Heterogeneity of the cancer cell line metabolic landscape. Shorthouse, D., Bradley, J., Critchlow, S. E, Bendtsen, C., & Hall, B. A Molecular Systems Biology, 18(11):e11006, November, 2022. Publisher: John Wiley & Sons, Ltd
Heterogeneity of the cancer cell line metabolic landscape [link]Paper  doi  abstract   bibtex   
The unravelling of the complexity of cellular metabolism is in its infancy. Cancer‐associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer‐associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer‐associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.
@article{shorthouse_heterogeneity_2022,
	title = {Heterogeneity of the cancer cell line metabolic landscape},
	volume = {18},
	issn = {1744-4292},
	url = {https://www.embopress.org/doi/full/10.15252/msb.202211006},
	doi = {10.15252/msb.202211006},
	abstract = {The unravelling of the complexity of cellular metabolism is in its infancy. Cancer‐associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer‐associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer‐associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.},
	number = {11},
	urldate = {2025-05-20},
	journal = {Molecular Systems Biology},
	author = {Shorthouse, David and Bradley, Jenna and Critchlow, Susan E and Bendtsen, Claus and Hall, Benjamin A},
	month = nov,
	year = {2022},
	note = {Publisher: John Wiley \& Sons, Ltd},
	keywords = {cancer, heterogeneity, metabolomics, mutation},
	pages = {e11006},
}

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