A comparative study of data‐dependent acquisition and data‐independent acquisition in proteomics analysis of clinical lung cancer tissues constrained by blood contamination. Issue 3 (28th December 2021)
- Record Type:
- Journal Article
- Title:
- A comparative study of data‐dependent acquisition and data‐independent acquisition in proteomics analysis of clinical lung cancer tissues constrained by blood contamination. Issue 3 (28th December 2021)
- Main Title:
- A comparative study of data‐dependent acquisition and data‐independent acquisition in proteomics analysis of clinical lung cancer tissues constrained by blood contamination
- Authors:
- Su, Tao
Zhong, Yi
Zeng, Weibiao
Zhang, Yong
Wang, Shisheng
Cheng, Jingqiu
Yang, Hao
Wei, Yiping
Gong, Meng - Abstract:
- Abstract: Proteomics analysis is often troubled by high‐abundance proteins in samples such as plasma. However, many surgical tissue samples inevitably have got contaminated with blood before cryopreservation. Selection of an appropriate method to minimize the effect of high‐abundance proteins is important for proteomics analysis of blood contaminated tissues. Here, we investigated and compared the abilities of data‐independent acquisition (DIA) and data‐dependent acquisition (DDA) strategies for the proteomics analysis of blood contaminated clinical tissue samples. Twelve pairs of carcinoma and para‐carcinoma tissue samples from lung cancer patients were used for proteomics assays separately by DIA and DDA, and the blood contamination level in samples was evaluated by contamination index (CI). Compared with the DDA strategy, DIA in whole exhibited much better analytical capabilities in proteomics analysis of these samples with more identified protein groups and a higher discovery of differential proteins. With CI value increasing, whether DIA or DDA showed decreasing analysis ability. However, for samples with high CI values, the DIA strategy still shows acceptable analytical capability and indicates better blood pollution resistance than the DDA strategy. Our results implied that for clinical tissue samples, particularly for those contaminated with blood, DIA strategy should be a preferred method in proteomics studies.
- Is Part Of:
- Proteomics. Volume 16:Issue 3(2022)
- Journal:
- Proteomics
- Issue:
- Volume 16:Issue 3(2022)
- Issue Display:
- Volume 16, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 16
- Issue:
- 3
- Issue Sort Value:
- 2022-0016-0003-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-12-28
- Subjects:
- blood contamination -- contamination index -- data‐dependent acquisition -- data‐independent acquisition -- differential proteins -- lung cancer -- proteomics -- surgical tissue samples
Proteomics -- Periodicals
572.605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1862-8354 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/prca.202000099 ↗
- Languages:
- English
- ISSNs:
- 1862-8346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6936.178500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21351.xml