Modeling Basins of Attraction for Breast Cancer Using Hopfield Networks

We are grateful for support from PrInt Fiocruz-CAPES Program.Submitted by Éder Freyre ([email protected]) on 2020-04-07T19:34:57Z No. of bitstreams: 1 Conforte_Alessandra_etal_PROCC_2020.pdf: 1533427 bytes, checksum: a8b03a9fe313dea5a026b35642b6e281 (MD5)Approved for entry into archive by Éder Freyre ([email protected]) on 2020-04-07T20:13:09Z (GMT) No. of bitstreams: 1 Conforte_Alessandra_etal_PROCC_2020.pdf: 1533427 bytes, checksum: a8b03a9fe313dea5a026b35642b6e281 (MD5)Made available in DSpace on 2020-04-07T20:13:09Z (GMT). No. of bitstreams: 1 Conforte_Alessandra_etal_PROCC_2020.pdf: 1533427 bytes, checksum: a8b03a9fe313dea5a026b35642b6e281 (MD5) Previous issue date: 2020FAPERJ.Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Laboratório de Modelagem de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Programa de Computação Científica. Laboratório de Modelagem Computacional de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil.Fundação Getúlio Vargas. Escola de Matemática Aplicada. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Rio de janeiro, RJ, Brasil.Fundação Getúlio Vargas. Escola de Matemática Aplicada. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Laboratório de Modelagem de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Programa de Computação Científica. Laboratório de Modelagem Computacional de Sistemas Biológicos. Rio de Janeiro, RJ, Brasil.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

Isolation and characterization of a promoter responsive to salt, osmotic and dehydration stresses in soybean

Abstract Drought stress is the main limiting factor of soybean yield. Currently, genetic engineering has been one important tool in the development of drought-tolerant cultivars. A widely used strategy is the fusion of genes that confer tolerance under the control of the CaMV35S constitutive promoter; however, stress-responsive promoters would constitute the best alternative to the generation of drought-tolerant crops. We characterized the promoter of α-galactosidase soybean (GlymaGAL) gene that was previously identified as highly up-regulated by drought stress. The β-glucuronidase (GUS) activity of Arabidopsis transgenic plants bearing 1000- and 2000-bp fragments of the GlymaGAL promoter fused to the uidA gene was evaluated under air-dried, polyethylene glycol (PEG) and salt stress treatments. After 24 h of air-dried and PEG treatments, the pGAL-2kb led to an increase in GUS expression in leaf and root samples when compared to the control samples. These results were corroborated by qPCR expression analysis of the uidA gene. The pGAL-1kb showed no difference in GUS activity between control and treated samples. The pGAL-2kb promoter was evaluated in transgenic soybean roots, leading to an increase in EGFP expression under air-dried treatment. Our data indicates that pGAL-2kb could be a useful tool in developing drought-tolerant cultivars by driving gene expression