#1798 Plasma metabolomics analysis of renal dysfunction in patients undergoing immune checkpoint inhibitor treatment

Abstract Background and Aims Immune checkpoint inhibitors (ICIs) have demonstrated remarkable efficacy in cancer treatment. However, their associated immune-related adverse events, particularly renal dysfunction remain a significant concern. The pathophysiology of ICI-associated renal impairment is still not fully understood, and there is a lack of specific, non-invasive biomarkers for diagnosing this condition. This study aims to analyze blood samples from patients with ICI-related renal dysfunction using metabolomics, with the goal of identifying metabolic biomarkers that could aid in diagnosis and provide new insights for clinical management. Method The study collected plasma samples from 38 patients with pan-cancer who had received ICI treatment, yielding a total of 76 samples. Patients were divided into two groups based on changes in estimated glomerular filtration rate (eGFR) following two consecutive ICIs treatments: the Yang group (n = 18, 36 samples) and the Yin group (n = 20, 40 samples). Plasma metabolomics analysis was performed using ultra-high-performance liquid chromatography-mass spectrometry. Differential metabolites were identified using T-tests, analysis of variance (ANOVA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). These metabolites were then structurally characterized by mass spectrometry and compared with the KEGG pathway database for further analysis. Results Twenty metabolites were identified as differentially expressed metabolites (DEMs) during the onset and progression of ICIs-associated renal impairment. Amino acids, fatty acids, and their analogues were the most prominently regulated metabolites, with dysregulation in amino acid and fatty acid metabolism playing a key role in ICIs-associated renal damage. Data analysis revealed a progressive increase in glutamine, citrulline, valine, histidine, and linoleic acid, while glutamic acid, docosahexaenoic acid, and cis-5-tetradecenoylcarnitine progressively decreased as renal function declined. Conclusion The metabolism of amino acids and fatty acids in vivo is altered with the decline in renal function, serving as relative metabolic biomarkers.