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Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling
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 sam...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3960606/ https://www.ncbi.nlm.nih.gov/pubmed/24548857 http://dx.doi.org/10.1038/bjc.2014.24 |
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author | Atrih, A Mudaliar, M A V Zakikhani, P Lamont, D J Huang, J T-J Bray, S E Barton, G Fleming, S Nabi, G |
author_facet | Atrih, A Mudaliar, M A V Zakikhani, P Lamont, D J Huang, J T-J Bray, S E Barton, G Fleming, S Nabi, G |
author_sort | Atrih, A |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3960606 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-39606062015-03-18 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 Nabi, G Br J Cancer Molecular Diagnostics 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. Nature Publishing Group 2014-03-18 2014-02-18 /pmc/articles/PMC3960606/ /pubmed/24548857 http://dx.doi.org/10.1038/bjc.2014.24 Text en Copyright © 2014 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/3.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ |
spellingShingle | Molecular Diagnostics Atrih, A Mudaliar, M A V Zakikhani, P Lamont, D J Huang, J T-J Bray, S E Barton, G Fleming, S Nabi, G Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
title | Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
title_full | Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
title_fullStr | Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
title_full_unstemmed | Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
title_short | Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
title_sort | quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling |
topic | Molecular Diagnostics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3960606/ https://www.ncbi.nlm.nih.gov/pubmed/24548857 http://dx.doi.org/10.1038/bjc.2014.24 |
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