Literature DB >> 25112814

Signaling networks in MS: a systems-based approach to developing new pharmacological therapies.

Ekaterina Kotelnikova1, Marti Bernardo-Faura2, Gilad Silberberg3, Narsis A Kiani3, Dimitris Messinis4, Ioannis N Melas5, Laura Artigas6, Elena Schwartz7, Ilya Mazo7, Mar Masso8, Leonidas G Alexopoulos9, Jose Manuel Mas6, Tomas Olsson10, Jesper Tegner3, Roland Martin11, Albert Zamora8, Friedemann Paul12, Julio Saez-Rodriguez2, Pablo Villoslada13.   

Abstract

The pathogenesis of multiple sclerosis (MS) involves alterations to multiple pathways and processes, which represent a significant challenge for developing more-effective therapies. Systems biology approaches that study pathway dysregulation should offer benefits by integrating molecular networks and dynamic models with current biological knowledge for understanding disease heterogeneity and response to therapy. In MS, abnormalities have been identified in several cytokine-signaling pathways, as well as those of other immune receptors. Among the downstream molecules implicated are Jak/Stat, NF-Kb, ERK1/3, p38 or Jun/Fos. Together, these data suggest that MS is likely to be associated with abnormalities in apoptosis/cell death, microglia activation, blood-brain barrier functioning, immune responses, cytokine production, and/or oxidative stress, although which pathways contribute to the cascade of damage and can be modulated remains an open question. While current MS drugs target some of these pathways, others remain untouched. Here, we propose a pragmatic systems analysis approach that involves the large-scale extraction of processes and pathways relevant to MS. These data serve as a scaffold on which computational modeling can be performed to identify disease subgroups based on the contribution of different processes. Such an analysis, targeting these relevant MS-signaling pathways, offers the opportunity to accelerate the development of novel individual or combination therapies.
© The Author(s), 2014.

Entities:  

Keywords:  Multiple sclerosis; drug discovery; pathways; signaling; systems biology

Mesh:

Year:  2014        PMID: 25112814     DOI: 10.1177/1352458514543339

Source DB:  PubMed          Journal:  Mult Scler        ISSN: 1352-4585            Impact factor:   6.312


  5 in total

1.  Differential Neuroproteomic and Systems Biology Analysis of Spinal Cord Injury.

Authors:  Ahmed Moghieb; Helen M Bramlett; Jyotirmoy H Das; Zhihui Yang; Tyler Selig; Richard A Yost; Michael S Wang; W Dalton Dietrich; Kevin K W Wang
Journal:  Mol Cell Proteomics       Date:  2016-05-05       Impact factor: 5.911

2.  MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysis.

Authors:  Ekaterina Kotelnikova; Narsis A Kiani; Dimitris Messinis; Inna Pertsovskaya; Vicky Pliaka; Marti Bernardo-Faura; Melanie Rinas; Gemma Vila; Irati Zubizarreta; Irene Pulido-Valdeolivas; Theodore Sakellaropoulos; Wolfgang Faigle; Gilad Silberberg; Mar Masso; Pernilla Stridh; Janina Behrens; Tomas Olsson; Roland Martin; Friedemann Paul; Leonidas G Alexopoulos; Julio Saez-Rodriguez; Jesper Tegner; Pablo Villoslada
Journal:  Proc Natl Acad Sci U S A       Date:  2019-04-19       Impact factor: 11.205

3.  Identifying characteristic miRNAs-genes and risk pathways of multiple sclerosis based on bioinformatics analysis.

Authors:  Deling Luo; Jin Fu
Journal:  Oncotarget       Date:  2018-01-02

4.  Dynamics and heterogeneity of brain damage in multiple sclerosis.

Authors:  Ekaterina Kotelnikova; Narsis A Kiani; Elena Abad; Elena H Martinez-Lapiscina; Magi Andorra; Irati Zubizarreta; Irene Pulido-Valdeolivas; Inna Pertsovskaya; Leonidas G Alexopoulos; Tomas Olsson; Roland Martin; Friedemann Paul; Jesper Tegnér; Jordi Garcia-Ojalvo; Pablo Villoslada
Journal:  PLoS Comput Biol       Date:  2017-10-26       Impact factor: 4.475

5.  Prediction of combination therapies based on topological modeling of the immune signaling network in multiple sclerosis.

Authors:  Melanie Rinas; Jakob Wirbel; Marti Bernardo-Faura; Inna Pertsovskaya; Vicky Pliaka; Dimitris E Messinis; Gemma Vila; Theodore Sakellaropoulos; Wolfgang Faigle; Pernilla Stridh; Janina R Behrens; Tomas Olsson; Roland Martin; Friedemann Paul; Leonidas G Alexopoulos; Pablo Villoslada; Julio Saez-Rodriguez
Journal:  Genome Med       Date:  2021-07-16       Impact factor: 11.117

  5 in total

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