Serum Eicosanoids Metabolomics Profile in a Mouse Model of Renal Cell Carcinoma: Predicting the Antitumor Efficacy of Anlotinib - Du, Ping; Xuan, Lingling; Hu, Ting; An, Zhuoling; Liu, Lihong (Frontiers in Immunology, 2022)
Anlotinib (ANL) showed promising efficacy in patients with renal cell cancer (RCC). Here, for the first time, a serum eicosanoids metabolomics profile and pharmacodynamics in a Renca syngeneic mice treated with ANL was performed and integrated using our previous HPLC-MS/MS method and multivariate statistical analysis. The tumor growth inhibition rates of ANL were 39% and 52% for at low (3 mg/kg) and high (6 mg/kg) dose level without obvious toxicity. A total of 15 disturbed metabolites were observed between normal group and model group, and the intrinsic metabolic phenotype alterations had occurred due to the treatment of ANL. A total of 8 potential metabolites from refined partial least squares (PLS) model were considered as potential predictive biomarker for efficacy of ANL, and the DHA held the most outstanding sensitivity and specificity, with area under the receiver operating characteristic curve of 0.88. Collectively, the results of this exploratory study not only provide powerful reference for understanding eicosanoids metabolic reprogramming of ANL but also offer innovation perspective for the development of therapeutic targets and strategies, discovery of predictive biomarkers and determination of effective tumor monitoring approaches.