Authors
Gustav Jonsson, Tiago Oliveira, Maura Hofmann, Ursula Lemberger, Karel Stejskal, Gabriela Krššáková, Irma Sakic, Maria Novatchkova, Stefan Mereiter, Gerlinde Grabmann, Thomas Köcher, Rubina Koglgruber, Zeljko Kikic, Sonia Camano Páez, Bárbara Luna Sanchez, Víctor Díez Nicolás, Gerald N Rechberger, Thomas Züllig, Astrid Hagelkruys, Bernhard Englinger, Manuela Schmidinger, Josef M Penninger
Published in
EMBO molecular medicine. Aug 11, 2026. Epub Aug 11, 2026.
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy. Yet, no rapid, non-invasive biomarkers are available for diagnosis or screening. Urine represents an ideal analyte matrix due to its accessibility, low invasiveness, longitudinal sampling, and the kidney's central role in filtration. Here, we integrated proteomic, lipidomic, and metabolomic analyses of urine from ccRCC patients and controls to identify diagnostic biomarkers. Multi-omics profiling revealed urogenital metabolic dysregulation in ccRCC, including increased lipid metabolism, altered mitochondrial respiration signatures, and elevated urinary lipid content. We identified three urinary protein biomarkers: serum amyloid A1 (SAA1), haptoglobin (HP), and lipocalin 15 (LCN15). Using a parallel reaction monitoring mass spectrometry workflow, we developed a rapid and sensitive assay and combined these markers into a diagnostic UrineScore. The UrineScore achieved 0.96 in an area under the receiver operating characteristic curve analysis in the discovery cohort, and 0.95 in an independent validation cohort. Together, these results support the feasibility of multi-omics-guided urinary biomarker discovery and represent a step toward accessible diagnostic platforms for ccRCC.
PMID:
42581140
Bibliographic data and abstract were imported from PubMed on 12 Aug 2026.
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