Integrative Metabolomic and Transcriptomic Analysis for the Study of Bladder Cancer

Autores de IIS La Fe

• Alba Loras Monfort

  Autor

• María Carmen Martínez Bisbal

  Autor

• Guillermo Quintas Soriano

  Autor

• Ramón Martínez Máñez

  Autor

• José Luis Ruiz Cerdá

  Autor

Participantes ajenos a IIS La Fe

• Suárez Cabrera, Cristian
• Paramio, Jesús M.
• GIL, S.

Grupos

• Unidad Mixta de Investigación en Nanomedicina y Sensores

  Leader

  Ramón Martínez Máñez

Abstract

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.

Keywords

• cancer biomarkers; bladder cancer; metabolomics; transcriptomics; metabolic pathways; tumor metabolome; cancer metabolic reprogramming