Volatile exometabolome profiling of human renal cell carcinoma cell lines for biomarker discovery

Renal Cell Carcinoma (RCC) constitutes approximately 90-95% of all kidney neoplasms and is the second most lethal urological cancer. Current diagnostic techniques rely on imaging techniques and an invasive procedure (biopsy) is always required for histopathologic confirmation of malignancy. For these reasons, the identification of accurate biomarkers to develop faster, less invasive and more sophisticated diagnostic techniques is of utmost importance. Metabolomics has been widely applied in cancer biomarker discovery arising from the fact that cancer cells are metabolically reprogrammed to control the energy required by the rapid growth and development of the tumor, producing a specific “metabolic signature”. Aim: To evaluate the potential of volatile organic compounds (VOCs) and volatile carbonyl compounds (VCCs) to discriminate the exometabolome of RCC from non-tumoral cell lines, and two different histological subtypes (clear cell and papillary RCC) in both metastatic and non-metastatic stages. Methods: Headspace-solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS)-based metabolomics was applied for the volatile profiling of culture medium of five different tumoral cell lines, namely three clear cell (769-P, 786-O and Caki-1) and two papillary RCC (Caki-2 and ACHN), and one non-tumoral cell line (HK-2). Results: Multivariate and univariate analysis unveiled a panel of metabolites responsible for the discrimination between each RCC cell line vs. non-tumoral cells, metastatic vs. non-metastatic and clear cell vs. papillary RCC cell lines, mostly belonging to alcohols, aldehydes, alkanes and ketones classes. Some metabolites were found similarly altered for all RCC cell lines compared to the non-tumoral, while others unveiled specificity for each RCC cell line. Discussion/Conclusion: The volatile exometabolome signature of RCC cells can provide candidate biomarkers for the development of a volatile sensor-based approach for non-invasive diagnosis of RCC in urine.