Pluto Bioinformatics

GSE142340: Optimized high-order low-dose drug mixtures boost selectivity and efficacy of colorectal carcinoma treatment

Bulk RNA sequencing

Colorectal carcinoma is currently treated with a combination of chemotherapeutics, often supplemented with targeted drugs. Despite recent improvements, an urgent need exists for improved efficacy, especially at late stage disease, and minimized side effects. Therefore, we employed the recently developed mathematical approach of the phenotypically-driven therapeutically guided multidrug optimization (TGMO) technology, to identify individualized optimal drug combinations (ODCs). Using this technology we obtained low dose synergistic and selective ODCs for a panel of human colorectal carcinoma cells, active in 3-dimensional heterotypic co-culture models. RNA sequencing and phosphoproteomics analyses showed that the mechanisms of action of these ODCs converge towards MAP kinase signaling and cell cycle inhibition despite differential cell mutation status, transcript expression levels and protein kinase phosphorylation state. Two cell-specific ODCs were subsequently translated to two in vivo models. Interestingly, the ODCs reduced tumor growth by approximately 80% and significantly outperformed the standard chemotherapy (FOLFOX). Complete lack of toxicity was observed for the ODCs, while still significant after FOLFOX therapy. Pharmacokinetics demonstrated that the drug combinations showed significantly enhanced bioavailability. Finally, the high-order ODCs were also active in freshly isolated cells from patient tumor tissues. Taken together, we show that the TGMO technology efficiently guides towards selective and potent low-dose drug combinations, optimized regardless of tumor mutation status and outperforming conventional chemotherapy. SOURCE: Celine Delucinge University of Geneva