Literature DB >> 29441565

Metabolomics and transcriptomics profiles reveal the dysregulation of the tricarboxylic acid cycle and related mechanisms in prostate cancer.

Yaping Shao1,2, Guozhu Ye1,2, Shancheng Ren3, Hai-Long Piao1,4, Xinjie Zhao1, Xin Lu1, Fubo Wang3, Wang Ma5, Jia Li1,2, Peiyuan Yin1, Tian Xia4, Chuanliang Xu3, Jane J Yu1,5,6, Yinghao Sun3, Guowang Xu1.   

Abstract

Genetic alterations drive metabolic reprograming to meet increased biosynthetic precursor and energy demands for cancer cell proliferation and survival in unfavorable environments. A systematic study of gene-metabolite regulatory networks and metabolic dysregulation should reveal the molecular mechanisms underlying prostate cancer (PCa) pathogenesis. Herein, we performed gas chromatography-mass spectrometry (GC-MS)-based metabolomics and RNA-seq analyses in prostate tumors and matched adjacent normal tissues (ANTs) to elucidate the molecular alterations and potential underlying regulatory mechanisms in PCa. Significant accumulation of metabolic intermediates and enrichment of genes in the tricarboxylic acid (TCA) cycle were observed in tumor tissues, indicating TCA cycle hyperactivation in PCa tissues. In addition, the levels of fumarate and malate were highly correlated with the Gleason score, tumor stage and expression of genes encoding related enzymes and were significantly related to the expression of genes involved in branched chain amino acid degradation. Using an integrated omics approach, we further revealed the potential anaplerotic routes from pyruvate, glutamine catabolism and branched chain amino acid (BCAA) degradation contributing to replenishing metabolites for TCA cycle. Integrated omics techniques enable the performance of network-based analyses to gain a comprehensive and in-depth understanding of PCa pathophysiology and may facilitate the development of new and effective therapeutic strategies.
© 2018 UICC.

Entities:  

Keywords:  metabolomics; prostate cancer; transcriptome; tricarboxylic acid cycle

Mesh:

Substances:

Year:  2018        PMID: 29441565     DOI: 10.1002/ijc.31313

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  18 in total

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Review 2.  Tumour metabolism and its unique properties in prostate adenocarcinoma.

Authors:  David A Bader; Sean E McGuire
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Journal:  J Extracell Vesicles       Date:  2020-07-14

4.  PPARα and PPARγ activation attenuates total free fatty acid and triglyceride accumulation in macrophages via the inhibition of Fatp1 expression.

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Journal:  Cell Death Dis       Date:  2019-01-15       Impact factor: 8.469

5.  STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer.

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Journal:  Mol Syst Biol       Date:  2020-04       Impact factor: 11.429

6.  Succinate Anaplerosis Has an Onco-Driving Potential in Prostate Cancer Cells.

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Journal:  Cancers (Basel)       Date:  2021-04-06       Impact factor: 6.639

Review 7.  Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches.

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Journal:  Cancers (Basel)       Date:  2022-01-25       Impact factor: 6.639

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9.  Integrated RNA and metabolite profiling of urine liquid biopsies for prostate cancer biomarker discovery.

Authors:  Bongyong Lee; Iqbal Mahmud; John Marchica; Paweł Dereziński; Feng Qi; Fubo Wang; Piyush Joshi; Felipe Valerio; Inoel Rivera; Vipul Patel; Christian P Pavlovich; Timothy J Garrett; Gary P Schroth; Yinghao Sun; Ranjan J Perera
Journal:  Sci Rep       Date:  2020-02-28       Impact factor: 4.379

Review 10.  Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics.

Authors:  Ana Rita Lima; Joana Pinto; Filipa Amaro; Maria de Lourdes Bastos; Márcia Carvalho; Paula Guedes de Pinho
Journal:  Metabolites       Date:  2021-03-19
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