TY - JOUR A1 - Baur, Florentin A1 - Nietzer, Sarah L. A1 - Kunz, Meik A1 - Saal, Fabian A1 - Jeromin, Julian A1 - Matschos, Stephanie A1 - Linnebacher, Michael A1 - Walles, Heike A1 - Dandekar, Thomas A1 - Dandekar, Gudrun T1 - Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models JF - Cancers N2 - To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification. KW - in silico simulation KW - 3D tissue models KW - colorectal cancer KW - BRAF mutation KW - targeted therapy KW - stratification Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193798 SN - 2072-6694 VL - 12 IS - 1 ER -