Differential proteome analysis of tumor-initiating cells

摘要

Pancreatic cancer is one of the most aggressive tumors with the worst survival rate that is less than 5 % within 5 years. Hence, there is a need for better understanding the molecular mechanisms of carcinogenesis and cancer metastasis. Moreover, recent studies have indicated that tumors are initiated by a small set of cells having the ability of self-renewal, differentiated proliferation, and increased expression of sonic hedgehog, a developmental signaling molecule. Those cells are not only highly tumorigenic, but also have a high survival rate after treatment with standardized medical therapy. Consequently, they become a main potential target for diagnosis and therapy. The heterogeneity of cells in the solid tumor tissue, with tumor-initiating cells representing only 0.2 - 0.8 % of the total tumor cell population, constitutes a significant challenge in proteome analysis of tumor-initiating cells. To reduce the enormous expenditure of time for shotgun proteomics employing two-dimensional fractionation, we designed a highly efficient one-dimensional separation scheme hyphenated to high-resolution Orbitrap mass spectrometry. Analysis of the data generated was optimized by application of specialized algorithmic, statistical, and bioinformatic tools.