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)

Research output: Contribution to journalArticle

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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

Fingerprint

Kidney Neoplasms
Tumor Biomarkers
Proteomics
Renal Cell Carcinoma
Proteins
Neoplasms
Kidney
Biological Phenomena
Oxidative Phosphorylation
Glycolysis
Proteome
Research
Trypsin
Biomarkers
Immunohistochemistry
Ions
Amino Acids

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

Cite this

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title = "Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling",
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.",
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author = "A. Atrih and Mudaliar, {M. A. V.} and P. Zakikhani and Lamont, {D. J.} and Huang, {J. T.-J.} and Bray, {S. E.} and G. Barton and S. Fleming and G. Nabi",
year = "2014",
doi = "10.1038/bjc.2014.24",
language = "English",
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pages = "1622--1633",
journal = "British Journal of Cancer",
issn = "0007-0920",
publisher = "Cancer Research UK",
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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. (Lead / Corresponding author).

In: British Journal of Cancer, Vol. 110, No. 6, 2014, p. 1622-1633.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

AU - Atrih, A.

AU - Mudaliar, M. A. V.

AU - Zakikhani, P.

AU - Lamont, D. J.

AU - Huang, J. T.-J.

AU - Bray, S. E.

AU - Barton, G.

AU - Fleming, S.

AU - Nabi, G.

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Aged

KW - Aged, 80 and over

KW - Carcinoma, Renal Cell

KW - Female

KW - Humans

KW - Kidney Neoplasms

KW - Male

KW - Mass Spectrometry

KW - Middle Aged

KW - Neoplasm Proteins

KW - Proteomics

KW - Signal Transduction

KW - Tumor Markers, Biological

U2 - 10.1038/bjc.2014.24

DO - 10.1038/bjc.2014.24

M3 - Article

VL - 110

SP - 1622

EP - 1633

JO - British Journal of Cancer

JF - British Journal of Cancer

SN - 0007-0920

IS - 6

ER -