title: Metabolic changes in rat serum after administration of suberoylanilide hydroxamic acid and discriminated by SVM.
abstract: Suberoylanilide hydroxamic acid (SAHA) exerts marked anticancer effects via promotion of apoptosis, cell cycle arrest, and prevention of oncogene expression. In this study, serum metabolomics and artificial intelligence recognition were used to investigate SAHA toxicity. Forty rats (220 ± 20 g) were randomly divided into control and three SAHA groups (low, medium, and high); the experimental groups were treated with 12.3, 24.5, or 49.0 mg kg-1SAHA once a day via intragastric administration. After 7 days, blood samples from the four groups were collected and analyzed by gas chromatography-mass spectrometry, and pathological changes in the liver were examined using microscopy. The results showed that increased levels of urea, oleic acid, and glutaconic acid were the most significant indicators of toxicity. Octadecanoic acid, pentadecanoic acid, glycerol, propanoic acid, and uric acid levels were lower in the high SAHA group. Microscopic observation revealed no obvious damage to the liver. Based on these data, a support vector machine (SVM) discrimination model was established that recognized the metabolic changes in the three SAHA groups and the control group with 100% accuracy. In conclusion, the main toxicity caused by SAHA was due to excessive metabolism of saturated fatty acids, which could be recognized by an SVM model.
authors.affiliation: 1 The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou City, China.
authors.forename: J
authors.initials: J
authors.lastname: Yu
authors.affiliation: 2 Department of Anesthesiology, Critical Care and Pain Medicine, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, China.
authors.forename: H
authors.initials: H
authors.lastname: Wu
authors.affiliation: 3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
authors.forename: Z
authors.initials: Z
authors.lastname: Lin
authors.affiliation: 3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
authors.forename: K
authors.initials: K
authors.lastname: Su
authors.affiliation: 3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
authors.forename: J
authors.initials: J
authors.lastname: Zhang
authors.affiliation: 3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
authors.forename: F
authors.initials: F
authors.lastname: Sun
authors.affiliation: 3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
authors.forename: X
authors.initials: X
authors.lastname: Wang
authors.affiliation: 3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
authors.forename: C
authors.initials: C
authors.lastname: Wen
authors.affiliation: 1 The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou City, China.
authors.forename: H
authors.initials: H
authors.lastname: Cao
authors.affiliation: 4 Department of Pharmacy, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
authors.forename: L
authors.initials: L
authors.lastname: Hu
mesh_terms: D000818:Animals; D004305:Dose-Response Relationship, Drug; D006877:Hydroxamic Acids / Q000633:toxicity*; D055432:Metabolomics; D011897:Random Allocation; D051381:Rats; D017207:Rats, Sprague-Dawley; D060388:Support Vector Machine; D000077337:Vorinostat
chemical_list: D006877:Hydroxamic Acids; D000077337:Vorinostat
keywords: Metabolomics; SVM; rat; suberoylanilide hydroxamic acid