Cell Therapy for Chronic TBI: Interim Analysis of the Randomized Controlled STEMTRA Trial.

OBJECTIVE: To determine if chronic motor deficits secondary to traumatic brain injury (TBI) can be improved by implantation of allogeneic modified bone marrow-derived mesenchymal stromal/stem cells (SB623). METHODS: This 6-month interim analysis of the 1-year double-blind, randomized, surgical sham-controlled, phase 2 STEMTRA trial (NCT02416492) evaluated safety and efficacy of the stereotactic intracranial implantation of SB623 in patients with stable chronic motor deficits secondary to TBI. Patients in this multi-center trial (N = 63) underwent randomization in a 1:1:1:1 ratio to 2.5 × 106, 5.0 × 106, 10 × 106 SB623 cells or control. Safety was assessed in patients who underwent surgery (N = 61), and efficacy in the modified intent-to-treat population of randomized patients who underwent surgery (N = 61; SB623 = 46, control = 15). RESULTS: The primary efficacy endpoint of significant improvement from baseline of Fugl-Meyer Motor Scale score at 6 months for SB623-treated patients was achieved. SB623-treated patients improved by (LS mean [SE]) +8.3 (1.4) vs +2.3 (2.5) for control at 6 months, the LS mean difference was 6.0 (95% CI: 0.3-11.8); p = 0.040. Secondary efficacy endpoints improved from baseline, but were not statistically significant vs control at 6 months. There were no dose-limiting toxicities or deaths, and 100% of SB623-treated patients experienced treatment-emergent adverse events vs 93.3% of control patients (p = 0.25). CONCLUSIONS: SB623 cell implantation appeared to be safe and well tolerated, and patients implanted with SB623 experienced significant improvement from baseline motor status at 6 months compared to controls. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that implantation of SB623 was well tolerated and associated with improvement in motor status.

Biological intratumoral therapy for the high-grade glioma part II: vector- and cell-based therapies and radioimmunotherapy.

Management of high-grade gliomas (HGGs) remains a complex challenge with an overall poor prognosis despite aggressive multimodal treatment. New translational research has focused on maximizing tumor cell eradication through improved tumor cell targeting while minimizing collateral systemic side effects. In particular, biological intratumoral therapies have been the focus of novel translational research efforts due to their inherent potential to be both dynamically adaptive and target specific. This two part review will provide an overview of biological intratumoral therapies that have been evaluated in human clinical trials in HGGs, and summarize key advances and remaining challenges in the development of these therapies as a potential new paradigm in the management of HGGs. Part II discusses vector-based therapies, cell-based therapies and radioimmunotherapy.

Biological intratumoral therapy for the high-grade glioma part I: intratumoral delivery and immunotoxins.

Management of high-grade gliomas remains a complex challenge. Standard of care consists of microsurgical resection, chemotherapy and radiation, but despite these aggressive multimodality therapies the overall prognosis remains poor. A major focus of ongoing translational research studies is to develop novel therapeutic strategies that can maximize tumor cell eradication while minimizing collateral side effects. Particularly, biological intratumoral therapies have been the focus of new translational research efforts due to their inherent potential to be both dynamically adaptive and target specific. This two-part review will provide an overview of biological intratumoral therapies and summarize key advances and remaining challenges in intratumoral biological therapies for high-grade glioma. Part I focuses on discussion of the concepts of intratumoral delivery and immunotoxin therapies.

Diabetes Insipidus following Endoscopic Transsphenoidal Surgery for Pituitary Adenoma.

Objectives Pituitary adenoma (PA), among the most commonly encountered sellar pathologies, accounts for 10% of primary intracranial tumors. The reported incidence of postoperative diabetes insipidus (DI) is highly variable. In this study, we report our experience with DI following endoscopic transsphenoidal surgery (TSS) for PAs, elucidating the risk factors of postoperative DI, the likelihood of long-term DI, and the impact of DI on the length of stay (LOS). Methods The study included 178 patients who underwent endoscopic resection of PAs. Early DI was defined as that occurring within the first postoperative week. The mean follow-up was 36 months. Long-term DI was considered as DI apparent in the last follow-up visit. Results Of the 178 patients included in the study, 77% of the tumors were macroadenomas. Forty-seven patients (26%) developed early DI. Long-term DI was observed in 18 (10.1%) of the full cohort. Age younger than 50 years was significantly associated with a higher incidence of long-term DI ( p = 0.02). Macroadenoma and gross total resection were significantly associated with higher incidence of early DI ( p = 0.05 and p = 0.04, respectively). The mean LOS was 4 days for patients with early postoperative DI and 3 days for those without it. Conclusion The reported incidence of postoperative DI is significantly variable. We identified age younger than 50 years a risk factor for developing long-term postoperative DI. Gross total surgical resection and tumor size (> 1 cm) were associated with development of early DI. Early DI increased the LOS on average by 1 day.

Cavernous Sinus Involvement by Pituitary Adenomas: Clinical Implications and Outcomes of Endoscopic Endonasal Resection.

Background Parasellar invasion of pituitary adenomas (PAs) into the cavernous sinus (CS) is common. The management of the CS component of PA remains controversial. Objective The objective of this study was to analyze CS involvement in PA treated with endoscopic endonasal approaches, including incidence, surgical risks, surgical strategies, long-term outcomes, and our treatment algorithm. Methods We reviewed a series of 176 surgically treated PA with particular attention to CS involvement and whether the CS tumor was approached medial or lateral to the internal carotid artery. Results The median duration of follow-up was 36 months. Macroadenomas and nonfunctional adenomas represented 77 and 60% of cases, respectively. CS invasion was documented in 23% of cases. CS involvement was associated with a significantly diminished odds of gross total resection (47 vs. 86%, odds ratio [OR]: 5.2) and increased the need for subsequent intervention (4 vs. 40%, OR: 14.4). Hormonal remission was achieved in 15% of hormonally active tumors. Rates of surgical complication were similar regardless of CS involvement. Conclusion Our tailored strategy beginning with a medial approach and adding lateral exposure as needed resulted in good outcomes with low morbidity in nonfunctional adenomas. Functional adenomas involving the CS were associated with low rates of hormonal remission necessitating higher rates of additional treatment.

Revealing cancer subtypes with higher-order correlations applied to imaging and omics data.

BACKGROUND: Patient stratification to identify subtypes with different disease manifestations, severity, and expected survival time is a critical task in cancer diagnosis and treatment. While stratification approaches using various biomarkers (including high-throughput gene expression measurements) for patient-to-patient comparisons have been successful in elucidating previously unseen subtypes, there remains an untapped potential of incorporating various genotypic and phenotypic data to discover novel or improved groupings. METHODS: Here, we present HOCUS, a unified analytical framework for patient stratification that uses a community detection technique to extract subtypes out of sparse patient measurements. HOCUS constructs a patient-to-patient network from similarities in the data and iteratively groups and reconstructs the network into higher order clusters. We investigate the merits of using higher-order correlations to cluster samples of cancer patients in terms of their associations with survival outcomes. RESULTS: In an initial test of the method, the approach identifies cancer subtypes in mutation data of glioblastoma, ovarian, breast, prostate, and bladder cancers. In several cases, HOCUS provides an improvement over using the molecular features directly to compare samples. Application of HOCUS to glioblastoma images reveals a size and location classification of tumors that improves over human expert-based stratification. CONCLUSIONS: Subtypes based on higher order features can reveal comparable or distinct groupings. The distinct solutions can provide biologically- and treatment-relevant solutions that are just as significant as solutions based on the original data.

Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment.

BACKGROUND: In previous clinical trials, antiangiogenic therapies such as bevacizumab did not show efficacy in patients with newly diagnosed glioblastoma (GBM). This may be a result of the heterogeneity of GBM, which has a variety of imaging-based phenotypes and gene expression patterns. In this study, we sought to identify a phenotypic subtype of GBM patients who have distinct tumor-image features and molecular activities and who may benefit from antiangiogenic therapies. METHODS: Quantitative image features characterizing subregions of tumors and the whole tumor were extracted from preoperative and pretherapy perfusion magnetic resonance (MR) images of 117 GBM patients in 2 independent cohorts. Unsupervised consensus clustering was performed to identify robust clusters of GBM in each cohort. Cox survival and gene set enrichment analyses were conducted to characterize the clinical significance and molecular pathway activities of the clusters. The differential treatment efficacy of antiangiogenic therapy between the clusters was evaluated. RESULTS: A subgroup of patients with elevated perfusion features was identified and was significantly associated with poor patient survival after accounting for other clinical covariates (P values <.01; hazard ratios > 3) consistently found in both cohorts. Angiogenesis and hypoxia pathways were enriched in this subgroup of patients, suggesting the potential efficacy of antiangiogenic therapy. Patients of the angiogenic subgroups pooled from both cohorts, who had chemotherapy information available, had significantly longer survival when treated with antiangiogenic therapy (log-rank P=.022). CONCLUSIONS: Our findings suggest that an angiogenic subtype of GBM patients may benefit from antiangiogenic therapy with improved overall survival.

Pituitary Apoplexy Associated with Carotid Compression and a Large Ischemic Penumbra.

BACKGROUND: Pituitary apoplexy is an acute clinical syndrome caused by pituitary gland hemorrhage or infarction. Rarely, this clinical syndrome is associated with cerebral infarction secondary to compression of an internal carotid artery. We report an unusual case of pituitary apoplexy associated with a cerebral infarct with a large ischemic penumbra. CASE DESCRIPTION: The patient presented with headaches and visual disturbance and was found to have pituitary apoplexy. Findings of his neurologic examination showed he had rapidly deteriorated, with obtundation, ophthalmoplegia, and left hemiplegia. Computed tomography perfusion images revealed a right hemispheric infarct with a large ischemic penumbra. Emergent decompressive transsphenoidal resection was performed. The patient had dramatic neurologic recovery, and postoperative imaging revealed salvage of most of the previously identified penumbra. CONCLUSIONS: Cerebral perfusion imaging is a useful diagnostic tool for identifying the subset of pituitary apoplexy patients that may benefit from emergent surgical intervention.

High-Resolution Microfluidic Single-Cell Transcriptional Profiling Reveals Clinically Relevant Subtypes among Human Stem Cell Populations Commonly Utilized in Cell-Based Therapies.

Stem cell therapies can promote neural repair and regeneration, yet controversy regarding optimal cell source and mechanism of action has slowed clinical translation, potentially due to undefined cellular heterogeneity. Single-cell resolution is needed to identify clinically relevant subpopulations with the highest therapeutic relevance. We combine single-cell microfluidic analysis with advanced computational modeling to study for the first time two common sources for cell-based therapies, human NSCs and MSCs. This methodology has the potential to logically inform cell source decisions for any clinical application.

Anti-CD47 Treatment Stimulates Phagocytosis of Glioblastoma by M1 and M2 Polarized Macrophages and Promotes M1 Polarized Macrophages In Vivo.

Tumor-associated macrophages (TAMs) represent an important cellular subset within the glioblastoma (WHO grade IV) microenvironment and are a potential therapeutic target. TAMs display a continuum of different polarization states between antitumorigenic M1 and protumorigenic M2 phenotypes, with a lower M1/M2 ratio correlating with worse prognosis. Here, we investigated the effect of macrophage polarization on anti-CD47 antibody-mediated phagocytosis of human glioblastoma cells in vitro, as well as the effect of anti-CD47 on the distribution of M1 versus M2 macrophages within human glioblastoma cells grown in mouse xenografts. Bone marrow-derived mouse macrophages and peripheral blood-derived human macrophages were polarized in vitro toward M1 or M2 phenotypes and verified by flow cytometry. Primary human glioblastoma cell lines were offered as targets to mouse and human M1 or M2 polarized macrophages in vitro. The addition of an anti-CD47 monoclonal antibody led to enhanced tumor-cell phagocytosis by mouse and human M1 and M2 macrophages. In both cases, the anti-CD47-induced phagocytosis by M1 was more prominent than that for M2. Dissected tumors from human glioblastoma xenografted within NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice and treated with anti-CD47 showed a significant increase of M1 macrophages within the tumor. These data show that anti-CD47 treatment leads to enhanced tumor cell phagocytosis by both M1 and M2 macrophage subtypes with a higher phagocytosis rate by M1 macrophages. Furthermore, these data demonstrate that anti-CD47 treatment alone can shift the phenotype of macrophages toward the M1 subtype in vivo.

Multiple Subsets of Brain Tumor Initiating Cells Coexist in Glioblastoma.

Brain tumor-initiating cells (BTICs) are self-renewing multipotent cells critical for tumor maintenance and growth. Using single-cell microfluidic profiling, we identified multiple subpopulations of BTICs coexisting in human glioblastoma, characterized by distinct surface marker expression and single-cell molecular profiles relating to divergent bulk tissue molecular subtypes. These data suggest BTIC subpopulation heterogeneity as an underlying source of intra-tumoral bulk tissue molecular heterogeneity, and will support future studies into BTIC subpopulation-specific therapies. Stem Cells 2016;34:1702-1707.

Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities.

Glioblastoma (GBM) is the most common and highly lethal primary malignant brain tumor in adults. There is a dire need for easily accessible, noninvasive biomarkers that can delineate underlying molecular activities and predict response to therapy. To this end, we sought to identify subtypes of GBM, differentiated solely by quantitative magnetic resonance (MR) imaging features, that could be used for better management of GBM patients. Quantitative image features capturing the shape, texture, and edge sharpness of each lesion were extracted from MR images of 121 single-institution patients with de novo, solitary, unilateral GBM. Three distinct phenotypic "clusters" emerged in the development cohort using consensus clustering with 10,000 iterations on these image features. These three clusters--pre-multifocal, spherical, and rim-enhancing, names reflecting their image features--were validated in an independent cohort consisting of 144 multi-institution patients with similar tumor characteristics from The Cancer Genome Atlas (TCGA). Each cluster mapped to a unique set of molecular signaling pathways using pathway activity estimates derived from the analysis of TCGA tumor copy number and gene expression data with the PARADIGM (Pathway Recognition Algorithm Using Data Integration on Genomic Models) algorithm. Distinct pathways, such as c-Kit and FOXA, were enriched in each cluster, indicating differential molecular activities as determined by the image features. Each cluster also demonstrated differential probabilities of survival, indicating prognostic importance. Our imaging method offers a noninvasive approach to stratify GBM patients and also provides unique sets of molecular signatures to inform targeted therapy and personalized treatment of GBM.

Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features.

PURPOSE: To derive quantitative image features from magnetic resonance (MR) images that characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to create radiogenomic maps associating these features with various molecular data. MATERIALS AND METHODS: Clinical, molecular, and MR imaging data for GBMs in 55 patients were obtained from the Cancer Genome Atlas and the Cancer Imaging Archive after local ethics committee and institutional review board approval. Regions of interest (ROIs) corresponding to enhancing necrotic portions of tumor and peritumoral edema were drawn, and quantitative image features were derived from these ROIs. Robust quantitative image features were defined on the basis of an intraclass correlation coefficient of 0.6 for a digital algorithmic modification and a test-retest analysis. The robust features were visualized by using hierarchic clustering and were correlated with survival by using Cox proportional hazards modeling. Next, these robust image features were correlated with manual radiologist annotations from the Visually Accessible Rembrandt Images (VASARI) feature set and GBM molecular subgroups by using nonparametric statistical tests. A bioinformatic algorithm was used to create gene expression modules, defined as a set of coexpressed genes together with a multivariate model of cancer driver genes predictive of the module's expression pattern. Modules were correlated with robust image features by using the Spearman correlation test to create radiogenomic maps and to link robust image features with molecular pathways. RESULTS: Eighteen image features passed the robustness analysis and were further analyzed for the three types of ROIs, for a total of 54 image features. Three enhancement features were significantly correlated with survival, 77 significant correlations were found between robust quantitative features and the VASARI feature set, and seven image features were correlated with molecular subgroups (P < .05 for all). A radiogenomics map was created to link image features with gene expression modules and allowed linkage of 56% (30 of 54) of the image features with biologic processes. CONCLUSION: Radiogenomic approaches in GBM have the potential to predict clinical and molecular characteristics of tumors noninvasively. Online supplemental material is available for this article.

Multiplex meta-analysis of medulloblastoma expression studies with external controls.

We propose and discuss a method for doing gene expression meta-analysis (multiple datasets) across multiplex measurement modalities measuring the expression of many genes simultaneously (e.g. microarrays and RNAseq) using external control samples and a method of heterogeneity detection to identify and filter on comparable gene expression measurements. We demonstrate this approach on publicly available gene expression datasets from samples of medulloblastoma and normal cerebellar tissue and identify some potential new targets in the treatment of medulloblastoma.

Sex differences in clinical presentation and treatment outcomes in Moyamoya disease.

BACKGROUND: Moyamoya (MM) disease is an idiopathic steno-occlusive angiopathy occurring more frequently in females. OBJECTIVE: To evaluate sex differences in preoperative symptoms and treatment outcomes after revascularization surgery. METHODS: We analyzed 430 MM disease patients undergoing 717 revascularization procedures spanning 19 years (1991-2010) and compared gender differences in preoperative symptoms and long-term outcomes after surgical revascularization. RESULTS: A total of 307 female and 123 male patients (ratio, 2.5:1) with a mean age of 31.0 ± 16.7 years and adults-to-children ratio of 2.5:1 underwent 717 revascularization procedures. Female patients were more likely to experience preoperative transient ischemic attacks (odds ratio: 2.1, P = .001) and less likely to receive a diagnosis of unilateral MM disease (odds ratio: 0.6, P = .04). No association was observed between sex and risk of preoperative ischemic or hemorrhagic stroke. There was no difference in neurological outcome because both male and female patients experienced significant improvement in the modified Rankin Scale score after surgery (P < .0001). On Kaplan-Meier survival analysis, 5-year cumulative risk of adverse postoperative events despite successful revascularization was 11.4% in female vs 5.3% in male patients (P = .05). In multivariate Cox proportional hazards analysis, female sex trended toward an association with adverse postoperative events (hazard ratio: 1.9, P = .14). CONCLUSION: Female patients are more susceptible to the development of preoperative transient ischemic attack and may be at higher risk of adverse postoperative events despite successful revascularization. There is, however, no sex difference in neurological outcome because patients of both sexes experience significant improvement in neurological status with low risk of the development of future ischemic events after surgical revascularization.

Clinical neuroproteomics and biomarkers: from basic research to clinical decision making.

Clinical neuroproteomics aims to advance our understanding of disease and injury affecting the central and peripheral nervous systems through the study of protein expression and the discovery of protein biomarkers to facilitate diagnosis and treatment. The general premise of the biomarker field is that in vivo factors present in either tissue or circulating biofluids, reflect pathological changes, and can be identified and analyzed. This approach offers an opportunity to illuminate changes occurring at both the population and patient levels toward the realization of personalized medicine. This review is intended to provide research-driven clinicians with an overview of protein biomarkers of disease and injury for clinical use and to highlight methodology and potential pitfalls. We examine the neuroproteomic biomarker field and discuss the hallmarks and the challenges of clinically relevant biomarker discovery relating to central nervous system pathology. We discuss the issues in the maturation of potential biomarkers from discovery to Food and Drug Administration approval and review several platforms for protein biomarker discovery, including protein microarray and mass spectrometry-based proteomics. We describe the application of microfluidic technologies to the evolution of a robust clinical test. Finally, we highlight several biomarkers currently in use for cancer, ischemia, and injury in the central nervous system. Future efforts using these technologies will result in the maturation of existing and the identification of de novo biomarkers that could guide clinical decision making and advance diagnostic and therapeutic options for the treatment of neurological disease and injury.

Gene expression profiling of blood in brain arteriovenous malformation patients.

Brain arteriovenous malformations (BAVMs) are an important cause of intracranial hemorrhage (ICH) in young adults. Gene expression profiling of blood has led to the identification of stroke biomarkers, and may help identify BAVM biomarkers and illuminate BAVM pathogenesis. It is unknown whether blood gene expression profiles differ between 1) BAVM patients and healthy controls, or 2) unruptured and ruptured BAVM patients at presentation. We characterized blood transcriptional profiles in 60 subjects (20 unruptured BAVM, 20 ruptured BAVM, and 20 healthy controls) using Affymetrix whole genome expression arrays. Expression differences between groups were tested by ANOVA, adjusting for potential confounders. Genes with absolute fold change ≥ 1.2 (false discovery rate corrected p ≤ 0.1) were selected as differentially expressed and evaluated for over-representation in KEGG biological pathways (p ≤ 0.05). Twenty-nine genes were differentially expressed between unruptured BAVM patients and controls, including 13 which may be predictive of BAVM. Patients with ruptured BAVM compared to unruptured BAVM differed in expression of 1490 genes, with over-representation of genes in 8 pathways including MAPK, VEGF, Wnt signaling and several inflammatory pathways. These results suggest clues to the pathogenesis of BAVM and/or BAVM rupture and point to potential biomarkers or new treatment targets.

Ten-year detection rate of brain arteriovenous malformations in a large, multiethnic, defined population.

BACKGROUND AND PURPOSE: To evaluate whether increased neuroimaging use is associated with increased brain arteriovenous malformation (BAVM) detection, we examined detection rates in the Kaiser Permanente Medical Care Program of northern California between 1995 and 2004. METHODS: We reviewed medical records, radiology reports, and administrative databases to identify BAVMs, intracranial aneurysms (IAs: subarachnoid hemorrhage [SAH] and unruptured aneurysms), and other vascular malformations (OVMs: dural fistulas, cavernous malformations, Vein of Galen malformations, and venous malformations). Poisson regression (with robust standard errors) was used to test for trend. Random-effects meta-analysis generated a pooled measure of BAVM detection rate from 6 studies. RESULTS: We identified 401 BAVMs (197 ruptured, 204 unruptured), 570 OVMs, and 2892 IAs (2079 SAHs and 813 unruptured IAs). Detection rates per 100 000 person-years were 1.4 (95% CI, 1.3 to 1.6) for BAVMs, 2.0 (95% CI, 1.8 to 2.3) for OVMs, and 10.3 (95% CI, 9.9 to 10.7) for IAs. Neuroimaging utilization increased 12% per year during the time period (P<0.001). Overall, rates increased for IAs (P<0.001), remained stable for OVMs (P=0.858), and decreased for BAVMs (P=0.001). Detection rates increased 15% per year for unruptured IAs (P<0.001), with no change in SAHs (P=0.903). However, rates decreased 7% per year for unruptured BAVMs (P=0.016) and 3% per year for ruptured BAVMs (P=0.005). Meta-analysis yielded a pooled BAVM detection rate of 1.3 (95% CI, 1.2 to 1.4) per 100 000 person-years, without heterogeneity between studies (P=0.25). CONCLUSIONS: Rates for BAVMs, OVMs, and IAs in this large, multiethnic population were similar to those in other series. During 1995 to 2004, a period of increasing neuroimaging utilization, we did not observe an increased rate of detection of unruptured BAVMs, despite increased detection of unruptured IAs.