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Towards Optimal Design of Cancer Nanomedicines: Multi-stage Nanoparticles for the Treatment of Solid Tumors.

ABSTRACT: Conventional drug delivery systems for solid tumors are composed of a nano-carrier that releases its therapeutic load. These two-stage nanoparticles utilize the enhanced permeability and retention (EPR) effect to enable preferential delivery to tumor tissue. However, the size-dependency of the EPR, the limited penetration of nanoparticles into the tumor as well as the rapid binding of the particles or the released cytotoxic agents to cancer cells and stromal components inhibit the uniform distribution of the drug and the efficacy of the treatment. Here, we employ mathematical modeling to study the effect of particle size, drug release rate and binding affinity on the distribution and efficacy of nanoparticles to derive optimal design rules. Furthermore, we introduce a new multi-stage delivery system. The system consists of a 20-nm primary nanoparticle, which releases 5-nm secondary particles, which in turn release the chemotherapeutic drug. We found that tuning the drug release kinetics and binding affinities leads to improved delivery of the drug. Our results also indicate that multi-stage nanoparticles are superior over two-stage nano-carriers provided they have a faster drug release rate and for high binding affinity drugs. Furthermore, our results suggest that smaller nanoparticles achieve better treatment outcome.

SUBMITTER: Stylianopoulos T

PROVIDER: S-EPMC4519365 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Towards Optimal Design of Cancer Nanomedicines: Multi-stage Nanoparticles for the Treatment of Solid Tumors.

Stylianopoulos Triantafyllos T Economides Eva-Athena EA Baish James W JW Fukumura Dai D Jain Rakesh K RK

Annals of biomedical engineering 20150211 9

Conventional drug delivery systems for solid tumors are composed of a nano-carrier that releases its therapeutic load. These two-stage nanoparticles utilize the enhanced permeability and retention (EPR) effect to enable preferential delivery to tumor tissue. However, the size-dependency of the EPR, the limited penetration of nanoparticles into the tumor as well as the rapid binding of the particles or the released cytotoxic agents to cancer cells and stromal components inhibit the uniform distri ...[more]

PMID: 25670323

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Project description:BACKGROUND: Electrochemotherapy treats tumors by combining specific chemotherapeutic drugs with an intracellular target and electric pulses, which increases drug uptake into the tumor cells. Electrochemotherapy has been successfully used for treatment of easily accessible superficial tumor nodules. In this paper, we present the first case of deep-seated tumor electrochemotherapy based on numerical treatment planning. METHODS: The aim of our study was to treat a melanoma metastasis in the thigh of a patient. Treatment planning for electrode positioning and electrical pulse parameters was performed for two different electrode configurations: one with four and another with five long needle electrodes. During the procedure, the four electrode treatment plan was adopted and the patient was treated accordingly by electrochemotherapy with bleomycin. The response to treatment was clinically and radiographically evaluated. Due to a partial response of the treated tumor, the metastasis was surgically removed after 2 months and pathological analysis was performed. RESULTS: A partial response of the tumor to electrochemotherapy was obtained. Histologically, the metastasis showed partial necrosis due to electrochemotherapy, estimated to represent 40-50% of the tumor. Based on the data obtained, we re-evaluated the electrical treatment parameters in order to correlate the treatment plan with the clinical response. Electrode positions in the numerical model were updated according to the actual positions during treatment. We compared the maximum value of the measured electric current with the current predicted by the model and good agreement was obtained. Finally, tumor coverage with an electric field above the reversible threshold was recalculated and determined to be approximately 94%. Therefore, according to the calculations, a small volume of tumor cells remained viable after electrochemotherapy, and these were sufficient for tumor regrowth. CONCLUSIONS: In this, the first reported clinical case, deep-seated melanoma metastasis in the thigh of the patient was treated by electrochemotherapy, according to a treatment plan obtained by numerical modeling and optimization. Although only a partial response was obtained, the presented work demonstrates that treatment of deep-seated tumor nodules by electrochemotherapy is feasible and sets the ground for numerical treatment planning-based electrochemotherapy. TRIAL REGISTRATION: EudraCT:2008-008290-54.

Project description:The distribution of nanomedicines inside solid tumors is often restricted to perivascular areas, leaving most distal tumor cells out of reach. This partly explains modest patient benefit of many nanomedicines compared to their free-form counterparts. The objective for this study is to develop a mathematical model to quantitatively analyze this phenomenon and the influencing factors to such perivascular distribution and seek for effective strategies to alleviate this. A spatial tumor distribution model was firstly constructed to mimic the geometrical structure of tumor vessels and the surrounding tumor cells. This tumor model was further integrated with a systemic pharmacokinetics model for nanoparticles. A variety of factors on the tumor spatial distributions of nanomedicines were considered in the model. With the model, we quantified the effect of these influencing factors on tumor delivery efficacy (ID %), the magnitude of heterogeneous distribution (H index), and the effect of enhanced permeability and retention (EPR). In particularly, we compared the spatial distributions of the nanoparticles and the free payloads insides tumors. The model predicted high degrees of distributional heterogeneity for both nanoparticles and free payloads. The degree of heterogeneity and the influencing factors for free payloads were markedly different from those for nanoparticles. We found that nanoparticle diffusion coefficient was the most effective factor in reducing the nanoparticle H index but exerted moderate influence on the free payloads H index. The most effective factor in reducing the H index of free payload was payload diffusion coefficient. The factors that improved free payload distribution were closely associated with higher drug efficacy. In contrast, the factors that improved nanoparticle spatial distributions did not always confer improved anti-tumor efficacy of the delivered drug. These findings highlight the importance of assessing the heterogeneous free payload distribution in tumors for the development of effective nanomedicines.

Dataset Information

Towards Optimal Design of Cancer Nanomedicines: Multi-stage Nanoparticles for the Treatment of Solid Tumors.

Publications

Towards Optimal Design of Cancer Nanomedicines: Multi-stage Nanoparticles for the Treatment of Solid Tumors.

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