Journal of Glycomics & Lipidomics
Libre accès

Abstrait

Differential proteomics by label-free quantification for early diagnosis and prognosis of cancers

Shama P. Mirza

In the last few years, differential proteomics has gained popularity due to its ability to distinguish proteome of different states by comparative analysis. This has a greater significance in identifying disease vs. healthy condition, and thereby advanced further to the application of early detection, diagnosis and prognosis of diseases using mass spectrometry (MS)-based protein quantification.Several strategies using labeling and label-free approaches have been established for both relative and absolute quantification of proteins. Recent developments in the MS instrumentation, extensive advances in bioinformatics and computing power facilitated protein quantification by label-free methods. Label-free quantification overcomes the expensive and extensive workflows required in the labeling techniques.In our laboratory, we are using a label- free quantification approach called spectral counting for the identification of disease-specific biomarkers for early diagnosis and prognosis of cancers, specifically glioblastomamultiforme (GBM) and endometrial cancer (EC). In this study, tumor biopsies and plasma/serum samples were analyzed by SDS- PAGE for minimizing the complexity of the proteome before analyzing by MS using nanoAquity UPLC-LTQ OrbitrapVelos MS. Data analysis was carried out using SEQUEST algorithm for protein identification and Visualize software for quantification of identified proteins using spectral counting method. In the GBM study, we identified 2214