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Extracellular vesicles (EVs) carry RNA, DNA, proteins, and lipids. Specifically, tumor-derived EVs have the potential to be utilized as disease-specific biomarkers. However, a lack of methods to isolate tumor-specific EVs has limited their use in clinical settings. Here we report a sensitive analytical microfluidic platform ( EV HB-Chip) that enables tumor-specific EV-RNA isolation within 3 h. Using the EV HB-Chip, we achieve 94% tumor-EV specificity, a limit of detection of 100 EVs per μL, and a 10-fold increase in tumor RNA enrichment in comparison to other methods. Our approach allows for the subsequent release of captured tumor EVs, enabling downstream characterization and functional studies. Processing serum and plasma samples from glioblastoma multiforme (GBM) patients, we can detect the mutant EGFRvIII mRNA. Moreover, using next-generation RNA sequencing, we identify genes specific to GBM as well as transcripts that are hallmarks for the four genetic subtypes of the disease. Extracellular vesicles can carry many different types of biological cargo and have been investigated as a biomarker for cancer diagnosis. Here the authors develop a microfluidic platform for rapid and sensitive isolation of tumor-specific extracellular vesicles.

Glioblastoma cells secrete extra-cellular vesicles (EVs) containing microRNAs (miRNAs). Analysis of these EV miRNAs in the bio-fluids of afflicted patients represents a potential platform for biomarker development. However, the analytic algorithm for quantitative assessment of EV miRNA remains under-developed. Here, we demonstrate that the reference transcripts commonly used for quantitative PCR (including GAPDH, 18S rRNA, and hsa-miR-103) were unreliable for assessing EV miRNA. In this context, we quantitated EV miRNA in absolute terms and normalized this value to the input EV number. Using this method, we examined the abundance of miR-21, a highly over-expressed miRNA in glioblastomas, in EVs. In a panel of glioblastoma cell lines, the cellular levels of miR-21 correlated with EV miR-21 levels (p<0.05), suggesting that glioblastoma cells actively secrete EVs containing miR-21. Consistent with this hypothesis, the CSF EV miR-21 levels of glioblastoma patients (n=13) were, on average, ten-fold higher than levels in EVs isolated from the CSF of non-oncologic patients (n=13, p<0.001). Notably, none of the glioblastoma CSF harbored EV miR-21 level below 0.25 copies per EV in this cohort. Using this cut-off value, we were able to prospectively distinguish CSF derived from glioblastoma and non-oncologic patients in an independent cohort of twenty-nine patients (Sensitivity=87%; Specificity=93%; AUC=0.91, p<0.01). Our results suggest that CSF EV miRNA analysis of miR-21 may serve as a platform for glioblastoma biomarker development.

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. 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. 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. 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.

Electrocorticography (ECoG) is becoming more prevalent due to improvements in fabrication and recording technology as well as its ease of implantation compared to intracortical electrophysiology, larger cortical coverage, and potential advantages for use in long term chronic implantation. Given the flexibility in the design of ECoG grids, which is only increasing, it remains an open question what geometry of the electrodes is optimal for an application. Conductive polymer, PEDOT:PSS, coated microelectrodes have an advantage that they can be made very small without losing low impedance. This makes them suitable for evaluating the required granularity of ECoG recording in humans and experimental animals. We used two-dimensional (2D) micro-ECoG grids to record intra-operatively in humans and during acute implantations in mouse with separation distance between neighboring electrodes (i.e., pitch) of 0.4 mm and 0.2/0.25 mm respectively. To assess the spatial properties of the signals, we used the average correlation between electrodes as a function of the pitch. In agreement with prior studies, we find a strong frequency dependence in the spatial scale of correlation. By applying independent component analysis (ICA), we find that the spatial pattern of correlation is largely due to contributions from multiple spatially extended, time-locked sources present at any given time. Our analysis indicates the presence of spatially structured activity down to the sub-millimeter spatial scale in ECoG despite the effects of volume conduction, justifying the use of dense micro-ECoG grids.

Glioblastoma (GBM) is an incurable primary malignant brain cancer hallmarked with a substantial protumorigenic immune component. Knowledge of the GBM immune microenvironment during tumor evolution and standard of care treatments is limited. Using single-cell transcriptomics and flow cytometry, we unveiled large-scale comprehensive longitudinal changes in immune cell composition throughout tumor progression in an epidermal growth factor receptor-driven genetic mouse GBM model. We identified subsets of proinflammatory microglia in developing GBMs and anti-inflammatory macrophages and protumorigenic myeloid-derived suppressors cells in end-stage tumors, an evolution that parallels breakdown of the blood–brain barrier and extensive growth of epidermal growth factor receptor+ GBM cells. A similar relationship was found between microglia and macrophages in patient biopsies of low-grade glioma and GBM. Temozolomide decreased the accumulation of myeloid-derived suppressor cells, whereas concomitant temozolomide irradiation increased intratumoral GranzymeB+ CD8+T cells but also increased CD4+ regulatory T cells. These results provide a comprehensive and unbiased immune cellular landscape and its evolutionary changes during GBM progression.Single-cell RNAseq during initiation and progression of mouse glioblastoma reveals a dynamic immune microenvironment transitioning from pro-inflammatory microglia in early tumors towards an infiltrating macrophage and suppressor cell-centric immune landscape in late-stage tumors.

Real-time monitoring of drug efficacy in glioblastoma multiforme (GBM) is a major clinical problem as serial re-biopsy of primary tumours is often not a clinical option. MGMT (O 6 -methylguanine DNA methyltransferase) and APNG (alkylpurine-DNA-N-glycosylase) are key enzymes capable of repairing temozolomide-induced DNA damages and their levels in tissue are inversely related to treatment efficacy. Yet, serial clinical analysis remains difficult, and, when done, primarily relies on promoter methylation studies of tumour biopsy material at the time of initial surgery. Here we present a microfluidic chip to analyse mRNA levels of MGMT and APNG in enriched tumour exosomes obtained from blood. We show that exosomal mRNA levels of these enzymes correlate well with levels found in parental cells and that levels change considerably during treatment of seven patients. We propose that if validated on a larger cohort of patients, the method may be used to predict drug response in GBM patients. Predicting and monitoring chemotherapy response remains a challenge for glioma treatment. Here the authors show that a microfluidic device can isolate glioma-derived exosomes from patient blood and accurately determine the levels of mRNA of key enzymes important for chemoresponsiveness.

Glioblastomas (GBM) are highly aggressive primary brain tumors. Complex and dynamic tumor microenvironment (TME) plays a crucial role in the sustained growth, proliferation, and invasion of GBM. Several means of intercellular communication have been documented between glioma cells and the TME, including growth factors, cytokines, chemokines as well as extracellular vesicles (EVs). EVs carry functional genomic and proteomic cargo from their parental cells and deliver that information to surrounding and distant recipient cells to modulate their behavior. EVs are emerging as crucial mediators of establishment and maintenance of the tumor by modulating the TME into a tumor promoting system. Herein we review recent literature in the context of GBM TME and the means by which EVs modulate tumor proliferation, reprogram metabolic activity, induce angiogenesis, escape immune surveillance, acquire drug resistance and undergo invasion. Understanding the multifaceted roles of EVs in the niche of GBM TME will provide invaluable insights into understanding the biology of GBM and provide functional insights into the dynamic EV-mediated intercellular communication during gliomagenesis, creating new opportunities for GBM diagnostics and therapeutics.

The specific loss of midbrain dopamine neurons (mDANs) causes major motor dysfunction in Parkinson’s disease, which makes cell replacement a promising therapeutic approach 1 – 4 . However, poor survival of grafted mDANs remains an obstacle to successful clinical outcomes 5 – 8 . Here we show that the surgical procedure itself (referred to here as ‘needle trauma’) triggers a profound host response that is characterized by acute neuroinflammation, robust infiltration of peripheral immune cells and brain cell death. When midbrain dopamine (mDA) cells derived from human induced pluripotent stem (iPS) cells were transplanted into the rodent striatum, less than 10% of implanted tyrosine hydroxylase (TH) + mDANs survived at two weeks after transplantation. By contrast, TH − grafted cells mostly survived. Notably, transplantation of autologous regulatory T (T reg ) cells greatly modified the response to needle trauma, suppressing acute neuroinflammation and immune cell infiltration. Furthermore, intra-striatal co-transplantation of T reg cells and human-iPS-cell-derived mDA cells significantly protected grafted mDANs from needle-trauma-associated death and improved therapeutic outcomes in rodent models of Parkinson’s disease with 6-hydroxydopamine lesions. Co-transplantation with T reg cells also suppressed the undesirable proliferation of TH − grafted cells, resulting in more compact grafts with a higher proportion and higher absolute numbers of TH + neurons. Together, these data emphasize the importance of the initial inflammatory response to surgical injury in the differential survival of cellular components of the graft, and suggest that co-transplanting autologous T reg cells effectively reduces the needle-trauma-induced death of mDANs, providing a potential strategy to achieve better clinical outcomes for cell therapy in Parkinson’s disease. In mouse and rat models of Parkinson’s disease, co-transplanting regulatory T cells (T reg cells) improves the survival of grafted midbrain dopamine neurons in cell therapies by reducing the inflammatory response caused by surgical injury.

To examine the relative incidence of newly recorded diagnosis of depression after spinal surgery as a proxy for the risk of post–spinal surgery depression. We used the longitudinal California Office of Statewide Health Planning and Development database (January 1, 2000, through December 31, 2010) to identify patients who underwent spinal surgery during these years. Patients with documented depression before surgery were excluded. Risk of new postoperative depression was determined via the incidence of newly recorded depression on any hospitalization subsequent to surgery. For comparison, this risk was also determined for patients hospitalized during the same time period for coronary artery bypass grafting, hysterectomy, cholecystectomy, chronic obstructive pulmonary disease, congestive heart failure exacerbation, or uncomplicated vaginal delivery. Our review identified 1,078,639 patients. Relative to the uncomplicated vaginal delivery cohort, the adjusted hazard ratios (HRs) for newly recorded depression within 5 years after the admission of interest were 5.05 for spinal surgery (95% CI, 4.79-5.33), 2.33 for coronary artery bypass grafting (95% CI, 2.15-2.54), 3.04 for hysterectomy (95% CI, 2.88-3.21), 2.51 for cholecystectomy (95% CI, 2.35-2.69), 2.44 for congestive heart failure exacerbation (95% CI, 2.28-2.61), and 3.04 for chronic obstructive pulmonary disease (95% CI, 2.83-3.26). Among patients who underwent spinal surgery, this risk of postoperative depression was highest for patients who underwent fusion surgery (HR, 1.28; 95% CI, 1.22-1.36) or had undergone multiple spinal operations (HR, 1.22; 95% CI, 1.16-1.29) during the analyzed period. Patients who undergo spinal surgery have a higher risk for postoperative depression than patients treated for other surgical or medical conditions known to be associated with depression.

Cancer cells shed large numbers of small, membrane-bound microvesicles (MVs) into the circulation, which have diagnostic potential but have proved difficult to analyze in a point-of-care setting. Huilin Shao and colleagues have developed a microfluidic chip with an integrated NMR detection system for the rapid profiling of circulating MVs directly from blood samples of patients with glioblastoma. The system was used to distinguish cancer cell–derived MVs from host cell–derived MVs and to measure treatment effects in vivo . Glioblastomas shed large quantities of small, membrane-bound microvesicles into the circulation. Although these hold promise as potential biomarkers of therapeutic response, their identification and quantification remain challenging. Here, we describe a highly sensitive and rapid analytical technique for profiling circulating microvesicles directly from blood samples of patients with glioblastoma. Microvesicles, introduced onto a dedicated microfluidic chip, are labeled with target-specific magnetic nanoparticles and detected by a miniaturized nuclear magnetic resonance system. Compared with current methods, this integrated system has a much higher detection sensitivity and can differentiate glioblastoma multiforme (GBM) microvesicles from nontumor host cell–derived microvesicles. We also show that circulating GBM microvesicles can be used to analyze primary tumor mutations and as a predictive metric of treatment-induced changes. This platform could provide both an early indicator of drug efficacy and a potential molecular stratifier for human clinical trials.