Most of the currently used cancer biomarkers were discovered following development of novel analytical techniques, such as immunological assays and the monoclonal antibody technology. It was then found that these molecules were elevated in biological fluids from cancer patients in comparison to normal subjects. Many cancer biomarkers were discovered by immunizing animals with extracts from tumors or cancer cell lines, and then screening for monoclonal antibodies that recognize "cancer-associated" antigens. More recently, and with the completion of the Human Genome Project, many researchers hypothesized that the best cancer biomarkers will likely be secreted proteins (21); about 20–25% of all cell proteins are secreted. However, this is not an absolute requirement because a number of classical cancer biomarkers (e.g. CEA, Her2-neu) are cell membrane-bound, but their extracellular domains are shed into the circulation. Other groups, including our own, are using bioinformatics, such as digital differential display and in silico Northern blotting, to compare gene expression between normal and cancerous tissues to identify overexpressed genes (22). Although one of the prevailing hypotheses in new biomarker discovery is that the most promising biomarkers should be overexpressed proteins, this is not generally true for some of the best known cancer biomarkers such as PSA (23). Overexpressed genes are now identified experimentally by using microarrays. Some of these genes have been proposed as candidate cancer biomarkers (24–26). Despite this reasonable hypothesis, very few cancer biomarkers have been discovered by using this approach (26, 27). We followed another approach, in which we postulated that if a molecule is already a known-cancer biomarker, members of the same family of genes/proteins may also constitute novel biomarkers. We have since shown that kallikreins, a group of serine proteases with high homology at both the DNA and protein levels (this family includes PSA), are candidate biomarkers for ovarian, prostate, and breast cancers (28, 29).
Over many years of developing cancer biomarkers, we came to understand that a molecule may become a practical serological biomarker if it has certain characteristics, i.e. it is a secreted or shed protein and has the ability to diffuse into the circulation during tumor development and progression, through either angiogenesis or invasion of surrounding tissues and vasculature by cancer cells. Preferably, such proteins should be stable (not degraded) and not bound to inhibitors that could interfere with their measurement. The experience with the classical biomarkers has taught us many lessons on the dynamic relationships between the patient and biological phenomena related to biomarkers such as appearance in the circulation, cleavage, binding to serum proteins, degradation, modification, elimination half-life, etc. In this review, I will use PSA as an example to compare what we know from such molecules with mass spectrometric approaches for diagnostics.