Renal cell carcinoma (RCC) is the most prevalent and lethal malignancy of the kidney. Despite all the efforts made, no tissue biomarker is currently used in the clinical management of patients with kidney cancer. A search for possible biomarkers in urine for clear cell renal cell carcinoma (ccRCC) has been conducted. Non-targeted metabolomic analyses were performed on paired samples of surgically removed renal cancer and normal tissue, as well as on urine samples. Extracts were analyzed by liquid chromatography/high-resolution mass spectrometry (LC-HRMS). Hydroxybutyrylcarnitine, decanoylcarnitine, propanoylcarnitine, carnitine, dodecanoylcarnitine, and norepinephrine sulfate were found in much higher concentrations in both cancer tissues (compared with the paired normal tissue) and in urine of cancer patients (compared with control urine). In contrast, riboflavin and acetylaspartylglutamate (NAAG) were present at significantly higher concentrations both in normal kidney tissue as well as in urine samples of healthy persons. This preliminary study resulted in the identification of several compounds that may be considered potential clear cell renal carcinoma biomarkers.
Graphical abstractPLS-DA plot based on LC-MS data for normal and cancer human tissue samples. The aim of this work was the identification of up- and downregulated compounds that could potentially serve as renal cancer biomarkers.
Electronic supplementary materialThe online version of this article (10.1007/s00216-018-1059-x) contains supplementary material, which is available to authorized users.
Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite all the efforts made, no serum-specific biomarker is currently used in the clinical management of patients with this tumor. In this study, comprehensive high-resolution proton nuclear magnetic resonance spectroscopy (
1
H NMR) and silver-109 nanoparticle-enhanced steel target laser desorption/ionization mass spectrometry (
109
AgNPET LDI MS) approaches were conducted, in conjunction with multivariate data analysis, to discriminate the global serum metabolic profiles of kidney cancer (
n
= 50) and healthy volunteers (
n
= 49). Eight potential biomarkers have been identified using
1
H NMR metabolomics and nine mass spectral features which differed significantly (
p
< 0.05) between kidney cancer patients and healthy volunteers, as observed by LDI MS. A partial least squares discriminant analysis (OPLS-DA) model generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from cancerous samples (Q
2
> 0.7), area under the receiver operative characteristic curve (ROC) AUC > 0.96. Compared with healthy human serum, kidney cancer serum had higher levels of glucose and lower levels of choline, glycerol, glycine, lactate, leucine,
myo
-inositol, and 1-methylhistidine. Analysis of differences between these metabolite levels in patients with different types and grades of kidney cancer was undertaken. Our results, derived from the combination of LDI MS and
1
H NMR methods, suggest that serum biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer.
Graphical abstract
Electronic supplementary material
The online version of this article (10.1007/s00216-020-02807-1) contains supplementary material, which is available to authorized users.
A new methodology applicable for both high-resolution laser desorption/ionization mass spectrometry and mass spectrometry imaging of amino acids is presented. The matrix-assisted laser desorption ionization-type target containing monoisotopic cationic Ag nanoparticles ( AgNPs) was used for rapid mass spectrometry measurements of 11 amino acids of different chemical properties. Amino acids were directly tested in 100,000-fold concentration change conditions ranging from 100 μg/mL to 1 ng/mL which equates to 50 ng to 500 fg of amino acid per measurement spot. Limit of detection values obtained suggest that presented method/target system is among the fastest and most sensitive ones in laser mass spectrometry. Mass spectrometry imaging of spots of human blood plasma spiked with amino acids showed their surface distribution allowing optimization of quantitative measurements.
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