Comparative untargeted proteomic analysis of ADME proteins and tumor antigens for tumor cell lines.
10.1016/j.apsb.2017.10.002
- Author:
Xiaomei GU
1
;
Qing XIAO
2
;
Qian RUAN
1
;
Yuezhong SHU
1
;
Ashok DONGRE
2
;
Ramaswamy IYER
1
;
W Griffith HUMPHREYS
1
;
Yurong LAI
1
Author Information
1. Pharmaceutical Candidate Optimization, Bristol-Myers Squibb Company, Princeton, NJ 08540, USA.
2. Genomics, Bristol-Myers Squibb Company, Princeton, NJ 08540, USA.
- Publication Type:Journal Article
- Keywords:
ABC transporters;
Cancer cell lines;
Cytochrome P450;
SLC transporters;
Tumor-associated membrane proteins;
Untargeted quantitative proteomics
- From:
Acta Pharmaceutica Sinica B
2018;8(2):252-260
- CountryChina
- Language:English
-
Abstract:
In the present study, total membrane proteins from tumor cell lines including HepG2, Hep3B2, H226, Ovcar3 and N87 were extracted and digested with LysC and trypsin. The resulting peptide lysate were pre-fractionated and subjected to untargeted quantitative proteomics analysis using a high resolution mass spectrometer. The mass spectra were processed by the MaxQuant and the protein abundances were estimated using total peak area (TPA) method. A total of 6037 proteins were identified, and the analysis resulted in the identification of 2647 membrane proteins. Of those, tumor antigens and absorption, metabolism, disposition and elimination (ADME) proteins including UDP-glucuronosyltransferase, cytochrome P450, solute carriers and ATP-binding cassette transporters were detected and disclosed significant variations among the cell lines. The principal component analysis was performed for the cluster of cell lines. The results demonstrated that H226 is closely related with N87, while Hep3B2 aligned with HepG2. The protein cluster of Ovcar3 was apart from that of other cell lines investigated. By providing for the first time quantitative untargeted proteomics analysis, the results delineated the expression profiles of membrane proteins. These findings provided a useful resource for selecting targets of choice for anticancer therapy through advancing data obtained from preclinical tumor cell line models to clinical outcomes.
