cysteine-glutathione-disulfide and Kidney-Neoplasms

A protocol for harvesting and extracting extracellular metabolites from an in vitro model of human renal cell lines was developed to profile the exometabolome by means of a discovery-based metabolomics approach using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry. Metabolic footprints provided by conditioned media (CM) samples ( n = 66) of two clear cell Renal Cell Carcinoma (ccRCC) cell lines with different genetic backgrounds and a nontumor renal cell line, were compared with the human serum metabolic profile of a pilot cohort ( n = 10) comprised of stage IV ccRCC patients and healthy individuals. Using a cross-validated orthogonal projection to latent structures-discriminant analysis model, a panel of 21 discriminant features selected by iterative multivariate classification, allowed differentiating control from tumor cell lines with 100% specificity, sensitivity, and accuracy. Isoleucine/leucine, phenylalanine, N-lactoyl-leucine, and N-acetyl-phenylalanine, and cysteinegluthatione disulfide (CYSSG) were identified by chemical standards, and hydroxyprolyl-valine was identified with MS and MS/MS experiments. A subset of 9 discriminant features, including the identified metabolites except for CYSSG, produced a fingerprint of classification value that enabled discerning ccRCC patients from healthy individuals. To our knowledge, this is the first time that N-lactoyl-leucine is associated with ccRCC. Results from this study provide a proof of concept that CM can be used as a serum proxy to obtain disease-related metabolic signatures.

Topics: Adult; Aged; Biomarkers, Tumor; Carcinoma, Renal Cell; Case-Control Studies; Cell Line, Tumor; Chromatography, Liquid; Cysteine; Discriminant Analysis; Female; Glutathione; HEK293 Cells; Humans; Kidney Neoplasms; Leucine; Male; Metabolome; Metabolomics; Middle Aged; Neoplasm Staging; Phenylalanine; Pilot Projects; Tandem Mass Spectrometry