Abstract
IntroductionKidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite advances in treatment, no specific biomarker is currently in use to guide therapeutic interventions.ObjectivesMajor aim of this work was to perform metabolomic and elemental profiling of human kidney cancer and normal tissue and to evaluate cancer biomarkers.MethodsMetabolic and elemental profiling of tumor and adjacent normal human kidney tissue from 50 patients with kidney cancer was undertaken using three different analytical methods.ResultsFive potential tissue biomarkers of kidney cancer were identified and quantified using with high-resolution nuclear magnetic resonance spectroscopy. The contents of selected chemical elements in tissues was analyzed using inductively coupled plasma optical emission spectrometry. Eleven mass spectral features differentiating between kidney cancer and normal tissues were detected using silver-109 nanoparticle enhanced steel target laser desorption/ionization mass spectrometry.ConclusionsOur results, derived from the combination of ICP-OES, LDI MS and 1H NMR methods, suggest that tissue biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer.
Highlights
Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer
Metabolite concentrations obtained by nuclear magnetic resonance (NMR) following log-transformation and auto-scaling were analyzed with principal component analysis (PCA) to assess whether the patient versus control groups could be separated based on distinct metabolite profiles
This work has demonstrated that value of high-resolution 1H NMR, ICP-OES and 109AgNPET LDI mass spectrometry (MS), along with multivariate statistics to characterize kidney tissue metabolome and metallome differences between tumor and normal tissue of patients suffering from kidney cancer
Summary
Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Objectives Major aim of this work was to perform metabolomic and elemental profiling of human kidney cancer and normal tissue and to evaluate cancer biomarkers. Results Five potential tissue biomarkers of kidney cancer were identified and quantified using with high-resolution nuclear magnetic resonance spectroscopy. Conclusions Our results, derived from the combination of ICP-OES, LDI MS and 1H NMR methods, suggest that tissue biomarkers identified appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer. More than 60% of RCC cases are diagnosed incidentally This tumor is difficult to detect, especially in its early stages, due to the lack of characteristic symptoms including lack of the classic triad of visible haematuria, flank pain and palpable abdominal mass symptoms. The 5-year survival rates of patients with metastatic disease are
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