In silico signaling modeling to understand cancer pathways and treatment responses. (15th April 2019)

• Record Type: Journal Article
• Authors: Kunz, Meik; Jeromin, Julian; Fuchs, Maximilian; Christoph, Jan; Veronesi, Giulia; Flentje, Michael; Nietzer, Sarah; Dandekar, Gudrun; Dandekar, Thomas
• Is Part Of: Briefings in bioinformatics. Volume 21:Number 3(2020)
• Page Start: 1115
• Page End: 1117
• Publication Date: 2019-04-15
• Subjects: in silico modeling -- cancer pathways -- precision medicine; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbz033
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Precision medicine has changed thinking in cancer therapy, highlighting a better understanding of the individual clinical interventions. But what role do the drivers and pathways identified from pan-cancer genome analysis play in the tumor? In this letter, we will highlight the importance of in silico modeling in precision medicine. In the current era of big data, tumor engines and pathways derived from pan-cancer analysis should be integrated into in silico models to understand the mutational tumor status and individual molecular pathway mechanism at a deeper level. This allows to pre-evaluate the potential therapy response and develop optimal patient-tailored treatment strategies which pave the way to support precision medicine in the clinic of the future.