We have used three profiling methods to characterise proteomic differences between the urine of colon cancer patients and non-cancer controls. Although no peaks were found to be unique to either the cancer patients or controls a number of changes in peak intensity were significantly associated with colon cancer and these, in conjunction with class prediction models, yielded a diagnostic sensitivity of 78% and specificity of 87%. These values are higher than those obtained with serum CEA but not as good as those obtained in similar profiling studies conducted on serum and the number and significance of proteomic changes in urine also appear to be less than in serum [6, 14, 15]. Although the reduction in concentration of abundant serum proteins in urine relative to serum should aid detection of more informative lower abundance species, urine is one step further removed from the tumour than blood and may have a more variable composition.
We find that, although the 3 profiling methods used here are complimentary (Figure 3) the simplest method, MALDI, found the most cancer associated proteomic changes and produced the best single method classifier. Both MALDI-DS and SELDI involve a binding step with selectivity for certain peptides which, by chance, excluded some of the polypeptides of interest. The MALDI-DS data gave marginally better reproducibility than MALDI whereas the SELDI data showed the highest variability of the 3 methods (probably partly due to the concentration of protein at the binding step being sub-optimal when using urine for SELDI) possibly masking some effects of cancer on the urinary proteome. When MFP was applied to all of the significant peaks from the 3 methods, peaks from both the MALDI and MALDI-DS datasets were selected to generate a classifier that performed better than that based on the MALDI data alone (Table 3 and Figure 5).
It is challenging to identify all of the peaks of interest in SELDI/MALDI profiling work for a range of reasons: we attempted to identify the discriminatory peaks with m/z ratios of 1606, 2051 and 5011. The m/z 1606 peak proved difficult to purify or obtain MS/MS data on. The m/z 2051 peak gave good MS/MS data but we were unable to obtain a database match and the m/z 5011 peak, although successfully purified, did not appear to generate identifiable tryptic peptides. Furthermore digestion using Asp-N, Glu-C, Lys-C or Arg-C failed to generate identifiable peptides. However we did successfully identify the polypeptides responsible for discriminatory peaks at m/z 1885, 2193 and 11,750. This is a prerequisite for both the development of alternative assay platforms for candidate biomarkers and for understanding the mechanisms underlying these proteomic changes. The cancer associated proteins that we have identified are hepcidin-20, β2-microglobulin and a 18 residue fragment of the α-subunit of fibrinogen. All 3 are proteins primarily synthesised in the liver and are likely to reflect secondary effects of cancer rather than direct secretion/leakage from the tumour itself. Hepcidin-20, decreased in the urine of cancer patients, is an N-terminally truncated form of the hormone hepcidin-25 which is elevated by iron overload and inflammation . Hepcidin-25 which is involved in iron homeostasis (which may be linked to colorectal cancer ) is not significantly different in the urine of the cancer patients and non-cancer controls although we did find a positive correlation with T stage . The intensities of the peaks corresponding to β2-microglobulin are, on average, elevated in the urine of the colorectal cancer patients. Serum levels of β2-microglobulin are known to be elevated during infection and in certain lymphoid malignancies . We have previously detected β2-microglobulin as slightly increased in the serum of hepatocellular carcinoma and colorectal cancer patients [6, 30]. It is attractive to link the increased urine β2-microglobulin concentration with the elevated serum concentration (although it could also be caused by decrease tubular reabsorbtion). The m/z 1885 peak corresponding to a 18 residue fragment of fibrinogen is present in non-cancer controls, but has an increased intensity in the colorectal cancer patients. Several proteomic profiling studies have now associated proteolytic fragments of abundant serum proteins with malignant disease [38, 39]. Thus the increase in the level of fibrinogen fragment, presumably generated in the blood, may arise from increased proteolytic activity or increased total fibrinogen levels (elevated fibrinogen has been reported in the serum of colorectal cancer patients ).
As SELDI and MALDI are not quantitative techniques we have used alternative assays to test whether the cancer associated changes in intensity of the MALDI/SELDI peaks of the 3 identified polypeptides truly reflect changes in concentration. Antibodies specific for the 1885 Da fragment of fibrinogen and hepcidin-20 do not exist so we spiked stable isotope labelled versions of these peptides in to samples prior to MALDI mass spectrometry. These internal standards should behave in an identical manner to the endogenous peptides during sample preparation and ionisation and enable peptide concentration determination regardless of inter-sample influences on the mass spectra. β2-microglobulin was determined by ELISA. For all 3 polypeptides a strong positive correlation (r>0.5) was found between MALDI/SELDI peak height and concentration indicating that peak heights can, in many cases, be used as an indicator of relative concentration. For one of the three polypeptides, hepcidin-20, the association with cancer lost statistical significance when the concentration was determined relative to the stable isotope standard. This, perhaps unsurprisingly, suggests that statistically significant changes in proteomic profiling experiments will not always yield useful biomarkers.
Even with effective screening tools such as faecal occult blood testing, that are now entering routine clinical practice, large numbers of 'false-positive' results will be generated, i.e. the faecal occult blood test is of low specificity and the requisite, more specific follow-up examinations such as colonoscopy represent a significant health care burden. If our preliminary figures for sensitivity can be improved it is conceivable that proteomic analysis of urine might, by identifying those with a low probability of having tumours, permit prioritisation of investigation to those at highest risk. What is more, the detectable cancer associated proteomic changes in urine may compliment those detected in serum  and a combined analysis might improve both sensitivity and specificity for early disease diagnosis.