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Summary: Sensing of extracellular ATP (eATP) controls CD8+ T cell function. Their accumulation can occur through export by specialized molecules, such as the release channel Pannexin 1 (Panx1). Whether Panx1 controls CD8+ T cell immune responses in vivo, however, has not been previously addressed. Here, we report that T-cell-specific Panx1 is needed for CD8+ T cell responses to viral infections and cancer. We found that CD8-specific Panx1 promotes both effector and memory CD8+ T cell responses. Panx1 favors initial effector CD8+ T cell activation through extracellular ATP (eATP) export and subsequent P2RX4 activation, which helps promote full effector differentiation through extracellular lactate accumulation and its subsequent recycling. In contrast, Panx1 promotes memory CD8+ T cell survival primarily through ATP export and subsequent P2RX7 engagement, leading to improved mitochondrial metabolism. In summary, Panx1-mediated eATP export regulates effector and memory CD8+ T cells through distinct purinergic receptors and different metabolic and signaling pathways.

Abstract Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with few effective treatments. EGFR alterations, including expression of the truncated variant EGFRvIII, are among the most frequent genomic changes in these tumors. EGFRvIII is known to preferentially signal through STAT5 for oncogenic activation in GBM, yet targeting EGFRvIII has yielded limited clinical success to date. In this study, we employed patient-derived xenograft (PDX) models expressing EGFRvIII to determine the key points of therapeutic vulnerability within the EGFRvIII-STAT5 signaling axis in GBM. Our findings reveal that exogenous expression of paralogs STAT5A and STAT5B augments cell proliferation and that inhibition of STAT5 phosphorylation in vivo improves overall survival in combination with temozolomide (TMZ). STAT5 phosphorylation is independent of JAK1 and JAK2 signaling, instead requiring Src family kinase (SFK) activity. Saracatinib, an SFK inhibitor, attenuates phosphorylation of STAT5 and preferentially sensitizes EGFRvIII+ GBM cells to undergo apoptotic cell death relative to wild-type EGFR. Constitutively active STAT5A or STAT5B mitigates saracatinib sensitivity in EGFRvIII+ cells. In vivo, saracatinib treatment decreased survival in mice bearing EGFR WT tumors compared to the control, yet in EGFRvIII+ tumors, treatment with saracatinib in combination with TMZ preferentially improves survival.

Abstract Background Glioblastoma is the most common primary brain tumor and remains uniformly fatal, highlighting the dire need for developing effective therapeutics. Significant intra- and inter-tumor heterogeneity and inadequate delivery of therapeutics across blood–brain barrier continue to be significant impediments towards developing therapies which can significantly enhance survival. We hypothesize that microRNAs have the potential to serve as effective therapeutics for glioblastoma as they modulate the activity of multiple signaling pathways, and hence can counteract heterogeneity if successfully delivered. Methods Using a computational approach, we identified microRNA-34a as a microRNA that maximally reduces the activation status of the three core signaling networks (the receptor tyrosine kinase, p53 and Rb networks) that have been found to be deregulated in most glioblastoma tumors. Glioblastoma cultures were transfected with microRNA-34a or control microRNA to assess biological function and therapeutic potential in vitro. Nanocells were derived from genetically modified bacteria and loaded with microRNA-34a for intravenous administration to orthotopic patient-derived glioblastoma xenografts in mice. Results Overexpression of microRNA-34a strongly reduced the activation status of the three core signaling networks. microRNA-34a transfection also inhibited the survival of multiple established glioblastoma cell lines, as well as primary patient-derived xenograft cultures representing the proneural, mesenchymal and classical subtypes. Transfection of microRNA-34a enhanced temozolomide (TMZ) response in in vitro cultures of glioblastoma cells with primary TMZ sensitivity, primary TMZ resistance and acquired TMZ resistance. Mechanistically, microRNA-34a downregulated multiple therapeutic resistance genes which are associated with worse survival in glioblastoma patients and are enriched in specific tumor spatial compartments. Importantly, intravenous administration of nanocells carrying miR-34a and targeted to epidermal growth factor receptor (EGFR) strongly enhanced TMZ sensitivity in an orthotopic patient-derived xenograft mouse model of glioblastoma. Conclusions Targeted bacterially-derived nanocells are an effective vehicle for the delivery of microRNA-34a to glioblastoma tumors. microRNA-34a inhibits survival and strongly sensitizes a wide range of glioblastoma cell cultures to TMZ, suggesting that combination therapy of TMZ with microRNA-34a loaded nanocells may serve as a novel therapeutic approach for the treatment of glioblastoma tumors.

Abstract Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients. The model generated predictions for regional EGFR amplification status (a common and important target in GBM) to resolve the intratumoral genetic heterogeneity across each individual tumor—a key factor for future personalized therapeutic paradigms. The model used probability distributions for each sample prediction to quantify uncertainty, and used transductive learning to reduce the overall uncertainty. We compared predictive accuracy and uncertainty of the transductive learning GP model against a standard GP model using leave-one-patient-out cross validation. Additionally, we used a separate dataset containing 24 image-localized biopsies from 7 high-grade glioma patients to validate the model. Predictive uncertainty informed the likelihood of achieving an accurate sample prediction. When stratifying predictions based on uncertainty, we observed substantially higher performance in the group cohort (75% accuracy, n = 95) and amongst sample predictions with the lowest uncertainty (83% accuracy, n = 72) compared to predictions with higher uncertainty (48% accuracy, n = 23), due largely to data interpolation (rather than extrapolation). On the separate validation set, our model achieved 78% accuracy amongst the sample predictions with lowest uncertainty. We present a novel approach to quantify radiogenomics uncertainty to enhance model performance and clinical interpretability. This should help integrate more reliable radiogenomics models for improved medical decision-making.

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and carries a discouraging prognosis. Its aggressive and highly infiltrative nature renders the current standard treatment of maximal surgical resection, radiation, and chemotherapy relatively ineffective. Identifying the signaling pathways that regulate GBM migration/invasion and resistance is required to develop more effective therapeutic regimens to treat GBM. Expression of TROY, an orphan receptor of the TNF receptor superfamily, increases with glial tumor grade, inversely correlates with patient overall survival, stimulates GBM cell invasion in vitro and in vivo, and increases resistance to temozolomide and radiation therapy. Conversely, silencing TROY expression inhibits GBM cell invasion, increases sensitivity to temozolomide, and prolongs survival in a preclinical intracranial xenograft model. Here, we have identified for the first time that TROY interacts with JAK1. Increased TROY expression increases JAK1 phosphorylation. In addition, increased TROY expression promotes STAT3 phosphorylation and STAT3 transcriptional activity that is dependent upon JAK1. TROY-mediated activation of STAT3 is independent of its ability to stimulate activity of NF-κB. Inhibition of JAK1 activity by ruxolitinib or knockdown of JAK1 expression by siRNA significantly inhibits TROY-induced STAT3 activation, GBM cell migration, and decreases resistance to temozolomide. Taken together, our data indicate that the TROY signaling complex may represent a potential therapeutic target with the distinctive capacity to exert effects on multiple pathways mediating GBM cell invasion and resistance.

Glioblastomas (GBMs) are the most aggressive primary brain tumours and have no known cure. Each individual tumour comprises multiple sub-populations of genetically-distinct cells that may respond differently to targeted therapies and may contribute to disappointing clinical trial results. Image-localized biopsy techniques allow multiple biopsies to be taken during surgery and provide information that identifies regions where particular sub-populations occur within an individual GBM, thus providing insight into their regional genetic variability. These sub-populations may also interact with one another in a competitive or cooperative manner; it is important to ascertain the nature of these interactions, as they may have implications for responses to targeted therapies. We combine genetic information from biopsies with a mechanistic model of interacting GBM sub-populations to characterise the nature of interactions between two commonly occurring GBM sub-populations, those with EGFR and PDGFRA genes amplified. We study population levels found across image-localized biopsy data from a cohort of 25 patients and compare this to model outputs under competitive, cooperative and neutral interaction assumptions. We explore other factors affecting the observed simulated sub-populations, such as selection advantages and phylogenetic ordering of mutations, which may also contribute to the levels of EGFR and PDGFRA amplified populations observed in biopsy data.

Abstract Background Temozolomide (TMZ) is the most commonly used chemotherapeutic agent used to treat glioblastoma (GBM), which causes significant DNA damage to highly proliferative cells. Our observations have added to accumulating evidence that TMZ induces stress-responsive cellular programs known to promote cell survival, including autophagy. As such, targeting these survival pathways may represent new vulnerabilities of GBM after treatment with TMZ. Methods Using the T98G human glioma cell line, we assessed the molecular signaling associated with TMZ treatment, the cellular consequences of using the pan-PI3K inhibitor PX-866, and performed clonogenic assays to determine the effect sequential treatment of TMZ and PX-866 had on colony formation. Additionally, we also use subcutaneous GBM patient derived xenograft (PDX) tumors to show relative LC3 protein expression and correlations between survival pathways and molecular markers which dictate clinical responsiveness to TMZ. Results Here, we report that TMZ can induce autophagic flux in T98G glioma cells. GBM patient-derived xenograft (PDX) tumors treated with TMZ also display an increase in the autophagosome marker LC3 II. Additionally, O6-methylguanine-DNA-methyltransferase (MGMT) expression correlates with PI3K/AKT activity, suggesting that patients with inherent resistance to TMZ (MGMT-high) would benefit from PI3K/AKT inhibitors in addition to TMZ. Accordingly, we have identified that the blood-brain barrier (BBB) penetrant pan-PI3K inhibitor, PX-866, is an early-stage inhibitor of autophagic flux, while maintaining its ability to inhibit PI3K/AKT signaling in glioma cells. Lastly, due to the induction of autophagic flux by TMZ, we provide evidence for sequential treatment of TMZ followed by PX-866, rather than combined co-treatment, as a means to shut down autophagy-induced survival in GBM cells and to enhance apoptosis. Conclusions The understanding of how TMZ induces survival pathways, such as autophagy, may offer new therapeutic vulnerabilities and opportunities to use sequential inhibition of alternate pro-survival pathways that regulate autophagy. As such, identification of additional ways to inhibit TMZ-induced autophagy could enhance the efficacy of TMZ.

Summary: We address whether combinations with a pan-RAF inhibitor (RAFi) would be effective in KRAS mutant pancreatic ductal adenocarcinoma (PDAC). Chemical library and CRISPR genetic screens identify combinations causing apoptotic anti-tumor activity. The most potent combination, concurrent inhibition of RAF (RAFi) and ERK (ERKi), is highly synergistic at low doses in cell line, organoid, and rat models of PDAC, whereas each inhibitor alone is only cytostatic. Comprehensive mechanistic signaling studies using reverse phase protein array (RPPA) pathway mapping and RNA sequencing (RNA-seq) show that RAFi/ERKi induced insensitivity to loss of negative feedback and system failures including loss of ERK signaling, FOSL1, and MYC; shutdown of the MYC transcriptome; and induction of mesenchymal-to-epithelial transition. We conclude that low-dose vertical inhibition of the RAF-MEK-ERK cascade is an effective therapeutic strategy for KRAS mutant PDAC.

Despite major drug discovery efforts, the therapeutic options for glioblastoma (GBM) remain inadequate. Here they analyze patient-derived xenograft model of GBM to quantitatively map distribution and cellular response to the EGFR inhibitor erlotinib, and report heterogeneous erlotinib delivery to intracranial tumors to be inadequate to inhibit EGFR signaling.

Glioblastoma multiforme (GBM) is the most common type of malignant brain tumors in adults and has a dismal prognosis. The highly aggressive invasion of malignant cells into the normal brain parenchyma renders complete surgical resection of GBM tumors impossible, increases resistance to therapeutic treatment, and leads to near-universal tumor recurrence. We have previously demonstrated that TROY (TNFRSF19) plays an important role in glioblastoma cell invasion and therapeutic resistance. However, the potential downstream effectors of TROY signaling have not been fully characterized. Here, we identified PDZ-RhoGEF as a binding partner for TROY that potentiated TROY-induced nuclear factor kappa B activation which is necessary for both cell invasion and survival. In addition, PDZ-RhoGEF also interacts with Pyk2, indicating that PDZ-RhoGEF is a component of a signalsome that includes TROY and Pyk2. PDZ-RhoGEF is overexpressed in glioblastoma tumors and stimulates glioma cell invasion via Rho activation. Increased PDZ-RhoGEF expression enhanced TROY-induced glioma cell migration. Conversely, silencing PDZ-RhoGEF expression inhibited TROY-induced glioma cell migration, increased sensitivity to temozolomide treatment, and extended survival of orthotopic xenograft mice. Furthermore, depletion of RhoC or RhoA inhibited TROY- and PDZ-RhoGEF–induced cell migration. Mechanistically, increased TROY expression stimulated Rho activation, and depletion of PDZ-RhoGEF expression reduced this activation. Taken together, these data suggest that PDZ-RhoGEF plays an important role in TROY signaling and provides insights into a potential node of vulnerability to limit GBM cell invasion and decrease therapeutic resistance.

Abstract Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci. Using this assay, we compared 7 cfDNA extraction kits and found cfDNA yield and fragment size vary significantly. We also compared 3 blood collection protocols using plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA Blood Collection Tubes processed within 24 and 72 hours) and found no significant differences in cfDNA yield, fragment size and background noise between these protocols. In 219 clinical samples, cfDNA fragments were shorter in plasma samples processed immediately after venipuncture compared to archived samples, suggesting contribution of background DNA by lysed peripheral blood cells. In summary, we have described a multiplexed ddPCR assay to assess quality of cfDNA samples prior to downstream molecular analyses and we have evaluated potential sources of pre-analytical variation in cfDNA studies.

Abstract Background RNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study. Results Both platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays. This reduced the number of differentially expressed genes and genes with predictive potential for RNA-seq compared to microarray data. Analysis of this variability revealed a lack of reads for short and low abundant genes; lncRNAs, being shorter and less abundant RNAs, were found especially susceptible to this issue. A major difference between the two platforms was uncovered by analysis of alternatively spliced genes. Investigation of differential exon abundance showed insufficient reads for many exons and exon junctions in RNA-seq while the detection on the array platform was more stable. Nevertheless, we identified 207 genes which undergo alternative splicing and were consistently detected by both techniques. Conclusions Despite the fact that the results of gene expression analysis were highly consistent between Human Transcriptome Arrays and RNA-seq platforms, the analysis of alternative splicing produced discordant results. We concluded that modern microarrays can still outperform sequencing for standard analysis of gene expression in terms of reproducibility and cost.

Rheumatoid arthritis (RA) is an autoimmune disease that affects ~1% of the world's population. B cells and autoantibodies play an important role in the pathogenesis of RA. The P2RX7 receptor is an ATP-gated cation channel and its activation results in the release of pro-inflammatory molecules. Thus, antagonists of P2RX7 have been considered to have potential as novel anti-inflammatory therapies. Although originally identified for its role in innate immunity, P2RX7 has recently been found to negatively control Peyer's patches (PP) T follicular helper cells (Tfh), which specialize in helping B cells, under homeostatic conditions. We have previously demonstrated that PP Tfh cells are required for the augmentation of autoimmune arthritis mediated by gut commensal segmented filamentous bacteria (SFB). Thus, we hypothesized that P2RX7 is required to control autoimmune disease by keeping the Tfh cell response in check. To test our hypothesis, we analyzed the impact of P2RX7 deficiency in vivo using both the original K/BxN autoimmune arthritis model and T cell transfers in the K/BxN system. We also examined the impact of P2RX7 ablation on autoimmune development in the presence of the gut microbiota SFB. Our data illustrate that contrary to exerting an anti-inflammatory effect, P2RX7 deficiency actually enhances autoimmune arthritis. Interestingly, SFB colonization can negate the difference in disease severity between WT and P2RX7-deficient mice. We further demonstrated that P2RX7 ablation in the absence of SFB caused reduced apoptotic Tfh cells and enhanced the Tfh response, leading to an increase in autoantibody production. It has been shown that activation of TIGIT, a well-known T cell exhaustion marker, up-regulates anti-apoptotic molecules and promotes T cell survival. We demonstrated that the reduced apoptotic phenotype of P2rx7−/− Tfh cells is associated with their increased expression of TIGIT. This suggested that while P2RX7 was regulating the Tfh population by promoting cell death, TIGIT may have been opposing P2RX7 by inhibiting cell death. Together, these results demonstrated that systemic administration of general P2RX7 antagonists may have detrimental effects in autoimmune therapies, especially in Tfh cell-dependent autoimmune diseases, and cell-specific targeting of P2RX7 should be considered in order to achieve efficacy for P2RX7-related therapy.

Archival tumor samples represent a rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and individual-specific germline variants. Archival sections often contain adjacent normal tissue, but this tissue can include infiltrating tumor cells. As existing comparative somatic variant callers are designed to exclude variants present in the normal sample, a novel approach is required to leverage adjacent normal tissue with infiltrating tumor cells for somatic variant calling. Here we present lumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient, built upon our previous single sample tumor only variant caller lumosVar 1.0. The approach assumes that the allelic fraction of somatic variants and germline variants follow different patterns as tumor content and copy number state change. lumosVar 2.0 estimates allele specific copy number and tumor sample fractions from the data, and uses a to model to determine expected allelic fractions for somatic and germline variants and to classify variants accordingly. To evaluate the utility of lumosVar 2.0 to jointly call somatic variants with tumor and adjacent normal samples, we used a glioblastoma dataset with matched high and low tumor content and germline whole exome sequencing data (for true somatic variants) available for each patient. Both sensitivity and positive predictive value were improved when analyzing the high tumor and low tumor samples jointly compared to analyzing the samples individually or in-silico pooling of the two samples. Finally, we applied this approach to a set of breast and prostate archival tumor samples for which tumor blocks containing adjacent normal tissue were available for sequencing. Joint analysis using lumosVar 2.0 detected several variants, including known cancer hotspot mutations that were not detected by standard somatic variant calling tools using the adjacent tissue as presumed normal reference. Together, these results demonstrate the utility of leveraging paired tissue samples to improve somatic variant calling when a constitutional sample is not available.

Glioblastoma (GBM) is one of the most common, deadly, and difficult-to-treat adult brain tumors. Surgical removal of the tumor, followed by radiotherapy (RT) and temozolomide (TMZ) administration, is the current treatment modality, but this regimen only modestly improves overall patient survival. Invasion of cells into the surrounding healthy brain tissue prevents complete surgical resection and complicates treatment strategies with the goal of preserving neurological function. Despite significant efforts to increase our understanding of GBM, there have been relatively few therapeutic advances since 2005 and even fewer treatments designed to effectively treat recurrent tumors that are resistant to therapy. Thus, while there is a pressing need to move new treatments into the clinic, emerging evidence suggests that key features unique to GBM location and biology, the blood-brain barrier (BBB) and intratumoral molecular heterogeneity, respectively, stand as critical unresolved hurdles to effective therapy. Notably, genomic analyses of GBM tissues has led to the identification of numerous gene alterations that govern cell growth, invasion and survival signaling pathways; however, the drugs that show pre-clinical potential against signaling pathways mediated by these gene alterations cannot achieve effective concentrations at the tumor site. As a result, identifying BBB-penetrating drugs and utilizing new and safer methods to enhance drug delivery past the BBB has become an area of intensive research. Repurposing and combining FDA-approved drugs with evidence of penetration into the central nervous system (CNS) has also seen new interest for the treatment of both primary and recurrent GBM. In this review, we discuss emerging methods to strategically enhance drug delivery to GBM and repurpose currently-approved and previously-studied drugs using rational combination strategies.

Glioblastoma multiforme (GBM) is the most frequent primary brain tumor in adults with a 5-year survival rate of 5% despite intensive research efforts. The poor prognosis is due, in part, to aggressive invasion into the surrounding brain parenchyma. Invasion is a complex process mediated by cell-intrinsic pathways, extrinsic microenvironmental cues, and biophysical cues from the peritumoral stromal matrix. Recent data have attributed GBM invasion to the glioma stem-like cell (GSC) subpopulation. GSCs are slowly dividing, highly invasive, therapy resistant, and are considered to give rise to tumor recurrence. GSCs are localized in a heterogeneous cellular niche, and cross talk between stromal cells and GSCs cultivates a fertile environment that promotes GSC invasion. Pro-migratory soluble factors from endothelial cells, astrocytes, macrophages, microglia, and non-stem-like tumor cells can stimulate peritumoral invasion of GSCs. Therefore, therapeutic efforts designed to target the invasive GSCs may enhance patient survival. In this review, we summarize the current understanding of extrinsic pathways and major stromal and immune players facilitating GSC maintenance and survival.

P311, an 8-kDa polypeptide, was previously shown to be highly expressed in invasive glioma cells. Here, we report the functional characteristics of P311 with regard to influencing glioma cell migration. P311 is constitutively serine-phosphorylated; decreased phosphorylation is observed in migration-activated glioma cells. The primary amino acid sequence of P311 indicates a putative serine phosphorylation site (S59) near the PEST domain. Site-directed mutagenesis of S59A retarded P311 degradation, induced glioma cell motility. In contrast, S59D mutation resulted in the rapid degradation of P311, reduced glioma cell migration. Coimmunoprecipitation coupled with matrixassisted laser desorption/ionization time-of-flight mass spectrometry analysis identified Filamin A as a binding partner of P311, immunofluorescence studies showed that both proteins colocalized at the cell periphery. Moreover, P311-induced cell migration was abrogated by inhibition of β1 integrin function using TACβ1A, a dominant-negative inhibitor of β1 integrin signaling, suggesting that P311 acts downstream of β1 signaling. Finally, overexpression of P311 or P311 S59A mutant protein activates Raci GTPase; small interfering RNA-mediated depletion of Raci suppresses P311-induced motility. Collectively, these results suggest a role for levels of P311 in regulating glioma motility, invasion through the reorganization of actin cytoskeleton at the cell periphery.

Glioblastoma multiforme is extraordinarily aggressive due to the propensity of cells to migrate away from the tumor core into the surrounding normal brain. In this report, we investigated the role of proline-rich tyrosine kinase 2 (Pyk2) and FAK with regard to influencing glioma cell phenotypes. Expression of Pyk2 stimulated glioma cell migration, whereas expression of FAK inhibited glioma cell migration and stimulated cell cycle progression. Pyk2 autophosphorylation was necessary, but not sufficient, to stimulate cellular migration. The N-terminal domain of Pyk2 is required for stimulation of migration as an N-terminally deleted variant of Pyk2 failed to stimulate migration, whereas expression of an autonomous Pyk2 N-terminal domain inhibited cell migration. Substitution of the C-terminal domain of Pyk2 with the corresponding domain of FAK stimulated cell migration as effectively as wild-type Pyk2; however, substitution of the N-terminal domain of Pyk2 with that of FAK inhibited cell migration, substantiating that the N-terminal domain of Pyk2 was required to stimulate migration. Silencing of Pyk2 expression by RNA interference significantly inhibited glioma migration. Cell migration was restored on reexpression of Pyk2, but expression of FAK in Pyk2 knockdown cells failed to restore migration. We conclude that Pyk2 plays a central role in the migratory behavior of glioblastomas.