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In silico signaling modeling to understand cancer pathways and treatment responses

 
: Kunz, Meik; Jeromin, Julian; Fuchs, Maximilian; Christoph, Jan; Veronesi, Giulia; Flentje, Michael; Nietzer, Sarah; Dandekar, Gudrun; Dandekar, Thomas

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Briefings in bioinformatics 21 (2020), Nr.3, S.1115-1117
ISSN: 1467-5463
ISSN: 1477-4054
Englisch
Zeitschriftenaufsatz
Fraunhofer ISC ()
in silico modeling; cancer pathways; precision medicine; cancer driver; BRAF mutation

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.

: http://publica.fraunhofer.de/dokumente/N-593119.html