Application of Atlas of Cancer Signalling Network in preclinical studies. (3rd May 2018)

• Record Type: Journal Article
• Authors: Monraz Gomez, L Cristobal; Kondratova, Maria; Ravel, Jean-Marie; Barillot, Emmanuel; Zinovyev, Andrei; Kuperstein, Inna
• Is Part Of: Briefings in bioinformatics. Volume 20:Number 2(2019)
• Page Start: 701
• Page End: 716
• Publication Date: 2018-05-03
• Subjects: systems biology -- cancer -- signalling network maps -- omics data integration and analysis -- data visualization -- synthetic interactions -- drug response; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby031
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Cancer initiation and progression are associated with multiple molecular mechanisms. The knowledge of these mechanisms is expanding and should be converted into guidelines for tackling the disease. Here, we discuss the formalization of biological knowledge into a comprehensive resource: the Atlas of Cancer Signalling Network (ACSN) and the Google Maps-based tool NaviCell, which supports map navigation. The application of ACSN for omics data visualization, in the context of signalling maps, is possible via the NaviCell Web Service module and through the NaviCom tool. It allows generation of network-based molecular portraits of cancer using multilevel omics data. We review how these resources and tools are applied for cancer preclinical studies. Structural analysis of the maps together with omics data helps to rationalize the synergistic effects of drugs and allows design of complex disease stage-specific druggable interventions. The use of ACSN modules and maps as signatures of biological functions can help in cancer data analysis and interpretation. In addition, they empowered finding of associations between perturbations in particular molecular mechanisms and the risk to develop a specific type of cancer. These approaches are helpful, among others, to study the interplay between molecular mechanisms of cancer. It opens an opportunity to decipher how gene interactions govern the hallmarks of cancer in specific contexts. We discuss a perspective to develop a flexible methodology and a pipeline to enable systematic omics data analysis in the context of signalling network maps, for stratifying patients and suggesting interventions points and drug repositioning in cancer and other diseases.