EV-TRACK

Search > Results

You searched for: EV210173 (EV-TRACK ID)

Showing 1 - 5 of 5

Results list Study Tree

Details	EV-TRACK ID	Experiment nr.	Species	Sample type	Separation protocol	First author	Year	EV-METRIC
	EV210173	1/5	Homo sapiens	U87MG	(d)(U)C Filtration	Wang, Huayi	2019	56%
Study summary Full title Evaluation of serum extracellular vesicles as noninvasive diagnostic markers of glioma All authors Huayi Wang, Dengzhi Jiang, Wenzhe Li, Xiang Xiang, Jun Zhao, Bin Yu, Chen Wang, Zhaohui He, Ling Zhu, Yanlian Yang Journal Theranostics Abstract Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CN (show more...)Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CNS). The lack of reliable noninvasive diagnostic and prognostic methods is one of the main reasons for the high mortality of glioma. Serum has become a useful biomarker for the diagnosis and prognosis prediction of glioma because extracellular vesicles (EVs) carry molecular components from their parental cells. Methods: To detect EVs and perform molecular analysis of serum EVs, we established and optimized a microbead-assisted method based on flow cytometry and estimated the efficacy of EGFR protein expression and NLGN3 and PTTG1 mRNA in serum EVs from glioma patients (n=23) and healthy individuals (n=12). We evaluated the ability of EGFR+ EVs to differentiate high-grade and low-grade glioma patients and checked the correlation between EGFR in EVs and the ki-67 labeling index (LI) in the tumor tissue. Results: We demonstrated that EGFR+ EVs are effective diagnostic and prognostic markers of glioma. The expression of EGFR in serum EVs can accurately differentiate high-grade and low-grade glioma patients, and EGFR in EVs positively correlates with ki-67 LI in the tumor tissue. We also showed the potential of NLGN3 and PTTG1 mRNA in EVs for detecting glioma patients. Conclusions: We demonstrate that the protein expression of EGFR in serum EVs is an effective diagnostic marker of glioma. EGFR in EVs highly correlates with the malignancy of glioma. We also show the potential of NLGN3 and PTTG1 in EVs for detecting glioma. The optimized flow cytometry with the aid of microbead-based EV enrichment show its potential as a noninvasive method for the detection of glioma and will be beneficial to the management of glioma. (hide) EV-METRIC 56% (90th percentile of all experiments on the same sample type) Reported Not reported Not applicable EV-enriched proteins Protein analysis: analysis of three or more EV-enriched proteins non EV-enriched protein Protein analysis: assessment of a non-EV-enriched protein qualitative and quantitative analysis Particle analysis: implementation of both qualitative and quantitative methods. For the quantitative method, the reporting of measured EV concentration is expected. electron microscopy images Particle analysis: inclusion of a widefield and close-up electron microscopy image density gradient Separation method: density gradient, at least as validation of results attributed to EVs EV density Separation method: reporting of obtained EV density ultracentrifugation specifics Separation method: reporting of g-forces, duration and rotor type of ultracentrifugation steps antibody specifics Protein analysis: antibody clone/reference number and dilution lysate preparation Protein analysis: lysis buffer composition Study data Sample type Cell culture supernatant Sample origin Control condition Focus vesicles extracellular vesicle Separation protocol Separation protocol Gives a short, non-chronological overview of the different steps of the separation protocol. dUC = (Differential) (ultra)centrifugation DG = density gradient UF = ultrafiltration SEC = size-exclusion chromatography IAF = immuno-affinity capture (d)(U)C Filtration Protein markers EV: CD81/ Flotillin1/ EGFR non-EV: Grp94 Proteomics no Show all info Study aim Biomarker/Technical analysis comparing/optimizing EV-related methods Sample Species Homo sapiens Sample Type Cell culture supernatant EV-producing cells U87MG EV-harvesting Medium EV-depleted medium Preparation of EDS Not specified Separation Method (Differential) (ultra)centrifugation dUC: centrifugation steps Below or equal to 800 g Between 800 g and 10,000 g Between 100,000 g and 150,000 g Pelleting performed Yes Pelleting: time(min) 120 Pelleting: rotor type Type 70 Ti Pelleting: speed (g) 100000 Wash: volume per pellet (ml) Not specified Wash: time (min) 120 Wash: Rotor Type Type 70 Ti Wash: speed (g) 100000 Filtration steps 0.22µm or 0.2µm Characterization: Protein analysis Protein Concentration Method BCA Western Blot Antibody details provided? No Detected EV-associated proteins Flotillin1/ EGFR/ CD81 Not detected contaminants Grp94 Flow cytometry aspecific beads Antibody details provided? No Detected EV-associated proteins EGFR Characterization: Lipid analysis No

	EV210173	2/5	Homo sapiens	U251	(d)(U)C Filtration	Wang, Huayi	2019	56%
Study summary Full title Evaluation of serum extracellular vesicles as noninvasive diagnostic markers of glioma All authors Huayi Wang, Dengzhi Jiang, Wenzhe Li, Xiang Xiang, Jun Zhao, Bin Yu, Chen Wang, Zhaohui He, Ling Zhu, Yanlian Yang Journal Theranostics Abstract Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CN (show more...)Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CNS). The lack of reliable noninvasive diagnostic and prognostic methods is one of the main reasons for the high mortality of glioma. Serum has become a useful biomarker for the diagnosis and prognosis prediction of glioma because extracellular vesicles (EVs) carry molecular components from their parental cells. Methods: To detect EVs and perform molecular analysis of serum EVs, we established and optimized a microbead-assisted method based on flow cytometry and estimated the efficacy of EGFR protein expression and NLGN3 and PTTG1 mRNA in serum EVs from glioma patients (n=23) and healthy individuals (n=12). We evaluated the ability of EGFR+ EVs to differentiate high-grade and low-grade glioma patients and checked the correlation between EGFR in EVs and the ki-67 labeling index (LI) in the tumor tissue. Results: We demonstrated that EGFR+ EVs are effective diagnostic and prognostic markers of glioma. The expression of EGFR in serum EVs can accurately differentiate high-grade and low-grade glioma patients, and EGFR in EVs positively correlates with ki-67 LI in the tumor tissue. We also showed the potential of NLGN3 and PTTG1 mRNA in EVs for detecting glioma patients. Conclusions: We demonstrate that the protein expression of EGFR in serum EVs is an effective diagnostic marker of glioma. EGFR in EVs highly correlates with the malignancy of glioma. We also show the potential of NLGN3 and PTTG1 in EVs for detecting glioma. The optimized flow cytometry with the aid of microbead-based EV enrichment show its potential as a noninvasive method for the detection of glioma and will be beneficial to the management of glioma. (hide) EV-METRIC 56% (90th percentile of all experiments on the same sample type) Reported Not reported Not applicable EV-enriched proteins Protein analysis: analysis of three or more EV-enriched proteins non EV-enriched protein Protein analysis: assessment of a non-EV-enriched protein qualitative and quantitative analysis Particle analysis: implementation of both qualitative and quantitative methods. For the quantitative method, the reporting of measured EV concentration is expected. electron microscopy images Particle analysis: inclusion of a widefield and close-up electron microscopy image density gradient Separation method: density gradient, at least as validation of results attributed to EVs EV density Separation method: reporting of obtained EV density ultracentrifugation specifics Separation method: reporting of g-forces, duration and rotor type of ultracentrifugation steps antibody specifics Protein analysis: antibody clone/reference number and dilution lysate preparation Protein analysis: lysis buffer composition Study data Sample type Cell culture supernatant Sample origin Control condition Focus vesicles extracellular vesicle Separation protocol Separation protocol Gives a short, non-chronological overview of the different steps of the separation protocol. dUC = (Differential) (ultra)centrifugation DG = density gradient UF = ultrafiltration SEC = size-exclusion chromatography IAF = immuno-affinity capture (d)(U)C Filtration Protein markers EV: CD81/ Flotillin1/ EGFR non-EV: Grp94 Proteomics no Show all info Study aim Biomarker/Technical analysis comparing/optimizing EV-related methods Sample Species Homo sapiens Sample Type Cell culture supernatant EV-producing cells U251 EV-harvesting Medium EV-depleted medium Preparation of EDS Not specified Separation Method (Differential) (ultra)centrifugation dUC: centrifugation steps Below or equal to 800 g Between 800 g and 10,000 g Between 100,000 g and 150,000 g Pelleting performed Yes Pelleting: time(min) 120 Pelleting: rotor type Type 70 Ti Pelleting: speed (g) 100000 Wash: volume per pellet (ml) Not specified Wash: time (min) 120 Wash: Rotor Type Type 70 Ti Wash: speed (g) 100000 Filtration steps 0.22µm or 0.2µm Characterization: Protein analysis Protein Concentration Method BCA Western Blot Antibody details provided? No Detected EV-associated proteins Flotillin1/ EGFR/ CD81 Not detected contaminants Grp94 Flow cytometry aspecific beads Antibody details provided? No Detected EV-associated proteins EGFR Characterization: Lipid analysis No

	EV210173	3/5	Homo sapiens	HA	(d)(U)C Filtration	Wang, Huayi	2019	56%
Study summary Full title Evaluation of serum extracellular vesicles as noninvasive diagnostic markers of glioma All authors Huayi Wang, Dengzhi Jiang, Wenzhe Li, Xiang Xiang, Jun Zhao, Bin Yu, Chen Wang, Zhaohui He, Ling Zhu, Yanlian Yang Journal Theranostics Abstract Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CN (show more...)Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CNS). The lack of reliable noninvasive diagnostic and prognostic methods is one of the main reasons for the high mortality of glioma. Serum has become a useful biomarker for the diagnosis and prognosis prediction of glioma because extracellular vesicles (EVs) carry molecular components from their parental cells. Methods: To detect EVs and perform molecular analysis of serum EVs, we established and optimized a microbead-assisted method based on flow cytometry and estimated the efficacy of EGFR protein expression and NLGN3 and PTTG1 mRNA in serum EVs from glioma patients (n=23) and healthy individuals (n=12). We evaluated the ability of EGFR+ EVs to differentiate high-grade and low-grade glioma patients and checked the correlation between EGFR in EVs and the ki-67 labeling index (LI) in the tumor tissue. Results: We demonstrated that EGFR+ EVs are effective diagnostic and prognostic markers of glioma. The expression of EGFR in serum EVs can accurately differentiate high-grade and low-grade glioma patients, and EGFR in EVs positively correlates with ki-67 LI in the tumor tissue. We also showed the potential of NLGN3 and PTTG1 mRNA in EVs for detecting glioma patients. Conclusions: We demonstrate that the protein expression of EGFR in serum EVs is an effective diagnostic marker of glioma. EGFR in EVs highly correlates with the malignancy of glioma. We also show the potential of NLGN3 and PTTG1 in EVs for detecting glioma. The optimized flow cytometry with the aid of microbead-based EV enrichment show its potential as a noninvasive method for the detection of glioma and will be beneficial to the management of glioma. (hide) EV-METRIC 56% (90th percentile of all experiments on the same sample type) Reported Not reported Not applicable EV-enriched proteins Protein analysis: analysis of three or more EV-enriched proteins non EV-enriched protein Protein analysis: assessment of a non-EV-enriched protein qualitative and quantitative analysis Particle analysis: implementation of both qualitative and quantitative methods. For the quantitative method, the reporting of measured EV concentration is expected. electron microscopy images Particle analysis: inclusion of a widefield and close-up electron microscopy image density gradient Separation method: density gradient, at least as validation of results attributed to EVs EV density Separation method: reporting of obtained EV density ultracentrifugation specifics Separation method: reporting of g-forces, duration and rotor type of ultracentrifugation steps antibody specifics Protein analysis: antibody clone/reference number and dilution lysate preparation Protein analysis: lysis buffer composition Study data Sample type Cell culture supernatant Sample origin Control condition Focus vesicles extracellular vesicle Separation protocol Separation protocol Gives a short, non-chronological overview of the different steps of the separation protocol. dUC = (Differential) (ultra)centrifugation DG = density gradient UF = ultrafiltration SEC = size-exclusion chromatography IAF = immuno-affinity capture (d)(U)C Filtration Protein markers EV: CD81/ Flotillin1/ EGFR non-EV: GRP94 Proteomics no Show all info Study aim Biomarker/Technical analysis comparing/optimizing EV-related methods Sample Species Homo sapiens Sample Type Cell culture supernatant EV-producing cells HA EV-harvesting Medium EV-depleted medium Preparation of EDS Not specified Separation Method (Differential) (ultra)centrifugation dUC: centrifugation steps Below or equal to 800 g Between 800 g and 10,000 g Between 100,000 g and 150,000 g Pelleting performed Yes Pelleting: time(min) 120 Pelleting: rotor type Type 70 Ti Pelleting: speed (g) 100000 Wash: volume per pellet (ml) Not specified Wash: time (min) 120 Wash: Rotor Type Type 70 Ti Wash: speed (g) 100000 Filtration steps 0.22µm or 0.2µm Characterization: Protein analysis Protein Concentration Method BCA Western Blot Antibody details provided? No Detected EV-associated proteins Flotillin1/ CD81 Not detected EV-associated proteins EGFR Not detected contaminants GRP94 Flow cytometry aspecific beads Antibody details provided? No Detected EV-associated proteins EGFR Characterization: Lipid analysis No

	EV210173	5/5	Homo sapiens	Serum	(d)(U)C Filtration	Wang, Huayi	2019	33%
Study summary Full title Evaluation of serum extracellular vesicles as noninvasive diagnostic markers of glioma All authors Huayi Wang, Dengzhi Jiang, Wenzhe Li, Xiang Xiang, Jun Zhao, Bin Yu, Chen Wang, Zhaohui He, Ling Zhu, Yanlian Yang Journal Theranostics Abstract Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CN (show more...)Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CNS). The lack of reliable noninvasive diagnostic and prognostic methods is one of the main reasons for the high mortality of glioma. Serum has become a useful biomarker for the diagnosis and prognosis prediction of glioma because extracellular vesicles (EVs) carry molecular components from their parental cells. Methods: To detect EVs and perform molecular analysis of serum EVs, we established and optimized a microbead-assisted method based on flow cytometry and estimated the efficacy of EGFR protein expression and NLGN3 and PTTG1 mRNA in serum EVs from glioma patients (n=23) and healthy individuals (n=12). We evaluated the ability of EGFR+ EVs to differentiate high-grade and low-grade glioma patients and checked the correlation between EGFR in EVs and the ki-67 labeling index (LI) in the tumor tissue. Results: We demonstrated that EGFR+ EVs are effective diagnostic and prognostic markers of glioma. The expression of EGFR in serum EVs can accurately differentiate high-grade and low-grade glioma patients, and EGFR in EVs positively correlates with ki-67 LI in the tumor tissue. We also showed the potential of NLGN3 and PTTG1 mRNA in EVs for detecting glioma patients. Conclusions: We demonstrate that the protein expression of EGFR in serum EVs is an effective diagnostic marker of glioma. EGFR in EVs highly correlates with the malignancy of glioma. We also show the potential of NLGN3 and PTTG1 in EVs for detecting glioma. The optimized flow cytometry with the aid of microbead-based EV enrichment show its potential as a noninvasive method for the detection of glioma and will be beneficial to the management of glioma. (hide) EV-METRIC 33% (76th percentile of all experiments on the same sample type) Reported Not reported Not applicable EV-enriched proteins Protein analysis: analysis of three or more EV-enriched proteins non EV-enriched protein Protein analysis: assessment of a non-EV-enriched protein qualitative and quantitative analysis Particle analysis: implementation of both qualitative and quantitative methods. For the quantitative method, the reporting of measured EV concentration is expected. electron microscopy images Particle analysis: inclusion of a widefield and close-up electron microscopy image density gradient Separation method: density gradient, at least as validation of results attributed to EVs EV density Separation method: reporting of obtained EV density ultracentrifugation specifics Separation method: reporting of g-forces, duration and rotor type of ultracentrifugation steps antibody specifics Protein analysis: antibody clone/reference number and dilution lysate preparation Protein analysis: lysis buffer composition Study data Sample type Serum Sample origin Glioma Focus vesicles extracellular vesicle Separation protocol Separation protocol Gives a short, non-chronological overview of the different steps of the separation protocol. dUC = (Differential) (ultra)centrifugation DG = density gradient UF = ultrafiltration SEC = size-exclusion chromatography IAF = immuno-affinity capture (d)(U)C Filtration Protein markers EV: EGFR/ EGFR/ FGF2/ CD81/ Flotillin-1 non-EV: HSA Proteomics no Show all info Study aim Biomarker/Technical analysis comparing/optimizing EV-related methods Sample Species Homo sapiens Sample Type Serum Separation Method (Differential) (ultra)centrifugation dUC: centrifugation steps Between 800 g and 10,000 g Equal to or above 150,000 g Pelleting performed Yes Pelleting: time(min) 480 Pelleting: rotor type Not specified Pelleting: speed (g) 150000 Wash: volume per pellet (ml) 26 Wash: time (min) 120 Wash: Rotor Type Not specified Wash: speed (g) 150000 Filtration steps 0.22µm or 0.2µm Characterization: Protein analysis Protein Concentration Method BCA Western Blot Antibody details provided? No Detected EV-associated proteins EGFR/ FGF2/ CD81/ Flotillin-1 Not detected contaminants HSA Flow cytometry aspecific beads Antibody details provided? No Detected EV-associated proteins EGFR Characterization: RNA analysis RNA analysis Type (RT)(q)PCR Database No Proteinase treatment No RNAse treatment No Characterization: Lipid analysis No

	EV210173	4/5	Homo sapiens	Serum	(d)(U)C Filtration	Wang, Huayi	2019	13%
Study summary Full title Evaluation of serum extracellular vesicles as noninvasive diagnostic markers of glioma All authors Huayi Wang, Dengzhi Jiang, Wenzhe Li, Xiang Xiang, Jun Zhao, Bin Yu, Chen Wang, Zhaohui He, Ling Zhu, Yanlian Yang Journal Theranostics Abstract Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CN (show more...)Rationale: Glioma is the most common malignant primary brain tumor in the central nervous system (CNS). The lack of reliable noninvasive diagnostic and prognostic methods is one of the main reasons for the high mortality of glioma. Serum has become a useful biomarker for the diagnosis and prognosis prediction of glioma because extracellular vesicles (EVs) carry molecular components from their parental cells. Methods: To detect EVs and perform molecular analysis of serum EVs, we established and optimized a microbead-assisted method based on flow cytometry and estimated the efficacy of EGFR protein expression and NLGN3 and PTTG1 mRNA in serum EVs from glioma patients (n=23) and healthy individuals (n=12). We evaluated the ability of EGFR+ EVs to differentiate high-grade and low-grade glioma patients and checked the correlation between EGFR in EVs and the ki-67 labeling index (LI) in the tumor tissue. Results: We demonstrated that EGFR+ EVs are effective diagnostic and prognostic markers of glioma. The expression of EGFR in serum EVs can accurately differentiate high-grade and low-grade glioma patients, and EGFR in EVs positively correlates with ki-67 LI in the tumor tissue. We also showed the potential of NLGN3 and PTTG1 mRNA in EVs for detecting glioma patients. Conclusions: We demonstrate that the protein expression of EGFR in serum EVs is an effective diagnostic marker of glioma. EGFR in EVs highly correlates with the malignancy of glioma. We also show the potential of NLGN3 and PTTG1 in EVs for detecting glioma. The optimized flow cytometry with the aid of microbead-based EV enrichment show its potential as a noninvasive method for the detection of glioma and will be beneficial to the management of glioma. (hide) EV-METRIC 13% (47th percentile of all experiments on the same sample type) Reported Not reported Not applicable EV-enriched proteins Protein analysis: analysis of three or more EV-enriched proteins non EV-enriched protein Protein analysis: assessment of a non-EV-enriched protein qualitative and quantitative analysis Particle analysis: implementation of both qualitative and quantitative methods. For the quantitative method, the reporting of measured EV concentration is expected. electron microscopy images Particle analysis: inclusion of a widefield and close-up electron microscopy image density gradient Separation method: density gradient, at least as validation of results attributed to EVs EV density Separation method: reporting of obtained EV density ultracentrifugation specifics Separation method: reporting of g-forces, duration and rotor type of ultracentrifugation steps antibody specifics Protein analysis: antibody clone/reference number and dilution lysate preparation Protein analysis: lysis buffer composition Study data Sample type Serum Sample origin Control condition Focus vesicles extracellular vesicle Separation protocol Separation protocol Gives a short, non-chronological overview of the different steps of the separation protocol. dUC = (Differential) (ultra)centrifugation DG = density gradient UF = ultrafiltration SEC = size-exclusion chromatography IAF = immuno-affinity capture (d)(U)C Filtration Protein markers EV: EGFR non-EV: None Proteomics no Show all info Study aim Biomarker/Technical analysis comparing/optimizing EV-related methods Sample Species Homo sapiens Sample Type Serum Separation Method (Differential) (ultra)centrifugation dUC: centrifugation steps Between 800 g and 10,000 g Equal to or above 150,000 g Pelleting performed Yes Pelleting: time(min) 480 Pelleting: rotor type Not specified Pelleting: speed (g) 150000 Wash: volume per pellet (ml) 26 Wash: time (min) 120 Wash: Rotor Type Not specified Wash: speed (g) 150000 Filtration steps 0.22µm or 0.2µm Characterization: Protein analysis Protein Concentration Method BCA Flow cytometry aspecific beads Antibody details provided? No Detected EV-associated proteins EGFR Characterization: RNA analysis RNA analysis Type (RT)(q)PCR Database No Proteinase treatment No RNAse treatment No Characterization: Lipid analysis No

				1 - 5 of 5

EV-TRACK ID	EV210173
species	Homo sapiens
sample type	Cell culture	Cell culture	Cell culture	Serum	Serum
cell type	U87MG	U251	HA	NA	NA
medium	EV-depleted medium	EV-depleted medium	EV-depleted medium	NA	NA
condition	Control condition	Control condition	Control condition	Glioma	Control condition
separation protocol	(d)(U)C Filtration	(d)(U)C Filtration	(d)(U)C Filtration	(d)(U)C Filtration	(d)(U)C Filtration
Exp. nr.	1	2	3	5	4
EV-METRIC %	56	56	56	33	13