In silico signaling modeling to understand cancer pathways and treatment responses

Author:

Kunz Meik1,Jeromin Julian2,Fuchs Maximilian2,Christoph Jan1,Veronesi Giulia3,Flentje Michael4,Nietzer Sarah5,Dandekar Gudrun56,Dandekar Thomas2

Affiliation:

1. Chair of Medical Informatics, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany

2. Functional Genomics and Systems Biology Group, Department of Bioinformatics, University of Würzburg, Würzburg, Germany

3. Humanitas Research Hospital, Rozzano (Milan), Italy

4. Department of Radiation Oncology, University Hospital of Würzburg, Würzburg, Germany

5. Chair of Tissue Engineering and Regenerative Medicine, University Hospital Wuerzburg, Roentgenring, Wuerzburg

6. Fraunhofer Institute for Silicate Research (ISC), Translational Center ‘Regenerative Therapies’ (TLC-RT), Roentgenring, Wuerzburg

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.

Funder

Federal Ministry of Education and Research

Era-Net

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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