Abstract P2-02-13: Computational metabolism modeling predicts risk of relapse in breast cancer patients

Abstract

Abstract Introduction Breast cancer is one of the most prevalent cancers in the world. In previous works we observed differences in glucose metabolism between breast cancer subtypes, suggesting that metabolism plays an important role in this disease. Flux Balance Analysis (FBA) is widely used to study metabolic networks, allowing predicting growth rates or the rate of production of a given metabolite. Material and methods Proteomics data from 96 breast cancer tumors were obtained applying a high-throughput proteomics approach to routinely archive formalin-fixed, paraffin-embedded tumor tissue. Proteomics tumor data were analyzed using the human metabolic reconstruction Recon2 and FBA. The tumor growth rate for each tumor was calculated. In order to analyze fluxes from the different metabolic pathways, flux activities were calculated as the sum of the fluxes of each reaction in each pathway defined in the Recon2. Then, flux activities were used to build prognostic models. Results and discussion Using the results obtained from FBA in the proteomics dataset, flux activities were calculated for each pathway. Employing these flux activities, a prognostic signature was built. Flux activities of vitamin A, tetrahydrobiopterin metabolism and beta-alanine metabolism pathways split our population into a low and a high risk group (p=0.044). Conclusion Vitamine A, beta-alanine and tetrahydrobiopterin metabolism flux activities could be used to predict relapse risk. Flux activities is a method proposed in a previous work to study response against drugs that now also demonstrated its utility in summarizing FBA data and is associated with prognosis. Citation Format: Zamora P, Trilla-Fuertes L, Gámez-Pozo A, Prado-Vázquez G, Zapater-Moros A, Ferrer-Gómez M, Díaz- Almirón M, López Vacas R, Espinosa E, Fresno Vara JA. Computational metabolism modeling predicts risk of relapse in breast cancer patients [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-02-13.