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• W2954816887 abstract "Abstract Cancer metabolism varies depending on tumor grade. Currently, there is an absence of integration of multi-omics data to predict Bladder cancer (BLCA) survival. We aimed to identify a metabolic signature in high-grade BLCA by integration of unbiased metabolomics, lipidomics and transcriptomics to predict patient survival and to discover novel therapeutic targets. In the current study, using a robust mass spectrometry platform, we conducted global unbiased metabolic and lipid profiling analysis. We identified 518 differential metabolites and 19 lipids of various classes using the NIST MS metabolomics compendium and lipidblast MS/MS libraries, respectively, between low-grade and high-grade BLCA then mapped them to associated genes. Pathway analysis revealed a unique set of biochemical pathways highly deregulated in high-grade BLCA. Integromics analysis identified a molecular gene signature associated with patient poor survival. Importantly, low expression of fatty acid associated enzymes in high-grade tumors was associated with low fatty acid β- oxidation and acyl carnitines in high-grade BLCA and confirmed using tissue microarray. Our key finding is that impaired fatty acid β-oxidation (FAO) by downregulation of fatty acid associate enzymes suggests a crucial role in the progression of low grade to high grade BLCA. Using a metabolic-centered multi-omics based integrative analysis provided a system-level perspective of BLCA that would facilitate the development of novel therapeutics for high-grade BLCA. Note: This abstract was not presented at the meeting. Citation Format: Venkata Rao Vantaku, Jianrong Dong, Chandrashekar R Ambati, Dimuthu Perera, Sri Ramya Donepudi, Chandra Sekhar Amara, Vasanta Putluri, Ravi Shiva Shankar, Matthew J Robertson, Danthasinghe Waduge Badrajee Piyarathna, Mariana Villanueva, Friedrich-Carl von Rundstedt, Balasubramanyam Karanam, Leomar Y Ballester, Martha K. Terris, Seth P. Lerner, Apolo B Andrea, Hugo Villanueva, Andrew Sikora, Yair Lotan, Arun Sreekumar, Cristian Coarfa, Nagireddy Putluri. Multi-omics integration analysis robustly predicts high grade patient survival and identified altered fatty acid metabolism in high grade bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5274." @default.
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• W2954816887 date "2019-07-01" @default.
• W2954816887 modified "2023-09-27" @default.
• W2954816887 title "Abstract 5274: Multi-omics integration analysis robustly predicts high grade patient survival and identified altered fatty acid metabolism in high grade bladder cancer" @default.
• W2954816887 doi "https://doi.org/10.1158/1538-7445.am2019-5274" @default.
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