Jiménez, C.R.

Knol, J.C.

Oudgenoeg, G.

Pham, T.V.

Piersma, S.R.

Repositorio Institucional de la Universidad de Córdoba

S6. Biomarker Discovery and Validation Plenary Lecture  PL25 99  LABEL-FREE MASS SPECTROMETRY-BASED PROTEOMICS FOR BIOMARKER DISCOVERY AND VALIDATION IN TISSUES AND BIOFLUIDS S. R. Piersma(1), T. V. Pham(1), G. Oudgenoeg(1), J. C. Knol(1), C. R. Jiménez(1) (1)OncoProteomics Laboratory, Dept. Medical Oncology, VU University Medical Center, Amsterdam Label-free mass spectrometry-based proteomics applied to biomarker-rich sub-cellular compartments in (pre)-clinical samples and proximal biofluids is emerging as a powerful, versatile approach for discovery of tissue-derived biomarkers with close association to the disease.  Our label-free workflow is based on 1D gel electrophoresis in gradient mini-gels, in gel-digestion, nanoLC-MS/MS, and spectral counting-based quantitation. We have shown that this workflow is reproducible and outperforms other commonly used workflows in terms of the total number of identified proteins and the total number of reproducible identified proteins [1].  Analyzing spectral count data generated in these studies is, however, not straightforward as commonly used techniques for genomics data analysis are not suitable. We have shown that the beta-binomial test performs favourably in comparison with other methods on several datasets in terms of both true detection rate and false positive rate [2]. This test is now routinely used in all our projects for significance analysis and available for down-load (www.oncoproteomics.nl).  Over the course of the past 4 years, using analyses of technical and biological replicates in feasibility studies, we have shown for different types of (pre)clinical samples that spectral counting provides a reliable strategy for label-free protein quantitation. This applies to samples that were obtained via a relatively simple workflow (cancer cell secretome, [1]) as well as for samples obtained via more complex workflows (depleted cerebrospinal fluid, [3], nuclear fractions, [4]).  For colon cancer, promising imageable biomarker candidates have been discovered and confirmed in tissue microarrays and SRM-MS-based validation of selected nuclear proteins and secretome differential proteins as serum and stool-based markers is underway.   Plenary Lecture S6. Biomarker Discovery and ValidationPL25 100   [1] Piersma SR, Fiedler U, Span S, Lingnau A, Pham T, Hoffmann S, Kubbutat MH, Jimenez CR. Workflow comparison for in-depth, quantitative secretome proteomics for cancer biomarker discovery: Method evaluation, differential analysis and verification in serum. J Proteome Res. 2010 Apr 5;9(4):1913-22 [2] Pham TV, Piersma SR, Warmoes M, Jimenez CR. On the beta binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics. Bioinformatics. 2010, Feb 1;26(3):363-9 [3] Fratantoni, SA., Piersma, SR., Jimenez, CR. Comparison of the performance of two affinity depletion spin filters for quantitative proteomics of cerebrospinal fluid: Evaluation of sensitivity and reproducibility of CSF analysis using GeLC-MS/MS and spectral counting. Prot. Clin. Applic. 2010, 4, 613-617 [4] Albrethsen J, Knol JC, Piersma S, Pham TV, de Wit M, Mongera S, Carvalho B, Verheul HM, Fijneman RJ, Meijer GA, Jimenez CR. Sub-nuclear proteomics in colorectal cancer: Identification of proteins enriched in the nuclear matrix fraction and regulation in adenoma to carcinoma progression. Mol Cell Proteomics. 2010 May;9(5):988-1005.  

Label-free mass spectrometry-based proteomics for biomarker discovery and validation in tissues and biofluids

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Repositorio Institucional de la Universidad de Córdoba