Quantitative Proteomics in Development of Disease Protein Biomarkers - Proteomic and Metabolomic Approaches to Biomarker Discovery

Biology Reference

In-Depth Information

18 O-labeled

clinical researchers readily using quantitative

proteomics to develop new protein biomarkers

for human disease. However, human sample

types vary and samples are heterogeneous. The

best practice for analyzing these complex pro-

teome samples is to closely collaborate with dedi-

cated proteomic specialists or developed core

facilities, in order to improve the con

reference-based quantitative

proteomics. J Proteome Res 2010;

“

universal

”

:4779 e 89.

9. Qian W-J, Liu T, Petyuk VA, et al. Large-scale multi-

plexed quantitative discovery proteomics enabled by

the use of an

18 O-labeled

“

universal

”

reference

:290 e 9.

10. Petritis BO, Qian WJ, Camp 2nd DG, et al. A simple

procedure for effective quenching of trypsin activity and

prevention of 18 O-labeling back-exchange. J Proteome Res

2009;

sample. J Proteome Res 2009;

dence in

discovered biomarker candidates and select the

right candidates for validation. MS-based

biomarker analysis has the

:2157 e 63.

11. Lopez-Ferrer D, Hixson KK, Smallwood H, et al.

Evaluation of a high-intensity focused ultrasound-

immobilized trypsin digestion and 18 O-labeling

method for quantitative proteomics. Anal Chem 2009;

flexibility, speed,

and cost advantages. However, innovation and

development of simple and automated sample

preparation devices are essential to protein

biomarker applications of MS in the clinical

setting.

:6272 e 7.

12. Bezstarosti K, Ghamari A, Grosveld FG, et al. Differen-

tial proteomics based on 18 O-labeling to determine the

cyclin dependent kinase 9 interactome. J Proteome Res

2010;

:4464 e 75.

13. Mortensen P, Gouw JW, Olsen JV, et al. MSQuant, an

open source platform for mass spectrometry-based

quantitative proteomics. J Proteome Res 2010;

Acknowledgments

Research support was provided by the Cystic Fibrosis

Foundation and the National Cancer Institute of the National

Institutes of Health.

:393 e 403.

14. Ye X, Luke BT, Johann Jr DJ, et al. Optimized method

for computing (18)O/(16)O ratios of differentially

stable-isotope labeled peptides in the context of post-

digestion (18)O exchange/labeling. Anal Chem 2010;

:5878 e 86.

15. Dasari S, Wilmarth PA, Reddy AP, et al. Quanti

ca-

tion of isotopically overlapping deamidated and

18 O-labeled peptides using isotopic envelope mixture

modeling. J Proteome Res 2009;

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Proteomic and Metabolomic Approaches to Biomarker Discovery

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