No abstract

SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.

Currently, no suitable biomarker for the early detection or follow-up of renal cell carcinoma (RCC) is available. We aimed to validate previously reported potential serum biomarkers for RCC obtained with Surface Enhanced Laser Desorption Ionisation-Time of Flight Mass Spectrometry (SELDI-TOF MS) in our laboratory using distinct patient populations. Two sets of sera from RCC patients and healthy controls (HC) were gathered from different institutes and analysed according to published procedures. The first set (40 RCC, 32 HC) consisted of mainly presurgery samples from patients with disease stages I-IV. The second set (26 RCC, 27 HC) were mostly sera from patients with stage-IV disease, drawn after nephrectomy. Only the increased expression of the previously found serum amyloid-a (SAA) peak cluster could be validated in a similar RCC patient subset in both our populations in two independent analyses. It was seen both in earlyand late-stage disease and in pre-and postsurgery samples. These results were also confirmed by ELISA. Other previously identified biomarker candidates (mass-to-charge ratio's (m/z) 3900, 4107, 4153, 5352 and 5987) proved difficult to reproduce upon duplicate analysis. Modification of the analytical protocol for these markers resulted in their detection, but we did not achieve satisfactory classification of patients and controls with these alleged biomarkers in any of our two sample sets. Instead, two new peaks (m/z 4289 and 8151) were identified with better performance (sensitivity and specificity B65-90%) for separating patients from controls in the first sample set. Concluding, only the SAA peak cluster was validated as a robust RCC biomarker candidate, which is present in a specific subset of these patients, regardless of disease stage or nephrectomy status. In addition, two new peaks were seen which might prove useful as biomarkers, provided these are validated in new populations. Renal cell carcinoma (RCC) is difficult to diagnose at early stages due to a lack of clear clinical symptoms. When symptoms do occur, about 30% of patients already have metastatic disease. In addition, a similar part of patients with resection of localised disease will have a recurrence. 1 Therefore, a need remains for reliable markers for diagnosis and follow-up of RCC, preferably in easy-accessible body fluids. Surface Enhanced Laser Desorption Ionisation-Time of Flight Mass Spectrometry (SELDI-TOF MS) 2,3 is being increasingly used to search for new and better tumour markers in (serum) protein profiles, for example, for ovarian, 4 breast, 5 prostate 6 and colorectal cancer. 7 Its appeal lies in the ease with which a multitude of samples can be analysed with a minimum of sample preparation in a single SELDI-TOF MS analysis. Indeed, SELDI-TOF MS has also been performed to identify biomarker proteins for early detection of RCC. Two studies describe protein profiling of serum with SELDI-TOF MS. 8,9 Tolson et al 8 reported a peak cluster at a mass-to-charge ratio (m/z) of approximately 11 000 from serum amyloid a-...

Background: Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.

Many proteins have been proposed as potential biomarkers for breast cancer. Yet, validation of their discriminative value using quantitative methods has scarcely been performed. In this study, we investigated the discriminative value of six peptides that were previously proposed to be generated by breast cancer specific exoproteases: bradykinin, des-Arg(9)-bradykinin, Hyp(3)-bradykinin, and fragments of fibrinogen alpha-chain (Fib-alpha ([605-629])), complement component 4a (C4a ([1337-1350])), and interalpha trypsin inhibitor heavy chain 4 (ITIH4 ([666-687])). Their absolute serum concentrations were measured with a completely validated liquid chromatography-tandem mass spectrometric assay (LC-MS/MS) and compared between 62 newly diagnosed breast cancer patients and 62 controls matched for age and sample storage duration. Both ITIH4 ([666-687]) and des-Arg(9)-bradykinin showed statistically significantly higher median concentrations in breast cancer samples than in matched control samples. Additionally, we analyzed serum samples collected after surgical removal of the tumor, in which median ITIH4 ([666-687]) and des-Arg(9)-bradykinin concentrations were significantly decreased and not statistically significantly different from concentrations in the controls anymore. In a combined analysis, ITIH4 (666-687]) and des-Arg(9)-bradykinin independently contributed to the discrimination between cases and controls. In this study, we confirmed that the exoprotease breakdown peptides, ITIH4 (666-687]) and des-Arg(9)-bradykinin, differed between breast cancer cases and controls, supporting the potential of degradome markers for the diagnosis of breast cancer.

Proteomics and subsequent validation yielded two novel prognostic markers and survival models which improved prediction of OS in mRCC patients over commonly used risk models. Implementation of these models has the potential to improve current risk stratification, although prospective validation will still be necessary.

Sample handling can have a profound effect on serum protein profiles, challenging results obtained with archived sera under non‐standardized sample collection. Here, we evaluate the influence of variations in sample handling on previous serum protein profiles for colorectal cancer (CRC) (Engwegen et al.,. World J. Gastroenterol. 2006, 12, 1536–1544). Sera were prospectively obtained from individuals with an indication for colonoscopy (n = 150: 65 controls, 52 adenomatous polyps, 29 CRC, 4 unknown), as well as from normal volunteers (n = 8). Protein profiles were acquired by SELDI‐TOF MS on CM10 chips at pH 5. We assessed the influence of storage temperature, type of collection tube, coagulation temperature and freeze‐thaw cycles on the serum protein profile. Several peptides occurred only in samples stored at –20°C, indicating proteolytic degradation during storage. One was a previous CRC biomarker candidate, an N‐terminal albumin fragment (m/z 3087), and two others complement C3f and a fragment thereof (m/z 2022 and 1863). Overall differences in protein profiles were also seen for different collection tubes, coagulation temperature and freeze‐thaw cycles. However, three of five of our previously defined CRC biomarker candidates are stable to variations in the sample handling protocol, justifying their further validation in prospective studies.

Colorectal cancer (CRC) is the second most common cause of cancer-related death in Europe and its prognosis is largely dependent on stage at diagnosis. Currently, there are no suitable tumour markers for early detection of CRC. In a retrospective study we previously found discriminative CRC serum protein profiles with surface enhanced laser desorption ionisation—time of flight mass spectrometry (SELDI-TOF MS). We now aimed at prospective validation of these profiles. Additionally, we assessed their applicability for follow-up after surgery and investigated tissue protein profiles of patients with CRC and adenomatous polyps (AP). Serum and tissue samples were collected from patients without known malignancy with an indication for colonoscopy and patients with AP and CRC during colonoscopy. Serum samples of controls (CON; n = 359), patients with AP (n = 177) and CRC (n = 73), as well as tissue samples from AP (n = 52) and CRC (n = 47) were analysed as described previously. Peak intensities were compared by non-parametric testing. Discriminative power of differentially expressed proteins was assessed with support vector machines (SVM). We confirmed the decreased serum levels of apolipoprotein C-1 in CRC in the current population. No differences were observed between CON and AP. Apolipoprotein C-I levels did not change significantly within 1 month post-surgery, although a gradual return to normal levels was observed. Several proteins differed between AP and CRC tissue, among which a peak with similar mass as apolipoprotein C-1. This peak was increased in CRC compared to AP. Although we prospectively validated the serum decrease of apolipoprotein C-1 in CRC, serum protein profiles did not yield SVM classifiers with suitable sensitivity and specificity for classification of our patient groups.