Cancers 2013, 5(2), 491-510; doi:10.3390/cancers5020491
Article

Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

1,2,3,†email, 2,4,†email, 2,5email, 2,6email, 2,5email, 7email, 1,2,3,* email and 1,2,3,4,5,* email
1 Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan 2 The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan 3 Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan 4 Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Room 410 BL Building, No. 1, Roosevelt Road, Sec. 4, Taipei 106, Taiwan 5 Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan 6 Graduate Institute of Networking and Multimedia, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan 7 Department of Pharmacology, National Taiwan University, 11 F No. 1 Sec. 1, Ren-ai Rd., Taipei 10051, Taiwan These authors contributed equally to this work.
* Authors to whom correspondence should be addressed.
Received: 12 April 2013; in revised form: 24 April 2013 / Accepted: 24 April 2013 / Published: 3 May 2013
(This article belongs to the Special Issue Cancer Metabolism)
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Abstract: Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.
Keywords: 1H-NMR spectroscopy; metabolic network; metabolomics; multivariate analysis; tumor hypoxia

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MDPI and ACS Style

Tsai, I.-L.; Kuo, T.-C.; Ho, T.-J.; Harn, Y.-C.; Wang, S.-Y.; Fu, W.-M.; Kuo, C.-H.; Tseng, Y.J. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data. Cancers 2013, 5, 491-510.

AMA Style

Tsai I-L, Kuo T-C, Ho T-J, Harn Y-C, Wang S-Y, Fu W-M, Kuo C-H, Tseng YJ. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data. Cancers. 2013; 5(2):491-510.

Chicago/Turabian Style

Tsai, I-Lin; Kuo, Tien-Chueh; Ho, Tsung-Jung; Harn, Yeu-Chern; Wang, San-Yuan; Fu, Wen-Mei; Kuo, Ching-Hua; Tseng, Yufeng J. 2013. "Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data." Cancers 5, no. 2: 491-510.

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