A novel serum extracellular vesicle protein signature to monitor glioblastoma tumor progression

Tzaridis, Theophilos; Weller, Johannes; Bachurski, Daniel; Shakeri, Farhad; Schaub, Christina; Hau, Peter; Buneß, Andreas; Schlegel, Uwe; Steinbach, Joachim-Peter; Seidel, Clemens; Goldbrunner, Roland; Schäfer, Niklas; Wechsler‐Reya, Robert J.; Hallek, Michael; Scheffler, Björn; Glas, Martin; Haeberle, Lothar; Herrlinger, Ulrich; Coch, Christoph; Reiners, Katrin S.; Hartmann, Gunther

doi:10.1002/ijc.34261

Cited by 9 publications

(7 citation statements)

References 39 publications

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“…Then EVs were directly lysed for protein and RNA coanalysis by Co-PAR (Figure A). Primer extension assay (PEA), , used for protein detection, consisted of five steps [Figure B(i)]. The first step was protein capture.…”

Section: Resultsmentioning

confidence: 99%

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis

He,

Long,

Zhai

et al. 2024

Anal. Chem.

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Tumor-derived extracellular vesicles (EVs) carry tumor-specific proteins and RNAs, thus becoming prevalent targets for early cancer diagnosis. However, low expression of EV cargos and insufficient diagnostic power of individual biomarkers hindered EVs application in clinical practice. Herein, we propose a multiplex Codetection platform of proteins and RNAs (Co-PAR) for EVs. Co-PAR adopted a pair of antibody-DNA probes to recognize the same target protein, which in turn formed a double-stranded DNA. Thus, the target protein could be quantified by detecting the double-stranded DNA via qPCR. Meanwhile, qRT-PCR simultaneously quantified the target RNAs. Thus, with a regular qPCR instrument, Co-PAR enabled the codetection of multiplex proteins and RNAs, with the sensitivity of 102 EVs/μL (targeting CD63) and 1 EV/μL (targeting snRNA U6). We analyzed the coexpressions of three protein markers (CD63, GPC-1, HER2) and three RNA markers (snRNA U6, GPC-1 mRNA, miR-10b) on EVs from three pancreatic cell lines and 30 human plasma samples using Co-PAR. The diagnostic accuracy of the 6-biomarker combination reached 92.9%, which was at least 6.2% higher than that of 3-biomarker combinations and at least 13.5% higher than that of 6 single biomarkers. Co-PAR, as a multiparameter detection platform for EVs, has great potential in early disease diagnosis.

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Section: Resultsmentioning

confidence: 99%

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis

He,

Long,

Zhai

et al. 2024

Anal. Chem.

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“… Changes in metabolic pathway miRNA expression in EV cargo were identified following radiotherapy. Tzaridis [ 42 ] 2021 67 GBM patients (36 + 31 in independent cohorts) 22 volunteers One sample pre-radiotherapy (28 patients) and at 2–4 surveillance MRI visits. 9ml in serum tubes.…”

Section: Resultsmentioning

confidence: 99%

Shooting the messenger: a systematic review investigating extracellular vesicle isolation and characterisation methods and their influence on understanding extracellular vesicles-radiotherapy interactions in glioblastoma

Robinson,

Samuels,

Jones

et al. 2023

BMC Cancer

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Background Extracellular vesicles (EVs) hold promise for improving our understanding of radiotherapy response in glioblastoma due to their role in intercellular communication within the tumour microenvironment (TME). However, methodologies to study EVs are evolving with significant variation within the EV research community. Methods We conducted a systematic review to critically appraise EV isolation and characterisation methodologies and how this influences our understanding of the findings from studies investigating radiotherapy and EV interactions in glioblastoma. 246 articles published up to 24/07/2023 from PubMed and Web of Science were identified using search parameters related to radiotherapy, EVs, and glioblastoma. Two reviewers evaluated study eligibility and abstracted data. Results In 26 articles eligible for inclusion (16 investigating the effects of radiotherapy on EVs, five investigating the effect of EVs on radiation response, and five clinical studies), significant heterogeneity and frequent omission of key characterisation steps was identified, reducing confidence that the results are related to EVs and their cargo as opposed to co-isolated bioactive molecules. However, the results are able to clearly identify interactions between EVs and radiotherapy bi-directionally within different cell types within the glioblastoma TME. These interactions facilitate transferable radioresistance and oncogenic signalling, highlighting that EVs are an important component in the variability of glioblastoma radiotherapy response. Conclusions Future multi-directional investigations interrogating the whole TME are required to improve subsequent clinical translation, and all studies should incorporate up to date controls and reporting requirements to increase the validity of their findings. This would be facilitated by increased collaboration between less experienced and more experienced EV research groups.

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“…For serum preparation, blood was collected in 9 ml S-monovettes (Sarstedt, Nuembrecht, Germany) and samples were processed as previously described [ 12 ]. In short, samples were rested in an upright position for 30 min to allow coagulation and then centrifuged at 2,000 × g at RT for 15 min.…”

Section: Methodsmentioning

confidence: 99%

“…EVs were isolated from 500 µl serum samples following the previously described method [ 12 ]. Briefly, the serum was pre-cleared by centrifugation at 10,000 × g for 45 min at 4 °C.…”

Section: Methodsmentioning

confidence: 99%

“…Neurodegeneration and brain tumors such as glioblastoma (GB), the most common malignant brain tumor [ 11 ], are commonly associated with neuroinflammatory conditions, known to promote BBB leakiness and EV shedding from brain microvascular endothelial cells. Therefore, brain-derived EVs possess high potential for minimal-invasive diagnosis and prognosis of diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS) and GB, which currently are only detected when clinical symptoms arise and considerable damage has already occurred to the brain [ 12 – 16 ]. Furthermore, EV-associated biomarkers may assist the differential diagnosis of diseases with overlapping clinical symptoms, as recently demonstrated for differentiating PD and Progressive Supranuclear Paralysis [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of technical and clinical utility of a bead-based flow cytometry platform for multiparametric phenotyping of CNS-derived extracellular vesicles

Brahmer,

Geiß,

Lygeraki

et al. 2023

Cell Commun Signal

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Background Extracellular vesicles (EVs) originating from the central nervous system (CNS) can enter the blood stream and carry molecules characteristic of disease states. Therefore, circulating CNS-derived EVs have the potential to serve as liquid-biopsy markers for early diagnosis and follow-up of neurodegenerative diseases and brain tumors. Monitoring and profiling of CNS-derived EVs using multiparametric analysis would be a major advance for biomarker as well as basic research. Here, we explored the performance of a multiplex bead-based flow-cytometry assay (EV Neuro) for semi-quantitative detection of CNS-derived EVs in body fluids. Methods EVs were separated from culture of glioblastoma cell lines (LN18, LN229, NCH82) and primary human astrocytes and measured at different input amounts in the MACSPlex EV Kit Neuro, human. In addition, EVs were separated from blood samples of small cohorts of glioblastoma (GB), multiple sclerosis (MS) and Alzheimer’s disease patients as well as healthy controls (HC) and subjected to the EV Neuro assay. To determine statistically significant differences between relative marker signal intensities, an unpaired samples t-test or Wilcoxon rank sum test were computed. Data were subjected to tSNE, heatmap clustering, and correlation analysis to further explore the relationships between disease state and EV Neuro data. Results Glioblastoma cell lines and primary human astrocytes showed distinct EV profiles. Signal intensities were increasing with higher EV input. Data normalization improved identification of markers that deviate from a common profile. Overall, patient blood-derived EV marker profiles were constant, but individual EV populations were significantly increased in disease compared to healthy controls, e.g. CD36+EVs in glioblastoma and GALC+EVs in multiple sclerosis. tSNE and heatmap clustering analysis separated GB patients from HC, but not MS patients from HC. Correlation analysis revealed a potential association of CD107a+EVs with neurofilament levels in blood of MS patients and HC. Conclusions The semi-quantitative EV Neuro assay demonstrated its utility for EV profiling in complex samples. However, reliable statistical results in biomarker studies require large sample cohorts and high effect sizes. Nonetheless, this exploratory trial confirmed the feasibility of discovering EV-associated biomarkers and monitoring circulating EV profiles in CNS diseases using the EV Neuro assay.

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A novel serum extracellular vesicle protein signature to monitor glioblastoma tumor progression

Cited by 9 publications

References 39 publications

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis

Shooting the messenger: a systematic review investigating extracellular vesicle isolation and characterisation methods and their influence on understanding extracellular vesicles-radiotherapy interactions in glioblastoma

Assessment of technical and clinical utility of a bead-based flow cytometry platform for multiparametric phenotyping of CNS-derived extracellular vesicles

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