A key challenge for single cell discovery analysis is to identify new cell types, describe them quantitatively, and seek these novel cells in new studies often using a different platform. Over the last decade, tools were developed to address identification and quantitative description of cells in human tissues and tumors. However, automated validation of populations at the single cell level has struggled due to the cytometry field's reliance on hierarchical, ordered use of features and on platform-specific rules for data processing and analysis. Here we present Velociraptor, a workflow that implements Marker Enrichment Modeling in three cross-platform modules: 1) identification of cells specific to disease states, 2) description of hallmark features for each cell and population, and 3) searching for cells matching one or more hallmark feature sets in a new dataset. A key advance is that Velociraptor registers cells between datasets, including between flow cytometry and quantitative imaging using different, overlapping feature sets. Four datasets were used to challenge Velociraptor and reveal new biological insights. Working at the individual sample level, Velociraptor tracked the abundance of clinically significant glioblastoma brain tumor cell subsets and characterized the cells that predominate in recurrent tumors as a close match for rare, negative prognostic cells originally observed in matched pre-treatment tumors. In patients with inborn errors of immunity, Velociraptor identified genotype-specific cells associated withGATA2haploinsufficiency. Finally, in cross-platform analysis of immune cells in multiplex imaging of breast cancer, Velociraptor sought and correctly identified memory T cell subsets in tumors. Different phenotypic descriptions generated by algorithms or humans were shown to be effective as search inputs, indicating that cell identity need not be described in terms of per-feature cutoffs or strict hierarchical analyses. Velociraptor thus identifies cells based on hallmark feature sets, such as protein expression signatures, and works effectively with data from multiple sources, including suspension flow cytometry, imaging, and search text based on known or theoretical cell features.

Abstract Adult IDH-wildtype glioblastoma (GBM) is an aggressive brain tumor with no established immunotherapy. Glioblastoma tumors that contact the ventricular-subventricular zone (V-SVZ) stem cell niche have especially poor clinical outcomes (PMC5771712, PMC5262526) and abnormal immune microenvironments filled with CD32+ HLA-DRhi macrophages that have displaced resident microglia (PMC10371245). Identifying the origin and role of these CD32+ macrophages is likely critical to developing successful GBM immunotherapies. Here, we present a mechanistic origin for these CD32+ cells as M_IL-8 macrophages. In ex vivo experiments with conditioned medium from primary human tumor cells, IL-8 was sufficient and necessary for tumor cells to instruct healthy macrophages, and inhibitory antibodies to IL-8 blocked the generation of CD32+ CD163+ M_IL-8 cells. Additionally, IL-8 protein was present in GBM tumor cells in vivo and especially common in tumors contacting the V-SVZ (p<0.0001, N=192 cores from 73 patients). Surface proteins CXCR1 and CXCR2, the primary receptors for IL-8, were detected on cells that were spatially separated from IL-8+ glioblastoma cells in tumors contacting the V-SVZ. These results suggest the hypothesis that glioblastoma-cell IL-8 instructs incoming CXCR1+ hematopoietic macrophages to adopt a suppressive M_IL-8 identity in V-SVZ-contacting GBM. Abundant HLA-DR (MHC II) observed on the CD32+ M_IL-8 cells closely matched the signature phenotype of cells in human tumors (PMC10371245) and contrasted with lower surface MHC II expression typically observed on human myeloid derived suppressor cells (PMC6608074). M_IL-8 cells might especially target CD4+ helper T cells required for effective cancer immunotherapy (PMC5312823). IL-8 and CD32+ macrophages should now be explored as targets in combination with GBM immunotherapies, especially for patients whose tumors present with radiographic contact with the V-SVZ stem cell niche. Some results here have been shared in a bioRxiv preprint by the these authors (PMC10996638).

Adult IDH-wildtype glioblastoma (GBM) is a highly aggressive brain tumor with no established immunotherapy or targeted therapy. Recently, CD32+ HLA-DRhi macrophages were shown to have displaced resident microglia in GBM tumors that contact the lateral ventricle stem cell niche. Since these lateral ventricle contacting GBM tumors have especially poor outcomes, identifying the origin and role of these CD32+ macrophages is likely critical to developing successful GBM immunotherapies. Here, we identify these CD32+ cells as M_IL-8 macrophages and establish that IL-8 is sufficient and necessary for tumor cells to instruct healthy macrophages into CD32+ M_IL-8 M2 macrophages. In ex vivo experiments with conditioned medium from primary human tumor cells, inhibitory antibodies to IL-8 blocked the generation of CD32+ M_IL-8 cells. Finally, using a set of 73 GBM tumors, IL-8 protein is shown to be present in GBM tumor cells in vivo and especially common in tumors contacting the lateral ventricle. These results provide a mechanistic origin for CD32+ macrophages that predominate in the microenvironment of the most aggressive GBM tumors. IL-8 and CD32+ macrophages should now be explored as targets in combination with GBM immunotherapies, especially for patients whose tumors present with radiographic contact with the ventricular-subventricular zone stem cell niche.

Radiographic contact of glioblastoma (GBM) tumors with the lateral ventricle and adjacent stem cell niche correlates with poor patient prognosis, but the cellular basis of this difference is unclear. Here, we reveal and functionally characterize distinct immune microenvironments that predominate in subtypes of GBM distinguished by proximity to the lateral ventricle. Mass cytometry analysis of isocitrate dehydrogenase wild-type human tumors identified elevated T cell checkpoint receptor expression and greater abundance of a specific CD32+CD44+HLA-DRhi macrophage population in ventricle-contacting GBM. Multiple computational analysis approaches, phospho-specific cytometry, and focal resection of GBMs validated and extended these findings. Phospho-flow quantified cytokine-induced immune cell signaling in ventricle-contacting GBM, revealing differential signaling between GBM subtypes. Subregion analysis within a given tumor supported initial findings and revealed intratumor compartmentalization of T cell memory and exhaustion phenotypes within GBM subtypes. Collectively, these results characterize immunotherapeutically targetable features of macrophages and suppressed lymphocytes in GBMs defined by MRI-detectable lateral ventricle contact.

Background Glioblastomas (GBM) account for ~60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit; however, no predictive immune features have informed therapeutic stratification. Radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse prognosis compared to patients with ventricle non-contacting GBM (NC-GBM), yet the influence of ventricle contact on anti-tumor immunity is unknown. This study characterized the GBM immune microenvironment and identified targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM patients. Methods Primary glioblastoma tissue was provided with written informed consent in accordance with the Declaration of Helsinki and with approval of the Vanderbilt Institutional Review Board (IRB #131870). Seventeen patients presented with primary, IDH-wildtype C-GBM and 15 with NC-GBM. Machine learning integrated 1) mass cytometry immunophenotyping, 2) metabolic phenotypes, 3) immune cytokine response patterns and induced intracellular signaling networks, and 4) matched multiplex immunohistochemistry on FFPE embedded tissue to identify phenotypic, functional, and spatial biomarkers correlating with patient outcome. Results C-GBM tumors were enriched in STAT3-driven CD32+CD44+HLA-DR+ monocyte-derived macrophages (MDM) compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p<0.001) and depleted in lymphocytes including subsets of T, B and NK cells (2.9 ± 1% vs. 7.6 ± 2%; p<0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p<0.001). Moreover, 45% of exhausted T cells in C-GBM co-expressed the checkpoint receptors PD-1 and TIGIT despite exhibiting metabolic activity consistent with retained functional capacity. As an orthogonal approach, we used multiplex IHC to identify the spatial distribution of immune cells throughout the GBM tumor tissue. K-means clustering identified 10 immunological niches in GBM tumors. Macrophage-tumor niches were most common in C-GBM (17.93% of niches), followed by T cell-microglia-tumor niches (17.72%). Within NC-GBM niches, T cell-T cell interactions were more prevalent in NC-GBM tumors (log odds ratio = 0.90) and correlated with improved survival outcome. Conclusions These findings suggest that factors within the periventricular space negatively influence the immune microenvironment within GBM tumors. Clinically targetable immune biomarkers (e.g. PD-1) were identified in C-GBM. Notably, this work highlights the potential impact of radiologic assessment of lateral ventricle contact as a guide for clinical trial design for immunotherapies in neuro-oncology based on tumor proximity to the lateral ventricle wall. Ethics Approval Primary glioblastoma tissue was provided with written informed consent in accordance with the Declaration of Helsinki and with approval of the Vanderbilt Institutional Review Board (IRB #131870). Consent No sensitive or identifiable information is included in this study.

Glioblastomas (GBM) are tumors for which immune-targeted therapies have failed to show clinical benefit and for which few biomarkers provide context for meaningful therapeutic stratification. Radiographic contact of GBM tumors with the lateral ventricle stem cell niche correlates with worse patient prognosis; however, the extent to which proximity to the ventricle impacts antitumor immunity remains unknown. We demonstrate that T cell checkpoint receptor expression is elevated in ventricle-contacting GBM as is the abundance of a specific, suppressive CD32 + CD44 + HLAD high myeloid population suggesting a distinct immunoregulatory influence on antitumor immunity in proximity to the lateral ventricle. Phospho-specific mass cytometric profiling revealed extensively impaired immune signaling in ventricle-contacting GBM in response to inflammatory cytokine stimulation, further supporting a suppressive milieu influencing immunity at the lateral ventricle. Collectively, we identify a regulatory impact of ventricle contact on antitumor immunity in the brain, and reveal novel clinically targetable mechanisms of immunomodulation in patients with glioblastoma. Significance Statement We demonstrate that the immune microenvironment of glioblastoma tumors contacting the lateral ventricle differs from non-contacting tumors. This work connects immune-biology to a radiographically detectable feature, the lateral ventricle, and highlights non-invasive imaging as a means to identify targetable immune features in glioblastoma tumors.

Glioblastomas (GBM) account for ~60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit; however, no predictive immune features have informed therapeutic stratification. Radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse prognosis compared to patients with ventricle non-contacting GBM (NC-GBM), yet the influence of ventricle contact on anti-tumor immunity is unknown. This study characterized the GBM immune microenvironment and identified targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM patients.Primary glioblastoma tissue was provided with written informed consent in accordance with the Declaration of Helsinki and with approval of the Vanderbilt Institutional Review Board (IRB #131870). Seventeen patients presented with primary, IDH-wildtype C-GBM and 15 with NC-GBM. Machine learning integrated mass cytometry and matched multiplex immunohistochemistry on FFPE embedded tissue to identify phenotypic, functional, and spatial biomarkers correlating with patient outcome. C-GBM tumors were enriched in STAT3-driven CD32+CD44+HLA-DR+ monocyte-derived macrophages (MDM) compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p< 0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p< 0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p< 0.001). Exhausted T cells in C-GBM co-expressed checkpoint receptors PD-1 and TIGIT. K-means clustering identified 10 immunological niches in GBM. Macrophage-tumor niches were most common in C-GBM (17.93% of niches), followed by T cell-microglia-tumor niches (17.72%). Within NC-GBM niches, T cell-T cell interactions were more prevalent (log odds ratio = 0.90) and correlated with improved outcome.These findings suggest that factors within the periventricular space negatively influence the immune microenvironment within GBM tumors. Clinically targetable immune biomarkers were identified in C-GBM. Notably, radiologic assessment of lateral ventricle contact may guide clinical trial design for immunotherapies in neuro-oncology based on tumor proximity to the ventricle wall.

BackgroundGlioblastomas (GBM) account for 60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit in GBM patients; however, no predictive immune features currently inform therapeutic stratification in GBM. We have shown that, independently of known prognosticators, radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse survival prognosis compared to patients with ventricle non-contacting GBM (NC-GBM). This study sought to characterize the GBM immune microenvironment and identify targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM.MethodsTwelve patients presented with pathologically confirmed primary, IDH wildtype C-GBM and thirteen with NC-GBM. Multiplex immunohistochemistry (mxIHC) was performed on formalin-fixed paraffin embedded (FFPE) tissue for each patient interrogating 8 predictive immune markers (CD3, CD4, CD8, FOXP3, CD68, IBA1, PD-1, and PD-L1). Machine learning tools characterized tumor-infiltrating immune populations and identified biomarkers correlating with C-GBM and patient survival. K-means clustering identified immunological neighborhoods within the tissue and a log odds ratio was used to quantify the likelihood of cell-cell interactions in the tissue.ResultsC-GBM tumors were enriched in monocyte-derived macrophages (MDM) compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p<0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p<0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p<0.001). Further, T cells in C-GBM co-expressed the checkpoint receptors PD-1, suggesting T cell exhaustion in the C-GBM tumor microenvironment. K-means clustering identified 10 immunological niches prevalent in GBM tissue. Macrophage-tumor niches were most common niche in the tissue accounting for 17.93% of all niches, followed by T cell-microglia-tumor niches (17.72%). Conversely, tumor-tumor niches were the least prevalent, accounting for only 2.51% of niches. Within niches, T cell-T cell interactions occurred more frequently than expected by random chance (log odds ratio = 0.90) whereas T cell-macrophage interactions occurred less frequently than expected by random chance (log odds ratio = -1.61). Pathological assessment of the tissue confirmed the presence of lymphoid aggregates in regions of myeloid exclusion in the tissue.ConclusionsThese findings suggest that factors within the periventricular space may influence antitumor immunity within GBM, and have identified clinically targetable immune biomarkers in glioblastoma. The prevalence of T cell niches in GBM tumors suggests the establishment tertiary lymphoid aggregates may be targetable to improve patient outcomes. Lastly, radiologic assessment of lateral ventricle contact by standard-of-care MRI may guide clinical trial design for immunotherapies in neuro-oncology.AcknowledgementsThis study was funded by NIH/NCI grant K00 CA212447 and supported by the Translational Pathology Shared Resource at Vanderbilt University (P30 CA068485).Ethics ApprovalPrimary glioblastoma tumors obtained in accordance with the Declaration of Helsinki and with institutional IRB approval (#131870) along with patient written informed consent.

In the development of telemanipulated surgical robots, a class of continuum robots known as concentric tube robots has drawn particular interest for clinical applications in which space is a major limitation. One such application is transnasal surgery, which is used to access surgical sites in the sinuses and at the skull base. Current techniques for performing these procedures require surgeons to maneuver multiple rigid tools through the narrow confines of the nasal passages, leaving them with limited dexterity at the surgical site. In this article, we present a complete robotic system for transnasal surgery featuring concentric tube manipulators. It illustrates a bagging concept for sterility, and intraoperatively interchangeable instruments that work in conjunction with it, which were developed with operating room workflow compatibility in mind. The system also includes a new modular, portable surgeon console, a variable view-angle endoscope to facilitate surgical field visualization, and custom motor control electronics. Furthermore, we demonstrate elastic instability avoidance for the first time on a physical prototype in a geometrically accurate surgical scenario, which facilitates use of higher curvature tubes than could otherwise be used safely in this application. From a surgical application perspective, this article presents the first robotic approach to removing tumors growing behind the eyes in the orbital apex region, which has not been attempted previously with a surgical robot.

Glioblastomas (GBM) account for 60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit in GBM patients; however, no predictive immune features currently inform therapeutic stratification in GBM. We have shown that, independently of known prognosticators, radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse prognosis compared to patients with ventricle non-contacting GBM (NC-GBM). This study sought to characterize the GBM immune microenvironment and identify targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM. Primary glioblastoma specimens were resected in accordance with the Declaration of Helsinki (IRB #131870). Twelve patients presented with C-GBM and thirteen with NC-GBM. Machine learning tools applied to mass cytometry data characterized tumor-infiltrating immune populations and identified biomarkers correlating with C-GBM and patient survival. C-GBM tumors were enriched in blood-derived macrophages compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p< 0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p< 0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p< 0.001). Further, T cells in C-GBM co-expressed the checkpoint receptors PD-1 and TIGIT, suggesting acute T cell exhaustion. Multiplex immunohistochemistry (mxIHC) on matched FFPE tissue provided spatial context to risk-stratifying immune populations, and defined structured immunological niches within the TME. Macrophage-tumor niches were most common (36%), followed by T cell-microglia-tumor niches (26%). Within niches, T cell-T cell interactions were more prevalent (log odds ratio = 0.90) whereas T cell-macrophage interactions were less prevalent (log odds ratio = -1.61). These findings suggest that factors within the periventricular space may influence antitumor immunity within tumors, and identify clinically targetable immune biomarkers in glioblastoma. Notably, radiologic assessment of lateral ventricle contact by standard-of-care MRI may guide clinical trial design for immunotherapies in neuro-oncology.

Open surgical approaches are still often employed in neurosurgery, despite the availability of neuroendoscopic approaches that reduce invasiveness. The challenge of maneuvering instruments at the tip of the endoscope makes neuroendoscopy demanding for the physician. The only way to aim tools passed through endoscope ports is to tilt the entire endoscope; but, tilting compresses brain tissue through which the endoscope passes and can damage it. Concentric tube robots can provide necessary dexterity without endoscope tilting, while passing through existing ports in the endoscope and carrying surgical tools in their inner lumen. In this paper we describe the mechatronic design of a new concentric tube robot that can deploy two concentric tube manipulators through a standard neuroendoscope. The robot uses a compact differential drive and features embedded motor control electronics and redundant position sensors for safety. In addition to the mechatronic design of this system, this paper contributes experimental validation in the context of colloid cyst removal, comparing our new robotic system to standard manual endoscopy in a brain phantom. The robotic approach essentially eliminated endoscope tilt during the procedure (17.09° for the manual approach vs. 1.16° for the robotic system). The robotic system also enables a single surgeon to perform the procedure - typically in a manual approach one surgeon aims the endoscope and another operates the tools delivered through its ports.

Glioblastomas (GBM) account for up to 60% of all adult primary brain tumors. With few advances in therapeutics, median overall survival (mOS) remains at 15-months post diagnosis. Success of immunotherapy in peripheral solid tumors may offer an alternative therapeutic approach for patients with GBM tumors; however, no predictive immune features currently inform therapeutic stratification for GBM. Recently, we have identified radiographic tumor contact with the lateral ventricle (LV) as a prognostic indicator of OS, as patients with LV+ GBM survive 7 months less than patients with LV- gliomas. This disparity was independent of known prognostic factors (e.g. KPS, extent of resection). Further, we have identified a correlation between greater immune infiltration and the frequency of tumor subtypes with more favorable prognosis. We therefore hypothesized that differences in overall survival between patients with LV+ and LV- are due, in part, to a uniquely immunosuppressive microenvironment within the LV. Using 35-parameter single-cell mass cytometry (CyTOF) we profiled the immune infiltrate of human GBM tissue acquired in accordance with the Declaration of Helsinki and with the approval of the institutional review board (IRB #131870). Computational approaches (tSNE, Citrus, RAPID) correlated natural killer (NK) cell populations correlating with prognosis. NK cells made of 1–14% of the total immune infiltrate in GBM. Ninety percent of NK cells infiltrating LV- tumors were CD16+CD56dim cytotoxic NK cells (cNK). LV+ gliomas, however, were enriched in CD16+CD56bright immunoregulatory NK cells (irNK). The presence of cNK cells correlated with a 2.5-fold improvement of OS, whereas irNK cells correlated with a 2.2-fold reduction in OS. Further, 30–60% of NK cells infiltrating LV+ tumors expressed checkpoint receptors (TIGIT, TIM3, B7-H3) compared to only 10–20% in LV- tumors. These results suggest that NK cells contribute to immunosuppression in the LV and may serve as alternative targets to T cell-based therapies for GBM.

Background Glioblastomas make up more than 60% of adult primary brain tumors and carry a median survival of less than 15 months despite aggressive therapy. Immunotherapy, now standard of care for many peripheral solid tumors, offers an appealing alternative platform that may improve survival outcomes for patients with glioblastoma; however, predictive features that could inform responsiveness to different immunotherapeutic modalities remains to be elucidated. Recent studies have demonstrated that patients whose tumors show radiographic contact with the lateral ventricle have diminished survival outcomes compared to patients whose tumors do not contact the lateral ventricle. While greater immune infiltrate correlates with more favorable outcomes and more effectual responses to immunotherapy, the anti-tumor immune response in the ventricle is unknown. We hypothesized that ventricle contact may provide a uniquely immunosuppressive microenvironment within the brain that promotes tumor growth by suppressing anti-tumor immunity, that may be overcome with appropriate targeting strategies. Methods Primary glioblastoma tumors obtained in accordance with the Declaration of Helsinki and with institutional IRB approval (#131870) were disaggregated into single-cell suspensions. Radiographic contact with the LV was identified by MRI imaging and confirmed by a trained neurosurgeon. Multi-dimensional single-cell mass cytometry (CyTOF) then measured >30 immune parameters in thirteen immune subpopulations infiltrating human glioblastomas, including T cells, natural killer cells, B cells, microglia, peripheral macrophages, and myeloid-derived suppressors cells (MDSC). Computational machine-learning pipelines including Citrus, t-SNE, FlowSOM, and MEM identified key differences in the abundance and phenotypes of immune infiltrates. Results On the basis of glioblastoma contact with the ventricle, we computationally identified consequential distinctions in the abundance of T cell, macrophage, and microglia subsets constituting five immunotype signatures among glioblastoma patients. Immunotypes associated with CD69+CD32+CD44+ peripheral macrophages and PD-1+TIGIT+ CD8 T cells correlated with ventricle contact, whereas immunotypes associated with enriched γδ T cells, B, NK cell, and tissue-resident microglial cells correlated with tumors distal to the ventricle. Further, immune infiltration in the tumor microenvironment correlated with patient outcome, with higher lymphocyte infiltrates correlating with more favorable outcomes, and immune exhaustion correlating with less favorable outcomes. Conclusions Single-cell mass cytometry in conjunction with the machine learning tools identified key differences in immune cell abundance between lateral ventricle contacting and non-contacting glioblastomas. These results provide key insights into the immune microenvironment of glioblastomas and elucidate several clinically actionable immunotherapeutic targets that may be used to optimize treatment strategies for glioblastomas based on ventricle contact status. Ethics Approval This study was approved by Vanderbilt University’s Institutional Ethics Board, approval number 131870

A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is unsupervised and automated, identifies phenotypically distinct cell populations, and determines whether these populations stratify patient survival. With a pilot mass cytometry dataset of 2 million cells from 28 glioblastomas, RAPID identified tumor cells whose abundance independently and continuously stratified patient survival. Statistical validation within the workflow included repeated runs of stochastic steps and cell subsampling. Biological validation used an orthogonal platform, immunohistochemistry, and a larger cohort of 73 glioblastoma patients to confirm the findings from the pilot cohort. RAPID was also validated to find known risk stratifying cells and features using published data from blood cancer. Thus, RAPID provides an automated, unsupervised approach for finding statistically and biologically significant cells using cytometry data from patient samples.

Glioblastomas make up more than 60% of adult primary brain tumors and carry a 15 month overall survival despite aggressive standard-of-care therapy. Recent advances in immunotherapy offer an appealing alternative that may improve outcomes for patients with glioblastoma; however, clinical trials have proven unsuccessful due in part to a lack of predictive features that may inform responsiveness to immunotherapy. We have recently shown a strong correlation between 1) immune infiltration, 2) tumor cell phenotype, and 3) patient outcome. Further, patients whose tumors demonstrate radiographic contact with the ventricular-subventricular zone (V-SVZ) have reduced survival compared to patients whose tumors do not contact the V-SVZ. We therefore hypothesized that the V-SVZ acts as a previously unappreciated immunosuppressive microenvironment within the brain that promotes tumor growth by suppressing anti-tumor immunity. Primary human glioblastomas were disaggregated into single-cell suspensions and mass cytometry (CyTOF) measured >30 parameters in thirteen immune populations infiltrating human glioblastomas. Cutting-edge machine-learning tools identified key differences in the abundance and phenotypes of T cells, B cells, NK cells, microglia, and peripheral macrophages infiltrating ventricle-contacting gliomas. Further, enriched expression of immune checkpoint receptors (PD-1, TIGIT, LAG-3, TIM3) correlated with ventricular contact and outcome. These results provide key insights into the immune microenvironment of glioblastomas and elucidate several clinically actionable immunotherapeutic targets that may be used to optimize treatment strategies for glioblastoma patients based on V-SVZ contact status.

Abstract Glioblastomas make up more than 60% of adult primary brain tumors and carry a median survival of less than 15 months despite aggressive standard therapy. Immunotherapy, which is now standard of care for many solid tumors, offers an appealing therapeutic approach that may improve outcomes for glioblastoma patients. Predictive features in glioblastomas that may inform responsiveness to different immunotherapeutic modalities, however, are still lacking. Recent studies have demonstrated that patients whose tumors show radiographic contact with the lateral ventricles, and thus the stem cell niche of the ventricular-subventricular zone (V-SVZ), have reduced survival outcomes compared to patients whose tumors do not contact the V-SVZ. We therefore hypothesized that tumor contact with the V-SVZ engenders a unique, immunosuppressive microenvironment that promotes tumor growth by suppressing anti-tumor immunity. Glioblastoma tumors, obtained in accordance with the Declaration of Helsinki and with institutional IRB approval (#131870, #030372, #181970), were disaggregated into single-cell suspensions and multi-dimensional single-cell mass cytometry was performed to interrogate >30 immune parameters in thirteen immune populations infiltrating human glioblastomas. Using advanced computational dimensionality-reduction tools (Citrus, t-SNE, FlowSOM, and MEM), we identified distinctions among the abundance and phenotypes of tumor-infiltrating immune cells. Firstly, on the basis of tumor contact with the V-SVZ, Citrus identified differential abundance of five T and myeloid cell subsets among glioblastomas. Secondly, differential expression of five functional immune markers was observed in seven distinct immune cell subsets infiltrating glioblastoma tumors. Further, both immune abundance and marker expression correlated with patient outcome. Manual gating analysis and parallel computational pipelines confirmed that comparable cell subsets could be identified with traditional approaches and unsupervised algorithmic analysis. These results provide key insights into the immune microenvironment of glioblastomas. In addition, several clinically actionable immunotherapeutic targets were uncovered that may be used to optimize treatment strategies for glioblastomas based on V-SVZ contact status.

Recent developments in machine learning implemented dimensionality reduction and clustering tools to classify the cellular composition of patient-derived tissue in multi-dimensional, single cell studies. Current approaches, however, require prior knowledge of either categorical clinical outcomes or cell type identities. These algorithms are not well suited for application in tumor biology, where clinical outcomes can be continuous and censored and cell identities may be novel and plastic. Risk Assessment Population IDentification (RAPID) is an unsupervised, machine learning algorithm that identifies single cell phenotypes and assesses clinical risk stratification as a continuous variable. Single cell mass cytometry evaluated 34 different phospho-proteins, transcription factors, and cell identity proteins in tumor tissue resected from patients bearing IDH wild-type glioblastomas. RAPID identified and characterized multiple biologically distinct tumor cell subsets that independently and continuously stratified patient outcome. RAPID is broadly applicable for single cell studies where atypical cancer and immune cells may drive disease biology and treatment responses.

In glioblastoma, changes in signaling, gene sequence, copy number, or transcript expression can define patient subgroups, but these subgroups are not yet associated with differential outcome for most patients with high-risk, IDH wild-type disease. Single cell interrogation of phospho-protein signaling has successfully revealed novel cell types associated with patient outcomes in blood cancers, suggesting that a comparable approach could be used in brain tumors. The goal of this study was to combine a single cell phospho-protein profiling approach with novel, automated computational analysis to identify abnormal glioblastoma cells that stratify patient clinical risk. Effective tissue dissociation strategies and validated antibody panels were created for mass cytometry analyses of resected glioblastoma tissue. These panels simultaneously measured 45 determinants of neural and glioma cell identity, including transcription factors, phospho-proteins, and surface receptors. 28 glioblastoma tumors were stained and analyzed using traditional gating, existing computational tools, and a new risk assessment population identification algorithm (RAPID, https://www.biorxiv.org/content/10.1101/632208v3). RAPID revealed two malignant cell types closely associated with differential patient outcomes. Glioblastoma negative prognostic (GNP) cells were associated with poor survival and defined by phospho-protein signaling in cells with aberrant neural developmental phenotypes. Glioblastoma positive prognostic (GPP) cells were associated with better progression free survival and defined by increased immunogenic signaling. A Cox proportional-hazards regression model was created to assess the influence of GNP and GPP cells on OS and PFS as continuous variables while accounting for other well-known clinical predictors. Each 1% increase of GNP cells was associated with an 7% increase in annual mortality rate (HR=1.07 [95% CI 1.03–1.12], p=0.001). Tumors containing GNP cells also significantly lacked CD45+ immune cell infiltration (Pearson r=-0.8). The signaling events that define these clinically significant glioblastoma cells represent a useful molecular classification, may indicate responsiveness to immunotherapy, and are themselves important targets of opportunity for new therapeutic approaches.

Vestibular schwannomas (VS) are treated with fractionated stereotactic radiosurgery (SRS) to attempt hearing preservation. There are no established predictors of longitudinal effect on tumor volume, pseudoprogression or necrosis. An institutional review board approved retrospective review of patients treated with 1, 3, or 5 fraction (fx) SRS for VS at our institution from 1998-2016, with at least 2 years of follow-up was performed. Radiographic follow-up by MRI was used to calculate tumor volume based on tridimensional measurements and non-spherical tumor volume was approximated by pi/6*x*y*z. Radiologic responders were those with reduction by at least 2mm in any dimension. Radiologic non-responders had no growth or reduction. Treatment failures grew at least 2mm in any dimension by last follow-up. Pseudoprogression was defined as any interval increase in tumor volume that later normalized or reduced to below baseline tumor volume. A total of 56 patients met selection criteria. Most patients were treated with 5 fractions (32, 57%), then 3 fractions (12, 21%) and 1 fraction (12, 21%). The most common dose and fractionation regimens were 1250 cGy x 1 (7, 12.5%), 700 cGy x 3 (12, 21.4%), 500 cGy x 5 (12, 21.4%), and 450 cGy x 5 (14, 25%). Patients treated with 1 fx had a median baseline tumor volume of 1.2 cc (range 0.04-3.88), median dose 1250 cGy per fx (range 1200-1600), and median percent reduction in tumor volume of 2.7 % (range -396 to 85). Patients treated with 3 fxs had a median baseline tumor volume of 1.2 cc (range 0.4-7.7), median dose of 700 cGy (range 700-700), and a median percent reduction in tumor volume of 24 % (range -272 to 92). Patients treated with 5 fxs had a median baseline tumor volume of 2.0 cc (range 0.07-7.49), median dose of 450 cGy (range 400-550), and a median percent reduction in tumor volume of 6 % (range -290 to 89). Regardless of the number of fxs, patients had similar rates of pseudoprogression (25% in single, 33% in 3 fx and 31% in 5 fx cohorts). Patients treated with 3 fxs had lower rates of radiographic necrosis (58% with 3 fx vs 75% with 1 or 5 fx) but higher rates of radiologic response (67% with 3 fx vs 33% with 1 fx or 44% with 5 fx) and lower rates of radiologic non-response (17% with 3 fx vs 58% with 1 fx or 38% with 5 fx). Patients with more fxs had higher rates of treatment failure (8% with 1 fx vs 17% with 3 fx or 19% with 5 fx). SRS with 1, 3, or 5 fxs was safe and effective in reducing tumor volume of VS. About one-third of all patients had evidence of pseudoprogression. Patients treated with 3 fx SRS had the largest % reduction in tumor volume (median 24%) and lowest rates of necrosis.