Exosomal Proteins as Diagnostic Biomarkers in Lung Cancer. Issue 10 (October 2016)
- Record Type:
- Journal Article
- Title:
- Exosomal Proteins as Diagnostic Biomarkers in Lung Cancer. Issue 10 (October 2016)
- Main Title:
- Exosomal Proteins as Diagnostic Biomarkers in Lung Cancer
- Authors:
- Sandfeld‐Paulsen, Birgitte
Jakobsen, Kristine Raaby
Bæk, Rikke
Folkersen, Birgitte Holst
Rasmussen, Torben Riis
Meldgaard, Peter
Varming, Kim
Jørgensen, Malene Møller
Sorensen, Boe Sandahl - Abstract:
- ABSTRACT : Introduction: : Exosomes have been suggested as promising biomarkers in NSCLC because they contain proteins from their originating cells and are readily available in plasma. In this study, we explored the potential of exosome protein profiling in diagnosing lung cancers of all stages and various histological subtypes in patients. Methods: : Plasma was isolated from 581 patients (431 with lung cancer and 150 controls). The extracellular vesicle array was used to phenotype exosomes. The extracellular vesicle array contained 49 antibodies for capturing exosomes. Subsequently, a cocktail of biotin‐conjugated CD9, CD81, and CD63 antibodies was used to detect and visualize captured exosomes. Multimarker models were made by combining two or more markers. The optimal multimarker model was evaluated by area under the curve (AUC) and random forests analysis. Results: : The markers CD151, CD171, and tetraspanin 8 were the strongest separators of patients with cancer of all histological subtypes versus patients without cancer (CD151: AUC = 0.68, p = 0.0002; CD171: AUC = 0.60, p = 0.0002; and TSPAN8: AUC = 0.60, p = 0.0002). The multimarker models with the largest AUC in the cohort of patients with all lung cancer histological subtypes and in the cohort of patients with adenocarcinoma only covered 10 markers (all cancer: AUC = 0.74 [95% confidence interval: 0.70–0.80]; adenocarcinoma only: AUC = 0.76 [95% confidence interval: 0.70–0.83]). In squamous cell cancer and SCLC,ABSTRACT : Introduction: : Exosomes have been suggested as promising biomarkers in NSCLC because they contain proteins from their originating cells and are readily available in plasma. In this study, we explored the potential of exosome protein profiling in diagnosing lung cancers of all stages and various histological subtypes in patients. Methods: : Plasma was isolated from 581 patients (431 with lung cancer and 150 controls). The extracellular vesicle array was used to phenotype exosomes. The extracellular vesicle array contained 49 antibodies for capturing exosomes. Subsequently, a cocktail of biotin‐conjugated CD9, CD81, and CD63 antibodies was used to detect and visualize captured exosomes. Multimarker models were made by combining two or more markers. The optimal multimarker model was evaluated by area under the curve (AUC) and random forests analysis. Results: : The markers CD151, CD171, and tetraspanin 8 were the strongest separators of patients with cancer of all histological subtypes versus patients without cancer (CD151: AUC = 0.68, p = 0.0002; CD171: AUC = 0.60, p = 0.0002; and TSPAN8: AUC = 0.60, p = 0.0002). The multimarker models with the largest AUC in the cohort of patients with all lung cancer histological subtypes and in the cohort of patients with adenocarcinoma only covered 10 markers (all cancer: AUC = 0.74 [95% confidence interval: 0.70–0.80]; adenocarcinoma only: AUC = 0.76 [95% confidence interval: 0.70–0.83]). In squamous cell cancer and SCLC, multimarker models did not exceed CD151 as an individual marker in separating patients with cancer from controls. Conclusion: : We have demonstrated exosome protein profiling to be a promising diagnostic tool in lung cancer independently of stage and histological subtype. Multimarker models could make a fair separation of patients, demonstrating the perspectives of exosome protein profiling as a biomarker. … (more)
- Is Part Of:
- Journal of thoracic oncology. Volume 11:Issue 10(2016)
- Journal:
- Journal of thoracic oncology
- Issue:
- Volume 11:Issue 10(2016)
- Issue Display:
- Volume 11, Issue 10 (2016)
- Year:
- 2016
- Volume:
- 11
- Issue:
- 10
- Issue Sort Value:
- 2016-0011-0010-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-10
- Subjects:
- Lung cancer -- Exosomes -- Diagnostic -- EV array
Chest -- Cancer -- Periodicals
Thoracic Neoplasms -- Periodicals
616.99494005 - Journal URLs:
- http://gateway.ovid.com/ovidweb.cgi?T=JS&MODE=ovid&NEWS=n&PAGE=toc&D=ovft&AN=01243894-000000000-00000 ↗
http://gateway.ovid.com/ovidweb.cgi?T=JS&MODE=ovid&PAGE=toc&D=ovft&AN=01243894-200601000-00001 ↗
http://www.sciencedirect.com/science/journal/15560864/ ↗
http://journals.lww.com/pages/default.aspx ↗ - DOI:
- 10.1016/j.jtho.2016.05.034 ↗
- Languages:
- English
- ISSNs:
- 1556-0864
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5069.124000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 808.xml