Liotta and colleagues are now substituting the original Ciphergen instrumentation with more sophisticated mass spectrometers of higher resolution. While these instruments do provide improved mass accuracy determination and more complicated spectra, they will not solve the problems outlined in this review regarding diagnostics, because the sample preparation procedures are still based on Ciphergen protein chips. Nevertheless, the results of the published and of the newer methods will require careful external validation by different laboratories. Clinical trials are now underway to examine if these methods are robust enough and suitable for clinical use. Until the external validation data become available, the method should not be used for clinical care.
NORMAL VERSUS ABNORMAL SERUM PROTEOMIC PATTERNS
One explanation for the published data is that the differences in serum proteomic patterns between controls and patients are due to the presence of cancer. Another explanation would be that these differences are not due to the presence of cancer but to a variety of unknown confounding factors. Possible confounders include: sample collection, processing and storage, patient selection and individual habits (e.g. gender, age, ethnicity, exercise, menopausal status, nutritional preferences, drugs, non-cancer diseases, etc.), inappropriate statistical design and/or analysis methods, machine instability, and variable chip performance. The effects of most of these parameters on serum proteomic patterns have not been studied.
Usually, classical tumor markers are evaluated by clinicians by using numerical and easy-to-understand cutoff points (64). All studies using SELDI-TOF technology for diagnostics compare "disease patterns" to "normal patterns." In practice, a normal pattern needs to be generated and used as reference to which the patient pattern will be compared. But how could such a "normal pattern" be generated when the reference group and the testing group are likely to be heterogeneous for the factors described above? It is likely that this "normal pattern" will be influenced by numerous parameters, including diseases different from the one that is being diagnosed. Because SELDI-TOF is a qualitative technique, data interpretation by comparing patterns may prove to be a daunting task.