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

A. Atrih, M. A. V. Mudaliar, P. Zakikhani, D. J. Lamont, J. T.-J. Huang, S. E. Bray, G. Barton, S. Fleming, G. Nabi (Lead / Corresponding author)

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Abstract

BACKGROUND:
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.
METHODS:
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.
RESULTS:
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.
CONCLUSIONS:
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.
Original languageEnglish
Pages (from-to)1622-1633
Number of pages12
JournalBritish Journal of Cancer
Volume110
Issue number6
DOIs
Publication statusPublished - 2014

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Keywords

  • Aged
  • Aged, 80 and over
  • Carcinoma, Renal Cell
  • Female
  • Humans
  • Kidney Neoplasms
  • Male
  • Mass Spectrometry
  • Middle Aged
  • Neoplasm Proteins
  • Proteomics
  • Signal Transduction
  • Tumor Markers, Biological

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