This study aimed to evaluate the potential of plasma-based proton magnetic resonance spectroscopy (1H-MRS) for non-invasive discrimination between clear cell renal cell carcinoma (ccRCC), benign renal masses (angiomyolipoma and oncocytoma) and healthy controls by identifying disease-specific metabolic signatures.
We performed 1H-MRS metabolic profiling of human plasma samples from 30 individuals divided into three cohorts: ccRCC (n = 10, all biopsy-confirmed, nonmetastatic T3 tumours), benign renal masses (n = 10, angiomyolipoma or oncocytoma) and healthy controls (n = 10). Multivariate and univariate statistical analyses were conducted to evaluate group separation and identify differentially abundant metabolites. Metabolite set enrichment analysis was used to identify significantly perturbed metabolic pathways associated with each state.
We observed altered metabolic plasma profiles in ccRCC patients compared to normal controls and benign patients. We detected significantly increased concentrations of hydroxybutyrate (normal vs. ccRCC, p = 0.008), glucose (normal vs. ccRCC, p = 0.020), (benign vs. ccRCC, p = 0.009), creatinine (normal vs. ccRCC, p = 0.015), (benign vs. ccRCC, p = 0.014) in ccRCC patients' plasma compared to normal controls and benign renal masses plasma. We also found that acetate and myoinositol were significantly elevated in benign (normal vs. benign, p = 0.0002) and ccRCC (normal vs. ccRCC, p = 0.0001) plasma compared to normal controls plasma. Pathway enrichment analysis revealed alterations in fatty acid biosynthesis, amino acid metabolism, nitrogen handling and glycolysis-related pathways consistent with ccRCC-associated metabolic reprogramming.
This pilot study demonstrates that plasma 1H-MRS can detect metabolic alterations associated with ccRCC and benign renal masses. These findings support the feasibility of using metabolomic profiling as a non-invasive diagnostic tool for renal mass characterization. Larger validation studies are warranted to confirm diagnostic accuracy and explore utility in clinical decision-making.
BJUI compass. 2026 Jun 16*** epublish ***
Raj Kumar Sharma, Meiyappan Solaiyappan, Ardit Feinaj, Stephan Brönimann, Nirmish Singla, Zaver M Bhujwalla, Yasser Ged
Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science The Johns Hopkins University School of Medicine Baltimore Maryland USA., Sidney Kimmel Comprehensive Cancer Center The Johns Hopkins University School of Medicine Baltimore Maryland USA., Brady Urologic Institute The Johns Hopkins University School of Medicine Baltimore Maryland USA.