Integrative Metabolomic and Transcriptomic Analysis for the Study of Bladder Cancer

[EN] Metabolism reprogramming is considered a hallmark of cancer. The study of bladder cancer (BC) metabolism could be the key to developing new strategies for diagnosis and therapy. This work aimed to identify tissue and urinary metabolic signatures as biomarkers of BC and get further insight into...

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Detalles Bibliográficos
Autores: Loras, Alba, Suárez-Cabrera, Cristian, Quintás, Guillermo, Paramio, Jesús M., Gil Grau, Salvador, Ruiz-Cerdá, José Luis, Martínez-Bisbal, M.Carmen|||0000-0002-8526-4413, Martínez-Máñez, Ramón|||0000-0001-5873-9674
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/193434
Acceso en línea:https://riunet.upv.es/handle/10251/193434
Access Level:acceso abierto
Palabra clave:Cancer biomarkers
Bladder cancer
Metabolomics
Transcriptomics
Metabolic pathways
Tumor metabolome
Cancer metabolic reprogramming
QUIMICA INORGANICA
Descripción
Sumario:[EN] Metabolism reprogramming is considered a hallmark of cancer. The study of bladder cancer (BC) metabolism could be the key to developing new strategies for diagnosis and therapy. This work aimed to identify tissue and urinary metabolic signatures as biomarkers of BC and get further insight into BC tumor biology through the study of gene-metabolite networks and the integration of metabolomics and transcriptomics data. BC and control tissue samples (n = 44) from the same patients were analyzed by High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance and microarrays techniques. Besides, urinary profiling study (n = 35) was performed in the same patients to identify a metabolomic profile, linked with BC tissue hallmarks, as a potential non-invasive approach for BC diagnosis. The metabolic profile allowed for the classification of BC tissue samples with a sensitivity and specificity of 100%. The most discriminant metabolites for BC tissue samples reflected alterations in amino acids, glutathione, and taurine metabolic pathways. Transcriptomic data supported metabolomic results and revealed a predominant downregulation of metabolic genes belonging to phosphorylative oxidation, tricarboxylic acid cycle, and amino acid metabolism. The urinary profiling study showed a relation with taurine and other amino acids perturbed pathways observed in BC tissue samples, and classified BC from non-tumor urine samples with good sensitivities (91%) and specificities (77%). This urinary profile could be used as a non-invasive tool for BC diagnosis and follow-up.