Metabolic landscape of clear cell renal cell carcinoma and search for metabolites predictive of drug response - Michinobu Ozawa; Sei Naito; Hideki Makinoshima; Hiromi Ito; Atsushi Tsuya; Takafumi Narisawa; Hiroki Fukuhara; Yuki Takai; Masaki Ushijima; Mayu Yagi; Hayato Nishida; Norihiko Tsuchiya (BMC Cancer)
Abstract Background Clear cell renal cell carcinoma (ccRCC) commonly exhibits biallelic inactivation of VHL genes, profoundly impacting intracellular metabolic pathways and utilization of metabolic substrates. The aims of this study were to validate the metabolomic profile previously identified in ccRCC surgical specimens, to construct a metabolic classification in ccRCC, and to exploratorily investigate metabolic biomarkers of systemic therapy response. Materials and methods We first examined the metabolome in 52 paired tumor/normal surgical ccRCC samples, and then compared the metabolites using paired t-test. Unsupervised clustering analysis was done, and the patients were divided into four subgroups. Then tumor grade and transcriptome analyses were compared among the four groups. Finally, to compare the metabolome according to the effect of systemic therapy, we analyzed 9 patients with vascular endothelial growth factor (VEGF)-tyrosine kinase inhibitor (VEGF-TKI) and 11 patients with immune checkpoint blockade (ICB), respectively. Results The upper stream of glycolysis and the pentose phosphate pathway were commonly activated, along with elevated glutamine levels and reduced proteinogenic amino acids (AAs) other than glutamine in ccRCC tissues, consistent with prior findings. Lactate levels, previously reported as elevated, varied across metabolic subgroups. he Metabolic subgroups enriched with high-grade tumors demonstrated lower expression of VEGF pathway-related genes. VEGF-TKI responders showed decreased levels of some fatty acids. ICI responders exhibited reduced levels of tryptophan and hydroquinone. alongside increased levels of pyruvic acid-oxime, 3-hydroxypropinoic acid, and hydroxylamine. Conclusions We validated the landscape of the ccRCC metabolome and identified some metabolites as potential biomarkers for predicting therapeutic response in RCC.