title: Large-scale profiling of metabolic dysregulation in ovarian cancer.
abstract: Ovarian cancer is the leading cause of death in gynecologic malignancies. Profiling of endogenous metabolites has potential to identify changes caused by cancer and provide inspiring insights into cancer metabolism. To systematically investigate ovarian cancer metabolism, we performed metabolic profiling of 448 plasma samples related to epithelial ovarian cancer (EOC) based on ultra-performance liquid chromatography mass spectrometry in both positive and negative modes. These unbiased metabolomic profiles could well distinguish EOC from benign ovarian tumor (BOT) and uterine fibroid (UF). Fifty-three metabolites were identified as specific biomarkers for EOC, and this is the first report of piperine, 3-indolepropionic acid, 5-hydroxyindoleacetaldehyde and hydroxyphenyllactate as metabolic biomarkers of EOC. The AUC values of these metabolites for discriminating EOC from BOT/UF and early-stage EOC from BOT/UF were 0.9100/0.9428 and 0.8385/0.8624, respectively. Meanwhile, our metabolites were able to distinguish early-stage EOC from late-stage EOC with an AUC of 0.8801. Importantly, analysis of dysregulated metabolic pathways extends our current understanding of EOC metabolism. Metabolic pathways in EOC patients are mainly characterized by abnormal phospholipid metabolism, altered l-tryptophan catabolism, aggressive fatty acid β-oxidation and aberrant metabolism of piperidine derivatives. Together, these metabolic pathways provide a foundation to support cancer development and progression. In conclusion, our large-scale plasma metabolomics study yielded fundamental insights into dysregulated metabolism in ovarian cancer, which could facilitate clinical diagnosis, therapy, prognosis and shed new lights on ovarian cancer pathogenesis.
authors.affiliation: Department of Epidemiology and Biostatistics, Public Health School, Harbin Medical University, Harbin, People's Republic of China.
authors.forename: Chaofu
authors.initials: C
authors.lastname: Ke
authors.forename: Yan
authors.initials: Y
authors.lastname: Hou
authors.forename: Haiyu
authors.initials: H
authors.lastname: Zhang
authors.forename: Lijun
authors.initials: L
authors.lastname: Fan
authors.forename: Tingting
authors.initials: T
authors.lastname: Ge
authors.forename: Bing
authors.initials: B
authors.lastname: Guo
authors.forename: Fan
authors.initials: F
authors.lastname: Zhang
authors.forename: Kai
authors.initials: K
authors.lastname: Yang
authors.forename: Jingtao
authors.initials: J
authors.lastname: Wang
authors.forename: Ge
authors.initials: G
authors.lastname: Lou
authors.forename: Kang
authors.initials: K
authors.lastname: Li
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000077216:Carcinoma, Ovarian Epithelial; D005260:Female; D006801:Humans; D055432:Metabolomics; D008875:Middle Aged; D009367:Neoplasm Staging; D009375:Neoplasms, Glandular and Epithelial / Q000378:metabolism* / Q000473:pathology; D010051:Ovarian Neoplasms / Q000378:metabolism* / Q000473:pathology; D014364:Tryptophan / Q000378:metabolism
chemical_list: D014364:Tryptophan
keywords: epithelial ovarian cancer; metabolic dysregulation; metabolomics; plasma