4.7 Article

Urinary Volatilomics Unveils a Candidate Biomarker Panel for Noninvasive Detection of Clear Cell Renal Cell Carcinoma

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 20, Issue 6, Pages 3068-3077

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00936

Keywords

clear cell renal cell carcinoma; diagnostic biomarkers; urine; volatilome; gas chromatography-mass spectrometry

Funding

  1. FEDER-Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020-Operacional Programme for Competitiveness and Internationalization (POCI)
  2. Portuguese funds through FCT-Fundacao para a Ciencia e a Tecnologia [POCI-01-0145-FEDER-030388-PTDC/SAUSER/30388/2017]
  3. FCT [SFRH/BD/123012/2016]
  4. project MindGAP by the European Union [BM-1-GEBC-H2020-FETOPEN-20182020]
  5. Fundação para a Ciência e a Tecnologia [SFRH/BD/123012/2016] Funding Source: FCT

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The study utilized urinary volatilome profiling to identify a volatile signature for distinguishing ccRCC patients from controls. Analysis revealed significant differences in 22 volatile metabolites between the two groups, with a six-biomarker panel showing high sensitivity and specificity for ccRCC detection. These findings suggest potential for the development of a bioelectronic sensor based on the dysregulated energy metabolism and enzyme overexpression in ccRCC urinary volatilome signature.
Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer usually associated with asymptomatic development and risk of systemic progression. Hence, reliable molecular biomarkers of ccRCC are needed to provide early and minimally invasive detection. In this study, urinary volatilome profiling of patients diagnosed with ccRCC (n = 75), and cancer-free controls (n = 75), was performed to investigate the presence of a volatile signature characteristic of ccRCC. Volatile organic compounds (VOCs) in general, and more specifically volatile carbonyl compounds (VCCs), present in urine were extracted by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS). Supervised multivariate models showed a good discriminatory power of ccRCC patients from controls in urine. Overall, 22 volatile metabolites were found significantly altered between the two groups, including aldehydes, ketones, aromatic hydrocarbons, and terpenoids. A candidate six-biomarker panel, comprising octanal, 3-methylbutanal, benzaldehyde, 2-furaldehyde, 4-heptanone, and p-cresol, depicted the best performance for ccRCC detection with 83% sensitivity, 79% specificity, and 81% accuracy. Moreover, the ccRCC urinary volatilome signature suggested dysregulation of energy metabolism and overexpression of enzymes associated with carcinogenesis. These findings provide the molecular basis for the fine-tuning of gas-sensing materials for application in the development of a bioelectronic sensor.

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