Literature DB >> 32126320

Urine metabolomic analysis in clear cell and papillary renal cell carcinoma: A pilot study.

Julia Oto1, Álvaro Fernández-Pardo1, Marta Roca2, Emma Plana3, Mª José Solmoirago1, José V Sánchez-González4, César D Vera-Donoso4, Manuel Martínez-Sarmiento4, Francisco España1, Silvia Navarro1, Pilar Medina5.   

Abstract

Renal cell carcinoma (RCC) is one of the most lethal type of tumors and is twice more frequent in men than in women. Initial symptoms are unspecific and belated thus increasing mortality. Moreover, current diagnostic and monitoring tools are harmful for the patient and unspecific in low-grade tumors. Therefore, novel minimally-invasive markers are needed to diagnose and monitor RCC patients. Urine represents the ideal sample source of non-invasive biomarkers for RCC. In our study we aimed to identify a urine metabolomic profile characteristic of RCC patients with diagnostic purposes and also to identify a profile with prognostic value. By an UPLC-Q-ToF MS untargeted metabolomic analysis, we compared the metabolomic profile of 23 RCC patients (14 clear cell RCC and 9 papillary RCC) before surgery and that of 23 healthy controls. Additionally, for the first time, we compared the metabolomic profile of these RCC patients pre-nephrectomy and 3 months and one year post-nephrectomy. We identified the dysregulated metabolomic variables by querying their exact mass against those presented in the Metlin and Human Metabolome Database. Next, we experimentally confirmed their identity. Both RCC subtypes showed similar metabolomic patterns at all stages. 51 metabolomic variables were significantly increased in RCC compared to controls and, among them, 4 were selected as potential discriminant metabolites between groups. We could experimentally confirm the identity of p-cresol glucuronide thus describing for the first time an increase in this metabolite in urine of RCC patients (fold change = 2.922, P = .012). Additionally, we confirmed that no metabolomic differences occur 3 months post-nephrectomy in RRC, while 188 variables were significantly increased one year post-nephrectomy. Of the 15 most discriminant metabolomic variables, we could experimentally confirm the identity of isobutyryl-l-carnitine (fold change = 2.098, P = .004) and l-proline betaine (fold change = 3.328, P = .004), for the first time. In summary, we have identified urine p-cresol glucuronide as potential diagnostic marker for RCC and isobutyryl-l-carnitine and l-proline betaine as potential prognostic markers. When confirmed in an independent cohort of RCC patients, these markers may improve the diagnosis and monitoring of RCC patients thus reducing current harmful diagnostic procedures. SIGNIFICANCE: The high-radiation dose of current imaging techniques available to diagnose and monitor renal cell carcinoma (RCC) are harmful for the patient and unspecific in low-grade tumors. Our untargeted metabolomic analysis carried out in urine samples from RCC patients and healthy individual reveals p-cresol glucuronide as potential diagnostic marker for RCC. Additionally, the analysis of RCC urine samples one year post-nephrectomy reveals isobutyryl-l-carnitine and l-proline betaine as potential prognostic markers. These novel non-invasive urine biomarkers may improve RCC management thus reducing the use of current harmful diagnostic techniques.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarker; Metabolomics; Renal cell carcinoma; Urine

Mesh:

Substances:

Year:  2020        PMID: 32126320     DOI: 10.1016/j.jprot.2020.103723

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  6 in total

Review 1.  LC-MS metabolomics of urine reveals distinct profiles for non-muscle-invasive and muscle-invasive bladder cancer.

Authors:  Julia Oto; Álvaro Fernández-Pardo; Marta Roca; Emma Plana; Fernando Cana; Raquel Herranz; Javier Pérez-Ardavín; César David Vera-Donoso; Manuel Martínez-Sarmiento; Pilar Medina
Journal:  World J Urol       Date:  2022-09-04       Impact factor: 3.661

2.  Molecular signature of renal cell carcinoma by means of a multiplatform metabolomics analysis.

Authors:  Marta Kordalewska; Renata Wawrzyniak; Julia Jacyna; Joanna Godzień; Ángeles López Gonzálves; Joanna Raczak-Gutknecht; Marcin Markuszewski; Piotr Gutknecht; Marcin Matuszewski; Janusz Siebert; Coral Barbas; Michał J Markuszewski
Journal:  Biochem Biophys Rep       Date:  2022-08-04

3.  Urine metabolomics analysis of sleep quality in deep-underground miners: A pilot study.

Authors:  Qiao Wen; Jing Zhou; Xiaoru Sun; Tengfei Ma; Yilin Liu; Yike Xie; Ling Wang; Juan Cheng; Jirui Wen; Jiang Wu; Jian Zou; Shixi Liu; Jifeng Liu
Journal:  Front Public Health       Date:  2022-08-19

Review 4.  Epidemiology and Prevention of Renal Cell Carcinoma.

Authors:  Tomoyuki Makino; Suguru Kadomoto; Kouji Izumi; Atsushi Mizokami
Journal:  Cancers (Basel)       Date:  2022-08-22       Impact factor: 6.575

5.  UPLC/Q-TOF MS-Based Urine Metabonomics Study to Identify Diffuse Axonal Injury Biomarkers in Rat.

Authors:  Peng Zhang; Sheng Wang; Meiqing Liu; Wenhui Li; Leilei Li; Shisheng Zhu; Qianyun Nie; Qifu Li
Journal:  Dis Markers       Date:  2022-09-21       Impact factor: 3.464

6.  Does the Urinary Proteome Reflect ccRCC Stage and Grade Progression?

Authors:  Lucia Santorelli; Martina Stella; Clizia Chinello; Giulia Capitoli; Isabella Piga; Andrew Smith; Angelica Grasso; Marco Grasso; Giorgio Bovo; Fulvio Magni
Journal:  Diagnostics (Basel)       Date:  2021-12-16
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.