01577nas a2200253 4500008004100000022001400041245005600055210005300111260001600164300000600180490000700186520083300193100001601026700002701042700002201069700001801091700002101109700002001130700001901150700002301169700002401192700002001216856008701236 2021 eng d a1756-038100aMechanistic modeling of the SARS-CoV-2 disease map.0 aMechanistic modeling of the SARSCoV2 disease map c2021 Jan 21 a50 v143 a

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.

1 aRian, Kinza1 aEsteban-Medina, Marina1 aHidalgo, Marta, R1 aCubuk, Cankut1 aFalco, Matias, M1 aLoucera, Carlos1 aGunyel, Devrim1 aOstaszewski, Marek1 aPeña-Chilet, Maria1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/mechanistic-modeling-sars-cov-2-disease-map02321nas a2200241 4500008004100000022001400041245014100055210006900196260001500265490000600280520146700286653001101753653004301764653001101807653000901818653001401827653002401841100001801865700001801883700002401901700002001925856013401945 2020 eng d a2073-440900aMechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments.0 aMechanistic Models of Signaling Pathways Reveal the Drug Action  c2020 06 290 v93 a

Despite the existence of differences in gene expression across numerous genes between males and females having been known for a long time, these have been mostly ignored in many studies, including drug development and its therapeutic use. In fact, the consequences of such differences over the disease mechanisms or the drug action mechanisms are completely unknown. Here we applied mechanistic mathematical models of signaling activity to reveal the ultimate functional consequences that gender-specific gene expression activities have over cell functionality and fate. Moreover, we also used the mechanistic modeling framework to simulate the drug interventions and unravel how drug action mechanisms are affected by gender-specific differential gene expression. Interestingly, some cancers have many biological processes significantly affected by these gender-specific differences (e.g., bladder or head and neck carcinomas), while others (e.g., glioblastoma or rectum cancer) are almost insensitive to them. We found that many of these gender-specific differences affect cancer-specific pathways or in physiological signaling pathways, also involved in cancer origin and development. Finally, mechanistic models have the potential to be used for finding alternative therapeutic interventions on the pathways targeted by the drug, which lead to similar results compensating the downstream consequences of gender-specific differences in gene expression.

10aFemale10aGene Expression Regulation, Neoplastic10aHumans10aMale10aNeoplasms10aSignal Transduction1 aCubuk, Cankut1 aCan, Fatma, E1 aPeña-Chilet, Maria1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/mechanistic-models-signaling-pathways-reveal-drug-action-mechanisms-behind-gender-specific02256nas a2200277 4500008004100000022001400041245011400055210006900169260001600238300000700254490000700261520126600268653002601534653004301560653001101603653004201614653002401656653001801680653002401698100002201722700001901744700001801763700003101781700002001812856014601832 2018 eng d a1745-615000aModels of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome.0 aModels of cell signaling uncover molecular mechanisms of highris c2018 Aug 22 a160 v133 a

BACKGROUND: Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40-50%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases.

RESULTS: Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression.

CONCLUSION: We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker.

REVIEWERS: This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers' comments section.

10aComputational Biology10aGene Expression Regulation, Neoplastic10aHumans10aJNK Mitogen-Activated Protein Kinases10aModels, Theoretical10aNeuroblastoma10aSignal Transduction1 aHidalgo, Marta, R1 aAmadoz, Alicia1 aCubuk, Cankut1 aCarbonell-Caballero, José1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/models-cell-signaling-uncover-molecular-mechanisms-high-risk-neuroblastoma-and-predict-disease-outcome