TY - JOUR
T1 - Application of Computational Screening Tools and Nanotechnology for Enhanced Drug Synergism in Cancer Therapy
AU - Ninh, Thu Thi Kim
AU - Tran, Tuan Hiep
AU - Huang, Chi Ying F.
AU - Nguyen, Chien Ngoc
N1 - Publisher Copyright:
© 2023 Bentham Science Publishers.
PY - 2023
Y1 - 2023
N2 - 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 dihydroar-temisinin (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 formu-lations. This novel approach could pave the way for the selection of combined drugs for precise cancer treatment.
AB - 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 dihydroar-temisinin (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 formu-lations. This novel approach could pave the way for the selection of combined drugs for precise cancer treatment.
KW - bio-computational tool
KW - cancer
KW - chemoresistance
KW - Combination therapy
KW - nanoparticles
KW - synergistic effect
UR - http://www.scopus.com/inward/record.url?scp=85158918162&partnerID=8YFLogxK
U2 - 10.2174/1567201819666220426092538
DO - 10.2174/1567201819666220426092538
M3 - Article
C2 - 35473527
AN - SCOPUS:85158918162
SN - 1567-2018
VL - 20
SP - 1015
EP - 1029
JO - Current Drug Delivery
JF - Current Drug Delivery
IS - 7
ER -