BERKELEY, CA (UroToday.com) - The main goal of clinical proteomics is the improvement of the status quo in medical practice. For this purpose, discovery and further validation of novel biomarkers has to be driven by clearly defined clinical needs and based on a specific disease context. Bladder cancer is one of the most common cancer types of the genitourinary system. The vast majority of diagnosed cases originates from the transitional epithelium and does not invade the muscle layer (non-muscle invasive bladder cancer). However, approximately one fourth of cases exhibit muscle-invasive phenotype characterized by poor prognosis and limited treatment options. In addition, the high recurrence rate imposes life-long monitoring of the patients after initial therapy. To date, the “gold standard” for diagnosis and monitoring of disease is invasive cystoscopy. Therefore, the research focus is on the development of accurate non-invasive tests for bladder cancer early diagnosis, detection or prognosis of recurrence and disease progression.[5, 6, 7] Since bladder cancer can be a highly heterogeneous disease, a single biomarker approach may be of limited potential. Alternatively, the combination of multiple markers into a biomarker panel could present increased performance in terms of sensitivity and specificity.
Figure 1. The overview on the development of a biomarker peptide panel as can be established by the application of CE-MS platform. Figure is adapted from Latosinska et al.
Development of novel biomarkers/biomarker panels is a multistep process, including initial discovery, verification in an independent cohort, and validation in an appropriately powered clinical study. At the initial discovery phase, mass spectrometry-based approaches have been widely applied, including LC-MS,[9, 10] CE-MS,[11, 12, 13, 14, 15] or 2DE-MS.[16, 17] Among these analytical platforms, CE-MS appears especially advantageous, as it can be applied for discovery, as well as for further validation of the initial findings, and subsequent clinical application. CE-MS is characterized by robustness and relatively short time of the analysis (< 1h), CE-MS platform repeatability, reproducibility and inter-laboratory variability have been well described, and, as such, collectively CE-MS is applicable for large scale studies and routine patient management.
This platform has been widely applied to investigate molecular changes in the context of genitourinary and renal disorders.[11, 12, 13, 15] In the case of urothelial carcinoma, an initial study by Theodorescu et al. established a 22-polypeptide panel of diagnostic potential. This panel was developed and tested in mostly advanced stage disease providing sensitivity of 100% and specificity of 73% in disease detection. Schiffer et al. extended the study to target specifically prediction of the muscle invasive phenotype. A panel consisting of 4 peptides presented moderate performance with 57% specificity and 81% sensitivity. Based on the data from these two studies, as well as recent additional sample analysis (collectively corresponding to 557 samples: 258 cases and 299 controls, Frantzi et al. unpublished data), a classifier enabling detection of bladder cancer based on urinary peptides was recently further refined to result in 95% sensitivity and 71% specificity in the training set upon complete take-one-out cross-validation. Prominent biomarkers in this classifier are collagen fragments, fibrinogen fragments, complement C3, membrane-associated progesterone receptor component 1, neurosecretory protein VGF, alpha-1-antitrypsin, sodium/potassium-transporting ATPase subunit gamma, xylosyltransferase 1, apolipoprotein AI, endothelial protein C receptor, osteopontin, transthyretin, and uromodulin peptides. The performance of this classifier is currently assessed in studies, including >1000 patients in the context of BCMolMED (http://bcmolmed.org/) and TransBioBC (http://transbiobc.org/).CE-MS has been applied for the investigation of peptides and low molecular weight proteins as biomarkers derived from several body fluids, especially urine. This involves a multistep process that includes appropriate sample preparation, data acquisition, statistical analysis, and establishment of putative biomarker panels.[20, 21] A schematic representation of the workflow is shown in Figure 1. In brief, CE-MS analysis results in characterization of the peptides based on the CE migration time, signal intensity, and molecular mass. Candidate biomarkers can be sequenced and identified by employing CE-MS/MS and LC-MS/MS. Subsequently, appropriate bioinformatics tools and algorithms are applied to enable CE-MS data assessment, peptide list extraction, and calibration using internal standard peptides. The obtained data are statistically evaluated, taking advantage of a large database of different disease cohorts available for in depth assessment of the biomarkers. Upon selection of the discriminatory biomarker peptides, a high-dimensional classifier is generated using support vector machines (SVM).[21, 24] The classifier is subsequently verified and, if appropriate, validated in independent cohorts and appropriate clinical trials. Based on the above, the performance of proteomics-based classifier is compared to the techniques routinely applied in clinical practice, e.g. in the case of bladder cancer, cytology and cystoscopy aiming at improvement of current management status.
Model calculations indicate that a biomarker-based non-invasive classifier with 95% sensitivity and 70% specificity can result in a decrease in the average number of cystoscopies per patient from 2.12 to 0.56. More importantly, along the same lines, a biomarker classifier for patient surveillance with the above performance could reduce the average number of cystoscopies from 4.37 to 1.34 in the low-risk group of bladder cancer recurrence patients. The above estimations are calculated based on the EORTC tables (European Organisation for Research and Treatment of Cancer) (Flühe et al. unpublished data).
The preliminary data available to date and the modeling approaches outlined above indicate that the implementation of a CE-MS-based non-invasive test for bladder cancer detection can be expected, once the findings are verified in the currently ongoing study. This non-invasive approach holds the promise of improving patient compliance and bringing significant improvement in patient management.
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Agnieszka Latosinska,a Maria Frantzi,b Leif Flühe,b and Harald Mischakb, c as part of Beyond the Abstract on UroToday.com. This initiative offers a method of publishing for the professional urology community. Authors are given an opportunity to expand on the circumstances, limitations etc... of their research by referencing the published abstract.
aBiomedical Research Foundation Academy of Athens, Biotechnology Division, Athens, Greece
bMosaiques Diagnostics GmbH, Hannover, Germany
cBHF Glasgow Cardiovascular Research Centre University of Glasgow, Glasgow, United Kingdom