Literature DB >> 26545398

Integration of Metabolomics and Transcriptomics Reveals Major Metabolic Pathways and Potential Biomarker Involved in Prostate Cancer.

Shancheng Ren1, Yaping Shao2, Xinjie Zhao2, Christopher S Hong3, Fubo Wang1, Xin Lu2, Jia Li2, Guozhu Ye2, Min Yan2, Zhengping Zhuang3, Chuanliang Xu1, Guowang Xu4, Yinghao Sun5.   

Abstract

Prostate cancer is a highly prevalent tumor affecting millions of men worldwide, but poor understanding of its pathogenesis has limited effective clinical management of patients. In addition to transcriptional profiling or transcriptomics, metabolomics is being increasingly utilized to discover key molecular changes underlying tumorigenesis. In this study, we integrated transcriptomics and metabolomics to analyze 25 paired human prostate cancer tissues and adjacent noncancerous tissues, followed by further validation of our findings in an additional cohort of 51 prostate cancer patients and 16 benign prostatic hyperplasia patients. We found several altered pathways aberrantly expressed at both metabolic and transcriptional levels, including cysteine and methionine metabolism, nicotinamide adenine dinucleotide metabolism, and hexosamine biosynthesis. Additionally, the metabolite sphingosine demonstrated high specificity and sensitivity for distinguishing prostate cancer from benign prostatic hyperplasia, particularly for patients with low prostate specific antigen level (0-10 ng/ml). We also found impaired sphingosine-1-phosphate receptor 2 signaling, downstream of sphingosine, representing a loss of tumor suppressor gene and a potential key oncogenic pathway for therapeutic targeting. By integrating metabolomics and transcriptomics, we have provided both a broad picture of the molecular perturbations underlying prostate cancer and a preliminary study of a novel metabolic signature, which may help to discriminate prostate cancer from normal tissue and benign prostatic hyperplasia.
© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2015        PMID: 26545398      PMCID: PMC4762514          DOI: 10.1074/mcp.M115.052381

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  57 in total

1.  Identification and expression analysis of miRNAs during batch culture of HEK-293 cells.

Authors:  Thong-Chuan Koh; Yih-Yean Lee; Siow-Qi Chang; Peter Morin Nissom
Journal:  J Biotechnol       Date:  2009-02-07       Impact factor: 3.307

2.  Rapid and sensitive HILIC-MS/MS analysis of carnitine and acetylcarnitine in biological fluids.

Authors:  Andrea C Isaguirre; Roberto A Olsina; Luis D Martinez; Alicia V Lapierre; Soledad Cerutti
Journal:  Anal Bioanal Chem       Date:  2013-07-23       Impact factor: 4.142

3.  AKT1 and MYC induce distinctive metabolic fingerprints in human prostate cancer.

Authors:  Carmen Priolo; Saumyadipta Pyne; Joshua Rose; Erzsébet Ravasz Regan; Giorgia Zadra; Cornelia Photopoulos; Stefano Cacciatore; Denise Schultz; Natalia Scaglia; Jonathan McDunn; Angelo M De Marzo; Massimo Loda
Journal:  Cancer Res       Date:  2014-10-16       Impact factor: 12.701

Review 4.  Targeting sphingosine-1-phosphate: a novel avenue for cancer therapeutics.

Authors:  Sheldon Milstien; Sarah Spiegel
Journal:  Cancer Cell       Date:  2006-03       Impact factor: 31.743

5.  Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression.

Authors:  Arun Sreekumar; Laila M Poisson; Thekkelnaycke M Rajendiran; Amjad P Khan; Qi Cao; Jindan Yu; Bharathi Laxman; Rohit Mehra; Robert J Lonigro; Yong Li; Mukesh K Nyati; Aarif Ahsan; Shanker Kalyana-Sundaram; Bo Han; Xuhong Cao; Jaeman Byun; Gilbert S Omenn; Debashis Ghosh; Subramaniam Pennathur; Danny C Alexander; Alvin Berger; Jeffrey R Shuster; John T Wei; Sooryanarayana Varambally; Christopher Beecher; Arul M Chinnaiyan
Journal:  Nature       Date:  2009-02-12       Impact factor: 49.962

Review 6.  Sphingosine-1-phosphate receptor 2.

Authors:  Mohamad Adada; Daniel Canals; Yusuf A Hannun; Lina M Obeid
Journal:  FEBS J       Date:  2013-08-19       Impact factor: 5.542

7.  Gene expression profiling identifies clinically relevant subtypes of prostate cancer.

Authors:  Jacques Lapointe; Chunde Li; John P Higgins; Matt van de Rijn; Eric Bair; Kelli Montgomery; Michelle Ferrari; Lars Egevad; Walter Rayford; Ulf Bergerheim; Peter Ekman; Angelo M DeMarzo; Robert Tibshirani; David Botstein; Patrick O Brown; James D Brooks; Jonathan R Pollack
Journal:  Proc Natl Acad Sci U S A       Date:  2004-01-07       Impact factor: 11.205

8.  Ligand-dependent inhibition of B16 melanoma cell migration and invasion via endogenous S1P2 G protein-coupled receptor. Requirement of inhibition of cellular RAC activity.

Authors:  Kayo Arikawa; Noriko Takuwa; Hironori Yamaguchi; Naotoshi Sugimoto; Joji Kitayama; Hirokazu Nagawa; Kazuhiko Takehara; Yoh Takuwa
Journal:  J Biol Chem       Date:  2003-06-16       Impact factor: 5.157

9.  Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression.

Authors:  John R Prensner; Matthew K Iyer; O Alejandro Balbin; Saravana M Dhanasekaran; Qi Cao; J Chad Brenner; Bharathi Laxman; Irfan A Asangani; Catherine S Grasso; Hal D Kominsky; Xuhong Cao; Xiaojun Jing; Xiaoju Wang; Javed Siddiqui; John T Wei; Daniel Robinson; Hari K Iyer; Nallasivam Palanisamy; Christopher A Maher; Arul M Chinnaiyan
Journal:  Nat Biotechnol       Date:  2011-07-31       Impact factor: 54.908

10.  Genetic polymorphisms of the glycine N-methyltransferase and prostate cancer risk in the health professionals follow-up study.

Authors:  Marcelo Chen; Yi-Ling Huang; Yu-Chuen Huang; Irene M Shui; Edward Giovannucci; Yen-Ching Chen; Yi-Ming Arthur Chen
Journal:  PLoS One       Date:  2014-05-06       Impact factor: 3.240

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  39 in total

1.  Molecular Characterization of Prostate Cancer with Associated Gleason Score Using Mass Spectrometry Imaging.

Authors:  Elizabeth C Randall; Giorgia Zadra; Paolo Chetta; Begona G C Lopez; Sudeepa Syamala; Sankha S Basu; Jeffrey N Agar; Massimo Loda; Clare M Tempany; Fiona M Fennessy; Nathalie Y R Agar
Journal:  Mol Cancer Res       Date:  2019-02-11       Impact factor: 5.852

Review 2.  Mass Spectrometry-based Metabolomics in Translational Research.

Authors:  Su Jung Kim; Ha Eun Song; Hyo Yeong Lee; Hyun Ju Yoo
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

3.  Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups.

Authors:  Daniil S Wiebe; Nadezhda A Omelyanchuk; Aleksei M Mukhin; Ivo Grosse; Sergey A Lashin; Elena V Zemlyanskaya; Victoria V Mironova
Journal:  Genes (Basel)       Date:  2020-04-17       Impact factor: 4.096

4.  Identification of ENTPD8 and cytidine in pancreatic cancer by metabolomic and transcriptomic conjoint analysis.

Authors:  Yong An; Huihua Cai; Yong Yang; Yue Zhang; Shengyong Liu; Xinquan Wu; Yunfei Duan; Donglin Sun; Xuemin Chen
Journal:  Cancer Sci       Date:  2018-09-03       Impact factor: 6.716

5.  Glycolytic potential enhanced by blockade of pyruvate influx into mitochondria sensitizes prostate cancer to detection and radiotherapy.

Authors:  Huan Xu; Junyi Chen; Zhi Cao; Xi Chen; Caihong Huang; Jin Ji; Yalong Xu; Junfeng Jiang; Yue Wang; Guowang Xu; Lina Zhou; Jingyi He; Xuedong Wei; Jason Boyang Wu; Zhong Wang; Shancheng Ren; Fubo Wang
Journal:  Cancer Biol Med       Date:  2022-08-17       Impact factor: 5.347

6.  Untargeted metabolomics and transcriptomics identified glutathione metabolism disturbance and PCS and TMAO as potential biomarkers for ER stress in lung.

Authors:  Zijing Wang; Peng Ma; Yisa Wang; Biyu Hou; Can Zhou; He Tian; Bowen Li; Guanghou Shui; Xiuying Yang; Guifen Qiang; Chengqian Yin; Guanhua Du
Journal:  Sci Rep       Date:  2021-07-19       Impact factor: 4.379

Review 7.  Integration of omics: more than the sum of its parts.

Authors:  Joerg Martin Buescher; Edward M Driggers
Journal:  Cancer Metab       Date:  2016-02-19

8.  Identification of SPOP related metabolic pathways in prostate cancer.

Authors:  Min Yan; Huan Qi; Jia Li; Guozhu Ye; Yaping Shao; Tongming Li; Jing Liu; Hai-Long Piao; Guowang Xu
Journal:  Oncotarget       Date:  2017-10-03

9.  Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics.

Authors:  Emily G Armitage; Andrew D Southam
Journal:  Metabolomics       Date:  2016-08-16       Impact factor: 4.290

10.  Increased transcriptional and metabolic capacity for lipid metabolism in the peripheral zone of the prostate may underpin its increased susceptibility to cancer.

Authors:  Omar Al Kadhi; Maria H Traka; Antonietta Melchini; Perla Troncoso-Rey; Wiktor Jurkowski; Marianne Defernez; Purnima Pachori; Robert D Mills; Richard Y Ball; Richard F Mithen
Journal:  Oncotarget       Date:  2017-05-17
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