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You searched for: EV160013 (EV-TRACK ID)

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Experiment number
  • If needed, multiple experiments were identified in a single publication based on differing sample types, separation protocols and/or vesicle types of interest.
Species
  • Species of origin of the EVs.
Separation protocol
  • Gives a short, non-chronological overview of the different steps of the separation protocol.
    • dUC = differential ultracentrifugation
    • DG = density gradient
    • UF = ultrafiltration
    • SEC = size-exclusion chromatography
Details EV-TRACK ID Experiment nr. Species Sample type separation protocol First author Year EV-METRIC
EV160013 2/3 Homo sapiens Serum (Differential) (ultra)centrifugation Dong L 2016 14%

Study summary

Full title
All authors
Dong L, Lin W, Qi P, Xu MD, Wu X, Ni S, Huang D, Weng WW, Tan C, Sheng W, Zhou X, Du X.
Journal
Cancer Epidemiol Biomarkers Prev
Abstract
BACKGROUND: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (≥200 nucleotides) compared with m (show more...)BACKGROUND: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (≥200 nucleotides) compared with miRNAs. In blood, long RNAs may be protected by serum extracellular vesicles, such as apoptotic bodies (AB), microvesicles (MV), and exosomes (EXO). They are potential biomarkers for identifying cancer. METHODS: Sera from 76 preoperative colorectal cancer patients, 76 age- and sex-matched healthy subjects, and 20 colorectal adenoma patients without colorectal cancer were collected. We investigated the distribution of long RNAs into the three vesicles. Seventy-nine cancer-related long RNAs were chosen and detected using qPCR. RESULTS: The quantity of long RNA has varying distribution among three subtypes of extracellular vesicles in serum. Most mRNA and lncRNA genes had higher quantity in EXOs than that in ABs and MVs, whereas MVs contain lowest quantity. We investigated 79 long RNAs chosen from The Cancer Genome Atlas and the LncRNADisease database in the sera of healthy patients, and those with colorectal cancer. In the training and test sets, the AUCs were 0.936 and 0.877, respectively. The AUC of total serum RNA was lower (0.857) than that of exosomal RNA in the same samples (0.936). CONCLUSION: The present study shows that exosomal mRNAs and lncRNAs in serum could be used as biomarkers to detect colorectal cancer. (hide)
EV-METRIC
14% (63rd 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
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
colorectal cancer
Focus vesicles
(shedding) microvesicle
Separation protocol
Separation protocol
  • Gives a short, non-chronological overview of the
    different steps of the separation protocol.
    • dUC = differential ultracentrifugation
    • DG = density gradient
    • UF = ultrafiltration
    • SEC = size-exclusion chromatography
(Differential) (ultra)centrifugation
Protein markers
EV: None
non-EV: None
Proteomics
no
Show all info
Study aim
Biomarker/Identification of content (omics approaches)
Sample
Species
Homo sapiens
Sample Type
Serum
Sample Condition
colorectal cancer
Separation Method
Differential ultracentrifugation
dUC: centrifugation steps
Between 800 g and 10,000 g
Between 10,000 g and 50,000 g
Pelleting: time(min)
60
Pelleting: rotor type
Not specified
Pelleting: speed (g)
12000
Protein Concentration Method
Not determined
Characterization: Particle analysis
NTA
Report type
Size range/distribution
Reported size (nm)
75-465
EV concentration
Yes
EM
EM-type
Transmission-EM
Image type
Close-up
EV160013 3/3 Homo sapiens Serum (Differential) (ultra)centrifugation
Filtration
Dong L 2016 14%

Study summary

Full title
All authors
Dong L, Lin W, Qi P, Xu MD, Wu X, Ni S, Huang D, Weng WW, Tan C, Sheng W, Zhou X, Du X.
Journal
Cancer Epidemiol Biomarkers Prev
Abstract
BACKGROUND: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (≥200 nucleotides) compared with m (show more...)BACKGROUND: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (≥200 nucleotides) compared with miRNAs. In blood, long RNAs may be protected by serum extracellular vesicles, such as apoptotic bodies (AB), microvesicles (MV), and exosomes (EXO). They are potential biomarkers for identifying cancer. METHODS: Sera from 76 preoperative colorectal cancer patients, 76 age- and sex-matched healthy subjects, and 20 colorectal adenoma patients without colorectal cancer were collected. We investigated the distribution of long RNAs into the three vesicles. Seventy-nine cancer-related long RNAs were chosen and detected using qPCR. RESULTS: The quantity of long RNA has varying distribution among three subtypes of extracellular vesicles in serum. Most mRNA and lncRNA genes had higher quantity in EXOs than that in ABs and MVs, whereas MVs contain lowest quantity. We investigated 79 long RNAs chosen from The Cancer Genome Atlas and the LncRNADisease database in the sera of healthy patients, and those with colorectal cancer. In the training and test sets, the AUCs were 0.936 and 0.877, respectively. The AUC of total serum RNA was lower (0.857) than that of exosomal RNA in the same samples (0.936). CONCLUSION: The present study shows that exosomal mRNAs and lncRNAs in serum could be used as biomarkers to detect colorectal cancer. (hide)
EV-METRIC
14% (63rd 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
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
colorectal cancer
Focus vesicles
exosome
Separation protocol
Separation protocol
  • Gives a short, non-chronological overview of the
    different steps of the separation protocol.
    • dUC = differential ultracentrifugation
    • DG = density gradient
    • UF = ultrafiltration
    • SEC = size-exclusion chromatography
(Differential) (ultra)centrifugation + Filtration
Protein markers
EV: None
non-EV: None
Proteomics
no
Show all info
Study aim
Biomarker/Identification of content (omics approaches)
Sample
Species
Homo sapiens
Sample Type
Serum
Sample Condition
colorectal cancer
Separation Method
Differential ultracentrifugation
dUC: centrifugation steps
Between 800 g and 10,000 g
Between 10,000 g and 50,000 g
Between 100,000 g and 150,000 g
Pelleting: time(min)
120
Pelleting: rotor type
Not specified
Pelleting: speed (g)
120000
Protein Concentration Method
Not determined
Characterization: Particle analysis
NTA
Report type
Size range/distribution
Reported size (nm)
45-205
EM
EM-type
Transmission-EM
Image type
Close-up
EV160013 1/3 Homo sapiens Serum (Differential) (ultra)centrifugation Dong L 2016 0%

Study summary

Full title
All authors
Dong L, Lin W, Qi P, Xu MD, Wu X, Ni S, Huang D, Weng WW, Tan C, Sheng W, Zhou X, Du X.
Journal
Cancer Epidemiol Biomarkers Prev
Abstract
BACKGROUND: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (≥200 nucleotides) compared with m (show more...)BACKGROUND: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (≥200 nucleotides) compared with miRNAs. In blood, long RNAs may be protected by serum extracellular vesicles, such as apoptotic bodies (AB), microvesicles (MV), and exosomes (EXO). They are potential biomarkers for identifying cancer. METHODS: Sera from 76 preoperative colorectal cancer patients, 76 age- and sex-matched healthy subjects, and 20 colorectal adenoma patients without colorectal cancer were collected. We investigated the distribution of long RNAs into the three vesicles. Seventy-nine cancer-related long RNAs were chosen and detected using qPCR. RESULTS: The quantity of long RNA has varying distribution among three subtypes of extracellular vesicles in serum. Most mRNA and lncRNA genes had higher quantity in EXOs than that in ABs and MVs, whereas MVs contain lowest quantity. We investigated 79 long RNAs chosen from The Cancer Genome Atlas and the LncRNADisease database in the sera of healthy patients, and those with colorectal cancer. In the training and test sets, the AUCs were 0.936 and 0.877, respectively. The AUC of total serum RNA was lower (0.857) than that of exosomal RNA in the same samples (0.936). CONCLUSION: The present study shows that exosomal mRNAs and lncRNAs in serum could be used as biomarkers to detect colorectal cancer. (hide)
EV-METRIC
0% (median: 13% 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
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
colorectal cancer
Focus vesicles
apoptotic body
Separation protocol
Separation protocol
  • Gives a short, non-chronological overview of the
    different steps of the separation protocol.
    • dUC = differential ultracentrifugation
    • DG = density gradient
    • UF = ultrafiltration
    • SEC = size-exclusion chromatography
(Differential) (ultra)centrifugation
Protein markers
EV: None
non-EV: None
Proteomics
no
Show all info
Study aim
Biomarker/Identification of content (omics approaches)
Sample
Species
Homo sapiens
Sample Type
Serum
Sample Condition
colorectal cancer
Separation Method
Differential ultracentrifugation
dUC: centrifugation steps
Between 800 g and 10,000 g
Pelleting: time(min)
30
Pelleting: rotor type
Not specified
Pelleting: speed (g)
2000
Protein Concentration Method
Not determined
Characterization: Particle analysis
1 - 3 of 3
  • CM = Commercial method
  • dUC = differential ultracentrifugation
  • DG = density gradient
  • UF = ultrafiltration
  • SEC = size-exclusion chromatography
EV-TRACK ID
EV160013
species
Homo sapiens
sample type
Serum
condition
colorectal cancer
separation protocol
dUC
dUC
Filtration
dUC
vesicle related term
(shedding)
microvesicle
exosome
apoptotic body
Exp. nr.
2
3
1
EV-METRIC %
14
14
0