Background Extracellular vesicles (EVs) play an important role in cell-cell communication, and tumor-derived EVs circulating in patient blood can serve as biomarkers. Here, we investigated the potential role of plasma EVs in meningioma patients for tumor detection and determined whether EVs secreted by meningioma cells reflect epigenetic, genomic and proteomic alterations of original tumors. Methods EV concentrations were quantified in patient plasma (n = 46). Short-term meningioma cultures were established (n = 26) and secreted EVs were isolated. Methylation and copy number profiling was performed using 850k arrays, and mutations were identified by targeted gene panel sequencing. Differential quantitative mass spectrometry was employed for proteomic analysis. Results Levels of circulating EVs were elevated in meningioma patients compared to healthy individuals, and the plasma EV concentration correlated with malignancy grade and extent of peritumoral edema. Postoperatively, EV counts dropped to normal levels, and the magnitude of the postoperative decrease was associated with extent of tumor resection. Methylation profiling of EV-DNA allowed correct tumor classification as meningioma in all investigated cases, and accurate methylation subclass assignment in almost all cases. Copy number variations present in tumors, as well as tumor-specific mutations were faithfully reflected in meningioma EV-DNA. Proteomic EV profiling did not permit original tumor identification but revealed tumor-associated proteins that could potentially be utilized to enrich meningioma EVs from biofluids. Conclusions Elevated EV levels in meningioma patient plasma could aid in tumor diagnosis and assessment of treatment response. Meningioma EV-DNA mirrors genetic and epigenetic tumor alterations and facilitates molecular tumor classification.
Background Seizures can present at any time before or after the diagnosis of a glioma. Roughly, 25-30 % of glioblastoma (GBM) patients initially present with seizures, and an additional 30 % develop seizures during the course of the disease. Early studies failed to show an effect of general administration of anti-epileptic drugs for glioblastoma patients, since they were unable to stratify patients into high- or low-risk seizure groups. Methods 111 patients, who underwent surgery for a GBM, were included. Genome-wide DNA methylation profiling was performed, before methylation subclasses and copy number changes inferred from methylation data were correlated with clinical characteristics. Independently, global gene expression was analyzed in GBM methylation subclasses from TCGA datasets (n=68). Results Receptor tyrosine Kinase (RTK) II GBM showed a significantly higher incidence of seizures than RTK I and mesenchymal (MES) GBM (p<0.01). Accordingly, RNA expression datasets revealed an upregulation of genes involved in neurotransmitter synapses and vesicle transport in RTK II glioblastomas. In a multivariate analysis, temporal location (p=0.02, OR 5.69) and RTK II (p=0.03, OR 5.01) were most predictive for preoperative seizures. During postoperative follow-up, only RTK II remained significantly associated with the development of seizures (p<0.01, OR 8.23). Consequently, the need for antiepileptic medication and its increase due to treatment failure was highly associated with the RTK II methylation subclass (p<0.01). Conclusion Our study shows a strong correlation of RTK II glioblastomas with preoperative and long-term seizures. These results underline the benefit of molecular glioblastoma profiling with important implications for postoperative seizure control.
INTRODUCTION Extracellular vesicles (EVs) carry biological information from their cell of origin that is useful for non-invasive detection of tumor biomarkers and disease monitoring. In glioblastoma (GBM), blood circulating EVs are elevated and carry GBM-associated proteins. However, it is still challenging to analyze tumor derived EVs for translational purposes. Here, we used imaging flow cytometry (IFCM) as a robust strategy to perform phenotyping of EVs with GBM related surface markers in human plasma. METHODS EVs were isolated via differential ultracentrifugation from plasma of (a) 40 GBM patients, pre- and post-surgery, (b) 11matched GBM relapses and (c) 12 healthy donors (HD). EV sizes and concentrations were evaluated by NTA. EV markers (CD9,CD63 and CD81) together with glioma-related markers (integrin beta-1 [ITGB1], tenascin C [TNC], Profilin-1 [PFN1], CD44,GPNMB, SPARC, HLA-II or CD133) were analyzed by IFCM. EV percentages and objects/mL plasma were compared among the groups and correlated with clinical parameters. RESULTS CD9 was the predominant tetraspanin in all groups (15-96%), while CD63 had the lowest levels (0-33%) and the strongestdecrease in GBM patients after surgery (fold change [FC]=-5.4, p<0.01). Among the glioma-related markers, ITGB1 and TNC displayed the most significant differences between the analyzed groups, especially the double positives ITGB1+/CD63+and TNC+/CD63+, which decreased in patients after tumor removal (FC=-3.5 and -12, respectively; p<0.001). Meanwhile,ITGB1+/CD9+and TNC+/CD9+EVs exhibited the highest levels in GBM when compared to HD subjects (FC=8.6 and 17.4;p<0.001) and upon tumor recurrence (FC=3.7 and 10.9, respectively; p<0.01). SUMMARY/CONCLUSION We identified EV surface antigens with potential clinical utility as GBM biomarkers. Among them, we highlight ITGB1 and TNC as the most promising markers.
Standard monitoring after meningioma resection relies on serial MRI examinations, which are time-consuming, expensive and provide no information on molecular alterations that may indicate progression towards a more aggressive tumor. Extracellular vesicles (EVs) secreted by tumor cells play an important role in cell-cell communication, and tumor-derived EVs circulating in patient blood can serve as biomarkers. We investigated the potential role of plasma EVs in meningioma patients for tumor detection and determined whether EVs secreted by meningioma cells reflect epigenetic, genomic and proteomic alterations of original tumors. EV concentrations were quantified in patient plasma (n = 46). Short-term meningioma cultures were established (n = 26) and secreted EVs were isolated. Methylation and copy number profiling was performed using 850k arrays, and mutations were identified by targeted gene panel sequencing. Differential quantitative mass spectrometry was employed for proteomic analysis. We found that the levels of circulating EVs were significantly elevated in meningioma patients compared to healthy individuals, and that plasma EV concentrations correlated with malignancy grade and extent of peritumoral edema. Postoperatively, EV counts dropped to normal levels, and the magnitude of the postoperative decrease was associated with extent of tumor resection (Simpson grade). Methylation profiling of EV-DNA allowed correct tumor classification as meningioma in all investigated cases, and accurate methylation subclass assignment in nearly all cases. Copy number variations present in tumors, as well as tumor-specific mutations were faithfully reflected in meningioma EV-DNA. Proteomic EV profiling did not permit original tumor identification but revealed tumor-associated proteins such as desmoplakin that could potentially be utilized to enrich meningioma EVs from biofluids. In conclusion, elevated EV levels in meningioma patient plasma may aid in tumor diagnosis and assessment of treatment response. Meningioma EV-DNA mirrors genetic and epigenetic tumor alterations and facilitates molecular tumor classification.
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