The metabolic rearrangements occurring in cancer cells can be effectively investigated with a Systems Biology approach supported by metabolic network modeling. We here present tissue-specific constraint-based core models for three different types of tumors (liver, breast and lung) that serve this purpose. The core models were extracted and manually curated from the corresponding genome-scale metabolic models in the Human Metabolic Atlas database with a focus on the pathways that are known to play a key role in cancer growth and proliferation. Along similar lines, we also reconstructed a core model from the original general human metabolic network to be used as a reference model. A comparative Flux Balance Analysis between the reference and the cancer models highlighted both a clear distinction between the two conditions and a heterogeneity within the three different cancer types in terms of metabolic flux distribution. These results emphasize the need for modeling approaches able to keep up with this tumoral heterogeneity in order to identify more suitable drug targets and develop effective treatments. According to this perspective, we identified key points able to reverse the tumoral phenotype toward the reference one or vice-versa.

DI FILIPPO, M., Colombo, R., Damiani, C., Pescini, D., Gaglio, D., Vanoni, M., et al. (2016). Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models. COMPUTATIONAL BIOLOGY AND CHEMISTRY, 62, 60-69 [10.1016/j.compbiolchem.2016.03.002].

Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models

DI FILIPPO, MARZIA;COLOMBO, RICCARDO
Secondo
;
DAMIANI, CHIARA;PESCINI, DARIO;GAGLIO, DANIELA;VANONI, MARCO ERCOLE;ALBERGHINA, LILIA
Penultimo
;
MAURI, GIANCARLO
Ultimo
2016

Abstract

The metabolic rearrangements occurring in cancer cells can be effectively investigated with a Systems Biology approach supported by metabolic network modeling. We here present tissue-specific constraint-based core models for three different types of tumors (liver, breast and lung) that serve this purpose. The core models were extracted and manually curated from the corresponding genome-scale metabolic models in the Human Metabolic Atlas database with a focus on the pathways that are known to play a key role in cancer growth and proliferation. Along similar lines, we also reconstructed a core model from the original general human metabolic network to be used as a reference model. A comparative Flux Balance Analysis between the reference and the cancer models highlighted both a clear distinction between the two conditions and a heterogeneity within the three different cancer types in terms of metabolic flux distribution. These results emphasize the need for modeling approaches able to keep up with this tumoral heterogeneity in order to identify more suitable drug targets and develop effective treatments. According to this perspective, we identified key points able to reverse the tumoral phenotype toward the reference one or vice-versa.
Articolo in rivista - Articolo scientifico
Cancer metabolic rewiring; Core metabolic model; Flux Balance Analysis; Network reconstruction;
Cancer metabolic rewiring; Network reconstruction; Core metabolic model; Flux Balance Analysis
English
14-mar-2016
2016
62
60
69
none
DI FILIPPO, M., Colombo, R., Damiani, C., Pescini, D., Gaglio, D., Vanoni, M., et al. (2016). Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models. COMPUTATIONAL BIOLOGY AND CHEMISTRY, 62, 60-69 [10.1016/j.compbiolchem.2016.03.002].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/107119
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