Computational metabolism modeling predicts risk of distant relapse-free survival in breast cancer patients.
Future Oncol
; 15(30): 3483-3490, 2019 Oct.
Article
in En
| MEDLINE
| ID: mdl-31580166
ABSTRACT
Aim:
Differences in metabolism among breast cancer subtypes suggest that metabolism plays an important role in this disease. Flux balance analysis is used to explore these differences as well as drug response. Materials &methods:
Proteomics data from breast tumors were obtained by mass-spectrometry. Flux balance analysis was performed to study metabolic networks. Flux activities from metabolic pathways were calculated and used to build prognostic models.Results:
Flux activities of vitamin A, tetrahydrobiopterin and ß-alanine metabolism pathways split our population into low- and high-risk patients. Additionally, flux activities of glycolysis and glutamate metabolism split triple negative tumors into low- and high-risk groups.Conclusion:
Flux activities summarize flux balance analysis data and can be associated with prognosis in cancer.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Breast Neoplasms
/
Computational Biology
/
Proteome
/
Neoplasm Recurrence, Local
Type of study:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Adult
/
Aged
/
Aged80
/
Female
/
Humans
/
Middle aged
Language:
En
Journal:
Future Oncol
Year:
2019
Type:
Article
Affiliation country:
Spain