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Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer
Kyoungmi Kim1, Sandra L Taylor, Sheila Ganti
1Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, California 95616, USA.
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.
Insights
Researchers identified specific urine metabolites, including quinolinate and gentisate, that are significantly altered in kidney cancer patients. These findings could lead to new diagnostic methods for this challenging disease.
Area of Science:
- Metabolomics
- Oncology
- Biochemistry
Background:
- Kidney cancer incidence is rising, often presenting at advanced stages with poor survival.
- Current diagnostic methods rely on imaging, lacking effective screening biofluid markers.
- Metabolomics offers a promising approach to discover novel biomarkers for kidney cancer.
Purpose of the Study:
- To identify differential urinary metabolites in kidney cancer patients using metabolomics.
- To investigate the metabolic pathways associated with identified biomarkers.
- To assess the impact of these metabolites on cancer cell proliferation.
Main Methods:
- Urine samples from kidney cancer patients and controls were analyzed using metabolomics.
- Statistical analysis identified significantly altered metabolites.
- In vitro experiments tested the effect of key metabolites on cancer cell lines.
Main Results:
- Quinolinate, 4-hydroxybenzoate, and gentisate were found to be differentially expressed in kidney cancer patients.
- These metabolites are linked to amino acid, energy metabolism, and the Warburg effect.
- Specific metabolites, including quinolinate and gentisate, influenced cancer cell proliferation in a cell-line-dependent manner.
Conclusions:
- Metabolomic analysis reveals potential urinary biomarkers for kidney cancer diagnosis.
- Identified metabolites provide insights into kidney cancer's metabolic reprogramming.
- Further validation may pave the way for new diagnostic and therapeutic strategies.
