Proteome analysis promises to be valuable for the identification of tissue and serum biomarkers associated with human malignancies. In addition, proteome technologies offer the opportunity to analyze protein expression profiles and to analyze the activity of signaling pathways. Many published proteomic studies of human tumor tissue are associated with weaknesses in tumor representativity, sample contamination by nontumor cells and serum proteins. Studies often include a moderate number of tumors which may not be representative of clinical materials. It is therefore very important that biomarkers identified by proteomics are validated in representative tumor materials by other techniques, such as immunohistochemistry. Proteome technologies can be used to identify disease markers in human serum. Tumor derived proteins are present at nanomolar to picomolar concentrations in cancer patient sera, 10(6)-10(9)-fold lower than albumin, and will give rise to correspondingly smaller spots/peaks in protein separations. This leads to the need to prefractionate serum samples before analysis. Despite various pitfalls, proteomic analysis is a promising approach to the identification of biomarkers, and for generation of protein expression profiles that can be analyzed by artificial learning methods for improved diagnosis of human malignancy. Recent advances in the field of proteomic analysis of human tumors are summarized in the present review.