Briefings in BioinformaticsSystems BiologyPeer-reviewed journal article
Application of Atlas of Cancer Signalling Network in pre-clinical studies
Luis Cristóbal Monraz GómeziD, Maria Kondratova, Jean‐Marie RaveliD, Emmanuel BarillotiD, Andrei Y. ZinovyeviD, Inna KupersteiniD
Abstract
Initiation and progression of cancer involve multiple molecular mechanisms. The knowledge on these mechanisms is expanding and should be converted into guidelines for tackling the disease. We discuss here formalization of biological knowledge into a comprehensive resource Atlas of Cancer Signalling Network (ACSN) and Google Maps-based tool NaviCell that supports map navigation. The application of maps for omics data visualisation in the context of signalling maps is possible using NaviCell Web Service module and NaviCom tool for generation of network-based molecular portraits of cancer using multi-level omics data. We review how these resources and tools are applied for cancer pre-clinical studies among others for rationalizing synergistic effect of drugs and designing complex disease stage-specific druggable interventions following structural analysis of the maps together with omics data. Modules and maps of ACSN as signatures of biological functions, can help in cancer data analysis and interpretation. In addition, they can also be used to find association between perturbations in particular molecular mechanisms to the risk of a specific cancer type development. These approaches and beyond help to study interplay between molecular mechanisms of cancer, deciphering how gene interactions govern hallmarks of cancer in specific context. 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 human diseases.
- organism: human
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- research focus: benchmarking
- approach: statistical model
- Citations
- 25
- FWCI
- 0.29
- Field percentile
- 27th percentile
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