Projects per year
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.
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 language | English |
|---|---|
| Pages (from-to) | 1622-1633 |
| Number of pages | 12 |
| Journal | British Journal of Cancer |
| Volume | 110 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2014 |
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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- 1 Finished
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Strategic Award: Wellcome Trust Technology Platform
Blow, J. (Investigator), Lamond, A. (Investigator) & Owen-Hughes, T. (Investigator)
1/01/13 → 30/09/18
Project: Research
Profiles
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Nabi, Ghulam
- Cancer Research - Clinical Professor (Teaching and Research) of Surgical Uro-Oncology
Person: Academic