» Articles » PMID: 23181020

Computational Modeling of the Metabolic States Regulated by the Kinase Akt

Overview
Journal Front Physiol
Date 2012 Nov 28
PMID 23181020
Citations 9
Authors
Affiliations
Soon will be listed here.
Abstract

Signal transduction and gene regulation determine a major reorganization of metabolic activities in order to support cell proliferation. Protein Kinase B (PKB), also known as Akt, participates in the PI3K/Akt/mTOR pathway, a master regulator of aerobic glycolysis and cellular biosynthesis, two activities shown by both normal and cancer proliferating cells. Not surprisingly considering its relevance for cellular metabolism, Akt/PKB is often found hyperactive in cancer cells. In the last decade, many efforts have been made to improve the understanding of the control of glucose metabolism and the identification of a therapeutic window between proliferating cancer cells and proliferating normal cells. In this context, we have modeled the link between the PI3K/Akt/mTOR pathway, glycolysis, lactic acid production, and nucleotide biosynthesis. We used a computational model to compare two metabolic states generated by two different levels of signaling through the PI3K/Akt/mTOR pathway: one of the two states represents the metabolism of a growing cancer cell characterized by aerobic glycolysis and cellular biosynthesis, while the other state represents the same metabolic network with a reduced glycolytic rate and a higher mitochondrial pyruvate metabolism. Biochemical reactions that link glycolysis and pentose phosphate pathway revealed their importance for controlling the dynamics of cancer glucose metabolism.

Citing Articles

Targeting glycolytic pathway in fibroblast-like synoviocytes for rheumatoid arthritis therapy: challenges and opportunities.

Li Q, Chen Y, Liu H, Tian Y, Yin G, Xie Q Inflamm Res. 2023; 72(12):2155-2167.

PMID: 37940690 DOI: 10.1007/s00011-023-01807-y.


Connecting signaling and metabolic pathways in EGF receptor-mediated oncogenesis of glioblastoma.

Bag A, Mandloi S, Jarmalavicius S, Mondal S, Kumar K, Mandal C PLoS Comput Biol. 2019; 15(8):e1007090.

PMID: 31386654 PMC: 6684045. DOI: 10.1371/journal.pcbi.1007090.


Crosstalk in transition: the translocation of Akt.

Gray C, Coster A J Math Biol. 2018; 78(4):919-942.

PMID: 30306249 DOI: 10.1007/s00285-018-1297-8.


Targeted AKT Inhibition in Prostate Cancer Cells and Spheroids Reduces Aerobic Glycolysis and Generation of Hyperpolarized [1-C] Lactate.

Tee S, Suster I, Truong S, Jeong S, Eskandari R, DiGialleonardo V Mol Cancer Res. 2018; 16(3):453-460.

PMID: 29330287 PMC: 6662159. DOI: 10.1158/1541-7786.MCR-17-0458.


Computational Model Predicts the Effects of Targeting Cellular Metabolism in Pancreatic Cancer.

Roy M, Finley S Front Physiol. 2017; 8:217.

PMID: 28446878 PMC: 5388762. DOI: 10.3389/fphys.2017.00217.


References
1.
Mosca E, Barcella M, Alfieri R, Bevilacqua A, Canti G, Milanesi L . Systems biology of the metabolic network regulated by the Akt pathway. Biotechnol Adv. 2011; 30(1):131-41. DOI: 10.1016/j.biotechadv.2011.08.004. View

2.
Clem B, Telang S, Clem A, Yalcin A, Meier J, Simmons A . Small-molecule inhibition of 6-phosphofructo-2-kinase activity suppresses glycolytic flux and tumor growth. Mol Cancer Ther. 2008; 7(1):110-20. DOI: 10.1158/1535-7163.MCT-07-0482. View

3.
Lunt S, Vander Heiden M . Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Annu Rev Cell Dev Biol. 2011; 27:441-64. DOI: 10.1146/annurev-cellbio-092910-154237. View

4.
Ghosh S, Matsuoka Y, Asai Y, Hsin K, Kitano H . Software for systems biology: from tools to integrated platforms. Nat Rev Genet. 2011; 12(12):821-32. DOI: 10.1038/nrg3096. View

5.
Kreeger P, Lauffenburger D . Cancer systems biology: a network modeling perspective. Carcinogenesis. 2009; 31(1):2-8. PMC: 2802670. DOI: 10.1093/carcin/bgp261. View