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There has been an impressive emergence of mass spectrometry based technologies applied toward the study of proteins. Equally notable is the rapid adaptation of these technologies to biomedical approaches in the realm of clinical proteomics. Concerted efforts toward the elucidation of the proteomes of organ sites or specific disease state are proliferating and from these efforts come the promise of better diagnostics/prognostics and therapeutic intervention. Prostate cancer has been a focus of many such studies with the promise of improved care to patients via biomarkers derived from these proteomic approaches. The newer technologies provide higher analytical capabilities, employ automated liquid handling systems, fractionation techniques and bioinformatics tools for greater sensitivity and resolving power, more robust and higher throughput sample processing, and greater confidence in analytical results. In this prospects, we summarize the proteomic technologies applied to date in prostate cancer, along with their respective advantages and disadvantages. The development of newer proteomic strategies for use in future applications is also discussed.

With the aim to detect candidate malignant primitive progenitor populations, we modified an original alkaline phosphatase (ALP) stem cell detection method based on the identification of alkaline phosphatase fluorescent cells in combination with flow cytometry immunophenotyping. Over a period of one year, we have been using this technique to study its activity in patients with leukemia and lymphoma, showing that changes in the alkaline phosphatase levels can be used to detect rare populations of highly refractory malignant cells. By screening different blood cancers, we have observed that this activity is not always restricted to CD34+ leukemic cells, and can be overexpressed in CD34 negative leukemia. We have verified that this method gives accurate and reproducible measurements and our preliminary results suggest that CD34+/ALP high cells appear to sustain leukemogenesis over time.

A novel approach to integrating quantitative description of cell aggregation dynamics and proteome analysis was used to identify early epigenetic transformations in cultured human breast cells. A transition from a power law to an exponential decay in MCF-7 cell aggregation was found and correlated with a down-regulation of calreticulin expression. A similar transition was not observed in the aggregation dynamics of MCF-10 nor in MDA-MB-231 cells, although they also exhibit changes in their global protein expression patterns during their prolonged culture. The down-regulation of calreticulin in MCF-7 cells may be associated with decreased cell–cell and cell–matrix adhesiveness and triggering the dynamic transition observed in their aggregation. The simple operational model presented here may be a relevant tool for uncovering fundamental early steps involved in neoplastic transformation in culture and carcinogenesis in vivo.