Literature DB >> 27473428

The development of plasma pseudotargeted GC-MS metabolic profiling and its application in bladder cancer.

Yang Zhou1,2, Ruixiang Song3, Zhensheng Zhang3, Xin Lu4, Zhongda Zeng1, Chunxiu Hu1, Xinyu Liu1,2, Yanli Li1, Jianguo Hou3, Yinghao Sun3, Chuanliang Xu5, Guowang Xu1.   

Abstract

Bladder cancer (BC) is a fatal malignancy with considerable mortality. BC urinary metabolomics has been extensively investigated for biomarker discovery, but few BC blood metabolomic studies have been performed. Hence, a plasma pseudotargeted metabolomic method based on gas chromatography-mass spectrometry with selected ion monitoring (GC-MS-SIM) was developed to study metabolic alterations in BC. The analytical performance of the developed method was compared with that of a nontargeted method. The relative standard deviation (RSD) values of 89 and 70.7 % of the peaks obtained using the pseudotargeted and nontargeted methods, respectively, were less than 20 %. The Pearson correlations of 90.7 and 78.3 % of the peaks obtained using the pseudotargeted and nontargeted methods, respectively, exceeded 0.90 in the linearity evaluation. Compared with the nontargeted method, the signal-to-noise ratios (S/N) of 97.9 and 69.3 % of the peaks increased two- and fivefold, respectively. The developed method was fully validated, with good precision, recovery, and stability of the trimethylsilyl (TMS) derivatives. The method was applied to investigate BC. Significant increases in the contents of metabolites involved in, for example, the pentose phosphate pathway (PPP) and nucleotide and fatty acid synthesis were found in the high-grade (HG) BC group compared to the healthy control (HC) group. These differences imply that the activated PPP may regulate BC cell proliferation by promoting lipid and nucleotide biosynthesis and the detoxification of reactive oxygen species (ROS). These results illustrate that the plasma pseudotargeted method is a powerful tool for metabolic profiling. Graphical abstract The plasma pseudotargeted metabolic profiling suggested the metabolic alterations in bladder cancer (BC) and the significantly differential metabolites for BC discrimination.

Entities:  

Keywords:  Bladder cancer; Gas chromatography–mass spectrometry; Metabolic profiling; Metabolomics; Plasma; Pseudotargeted

Mesh:

Year:  2016        PMID: 27473428     DOI: 10.1007/s00216-016-9797-0

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  17 in total

1.  Metabolic profiling of acromegaly using a GC-MS-based nontargeted metabolomic approach.

Authors:  Hengchi Yu; Yaqun Zhao; Yazhuo Zhang; Liyong Zhong
Journal:  Endocrine       Date:  2019-12-24       Impact factor: 3.633

Review 2.  Recent advances in the metabolomic study of bladder cancer.

Authors:  Chandra Sekhar Amara; Venkatrao Vantaku; Yair Lotan; Nagireddy Putluri
Journal:  Expert Rev Proteomics       Date:  2019-02-26       Impact factor: 3.940

3.  Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry.

Authors:  Fujian Zheng; Xinjie Zhao; Zhongda Zeng; Lichao Wang; Wangjie Lv; Qingqing Wang; Guowang Xu
Journal:  Nat Protoc       Date:  2020-06-24       Impact factor: 13.491

4.  Prognosis prediction of hepatocellular carcinoma after surgical resection based on serum metabolic profiling from gas chromatography-mass spectrometry.

Authors:  Chengnan Fang; Benzhe Su; Tianyi Jiang; Chao Li; Yexiong Tan; Qingqing Wang; Liwei Dong; Xinyu Liu; Xiaohui Lin; Guowang Xu
Journal:  Anal Bioanal Chem       Date:  2021-04-02       Impact factor: 4.142

5.  Enhancement of mitochondrial biogenesis and paradoxical inhibition of lactate dehydrogenase mediated by 14-3-3η in oncocytomas.

Authors:  Jie Feng; Qi Zhang; Chuzhong Li; Yang Zhou; Sida Zhao; Lichuan Hong; Qi Song; Shenyuan Yu; Chunxiu Hu; Herui Wang; Chengyuan Mao; Matthew J Shepard; Shuyu Hao; Gifty Dominah; Mitchell Sun; Hong Wan; Deric M Park; Mark R Gilbert; Guowang Xu; Zhengping Zhuang; Yazhuo Zhang
Journal:  J Pathol       Date:  2018-05-29       Impact factor: 7.996

Review 6.  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

Review 7.  Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer.

Authors:  Bo Yang; Guo-Qiang Liao; Xiao-Fei Wen; Wei-Hua Chen; Sheng Cheng; Jens-Uwe Stolzenburg; Roman Ganzer; Jochen Neuhaus
Journal:  J Zhejiang Univ Sci B       Date:  2017 Nov.       Impact factor: 3.066

Review 8.  Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer.

Authors:  Nicola Antonio di Meo; Davide Loizzo; Savio Domenico Pandolfo; Riccardo Autorino; Matteo Ferro; Camillo Porta; Alessandro Stella; Cinzia Bizzoca; Leonardo Vincenti; Felice Crocetto; Octavian Sabin Tataru; Monica Rutigliano; Michele Battaglia; Pasquale Ditonno; Giuseppe Lucarelli
Journal:  Int J Mol Sci       Date:  2022-04-10       Impact factor: 6.208

9.  Discovery and validation of potential urinary biomarkers for bladder cancer diagnosis using a pseudotargeted GC-MS metabolomics method.

Authors:  Yang Zhou; Ruixiang Song; Chong Ma; Lina Zhou; Xinyu Liu; Peiyuan Yin; Zhensheng Zhang; Yinghao Sun; Chuanliang Xu; Xin Lu; Guowang Xu
Journal:  Oncotarget       Date:  2017-03-28

Review 10.  Epigenomic and Metabolomic Integration Reveals Dynamic Metabolic Regulation in Bladder Cancer.

Authors:  Alba Loras; Cristina Segovia; José Luis Ruiz-Cerdá
Journal:  Cancers (Basel)       Date:  2021-05-31       Impact factor: 6.639

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