Relative protein quantification and accessible biology in lung tumor proteomes from four LC‐MS/MS discovery platforms. Issue 6 (March 2017)
- Record Type:
- Journal Article
- Title:
- Relative protein quantification and accessible biology in lung tumor proteomes from four LC‐MS/MS discovery platforms. Issue 6 (March 2017)
- Main Title:
- Relative protein quantification and accessible biology in lung tumor proteomes from four LC‐MS/MS discovery platforms
- Authors:
- Stewart, Paul A.
Fang, Bin
Slebos, Robbert J. C.
Zhang, Guolin
Borne, Adam L.
Fellows, Katherine
Teer, Jamie K.
Chen, Y. Ann
Welsh, Eric
Eschrich, Steven A.
Haura, Eric B.
Koomen, John M. - Other Names:
- Pandey Akhilesh guestEditor.
- Abstract:
- Abstract : Discovery proteomics experiments include many options for sample preparation and MS data acquisition, which are capable of creating datasets for quantifying thousands of proteins. To define a strategy that would produce a dataset with sufficient content while optimizing required resources, we compared (1) single‐sample LC‐MS/MS with data‐dependent acquisition to single‐sample LC‐MS/MS with data‐independent acquisition and (2) peptide fractionation with label‐free (LF) quantification to peptide fractionation with relative quantification of chemically labeled peptides (sixplex tandem mass tags (TMT)). These strategies were applied to the same set of four frozen lung squamous cell carcinomas and four adjacent tissues, and the overall outcomes of each experiment were assessed. We identified 6656 unique protein groups with LF, 5535 using TMT, 3409 proteins from single‐sample analysis with data‐independent acquisition, and 2219 proteins from single‐sample analysis with data‐dependent acquisition. Pathway analysis indicated the number of proteins per pathway was proportional to the total protein identifications from each method, suggesting limited biological bias between experiments. The results suggest the use of single‐sample experiments as a rapid tissue assessment tool and digestion quality control or as a technique to maximize output from limited samples and use of TMT or LF quantification as methods for larger amounts of tumor tissue with the selection being drivenAbstract : Discovery proteomics experiments include many options for sample preparation and MS data acquisition, which are capable of creating datasets for quantifying thousands of proteins. To define a strategy that would produce a dataset with sufficient content while optimizing required resources, we compared (1) single‐sample LC‐MS/MS with data‐dependent acquisition to single‐sample LC‐MS/MS with data‐independent acquisition and (2) peptide fractionation with label‐free (LF) quantification to peptide fractionation with relative quantification of chemically labeled peptides (sixplex tandem mass tags (TMT)). These strategies were applied to the same set of four frozen lung squamous cell carcinomas and four adjacent tissues, and the overall outcomes of each experiment were assessed. We identified 6656 unique protein groups with LF, 5535 using TMT, 3409 proteins from single‐sample analysis with data‐independent acquisition, and 2219 proteins from single‐sample analysis with data‐dependent acquisition. Pathway analysis indicated the number of proteins per pathway was proportional to the total protein identifications from each method, suggesting limited biological bias between experiments. The results suggest the use of single‐sample experiments as a rapid tissue assessment tool and digestion quality control or as a technique to maximize output from limited samples and use of TMT or LF quantification as methods for larger amounts of tumor tissue with the selection being driven mainly by instrument time limitations. Data are available via ProteomeXchange with identifiers PXD004682, PXD004683, PXD004684, and PXD005733. … (more)
- Is Part Of:
- Proteomics. Volume 17:Issue 6(2017)
- Journal:
- Proteomics
- Issue:
- Volume 17:Issue 6(2017)
- Issue Display:
- Volume 17, Issue 6 (2017)
- Year:
- 2017
- Volume:
- 17
- Issue:
- 6
- Issue Sort Value:
- 2017-0017-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2017-03
- Subjects:
- Data‐independent acquisition -- Discovery proteomics -- Label‐free quantification -- Lung squamous cell carcinoma -- TMT
Proteins -- Separation -- Periodicals
Bioinformatics -- Periodicals
Proteomics -- Periodicals
Genomes -- Periodicals
Molecular genetics -- Periodicals
572.605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1615-9861 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/pmic.201600300 ↗
- Languages:
- English
- ISSNs:
- 1615-9853
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6936.178000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 618.xml