Cancer proteomics expression proteomic studies

Many diseases are characterized by the expression of specific proteins1 in some cases, malignant cells yield unique protein profiles when total cellular protein extracts are analyzed by proteomic methods such as two-dimensional gel electrophoresis or matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS).2 High-throughput proteomic studies may be useful to differentiate normal cells from cancer cells, to identify and define the use of biomarkers for specific cancers, and to characterize the clinical course of disease. Proteomics can also be used to isolate and characterize potential drug targets and to evaluate the efficacy of treatments. 

The term proteome means the total protein complement of a genome, and pro-teomics means the analysis for proteome. The combination of two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS) is a proteomic method of high-throughput analysis of protein expression. By using this 2-DE and MS, proteomic studies have identified many proteins that may be involved in the pathogenic mechanism of cancers. These studies analyzed cancer cell lines, as well as cancer tissues or serum from patients. 

Many proteomic studies have identified diverse proteins that may be involved in the pathogenic mechanism of disease and which may be disease markers. Most of the applications use expression proteomics to determine expression profiles of proteins in cells and tissues in normal or disease states. In the present study, we analyzed protein expression in cancer tissue samples and corresponding non-cancerous tissue samples to find proteins that might be involved in carcinogenesis or pathogenesis. 

It is within the context of finding products that have an effect on human health that a study has been published regarding the gene expression of prostate cancer cells treated with pomegranate fruit juice (70) where a comparative proteomics study provided insights for prostate cancer evolution. The involvement of pomegranate fruit products in the molecular mechanism of inducing prostate cancer cell apoptosis has been evidenced. Thus, a possible... 

As of today, expression proteomic studies are available for all common human cancers and some rare tumors. 

Reymond MA, Steinert R, Kahne T, Sagynaliev E, Allal AS, Lippert H. Expression and functional proteomics studies in colorectal cancer. Pathol Res Pract 2004 200(2) 119-127. Review. 

Zhang, D., Tai, L.K., Wong, L.L., Chiu, L.L., Sethi, S.K. and Koay, E.S., Proteomic study reveals that proteins involved in metabolic and detoxification pathways are highly expressed in HER-2/neu-positive breast cancer. Mol. Cell Proteomics, 4(11), 1686-1696 (2005). 

In the present study, we analyzed proteome in hepatocellular carcinoma (HCC), esophageal cancer, and pancreatic cancer tissues. We identified many proteins whose expression in cancer tissues was different from corresponding non-cancerous tissues by using 2-DE and MS. Furthermore, we identified some auto-antibodies reacting to proteins in HCC cancer tissues. In this chapter, we will describe the method, our experimental result, and reports from other researchers about proteomic analysis in cancer patients. 

In this study, a machine learning model system was developed to classify cell line chemosensitivity exclusively based on proteomic profiling. Using reverse-phase protein lysate microarrays, protein expression levels were measured by 52 antibodies in a panel of 60 human cancer cell (NCI-60) lines. The model system combined several well-known algorithms, including Random forests, Relief, and the nearest neighbor methods, to construct the protein expression-based chemosensitivity classifiers. 

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