributing to immunovirotherapy resistance. While CCN1 and its cell surface integrin binding partners are ostensible drug targets for overcoming this resistance, pharmacologic interventions that target CCN1-specific high flow edges in our prioritized PPI network may be more effective. Citation Format: Dileep D. Monie, Cristina Correia, Cheng Zhang, Choong Ung, Richard G. Vile, Hu Li. Innate immunity and cytokine signaling pathways drive resistance to HSV-1 oncolytic immunovirotherapy in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1679.

Oncolytic viruses (OVs) are a class of immunotherapeutic agents with promising preclinical results for the treatment of glioblastoma (GBM) but have shown limited success in recent clinical trials. Advanced bioengineering principles from disciplines such as synthetic and systems biology are needed to overcome the current challenges faced in developing effective OV-based immunotherapies for GBMs, including off-target effects and poor clinical responses. Synthetic biology is an emerging field that focuses on the development of synthetic DNA constructs that encode networks of genes and proteins (synthetic genetic circuits) to perform novel functions, whereas systems biology is an analytical framework that enables the study of complex interactions between host pathways and these synthetic genetic circuits. In this review, the authors summarize synthetic and systems biology concepts for developing programmable, logic-based OVs to treat GBMs. Programmable OVs can increase selectivity for tumor cells and enhance the local immunological response using synthetic genetic circuits. The authors discuss key principles for developing programmable OV-based immunotherapies, including how to 1) select an appropriate chassis, a vector that carries a synthetic genetic circuit, and 2) design a synthetic genetic circuit that can be programmed to sense key signals in the GBM microenvironment and trigger release of a therapeutic payload. To illustrate these principles, some original laboratory data are included, highlighting the need for systems biology studies, as well as some preliminary network analyses in preparation for synthetic biology applications. Examples from the literature of state-of-the-art synthetic genetic circuits that can be packaged into leading candidate OV chassis are also surveyed and discussed.

Abstract BACKGROUND Conventional magnetic resonance imaging (MR) guides patient care in GBM. However, there is mounting awareness that MR enhancement is non-specific reflecting either tumor progression or non-tumoral inflammatory changes. Histological evaluation of GBM is held as the gold standard for disease assessment. However, the invasiveness of this methodology and the sample sparsity limit its usefulness. Methods to infer histological underpinnings of MRI are needed to improve clinical care. METHODS A transfer learning mixed effects model based on T1Gd and FLAIR MR voxel based image features trained and cross-validated to predict FPKM values of CD68, CASP3, CD8A and IL13RA2. Training data included RNAseq from 38 image-localized biopsies from 15 newly-diagnosed GBM patients. These models were then applied to two independent patients, chosen based on therapy and the quality of image registration, at three different time points, just prior to receiving IL13RA2 targeted CAR-T therapy for rGBM, after 2 cycles and after 4 cycles, resulting in a voxel-based prediction of the relative expression levels of these genes. RESULTS Cross-validation of the proposed machine learning models demonstrated a Pearson Correlation coefficient between predicted and observed FPKM values of 0.89 (CD68), 0.92 (CASP3), 0.93 (CD8A), and 0.88 (IL13RA2). When the models were applied to the two CAR-T patients, CD68-modeled expression levels were seen to increase throughout therapy for one patient, while remaining stable for the other. Survival from first CAR-T infusion was, respectively, 412 and 83 days suggesting that the increased CD68 was indicative of therapeutic effectivity. Further, the spatial activity predictions were consistent with expected therapeutic action as the correlation coefficient between CASP3 and the product of IL13R2 and CD8A expression was 0.81, suggesting the T-cells targeting IL13RA2 were inducing cell death. CONCLUSIONS Preliminary results with our model highlights the potential of spatially resolved radiomic maps to provide insight into regional therapeutic effectivity.

OBJECTIVEThe authors sought to investigate the incidence and predictors of venous thromboembolic events (VTEs) after craniotomy for tumor resection, which are not well established, and the efficacy of and risks associated with VTE chemoprophylaxis, which remains controversial.METHODSThe authors investigated the incidence of VTEs in a consecutive series of patients presenting to the authors’ institution for resection of an intracranial lesion between 2012 and 2017. Information on patient and tumor characteristics was collected and independent predictors of VTEs were determined using stepwise multivariate logistic regression analysis. Review of the literature was performed by searching MEDLINE using the keywords “venous thromboembolism,” “deep venous thrombosis,” “pulmonary embolism,” “craniotomy,” and “brain neoplasms.”RESULTSThere were 1622 patients included for analysis. A small majority of patients were female (52.6%) and the mean age of the cohort was 52.9 years (SD 15.8 years). A majority of intracranial lesions were intraaxial (59.3%). The incidence of VTEs was 3.0% and the rates of deep venous thromboses and pulmonary emboli were 2.3% and 0.9%, respectively. On multivariate analysis, increasing patient age (unit OR 1.02, 95% CI 1.00–1.05; p = 0.018), history of VTE (OR 7.26, 95% CI 3.24–16.27; p < 0.001), presence of motor deficit (OR 2.64, 95% CI 1.43–4.88; p = 0.002), postoperative intracranial hemorrhage (OR 4.35, 95% CI 1.51–12.55; p < 0.001), and prolonged intubation or reintubation (OR 3.27, 95% CI 1.28–8.32; p < 0.001) were independently associated with increased odds of a VTE. There were 192 patients who received VTE chemoprophylaxis (11.8%); the mean postoperative day of chemoprophylaxis initiation was 4.6 (SD 3.8). The incidence of VTEs was higher in patients receiving chemoprophylaxis than in patients not receiving chemoprophylaxis (8.3% vs 2.2%; p < 0.001). There were 30 instances of clinically significant postoperative hemorrhage (1.9%), with only 1 hemorrhage occurring after initiation of VTE chemoprophylaxis (0.1%).CONCLUSIONSThe study results show the incidence and predictors of VTEs after craniotomy for tumor resection in this patient population. The incidence of VTE within this cohort appears low and comparable to that observed in other institutional series, despite the lack of routine prophylactic anticoagulation in the postoperative setting.