We generated human and mouse gastric cancer organoids modelling typical characteristics and altered pathways of human gastric cancer. Successful interference with activated pathways demonstrates their potential usefulness as living biomarkers for therapy response testing.

Drug-induced gene-expression profiles that invert disease profiles have recently been illustrated to be a starting point for drug repositioning. In this study, we validate this approach and focus on prediction of novel drugs for colorectal cancer, for which there is a pressing need to find novel antimetastatic compounds. We computationally predicted three novel and still unknown compounds against colorectal cancer: citalopram (an antidepressant), troglitazone (an antidiabetic), and enilconazole (a fungicide). We verified the compounds by in vitro assays of clonogenic survival, proliferation, and migration and in a subcutaneous mouse model. We found evidence that the mode of action of these compounds may be through inhibition of TGFb signaling. Furthermore, one compound, citalopram, reduced tumor size as well as the number of circulating tumor cells and metastases in an orthotopic mouse model of colorectal cancer. This study proposes citalopram as a potential therapeutic option for patients with colorectal cancer, illustrating the potential of systems pharmacology. Cancer Res; 74(20); 5690-9. Ó2014 AACR.

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