Cancer is a genetically and clinically diverse disease, and patients with cancers of similar clinical stages often exhibit different responses to treatment. To develop optimized therapeutic strategies, improved characterization of cancer phenotypes has long been desired. Electrophoresis is a fundamental technique to separate and quantify various molecules, and it allows molecular profiling of tumor tissues and body fluids. By combining the molecular profiles of electrophoresis and clinicopathological data, it is possible to identify key molecules that regulate malignant features and influence clinical outcomes. Such molecules should be considered as biomarker candidates for the characterization of cancer cells. Since these molecules are likely to be involved in the molecular pathways for metastasis, recurrence, and resistance to treatments, they can also be used as therapeutic targets. With an aim to develop biomarkers for characterizing cancer phenotypes, we created global protein expression profiles by electrophoresis and attempted to identify proteins that influenced clinical outcomes. A novel electrophoresis method such as two-dimensional difference gel electrophoresis (2D-DIGE) enables quantitative, reproducible, sensitive, high throughput, and exhaustive global protein expression profiling. Using 2D-DIGE and a large scale clinical sample set with a detailed clinicopathological data set, we identified proteins that influenced metastasis after surgery and induced resistance to standard chemotherapy. Another approach to identify these proteins is by using antibodies, wherein protein expression profiles are created by western blotting using a large-scale antibody library. Hence, we conclude that electrophoresis is a powerful tool for developing cancer biomarkers.
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