Assessing the Accuracy of Spinal Instrumentation Using Augmented Reality (AR): A Systematic Review of the Literature and Meta-Analysis.

Technological advancements, particularly in the realm of augmented reality (AR), may facilitate more accurate and precise pedicle screw placement. AR integrates virtual data into the operator's real-world view, allowing for the visualization of patient-specific anatomy and navigated trajectories. We aimed to conduct a meta-analysis of the accuracy of pedicle screw placement using AR-based systems. A systematic review of the literature and meta-analysis was performed using the PubMed/MEDLINE database, including studies reporting the accuracy of pedicle screw placement using AR. In total, 8 studies with 163 patients and 1259 screws were included in the analysis. XVision (XVS) was the most commonly used AR system (595 screws) followed by the Allura AR surgical navigation system (ARSN) (462 screws). The overall accuracy was calculated as 97.2% (95% CI 96.2-98.1% p < 0.001). Subgroup analysis revealed that there was no statistically significant difference in the accuracy rates achieved by XVS and Allura ARSN (p = 0.092). AR enables reliable, accurate placement of spinal instrumentation. Future research efforts should focus on comparative studies, cost effectiveness, operative time, and radiation exposure.

TCR-engineered adoptive cell therapy effectively treats intracranial murine glioblastoma.

BACKGROUND: Adoptive cellular therapies with chimeric antigen receptor T cells have revolutionized the treatment of some malignancies but have shown limited efficacy in solid tumors such as glioblastoma and face a scarcity of safe therapeutic targets. As an alternative, T cell receptor (TCR)-engineered cellular therapy against tumor-specific neoantigens has generated significant excitement, but there exist no preclinical systems to rigorously model this approach in glioblastoma. METHODS: We employed single-cell PCR to isolate a TCR specific for the Imp3D81N neoantigen (mImp3) previously identified within the murine glioblastoma model GL261. This TCR was used to generate the Mutant Imp3-Specific TCR TransgenIC (MISTIC) mouse in which all CD8 T cells are specific for mImp3. The therapeutic efficacy of neoantigen-specific T cells was assessed through a model of cellular therapy consisting of the transfer of activated MISTIC T cells and interleukin 2 into lymphodepleted tumor-bearing mice. We employed flow cytometry, single-cell RNA sequencing, and whole-exome and RNA sequencing to examine the factors underlying treatment response. RESULTS: We isolated and characterized the 3×1.1C TCR that displayed a high affinity for mImp3 but no wild-type cross-reactivity. To provide a source of mImp3-specific T cells, we generated the MISTIC mouse. In a model of adoptive cellular therapy, the infusion of activated MISTIC T cells resulted in rapid intratumoral infiltration and profound antitumor effects with long-term cures in a majority of GL261-bearing mice. The subset of mice that did not respond to the adoptive cell therapy showed evidence of retained neoantigen expression but intratumoral MISTIC T cell dysfunction. The efficacy of MISTIC T cell therapy was lost in mice bearing a tumor with heterogeneous mImp3 expression, showcasing the barriers to targeted therapy in polyclonal human tumors. CONCLUSIONS: We generated and characterized the first TCR transgenic against an endogenous neoantigen within a preclinical glioma model and demonstrated the therapeutic potential of adoptively transferred neoantigen-specific T cells. The MISTIC mouse provides a powerful novel platform for basic and translational studies of antitumor T-cell responses in glioblastoma.

The Conventional Dendritic Cell 1 Subset Primes CD8+ T Cells and Traffics Tumor Antigen to Drive Antitumor Immunity in the Brain.

The central nervous system (CNS) antigen-presenting cell (APC) that primes antitumor CD8+ T-cell responses remains undefined. Elsewhere in the body, the conventional dendritic cell 1 (cDC1) performs this role. However, steady-state brain parenchyma cDC1 are extremely rare; cDCs localize to the choroid plexus and dura. Thus, whether the cDC1 play a function in presenting antigen derived from parenchymal sources in the tumor setting remains unknown. Using preclinical glioblastoma (GBM) models and cDC1-deficient mice, we explored the presently unknown role of cDC1 in CNS antitumor immunity. We determined that, in addition to infiltrating the brain tumor parenchyma itself, cDC1 prime neoantigen-specific CD8+ T cells against brain tumors and mediate checkpoint blockade-induced survival benefit. We observed that cDC, including cDC1, isolated from the tumor, the dura, and the CNS-draining cervical lymph nodes harbored a traceable fluorescent tumor antigen. In patient samples, we observed several APC subsets (including the CD141+ cDC1 equivalent) infiltrating glioblastomas, meningiomas, and dura. In these same APC subsets, we identified a tumor-specific fluorescent metabolite of 5-aminolevulinic acid, which fluorescently labeled tumor cells during fluorescence-guided GBM resection. Together, these data elucidate the specialized behavior of cDC1 and suggest that cDC1 play a significant role in CNS antitumor immunity.

GATA2 Regulates Constitutive PD-L1 and PD-L2 Expression in Brain Tumors.

Encouraging clinical results using immune checkpoint therapies to target the PD-1 axis in a variety of cancer types have paved the way for new immune therapy trials in brain tumor patients. However, the molecular mechanisms that regulate expression of the PD-1 pathway ligands, PD-L1 and PD-L2, remain poorly understood. To address this, we explored the cell-intrinsic mechanisms of constitutive PD-L1 and PD-L2 expression in brain tumors. PD-L1 and PD-L2 expression was assessed by flow cytometry and qRT-PCR in brain tumor cell lines and patient tumor-derived brain tumor-initiating cells (BTICs). Immunologic effects of PD-L2 overexpression were evaluated by IFN-γ ELISPOT. CD274 and PDCD1LG2 cis-regulatory regions were cloned from genomic DNA and assessed in full or by mutating and/or deleting regulatory elements by luciferase assays. Correlations between clinical responses and PD-L1 and PD-L2 expression status were evaluated in TCGA datasets in LGG and GBM patients. We found that a subset of brain tumor cell lines and BTICs expressed high constitutive levels of PD-L1 and PD-L2 and that PD-L2 overexpression inhibited neoantigen specific T cell IFN-γ production. Characterization of novel cis-regulatory regions in CD274 and PDCD1LG2 lead us to identify that GATA2 is sufficient to drive PD-L1 and PD-L2 expression and is necessary for PD-L2 expression. Importantly, in TCGA datasets, PD-L2 correlated with worse clinical outcomes in glioma patients.. By perturbing GATA2 biology, targeted therapies may be useful to decrease inhibitory effects of PD-L2 in the microenvironment.

Treatment of an aggressive orthotopic murine glioblastoma model with combination checkpoint blockade and a multivalent neoantigen vaccine.

BACKGROUND: Although clinical trials testing immunotherapies in glioblastoma (GBM) have yielded mixed results, new strategies targeting tumor-specific somatic coding mutations, termed "neoantigens," represent promising therapeutic approaches. We characterized the microenvironment and neoantigen landscape of the aggressive CT2A GBM model in order to develop a platform to test combination checkpoint blockade and neoantigen vaccination. METHODS: Flow cytometric analysis was performed on intracranial CT2A and GL261 tumor-infiltrating lymphocytes (TILs). Whole-exome DNA and RNA sequencing of the CT2A murine GBM was employed to identify expressed, somatic mutations. Predicted neoantigens were identified using the pVAC-seq software suite, and top-ranking candidates were screened for reactivity by interferon-gamma enzyme linked immunospot assays. Survival analysis was performed comparing neoantigen vaccination, anti-programmed cell death ligand 1 (αPD-L1), or combination therapy. RESULTS: Compared with the GL261 model, CT2A exhibited immunologic features consistent with human GBM including reduced αPD-L1 sensitivity and hypofunctional TILs. Of the 29 CT2A neoantigens screened, we identified neoantigen-specific CD8+ T-cell responses in the intracranial TIL and draining lymph nodes to two H2-Kb restricted (Epb4H471L and Pomgnt1R497L) and one H2-Db restricted neoantigen (Plin2G332R). Survival analysis showed that therapeutic neoantigen vaccination with Epb4H471L, Pomgnt1R497L, and Plin2G332R, in combination with αPD-L1 treatment was superior to αPD-L1 alone. CONCLUSIONS: We identified endogenous neoantigen specific CD8+ T cells within an αPD-L1 resistant murine GBM and show that neoantigen vaccination significantly augments survival benefit in combination with αPD-L1 treatment. These observations provide important preclinical correlates for GBM immunotherapy trials and support further investigation into the effects of multimodal immunotherapeutic interventions on antiglioma immunity. KEY POINTS: 1. Neoantigen vaccines combined with checkpoint blockade may be promising treatments.2. CT2A tumors exhibit features of human GBM microenvironments.3. Differential scanning fluorimetry assays may complement in silico neoantigen prediction tools.

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. This is a cross-disciplinary challenge, involving genomics, proteomics, immunology, and computational approaches. We have built a computational framework called pVACtools that, when paired with a well-established genomics pipeline, produces an end-to-end solution for neoantigen characterization. pVACtools supports identification of altered peptides from different mechanisms, including point mutations, in-frame and frameshift insertions and deletions, and gene fusions. Prediction of peptide:MHC binding is accomplished by supporting an ensemble of MHC Class I and II binding algorithms within a framework designed to facilitate the incorporation of additional algorithms. Prioritization of predicted peptides occurs by integrating diverse data, including mutant allele expression, peptide binding affinities, and determination whether a mutation is clonal or subclonal. Interactive visualization via a Web interface allows clinical users to efficiently generate, review, and interpret results, selecting candidate peptides for individual patient vaccine designs. Additional modules support design choices needed for competing vaccine delivery approaches. One such module optimizes peptide ordering to minimize junctional epitopes in DNA vector vaccines. Downstream analysis commands for synthetic long peptide vaccines are available to assess candidates for factors that influence peptide synthesis. All of the aforementioned steps are executed via a modular workflow consisting of tools for neoantigen prediction from somatic alterations (pVACseq and pVACfuse), prioritization, and selection using a graphical Web-based interface (pVACviz), and design of DNA vector-based vaccines (pVACvector) and synthetic long peptide vaccines. pVACtools is available at http://www.pvactools.org.

Detection of neoantigen-specific T cells following a personalized vaccine in a patient with glioblastoma.

Neoantigens represent promising targets for personalized cancer vaccine strategies. However, the feasibility of this approach in lower mutational burden tumors like glioblastoma (GBM) remains unknown. We have previously reported the use of an immunogenomics pipeline to identify candidate neoantigens in preclinical models of GBM. Here, we report the application of the same immunogenomics pipeline to identify candidate neoantigens and guide screening for neoantigen-specific T cell responses in a patient with GBM treated with a personalized synthetic long peptide vaccine following autologous tumor lysate DC vaccination. Following vaccination, reactivity to three HLA class I- and five HLA class II-restricted candidate neoantigens were detected by IFN-γ ELISPOT in peripheral blood. A similar pattern of reactivity was observed among isolated post-treatment tumor-infiltrating lymphocytes. Genomic analysis of pre- and post-treatment GBM reflected clonal remodeling. These data demonstrate the feasibility and translational potential of a therapeutic neoantigen-based vaccine approach in patients with primary CNS tumors.

Accounting for proximal variants improves neoantigen prediction.

Recent efforts to design personalized cancer immunotherapies use predicted neoantigens, but most neoantigen prediction strategies do not consider proximal (nearby) variants that alter the peptide sequence and may influence neoantigen binding. We evaluated somatic variants from 430 tumors to understand how proximal somatic and germline alterations change the neoantigenic peptide sequence and also affect neoantigen binding predictions. On average, 241 missense somatic variants were analyzed per sample. Of these somatic variants, 5% had one or more in-phase missense proximal variants. Without incorporating proximal variant correction for major histocompatibility complex class I neoantigen peptides, the overall false discovery rate (incorrect neoantigens predicted) and the false negative rate (strong-binding neoantigens missed) across peptides of lengths 8-11 were estimated as 0.069 (6.9%) and 0.026 (2.6%), respectively.