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Tumor Biology

, Volume 35, Issue 3, pp 1833–1846 | Cite as

Identification and validation of dysregulated metabolic pathways in metastatic renal cell carcinoma

  • Nicole M. A. White
  • Daniel W. Newsted
  • Olena Masui
  • Alexander D. Romaschin
  • K. W. Michael Siu
  • George M. Yousef
Research Article

Abstract

Metastatic renal cell carcinoma (mRCC) is a devastating disease with a 5-year survival rate of approximately 9 % and low response to chemotherapy and radiotherapy. Targeted therapies have slightly improved patient survival, but are only effective in a small subset of patients, who eventually develop resistance. A better understanding of pathways contributing to tumor progression and metastasis will allow for the development of novel targeted therapies and accurate prognostic markers. We performed extensive bioinformatics coupled with experimental validation on proteins dysregulated in mRCC. Gene ontology analysis showed that many proteins are involved in oxidation reduction, metabolic processes, and signal transduction. Pathway analysis showed metabolic pathways are altered in mRCC including glycolysis and pyruvate metabolism, the citric acid cycle, and the pentose phosphate pathway. RT-qPCR analysis showed that genes involved in the citric acid cycle were downregulated in metastatic RCC while genes of the pentose phosphate pathway were overexpressed. Protein–protein interaction analysis showed that most of the 198 proteins altered in mRCC clustered together and many were involved in glycolysis and pyruvate metabolism. We identified 29 reported regions of chromosomal aberrations in metastatic disease that correlate with the direction of protein dysregulation in mRCC. Furthermore, 36 proteins dysregulated in mRCC are predicted to be targets of metastasis-related miRNAs. A more comprehensive understanding of the pathways dysregulated in metastasis can be useful for the development of new therapies and novel prognostic markers. Also, multileveled analyses provide a unique “snapshot” of the molecular “environment” in RCC with prognostic and therapeutic implications.

Keywords

Renal cell carcinoma Proteomics Metastasis Pathway analysis Protein–protein interactions Bioinformatics Personalized medicine miRNA Tumor markers Citric acid cycle Glucose metabolism Pentose phosphate pathway 

Notes

Acknowledgments

GMY is supported by grants from the Canadian Cancer Society (grant #20185), Prostate Cancer Canada (grant #2010-555), Ministry of Research and Innovation of the Government of Ontario, and the Kidney Foundation of Canada. NMA White is supported through fellowships from the Cancer Research Society and the Canadian Institutes of Health Research. Dr. Yousef is supported by grants from the Canadian Institute of Health Research (CIHR) (grant# 268936) as well.

Supplementary material

13277_2013_1245_MOESM1_ESM.ppt (558 kb)
ESM 1 Protein–protein interaction analysis using a random list of proteins showed that a random set of unrelated proteins did not cluster together (PPT 558 kb)
13277_2013_1245_MOESM2_ESM.xls (218 kb)
ESM 2 XLS 218 kb

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Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2013

Authors and Affiliations

  • Nicole M. A. White
    • 1
    • 2
  • Daniel W. Newsted
    • 1
  • Olena Masui
    • 3
  • Alexander D. Romaschin
    • 2
  • K. W. Michael Siu
    • 3
  • George M. Yousef
    • 1
    • 2
  1. 1.Department of Laboratory Medicine and the Keenan Research CentreLi Ka Shing Knowledge Institute of St. Michael’s HospitalTorontoCanada
  2. 2.Department of Laboratory Medicine and PathobiologyUniversity of TorontoTorontoCanada
  3. 3.Department of Chemistry and Centre for Research in Mass SpectrometryYork UniversityTorontoCanada

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