Dataset Information

Comparison of Lung Cancer Proteome Profiles 1: Label Free Quantification

ABSTRACT: The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung, Epithelial Cell

DISEASE(S): Non-small Cell Lung Carcinoma

SUBMITTER: John Koomen

LAB HEAD: John Koomen

PROVIDER: PXD004682 | Pride | 2017-02-16

REPOSITORIES: Pride

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Dataset's files

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			Action	DRS
	20150912_Haura-Pilot_N0294_bRPLC01-1.mzid.gz	Mzid
	20150912_Haura-Pilot_N0294_bRPLC01-1.mzid_20150912_Haura-Pilot_N0294_bRPLC01-1.MGF	Mzid
	20150912_Haura-Pilot_N0294_bRPLC01-1.mzid_20150912_Haura-Pilot_N0294_bRPLC01-1.pride.mgf.gz	Mzid
	20150912_Haura-Pilot_N0294_bRPLC01-1.pride.mztab.gz	Mztab
	20150912_Haura-Pilot_N0294_bRPLC01-1.raw	Raw

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Publications

Relative protein quantification and accessible biology in lung tumor proteomes from four LC-MS/MS discovery platforms.

Stewart Paul A PA Fang Bin B Slebos Robbert J C RJ Zhang Guolin G Borne Adam L AL Fellows Katherine K Teer Jamie K JK Chen Y Ann YA Welsh Eric E Eschrich Steven A SA Haura Eric B EB Koomen John M JM

Proteomics 20170301 6

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 f ...[more]

PMID: 28195392

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