LC-MS-Based Plasma Metabolomics and Lipidomics Analyses for Differential Diagnosis of Bladder Cancer and Renal Cell Carcinoma - Liu, Xiang; Zhang, Mingxin; Cheng, Xiangming; Liu, Xiaoyan; Sun, Haidan; Guo, Zhengguang; Li, Jing; Tang, Xiaoyue; Wang, Zhan; Sun, Wei; Zhang, Yushi; Ji, Zhigang (Frontiers in Oncology, 2020)
Bladder cancer (BC) and Renal carcinoma(RC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography—mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC=0.99). Then, separation was observed between the BC and RC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898 and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.