Literature DB >> 18241004

Metabolomics in biomarker discovery: future uses for cancer prevention.

Young S Kim1, Padma Maruvada, John A Milner.   

Abstract

Metabolomics is the systematic study of small-molecular-weight substances in cells, tissues and/or whole organisms as influenced by multiple factors including genetics, diet, lifestyle and pharmaceutical interventions. These substances may directly or indirectly interact with molecular targets and thereby influence the risk and complications associated with various diseases, including cancer. Since the interaction between metabolites and specific targets is dynamic, knowledge regarding genetics, susceptibility factors, timing, and degree of exposure to an agent (drug or food component) is fundamental to understanding the metabolome and its potential use for predicting and preventing early phenotypic changes. The future of metabolomics rests with its ability to monitor subtle changes in the metabolome that occur prior to the detection of a gross phenotypic change reflecting disease. The integrated analysis of metabolomics and other 'omics' may provide more sensitive ways to detect changes related to disease and discover novel biomarkers. Knowledge regarding these multivariant characteristics is critical for establishing validated and predictive metabolomic models for cancer prevention. Understanding the metabolome will not only provide insights into the critical sites of regulation in health promotion, but will also assist in identifying intermediate or surrogate cancer biomarkers for establishing preemptive/preventative or therapeutic approaches for health. While unraveling the metabolome will not be simple, the societal implications are enormous.

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Year:  2008        PMID: 18241004     DOI: 10.2217/14796694.4.1.93

Source DB:  PubMed          Journal:  Future Oncol        ISSN: 1479-6694            Impact factor:   3.404


  31 in total

1.  Waterborne manganese exposure alters plasma, brain, and liver metabolites accompanied by changes in stereotypic behaviors.

Authors:  Steve Fordahl; Paula Cooney; Yunping Qiu; Guoxiang Xie; Wei Jia; Keith M Erikson
Journal:  Neurotoxicol Teratol       Date:  2011-10-21       Impact factor: 3.763

Review 2.  Database resources in metabolomics: an overview.

Authors:  Eden P Go
Journal:  J Neuroimmune Pharmacol       Date:  2009-05-07       Impact factor: 4.147

3.  Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra.

Authors:  Pascal Mercier; Michael J Lewis; David Chang; David Baker; David S Wishart
Journal:  J Biomol NMR       Date:  2011-03-01       Impact factor: 2.835

4.  Omics-based molecular target and biomarker identification.

Authors:  Zhang-Zhi Hu; Hongzhan Huang; Cathy H Wu; Mira Jung; Anatoly Dritschilo; Anna T Riegel; Anton Wellstein
Journal:  Methods Mol Biol       Date:  2011

5.  A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women.

Authors:  Li Jiao; Suman Maity; Cristian Coarfa; Kimal Rajapakshe; Liang Chen; Feng Jin; Vasanta Putluri; Lesley F Tinker; Qianxing Mo; Fengju Chen; Subrata Sen; Haleh Sangi-Hyghpeykar; Hashem B El-Serag; Nagireddy Putluri
Journal:  Cancer Prev Res (Phila)       Date:  2019-02-05

Review 6.  Metabolomics in the fields of oncology: a review of recent research.

Authors:  Yanlei Ma; Peng Zhang; Yongzhi Yang; Feng Wang; Huanlong Qin
Journal:  Mol Biol Rep       Date:  2012-02-16       Impact factor: 2.316

Review 7.  Bioactive food components and cancer-specific metabonomic profiles.

Authors:  Young S Kim; John A Milner
Journal:  J Biomed Biotechnol       Date:  2010-11-11

Review 8.  Genomic and proteomic biomarkers for cancer: a multitude of opportunities.

Authors:  Michael A Tainsky
Journal:  Biochim Biophys Acta       Date:  2009-05-04

9.  A pilot study of gas chromatograph/mass spectrometry-based serum metabolic profiling of colorectal cancer after operation.

Authors:  Yanlei Ma; Weijie Liu; Jiayuan Peng; Long Huang; Peng Zhang; Xiaoping Zhao; Yiyu Cheng; Huanlong Qin
Journal:  Mol Biol Rep       Date:  2009-04-02       Impact factor: 2.316

10.  Noninvasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer.

Authors:  Ewy A Mathé; Andrew D Patterson; Majda Haznadar; Soumen K Manna; Kristopher W Krausz; Elise D Bowman; Peter G Shields; Jeffrey R Idle; Philip B Smith; Katsuhiro Anami; Dickran G Kazandjian; Emmanuel Hatzakis; Frank J Gonzalez; Curtis C Harris
Journal:  Cancer Res       Date:  2014-04-15       Impact factor: 12.701

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