Synergistic Enhancement of Lung Cancer Therapy Through Nanocarrier‐Mediated Sequential Delivery of Superantigen and Tyrosin Kinase Inhibitor

Li, Da; Li, Yongbin; Xing, Haibo; Guo, Junling; Yuan, Ping; Tang, Guping

doi:10.1002/adfm.201400456

Cited by 19 publications

(22 citation statements)

References 45 publications

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“…11,99–101 As the liposomes constituted a structural component of the hybrid hydrogels, we anticipated that the multicomponent network would offer opportunities for dual encapsulation and differential release of multiple therapeutic cargo molecules. To examine the potential suitability of these hybrid hydrogels for such applications, cytochrome c, a small mitochondrial protein (~12 kDa) that can initiate an apoptotic cascade leading to programmed cell death upon cytoplasmic release, 102–105 was chosen as a second therapeutic molecule.…”

Section: Resultsmentioning

confidence: 99%

Liposome-Cross-Linked Hybrid Hydrogels for Glutathione-Triggered Delivery of Multiple Cargo Molecules

Liang¹,

Kiick

2016

Biomacromolecules

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Novel, liposome-cross-linked hybrid hydrogels cross-linked by the Michael-type addition of thiols with maleimides were prepared via the use of maleimide-functionalized liposome cross-linkers and thiolated polyethylene glycol (PEG) polymers. Gelation of the materials was confirmed by oscillatory rheology experiments. These hybrid hydrogels are rendered degradable upon exposure to thiol-containing molecules such as glutathione (GSH), via the incorporation of selected thioether succinimide cross-links between the PEG polymers and liposome nanoparticles. Dynamic light scattering (DLS) characterization confirmed that intact liposomes were released upon network degradation. Owing to the hierarchical structure of the network, multiple cargo molecules relevant for chemotherapies, namely doxorubicin (DOX) and cytochrome c, were encapsulated and simultaneously released from the hybrid hydrogels, with differential release profiles that were driven by degradation-mediated release and Fickian diffusion, respectively. This work introduces a facile approach for the development of advanced, hybrid drug delivery vehicles that exhibit novel chemical degradation.

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Section: Resultsmentioning

confidence: 99%

Liposome-Cross-Linked Hybrid Hydrogels for Glutathione-Triggered Delivery of Multiple Cargo Molecules

Liang¹,

Kiick

2016

Biomacromolecules

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“…The other strategy to achieve programmed release of the combined drugs is through multiple intravenous injections of single‐drug loaded nanoparticles at different times. Sequential treatment through this strategy revealed a synergistic effect on tumor inhibition, however, the strategy caused inconvenience in the treatment process and the limitations of intravenous injection still existed …”

Section: Introductionmentioning

confidence: 99%

A Time‐Programmed Release of Dual Drugs from an Implantable Trilayer Structured Fiber Device for Synergistic Treatment of Breast Cancer

Hou

et al. 2019

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Combination chemotherapy with time‐programmed administration of multiple drugs is a promising method for cancer treatment. However, realizing time‐programmed release of combined drugs from a single carrier is still a great challenge in enhanced cancer therapy. Here, an implantable trilayer structured fiber device is developed to achieve time‐programmed release of combined drugs for synergistic treatment of breast cancer. The fiber device is prepared by a modified microfluidic‐electrospinning technique. The glycerol solution containing chemotherapy agent doxorubicin (Dox) forms the internal periodic cavities of the fiber, and poly(l‐lactic acid) and poly(ε‐caprolactone) containing the angiogenesis inhibitor apatinib (Apa) form the double walls of the fiber. Rapid release of Dox can be obtained by adjusting the wall thickness of the cavities, meanwhile sustained release of Apa is achieved through the slow degradation of the fiber matrix. After the fiber device is implanted subcutaneously near to the implanted solid tumor of mice, an excellent synergistic therapeutic effect is achieved through time‐programmed release of the combined dual drugs. The fiber device provides a platform to sequentially co‐deliver dual or multiple drugs for enhanced combined therapeutic efficacy.

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“…For example, Huang et al [136] designed a computational tool that can be used to predict synergistic drug combinations based on network analysis of genomic profiles of both drugs and cancers. In addition, the scheduling of drug administration in terms of timing and dose in the temporal combination of drugs profoundly influences therapeutic efficacy [141, 142]. In the future, computational modeling is anticipated to facilitate the design of the temporal combination of drugs and to optimize the scheduling of drug administration for improving treatment efficacy.…”

Section: Discussionmentioning

confidence: 99%

Mathematical modeling and computational prediction of cancer drug resistance

Sun

2017

Briefings in Bioinformatics

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Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine.

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Synergistic Enhancement of Lung Cancer Therapy Through Nanocarrier‐Mediated Sequential Delivery of Superantigen and Tyrosin Kinase Inhibitor

Cited by 19 publications

References 45 publications

Liposome-Cross-Linked Hybrid Hydrogels for Glutathione-Triggered Delivery of Multiple Cargo Molecules

Liposome-Cross-Linked Hybrid Hydrogels for Glutathione-Triggered Delivery of Multiple Cargo Molecules

A Time‐Programmed Release of Dual Drugs from an Implantable Trilayer Structured Fiber Device for Synergistic Treatment of Breast Cancer

Mathematical modeling and computational prediction of cancer drug resistance

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