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本文引用的文献

1
Merging transcriptomics and metabolomics--advances in breast cancer profiling.转录组学和代谢组学的融合——乳腺癌分析的新进展。
BMC Cancer. 2010 Nov 16;10:628. doi: 10.1186/1471-2407-10-628.
2
Metabolomics and detection of colorectal cancer in humans: a systematic review.代谢组学与人类结直肠癌的检测:系统综述。
Future Oncol. 2010 Sep;6(9):1395-406. doi: 10.2217/fon.10.107.
3
Understanding the "lethal" drivers of tumor-stroma co-evolution: emerging role(s) for hypoxia, oxidative stress and autophagy/mitophagy in the tumor micro-environment.理解肿瘤-基质共进化的“致命”驱动因素:缺氧、氧化应激和自噬/线粒体自噬在肿瘤微环境中的新作用。
Cancer Biol Ther. 2010 Sep 15;10(6):537-42. doi: 10.4161/cbt.10.6.13370. Epub 2010 Sep 19.
4
Hypoxia-induced metabolic shifts in cancer cells: moving beyond the Warburg effect.缺氧诱导的肿瘤细胞代谢重编程:超越沃伯格效应。
Int J Biochem Cell Biol. 2011 Jul;43(7):981-9. doi: 10.1016/j.biocel.2010.08.009. Epub 2010 Aug 24.
5
Uncovering the metabolomic fingerprint of breast cancer.揭示乳腺癌的代谢组学特征。
Int J Biochem Cell Biol. 2011 Jul;43(7):1010-20. doi: 10.1016/j.biocel.2010.05.001. Epub 2010 May 10.
6
Metabolic profiling of human colorectal cancer using high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and gas chromatography mass spectrometry (GC/MS).使用高分辨率魔角旋转核磁共振(HR-MAS NMR)光谱法和气相色谱-质谱联用(GC/MS)对人类结直肠癌进行代谢谱分析。
J Proteome Res. 2009 Jan;8(1):352-61. doi: 10.1021/pr8006232.
7
Comparison of HR MAS MR spectroscopic profiles of breast cancer tissue with clinical parameters.乳腺癌组织的高分辨魔角旋转磁共振波谱特征与临床参数的比较。
NMR Biomed. 2006 Feb;19(1):30-40. doi: 10.1002/nbm.992.

代谢组学除了基因组学之外,还能为乳腺癌的预后和预测信息增添价值吗?

Can metabolomics in addition to genomics add to prognostic and predictive information in breast cancer?

机构信息

School of Cancer and Enabling Studies, University of Manchester, Paterson Institute for Cancer Research, Manchester, UK.

出版信息

BMC Med. 2010 Nov 16;8:73. doi: 10.1186/1741-7015-8-73.

DOI:10.1186/1741-7015-8-73
PMID:21080936
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2995773/
Abstract

Genomic data from breast cancers provide additional prognostic and predictive information that is beginning to be used for patient management. The question arises whether additional information derived from other 'omic' approaches such as metabolomics can provide additional information. In an article published this month in BMC Cancer, Borgan et al. add metabolomic information to genomic measures in breast tumours and demonstrate, for the first time, that it may be possible to further define subgroups of patients which could be of value clinically. See research article: http://www.biomedcentral.com/1471-2407/10/628.

摘要

乳腺癌的基因组数据提供了额外的预后和预测信息,这些信息开始被用于患者管理。问题是,其他“组学”方法(如代谢组学)获得的额外信息是否可以提供更多信息。在本月发表在 BMC 癌症杂志上的一篇文章中,Borgan 等人在乳腺癌肿瘤的基因组测量中加入了代谢组学信息,并首次证明,进一步定义可能具有临床价值的患者亚组是有可能的。见研究文章:http://www.biomedcentral.com/1471-2407/10/628。