Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer

Kyoungmi Kim, Sandra L. Taylor, Sheila Ganti, Lining Guo, Michael V. Osier, Robert H Weiss

Research output: Contribution to journalArticle

92 Scopus citations

Abstract

Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy.

Original languageEnglish (US)
Pages (from-to)293-303
Number of pages11
JournalOMICS A Journal of Integrative Biology
Volume15
Issue number5
DOIs
StatePublished - May 1 2011

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Genetics
  • Molecular Biology
  • Molecular Medicine

Fingerprint Dive into the research topics of 'Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer'. Together they form a unique fingerprint.

  • Cite this