Jeffrey M. Treiber

Impaired thalamocortical connectivity in autism spectrum disorder: a study of functional and anatomical connectivity

The thalamus plays crucial roles in the development and mature functioning of numerous sensorimotor, cognitive and attentional circuits. Currently limited evidence suggests that autism spectrum disorder may be associated with thalamic abnormalities, potentially related to sociocommunicative and other impairments in this disorder. We used functional connectivity magnetic resonance imaging and diffusion tensor imaging probabilistic tractography to study the functional and anatomical integrity of thalamo-cortical connectivity in children and adolescents with autism spectrum disorder and matched typically developing children. For connectivity with five cortical seeds (prefontal, parieto-occipital, motor, somatosensory and temporal), we found evidence of both anatomical and functional underconnectivity. The only exception was functional connectivity with the temporal lobe, which was increased in the autism spectrum disorders group, especially in the right hemisphere. However, this effect was robust only in partial correlation analyses (partialling out time series from other cortical seeds), whereas findings from total correlation analyses suggest that temporo-thalamic overconnectivity in the autism group was only relative to the underconnectivity found for other cortical seeds. We also found evidence of microstructural compromise within the thalamic motor parcel, associated with compromise in tracts between thalamus and motor cortex, suggesting that the thalamus may play a role in motor abnormalities reported in previous autism studies. More generally, a number of correlations of diffusion tensor imaging and functional connectivity magnetic resonance imaging measures with diagnostic and neuropsychological scores indicate involvement of abnormal thalamocortical connectivity in sociocommunicative and cognitive impairments in autism spectrum disorder.

Iterative Probabilistic Voxel Labeling: Automated Segmentation for Analysis of The Cancer Imaging Archive Glioblastoma Images

BACKGROUND AND PURPOSE: Robust, automated segmentation algorithms are required for quantitative analysis of large imaging datasets. We developed an automated method that identifies and labels brain tumor–associated pathology by using an iterative probabilistic voxel labeling using k-nearest neighbor and Gaussian mixture model classification. Our purpose was to develop a segmentation method which could be applied to a variety of imaging from The Cancer Imaging Archive. MATERIALS AND METHODS: Images from 2 sets of 15 randomly selected subjects with glioblastoma from The Cancer Imaging Archive were processed by using the automated algorithm. The algorithm-defined tumor volumes were compared with those segmented by trained operators by using the Dice similarity coefficient. RESULTS: Compared with operator volumes, algorithm-generated segmentations yielded mean Dice similarities of 0.92 ± 0.03 for contrast-enhancing volumes and 0.84 ± 0.09 for FLAIR hyperintensity volumes. These values compared favorably with the means of Dice similarity coefficients between the operator-defined segmentations: 0.92 ± 0.03 for contrast-enhancing volumes and 0.92 ± 0.05 for FLAIR hyperintensity volumes. Robust segmentations can be achieved when only postcontrast T1WI and FLAIR images are available. CONCLUSIONS: Iterative probabilistic voxel labeling defined tumor volumes that were highly consistent with operator-defined volumes. Application of this algorithm could facilitate quantitative assessment of neuroimaging from patients with glioblastoma for both research and clinical indications.

Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images.

Introduction Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. Method We evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions. Results Evaluation of the algorithm’s performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5th and 95th percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion. Conclusion Using EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice.

Immune evasion mediated by PD-L1 on glioblastoma-derived extracellular vesicles

Glioblastoma can suppress immunity by using surface PD-L1 on extracellular vesicles to block T cell receptor–mediated T cell activation. Binding of programmed death ligand-1 (PD-L1) to programmed cell death protein-1 (PD1) leads to cancer immune evasion via inhibition of T cell function. One of the defining characteristics of glioblastoma, a universally fatal brain cancer, is its profound local and systemic immunosuppression. Glioblastoma has also been shown to generate extracellular vesicles (EVs), which may play an important role in tumor progression. We thus hypothesized that glioblastoma EVs may be important mediators of immunosuppression and that PD-L1 could play a role. We show that glioblastoma EVs block T cell activation and proliferation in response to T cell receptor stimulation. PD-L1 was expressed on the surface of some, but not of all, glioblastoma-derived EVs, with the potential to directly bind to PD1. An anti-PD1 receptor blocking antibody significantly reversed the EV-mediated blockade of T cell activation but only when PD-L1 was present on EVs. When glioblastoma PD-L1 was up-regulated by IFN-γ, EVs also showed some PD-L1–dependent inhibition of T cell activation. PD-L1 expression correlated with the mesenchymal transcriptome profile and was anatomically localized in the perinecrotic and pseudopalisading niche of human glioblastoma specimens. PD-L1 DNA was present in circulating EVs from glioblastoma patients where it correlated with tumor volumes of up to 60 cm3. These results suggest that PD-L1 on EVs may be another mechanism for glioblastoma to suppress antitumor immunity and support the potential of EVs as biomarkers in tumor patients.

Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis

Introduction The subventricular zone (SVZ) has been implicated in the pathogenesis of glioblastoma. Whether molecular subtypes of glioblastoma arise from unique niches of the brain relative to the SVZ remains largely unknown. Here, we tested whether these subtypes of glioblastoma occupy distinct regions of the cerebrum and examined glioblastoma localization in relation to the SVZ. Methods Pre-operative MR images from 217 glioblastoma patients from The Cancer Imaging Archive were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Probabilistic maps of tumor location were generated for each subtype and distances were calculated from the centroid of CE tumor volumes to the SVZ. Glioblastomas that arose in a Genetically Modified Murine Model (GEMM) model were also analyzed with regard to SVZ distance and molecular subtype. Results Classical and mesenchymal glioblastomas were more diffusely distributed and located farther from the SVZ. In contrast, proneural and neural glioblastomas were more likely to be located in closer proximity to the SVZ. Moreover, in a GFAP-CreER; PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1−/− GEMM model of glioblastoma where tumor can spontaneously arise in different regions of the cerebrum, tumors that arose near the SVZ were more likely to be of proneural subtype (p < 0.0001). Conclusions Glioblastoma subtypes occupy different regions of the brain and vary in proximity to the SVZ. These findings harbor implications pertaining to the pathogenesis of glioblastoma subtypes.

Restriction Spectrum Imaging As a Potential Measure of Cortical Neurite Density in Autism

Autism postmortem studies have shown various cytoarchitectural anomalies in cortical and limbic areas including increased cell packing density, laminar disorganization, and narrowed minicolumns. However, there is little evidence on dendritic and axonal organization in ASD. Recent imaging techniques have the potential for non-invasive, in vivo studies of small-scale structure in the human brain, including gray matter. Here, Restriction Spectrum Imaging (RSI), a multi-shell diffusion-weighted imaging technique, was used to examine gray matter microstructure in 24 children with ASD (5 female) and 20 matched typically developing (TD) participants (2 female), ages 7–17 years. RSI extends the spherical deconvolution model to multiple length scales to characterize neurite density (ND) and organization. Measures were examined in 48 cortical regions of interest per hemisphere. To our knowledge, this is the first time that a multi-compartmental diffusion model has been applied to cortical gray matter in ASD. The ND measure detected robust age effects showing a significant positive relationship to age in all lobes except left temporal when groups were combined. Results were also suggestive of group differences (ASDTD) in bilateral parietal regions as well as widespread age effects were detected. Our findings support the value of multi-shell diffusion imaging for assays of cortical gray matter. This approach has the potential to add to postmortem literature, examining intracortical organization, intracortical axonal content, myelination, or caliber. Robust age effects further support the validity of the ND metric for in vivo examination of gray matter microstructure in ASD and across development. While diffusion MRI does not approach the precision of histological studies, in vivo imaging measures of microstructure can complement postmortem studies, by allowing access to large sample sizes, a whole-brain field of view, longitudinal designs, and combination with behavioral and functional assays. This makes multi-shell diffusion imaging a promising technique for understanding the underlying cytoarchitecture of the disorder.

Quantification of glioblastoma mass effect by lateral ventricle displacement

Mass effect has demonstrated prognostic significance for glioblastoma, but is poorly quantified. Here we define and characterize a novel neuroimaging parameter, lateral ventricle displacement (LVd), which quantifies mass effect in glioblastoma patients. LVd is defined as the magnitude of displacement from the center of mass of the lateral ventricle volume in glioblastoma patients relative to that a normal reference brain. Pre-operative MR images from 214 glioblastoma patients from The Cancer Imaging Archive (TCIA) were segmented using iterative probabilistic voxel labeling (IPVL). LVd, contrast enhancing volumes (CEV) and FLAIR hyper-intensity volumes (FHV) were determined. Associations with patient survival and tumor genomics were investigated using data from The Cancer Genome Atlas (TCGA). Glioblastoma patients had significantly higher LVd relative to patients without brain tumors. The variance of LVd was not explained by tumor volume, as defined by CEV or FLAIR. LVd was robustly associated with glioblastoma survival in Cox models which accounted for both age and Karnofsky’s Performance Scale (KPS) (p = 0.006). Glioblastomas with higher LVd demonstrated increased expression of genes associated with tumor proliferation and decreased expression of genes associated with tumor invasion. Our results suggest LVd is a quantitative measure of glioblastoma mass effect and a prognostic imaging biomarker.

Molecular physiology of contrast enhancement in glioblastomas: An analysis of The Cancer Imaging Archive (TCIA)

The physiologic processes underlying MRI contrast enhancement in glioblastoma patients remain poorly understood. MRIs of 148 glioblastoma subjects from The Cancer Imaging Archive were segmented using Iterative Probabilistic Voxel Labeling (IPVL). Three aspects of contrast enhancement (CE) were parametrized: the mean intensity of all CE voxels (CEi), the intensity heterogeneity in CE (CEh), and volumetric ratio of CE to necrosis (CEr). Associations between these parameters and patterns of gene expression were analyzed using DAVID functional enrichment analysis. Glioma CpG island methylator phenotype (G-CIMP) glioblastomas were poorly enhancing. Otherwise, no differences in CE parameters were found between proneural, neural, mesenchymal, and classical glioblastomas. High CEi was associated with expression of genes that mediate inflammatory responses. High CEh was associated with increased expression of genes that regulate remodeling of extracellular matrix (ECM) and endothelial permeability. High CEr was associated with increased expression of genes that mediate cellular response to stressful metabolic states, including hypoxia and starvation. Our results indicate that CE in glioblastoma is associated with distinct biological processes involved in inflammatory response and tissue hypoxia. Integrative analysis of these CE parameters may yield meaningful information pertaining to the biologic state of glioblastomas and guide future therapeutic paradigms.

Abstract 2737: Modulation of mitotic DNA damage as a paradigm for glioblastoma therapy

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA The clinical efficacies of molecularly targeted glioblastomas therapies have been vastly disappointing. The multitudes of resistance mechanisms suggest that glioblastomas possess highly dynamic molecular circuits grounded in functional redundancy. Emerging data suggests that the expression of functionally redundant oncogenes induced similar forms of cellular stress, requiring hyper-activation of common compensatory pathways to ensure cell viability. Targeting these pathways, therefore, afford potential opportunities for tumor ablation while by-passing the redundancy of oncogenic circuitry. To explore this paradigm, we carried out a siRNA screen to identify synthetic lethal partners of the oncogenic Epidermal Growth Factor Receptor variant III (EGFRvIII) in glioblastoma cells and identified Polo-Like Kinase 1 (PLK1). Treatment using a PLK1 inhibitor, BI2536, or siRNAs induced preferential toxicity to the EGFRvIII expressing glioblastoma cells in multiple in vitro (serum and neurosphere lines) and in vivo models (heterotopic and orthotopic xenograft models). Consistent with the heightened PLK1 requirement, EGFRvIII expressing glioblastomas harbored increased levels of the p-Thr210 PLK1 (an activated form of PLK1). Inhibition of PLK1 by BI2536 treatment induced an increase in the proportion of cells that co-stained for p-Histone H3 and γH2AX foci, suggesting accumulation of mitotic DNA damage. This effect was exacerbated by EGFRvIII expression, implicating induction of mitotic DNA damage as a major contributor to the observed synthetic lethality. Consistent with this observation, EGFRvIII expression induced the formation of aberrant mitosis as well as prolonged mitotic progression. Further supporting an essential role for PLK1 in suppressing DNA damage accumulation, BI2536 treatment significantly enhanced the tumoricidal effect of the DNA damaging chemotherapy, temozolomide. Mechanistically, inhibition of PLK1 suppressed the expression of Rad51, the accumulation of pS14 Rad51 (an active form of Rad51), as well as overall homologous recombination efficiency in vitro. We validated the clinical pertinence of these results using three clinically annotated glioblastoma databases (TCGA, REMEBMRANDT, CGGA). In all three datasets, increased expression of a PLK1 signature consistently associated with increased expression of HR genes and lowered gene expression signature associated with DNA damage accumulation. Supporting our proposed paradigm, the tumoricidal effect of BI2536 was universally observed in a panel of eight murine ink4a/arf (-/-) EGFRvIII expressing glioblastoma clones that developed resistance to EGFR inhibitors by distinct and independent mechanisms. In aggregate, our results support the essential role of PLK1 in suppressing mitotic DNA damage and provide a novel framework for glioblastoma therapy. Citation Format: Ying Shen, Masayuki Nitta, Jie Li, Diahnn Futalan, Tyler Steed, Zack Taich, Jeffrey M. Treiber, Deanna Stevens, Mark A. Schroeder, Jann N. Sarkaria, Hong-Zhuan Chen, Tao Jiang, Bob S. Carter, Fumiko Esashi, Jill Wakosky, Frank Furnari, Webster K. Cavenee, Arshad Desai, Clark C. Chen. Modulation of mitotic DNA damage as a paradigm for glioblastoma therapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2737. doi:10.1158/1538-7445.AM2014-2737