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Application of ex vivo 1 H NMR metabonomics to the characterization and possible detection of renal cell carcinoma metastases

Journal of Cancer Research and Clinical Oncology(2012)

Cited 66|Views13
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Abstract
Purpose Renal cell carcinoma (RCC) is the most prevalent malignancy of the kidney. Its survival rates are very low since most of patients develop metastases beyond the kidney at the time of diagnosis. Early detection is currently by far the most promising approach to reduce RCC mortality. Metabolic alterations have been suggested to have a crucial role in cancer development. Metabonomics can present a holistic picture of the metabolites alterations and provide biomarkers that could revolutionize disease characterization and detection. Methods Ex vivo 1 H NMR spectra of tumors and the paired adjacent tissues obtained from living patients with RCC were recorded and analyzed using multivariate statistical techniques combined with quantitative statistical analyses. Results In the present study, we showed that the metabonomes of RCC, either with or without metastases, differ markedly from those of their adjacent tissues. Besides, the RCC patients with metastases can be distinctly differentiated from those without metastases. Metabolic perturbations arising from malignant transformations were also systematically characterized. Compared to the adjacent tissues, RCC tumors had elevated levels of lactate, glutamate, pyruvate, glutamine, and creatine, but decreased levels of acetate, malate, and amino acids including valine, alanine, and aspartate. Conclusions Systemic changes in metabolite concentrations are most likely the result of cells switching to glycolysis to maintain energy homeostasis. The results suggest that metabonomics may also facilitate the discovery of novel cancer biomarkers and allows the stratification of tumors under different pathophysiological conditions, which might be a valuable future tool for RCC detection and possibly other cancers.
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Key words
metabonomics,metastases,nmr,renal cell carcinoma
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