Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

Atrih, A., Mudaliar, M. A. V. , Zakikhani, P., Lamont, D. J., Huang, J. T.-J., Bray, S. E., Barton, G., Fleming, S. and Nabi, G. (2014) Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling. British Journal of Cancer, 110(6), pp. 1622-1633. (doi: 10.1038/bjc.2014.24)

Abstract

<b>Background:</b>  Proteomics-based approaches for biomarker discovery are promising strategies used in cancer research. We present state-of-art label-free quantitative proteomics method to assess proteome of renal cell carcinoma (RCC) compared with noncancer renal tissues.<p></p> <b>Methods:</b>  Fresh frozen tissue samples from eight primary RCC lesions and autologous adjacent normal renal tissues were obtained from surgically resected tumour-bearing kidneys. Proteins were extracted by complete solubilisation of tissues using filter-aided sample preparation (FASP) method. Trypsin digested proteins were analysed using quantitative label-free proteomics approach followed by data interpretation and pathways analysis.<p></p> <b>Results:</b>  A total of 1761 proteins were identified and quantified with high confidence (MASCOT ion score threshold of 35 and P-value <0.05). Of these, 596 proteins were identified as differentially expressed between cancer and noncancer tissues. Two upregulated proteins in tumour samples (adipose differentiation-related protein and Coronin 1A) were further validated by immunohistochemistry. Pathway analysis using IPA, KOBAS 2.0, DAVID functional annotation and FLink tools showed enrichment of many cancer-related biological processes and pathways such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways.<p></p> <b>Conclusions:<b>  Our study identified a number of differentially expressed proteins and pathways using label-free proteomics approach in RCC compared with normal tissue samples. Two proteins validated in this study are the focus of on-going research in a large cohort of patients.<p></p>

• Item Type: Articles
• Keywords: Label-free quantitative proteomics, Translational Research, Kidney Cancer
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Mudaliar, Dr Manikhandan
• Authors: Atrih, A., Mudaliar, M. A. V., Zakikhani, P., Lamont, D. J., Huang, J. T.-J., Bray, S. E., Barton, G., Fleming, S., and Nabi, G.
• Subjects: R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
• College/School: College of Medical Veterinary and Life Sciences
• Research Group: Glasgow Polyomics
• Journal Name: British Journal of Cancer
• Publisher: Nature Publishing Group
• ISSN: 0007-0920
• ISSN (Online): 1532-1827