Application of Computational Screening Tools and Nanotechnology for Enhanced Drug Synergism in Cancer Therapy

Background: Chemoresistance continues to limit the recovery of patients with cancer. New strategies, such as combination therapy or nanotechnology, can be further improved. Objective: In this study, we applied the computational strategy by exploiting two databases (CellMiner and Prism) to sort out the cell lines sensitive to both anti-cancer drugs, paclitaxel (PTX) and dihydroartemisinin (DHA); both of which are potentially synergistic in several cell lines. Methods: The combination of PTX and DHA was screened at different ratios to select the optimal ratio that could inhibit lung adenocarcinoma NCI-H23 the most. To further enhance therapeutic efficacy, these combinations of drugs were incorporated into a nanosystem. Results: At a PTX:DHA ratio of 1:2 (w/w), the combined drugs obtained the best combination index (0.84), indicating a synergistic effect. The drug-loaded nanoparticles sized at 135 nm with the drug loading capacity of 15.5 ± 1.34 and 13.8 ± 0.56 corresponding to DHA and PTX, respectively, were used. The nano-sized particles improved drug internalization into the cells, resulting in the significant inhibition of cell growth at all tested concentrations (p < 0.001). Additionally, α-tubulin aggregation, DNA damage suggested the molecular mechanism behind cell death upon PTX-DHA-loaded nanoparticle treatment. Moreover, the rate of apoptosis increased from approximately 5% to more than 20%, and the expression of apoptotic proteins changed 4 and 3 folds corresponding to p-53 and Bcl-2, respectively. Conclusion: This study was designed thoroughly by screening cell lines for the optimization of formulations. This novel approach could pave the way for the selection of combined drugs for precise cancer treatment.