| Author | Silva, Fabricio Alves Barbosa da | |
| Author | Conforte, Alessandra Jordano | |
| Author | Alves, Leon Diniz | |
| Author | Coelho, Flávio Codeço | |
| Author | Carels, Nicolas | |
| Access date | 2020-04-07T20:13:09Z | |
| Available date | 2020-04-07T20:13:09Z | |
| Document date | 2020 | |
| Citation | CONFORTE, Alessandra Jordano et al. Modeling basins of attraction for breast cancer using Hopfield Networks. Frontiers in Genetics, Switzerland, v. 11, n. 4, p. 1-17, 2020. 07 Apr. 2020. | pt_BR |
| ISSN | 1664-8021 | pt_BR |
| URI | https://www.arca.fiocruz.br/handle/icict/40674 | |
| Description | We are grateful for support from PrInt Fiocruz-CAPES Program. | pt_BR |
| Sponsorship | FAPERJ. | pt_BR |
| Language | eng | pt_BR |
| Publisher | Frontiers in Genetics | pt_BR |
| Rights | open access | |
| Title | Modeling basins of attraction for breast cancer using Hopfield Networks | pt_BR |
| Type | Article | |
| DOI | 10.3389/fgene.2020.00314 | pt_BR |
| Abstract | Cancer is a genetic disease for which traditional treatments cause harmful side effects. After two decades of genomics technological breakthroughs, personalized medicine is being used to improve treatment outcomes and mitigate side effects. In mathematical modeling, it has been proposed that cancer matches an attractor in Waddington’s epigenetic landscape. The use of Hopfield networks is an attractive modeling approach because it requires neither previous biological knowledge about protein-protein interactions nor kinetic parameters. In this report, Hopfield network modeling was used to analyze bulk RNA-Seq data of paired breast tumor and control samples from 70 patients. We characterized the control and tumor attractors with respect to their size and potential energy and correlated the Euclidean distances between the tumor samples and the control attractor with their corresponding clinical data. In addition, we developed a protocol that outlines the key genes involved in tumor state stability. We found that the tumor basin of attraction is larger than that of the control and that tumor samples are associated with a more substantial negative energy than control samples, which is in agreement with previous reports. Moreover, we found a negative correlation between the Euclidean distances from tumor samples to the control attractor and patient overall survival. The ascending order of each node’s density in the weight matrix and the descending order of the number of patients that have the target active only in the tumor sample were the parameters that withdrew more tumor samples from the tumor basin of attraction with fewer gene inhibitions. The combinations of therapeutic targets were specific to each patient. We performed an initial validation through simulation of trastuzumab treatment effects in HER2+ breast cancer samples. For that, we built an energy landscape composed of single-cell and bulk RNA-Seq data from trastuzumab-treated and non-treated HER2+ samples. The trajectory from the non-treated bulk sample toward the treated bulk sample was inferred through the perturbation of differentially expressed genes between these samples. Among them, we characterized key genes involved in the trastuzumab response according to the literature. | en |
| Affilliation | Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Laboratório de Modelagem de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Presidência. Programa de Computação Científica. Laboratório de Modelagem Computacional de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Affilliation | Fundação Getúlio Vargas. Escola de Matemática Aplicada. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Programa de Pós-graduação em Biologia Computacional e Sistemas. Rio de janeiro, RJ, Brasil. | pt_BR |
| Affilliation | Fundação Getúlio Vargas. Escola de Matemática Aplicada. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Affilliation | Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Laboratório de Modelagem de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Affilliation | Fundação Oswaldo Cruz. Presidência. Programa de Computação Científica. Laboratório de Modelagem Computacional de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil. | pt_BR |
| Subject | Breast cancer | en |
| Subject | Hopfield network | en |
| Subject | Basin region of attraction of a minimizer | en |
| Subject | Systems biology | en |
| Subject | Dynamic system | en |
| Subject | Breast neoplasms | en |
| DeCS | Neoplasias da Mama | pt_BR |
