The Tumor Microenvironment as a Barrier to Cancer Nanotherapy

Polyvinylpyrrolidone Assisted One-Pot Synthesis of Size-Tunable Cocktail Nanodrug for Multifunctional Combat of Cancer

Background

The in vivo barriers and multidrug resistance (MDR) are well recognized as great challenges for the fulfillment of antitumor effects of current drugs, which calls for the development of novel therapeutic agents and innovative drug delivery strategies. Nanodrug (ND) combining multiple drugs with distinct modes of action holes the potential to circumvent these challenges, while the introduction of photothermal therapy (PTT) can give further significantly enhanced efficacy in cancer therapy. However, facile preparation of ND which contains dual drugs and photothermal capability with effective cancer treatment ability has rarely been reported.

Methods

In this study, we selected curcumin (Cur) and doxorubicin (Dox) as two model drugs for the creation of a cocktail ND (Cur-Dox ND). We utilized polyvinylpyrrolidone (PVP) as a stabilizer and regulator to prepare Cur-Dox ND in a straightforward one-pot method.

Results

The size of the resulting Cur-Dox ND can be easily adjusted by tuning the charged ratios. It was noted that both loaded drugs in Cur-Dox ND can realize their functions in the same target cell. Especially, the P-glycoprotein inhibition effect of Cur can synergistically cooperate with Dox, leading to enhanced inhibition of 4T1 cancer cells. Furthermore, Cur-Dox ND exhibited pH-responsive dissociation of loaded drugs and a robust photothermal translation capacity to realize multifunctional combat of cancer for photothermal enhanced anticancer performance. We further demonstrated that this effect can also be realized in 3D multicellular model, which possibly attributed to its superior drug penetration as well as photothermal-enhanced cellular uptake and drug release.

Conclusion

In summary, Cur-Dox ND might be a promising ND for better cancer therapy.

Anti-tumor effect of pH-sensitive drug-loaded nanoparticles optimized via an integrated computational/experimental approach

The acidic pH of tumor tissue has been used to trigger drug release from nanoparticles. However, dynamic interactions between tumor pH and vascularity present challenges to optimize therapy to particular microenvironment conditions. Despite recent development of pH-sensitive nanomaterials that can accurately quantify drug release from nanoparticles, tailoring release to maximize tumor response remains elusive. This study hypothesizes that a computational modeling-based platform that simulates the heterogeneously vascularized tumor microenvironment can enable evaluation of the complex intra-tumoral dynamics involving nanoparticle transport and pH-dependent drug release, and predict optimal nanoparticle parameters to maximize the response. To this end, SPNCD nanoparticles comprising superparamagnetic cores of iron oxide (Fe3O4) and a poly(lactide-co-glycolide acid) shell loaded with doxorubicin (DOX) were fabricated. Drug release was measured in vitro as a function of pH. A 2D model of vascularized tumor growth was calibrated to experimental data and used to evaluate SPNCD effect as a function of drug release rate and tissue vascular heterogeneity. Simulations show that pH-dependent drug release from SPNCD delays tumor regrowth more than DOX alone across all levels of vascular heterogeneity, and that SPNCD significantly inhibit tumor radius over time compared to systemic DOX. The minimum tumor radius forecast by the model was comparable to previous in vivo SPNCD inhibition data. Sensitivity analyses of the SPNCD pH-dependent drug release rate indicate that slower rates are more inhibitory than faster rates. We conclude that an integrated computational and experimental approach enables tailoring drug release by pH-responsive nanomaterials to maximize the tumor response.

Biologic Impact of Green Synthetized Magnetic Iron Oxide Nanoparticles on Two Different Lung Tumorigenic Monolayers and a 3D Normal Bronchial Model-EpiAirwayTM Microtissue

The present study reports the successful synthesis of biocompatible magnetic iron oxide nanoparticles (MNPs) by an ecofriendly single step method, using two ethanolic extracts based on leaves of Camellia sinensis L. and Ocimum basilicum L. The effect of both green raw materials as reducing and capping agents was taken into account for the development of MNPs, as well as the reaction synthesis temperature (25 °C and 80 °C). The biological effect of the MNPs obtained from Camellia sinensis L. ethanolic extract (Cs 25, Cs 80) was compared with that of the MNPs obtained from Ocimum basilicum L. ethanolic extract (Ob 25, Ob 80), by using two morphologically different lung cancer cell lines (A549 and NCI-H460); the results showed that the higher cell viability impairment was manifested by A549 cells after exposure to MNPs obtained from Ocimum basilicum L. ethanolic extract (Ob 25, Ob 80). Regarding the biosafety profile of the MNPs, it was shown that the EpiAirway^TM models did not elicit important viability decrease or significant histopathological changes after treatment with none of the MNPs (Cs 25, Cs 80 and Ob 25, Ob 80), at concentrations up to 500 µg/mL.

Gold Nanoparticles Contact with Cancer Cell: A Brief Update

The fine-tuning of the physicochemical properties of gold nanoparticles has facilitated the rapid development of multifunctional gold-based nanomaterials with diagnostic, therapeutic, and therapeutic applications. Work on gold nanoparticles is increasingly focusing on their cancer application. This review provides a summary of the main biological effects exerted by gold nanoparticles on cancer cells and highlights some critical factors involved in the interaction process (protein corona, tumor microenvironment, surface functionalization). The review also contains a brief discussion of the application of gold nanoparticles in target discovery.

Gold nanoparticles and obese adipose tissue microenvironment in cancer treatment

The epidemiological correlation between obesity and cancer is well characterized, but the biological mechanisms which regulate tumor development and response to therapy in obese cancer patients remain unclear. The tumor microenvironment plays an important role in protecting cancer cells by altering the delivery of anticancer therapy to the tumor tissue, reducing the efficacy of treatment. Obese tumor microenvironment provides additional benefits to the survival of tumor cells against anticancer therapies by altering the extracellular matrix composition, angiogenesis processes and the immune cells profile. Nanotechnology, and in particular gold nanoparticles, are being researched as a theranostic strategy for cancer treatment due to their ability to sensitize cancer cells to radiation and photodynamic therapy, enhance delivery of drugs to tumor cells, and in diagnostic applications. Adipose tissue and the obese tumor microenvironment may alter the activity of nanotherapeutics. In this article, we reviewed the current state of our understanding about the mechanisms by which the obese tumor microenvironment may alter the delivery and efficacy of anti-cancer treatments, and why the use of gold nanoparticles may represent an interesting strategy for cancer treatment in the obesity setting.

Evaluation of solid tumor response to sequential treatment cycles via a new computational hybrid approach

The development of an in silico approach that evaluates and identifies appropriate treatment protocols for individuals could help grow personalized treatment and increase cancer patient lifespans. With this motivation, the present study introduces a novel approach for sequential treatment cycles based on simultaneously examining drug delivery, tumor growth, and chemotherapy efficacy. This model incorporates the physical conditions of tumor geometry, including tumor, capillary network, and normal tissue assuming real circumstances, as well as the intravascular and interstitial fluid flow, drug concentration, chemotherapy efficacy, and tumor recurrence. Three treatment approaches-maximum tolerated dose (MTD), metronomic chemotherapy (MC), and chemo-switching (CS)-as well as different chemotherapy schedules are investigated on a real tumor geometry extracted from image. Additionally, a sensitivity analysis of effective parameters of drug is carried out to evaluate the potential of using different other drugs in cancer treatment. The main findings are: (i) CS, MC, and MTD have the best performance in reducing tumor cells, respectively; (ii) multiple doses raise the efficacy of drugs that have slower clearance, higher diffusivity, and lower to medium binding affinities; (iii) the suggested approach to eradicating tumors is to reduce their cells to a predetermined rate through chemotherapy and then apply adjunct therapy.

Complex Factors and Challenges that Affect the Pharmacology, Safety and Efficacy of Nanocarrier Drug Delivery Systems

Major developments in nanomedicines, such as nanoparticles (NPs), nanosomes, and conjugates, have revolutionized drug delivery capabilities over the past four decades. Although nanocarrier agents provide numerous advantages (e.g., greater solubility and duration of systemic exposure) compared to their small-molecule counterparts, there is considerable inter-patient variability seen in the systemic disposition, tumor delivery and overall pharmacological effects (i.e., anti-tumor efficacy and unwanted toxicity) of NP agents. This review aims to provide a summary of fundamental factors that affect the disposition of NPs in the treatment of cancer and why they should be evaluated during preclinical and clinical development. Furthermore, this chapter will highlight some of the translational challenges associated with elements of NPs and how these issues can only be addressed by detailed and novel pharmacology studies.

Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis

The tumor microenvironment (TME) presents a challenging barrier for effective nanotherapy-mediated drug delivery to solid tumors. In particular for tumors less vascularized than the surrounding normal tissue, as in liver metastases, the structure of the organ itself conjures with cancer-specific behavior to impair drug transport and uptake by cancer cells. Cells and elements in the TME of hypovascularized tumors play a key role in the process of delivery and retention of anti-cancer therapeutics by nanocarriers. This brief review describes the drug transport challenges and how they are being addressed with advanced in vitro 3D tissue models as well as with in silico mathematical modeling. This modeling complements network-oriented techniques, which seek to interpret intra-cellular relevant pathways and signal transduction within cells and with their surrounding microenvironment. With a concerted effort integrating experimental observations with computational analyses spanning from the molecular- to the tissue-scale, the goal of effective nanotherapy customized to patient tumor-specific conditions may be finally realized.

Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles

The pharmacokinetics of nanoparticle-borne drugs targeting tumors depends critically on nanoparticle design. Empirical approaches to evaluate such designs in order to maximize treatment efficacy are time- and cost-intensive. We have recently proposed the use of computational modeling of nanoparticle-mediated drug delivery targeting tumor vasculature coupled with numerical optimization to pursue optimal nanoparticle targeting and tumor uptake. Here, we build upon these studies to evaluate the effect of tumor size on optimal nanoparticle design by considering a cohort of heterogeneously-sized tumor lesions, as would be clinically expected. The results indicate that smaller nanoparticles yield higher tumor targeting and lesion regression for larger-sized tumors. We then augment the nanoparticle design optimization problem by considering drug diffusivity, which yields a two-fold tumor size decrease compared to optimizing nanoparticles without this consideration. We quantify the tradeoff between tumor targeting and size decrease using bi-objective optimization, and generate five Pareto-optimal nanoparticle designs. The results provide a spectrum of treatment outcomes - considering tumor targeting vs. antitumor effect - with the goal to enable therapy customization based on clinical need. This approach could be extended to other nanoparticle-based cancer therapies, and support the development of personalized nanomedicine in the longer term.

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.

Enhanced penetration and cytotoxicity of metformin and collagenase conjugated gold nanoparticles in breast cancer spheroids

AIMS

The extracellular matrix (ECM) within the tumor nest plays a key role in cancer cell proliferation and invasion. It has been proven that the increased density of ECM, especially collagen network, correlates with the poor distribution of gold-nanoparticles (GNPs) to the tumor mass. Here, for the first time, we examined the combined effect of collagenase (COL) with metformin (MET)-conjugated GNPs on mammosphere generated from JIMT-1 breast cell line in vitro.

MAIN METHODS

Mammospheres (on days 7 and 14) and monolayer culture were treated with MET, MET-GNPs, and a mixture of COL-GNPs and MET-GNPs for 5 days. To assess the impacts of the engineered nanoparticles (NPs) on the survival/apoptosis of cancer cells and cancer stem cells (CSCs), the amount/activity of collagen and the expression of pyruvate kinase M2, different methods were applied, including MTT, flow cytometry, immunofluorescence, ELISA and real-time PCR analyses. Our results confirmed the enhanced cytotoxic effects of MET-GNPs combined with COL-GNPs on mammospheres compared to the cells treated with MET alone or MET-GNPs.

KEY FINDINGS

Upon treatment with the mixture of MET-GNPs and COL-GNPs, the population of the apoptotic cells was significantly increased. A marked reduction was found in the number of CD24^-/CD44⁺ CSCs and the amount of collagen in the group received a mixture of MET-GNPs and COL-GNPs.

SIGNIFICANCE

Based on our findings, the use of COL can improve the cellular interaction/penetration of MET-GNPs in mammospheres and its antitumor impacts on the CSCs.

Design Optimization of Tumor Vasculature-Bound Nanoparticles

Nanotherapy may constitute a promising approach to target tumors with anticancer drugs while minimizing systemic toxicity. Computational modeling can enable rapid evaluation of nanoparticle (NP) designs and numerical optimization. Here, an optimization study was performed using an existing tumor model to find NP size and ligand density that maximize tumoral NP accumulation while minimizing tumor size. Optimal NP avidity lies at lower bound of feasible values, suggesting reduced ligand density to prolong NP circulation. For the given set of tumor parameters, optimal NP diameters were 288 nm to maximize NP accumulation and 334 nm to minimize tumor diameter, leading to uniform NP distribution and adequate drug load. Results further show higher dependence of NP biodistribution on the NP design than on tumor morphological parameters. A parametric study with respect to drug potency was performed. The lower the potency of the drug, the bigger the difference is between the maximizer of NP accumulation and the minimizer of tumor size, indicating the existence of a specific drug potency that minimizes the differential between the two optimal solutions. This study shows the feasibility of applying optimization to NP designs to achieve efficacious cancer nanotherapy, and offers a first step towards a quantitative tool to support clinical decision making.

Nanoparticle-mediated drug delivery to treat infections in the female reproductive tract: evaluation of experimental systems and the potential for mathematical modeling

A variety of drug-delivery platforms have been employed to deliver therapeutic agents across cervicovaginal mucus (CVM) and the vaginal mucosa, offering the capability to increase the longevity and retention of active agents to treat infections of the female reproductive tract (FRT). Nanoparticles (NPs) have been shown to improve retention, diffusion, and cell-specific targeting via specific surface modifications, relative to other delivery platforms. In particular, polymeric NPs represent a promising option that has shown improved distribution through the CVM. These NPs are typically fabricated from nontoxic, non-inflammatory, US Food and Drug Administration-approved polymers that improve biocompatibility. This review summarizes recent experimental studies that have evaluated NP transport in the FRT, and highlights research areas that more thoroughly and efficiently inform polymeric NP design, including mathematical modeling. An overview of the in vitro, ex vivo, and in vivo NP studies conducted to date – whereby transport parameters are determined, extrapolated, and validated – is presented first. The impact of different NP design features on transport through the FRT is summarized, and gaps that exist due to the limitations of iterative experimentation alone are identified. The potential of mathematical modeling to complement the characterization and evaluation of diffusion and transport of delivery vehicles and active agents through the CVM and mucosa is discussed. Lastly, potential advancements combining experimental and mathematical knowledge are suggested to inform next-generation NP designs, such that infections in the FRT may be more effectively treated.

Modeling triple-negative breast cancer heterogeneity: Effects of stromal macrophages, fibroblasts and tumor vasculature

A hallmark of breast tumors is its spatial heterogeneity that includes its distribution of cancer stem cells and progenitor cells, but also heterogeneity in the tumor microenvironment. In this study we focus on the contributions of stromal cells, specifically macrophages, fibroblasts, and endothelial cells on tumor progression. We develop a computational model of triple-negative breast cancer based on our previous work and expand it to include macrophage infiltration, fibroblasts, and angiogenesis. In vitro studies have shown that the secretomes of tumor-educated macrophages and fibroblasts increase both the migration and proliferation rates of triple-negative breast cancer cells. In vivo studies also demonstrated that blocking signaling of selected secreted factors inhibits tumor growth and metastasis in mouse xenograft models. We investigate the influences of increased migration and proliferation rates on tumor growth, the effect of the presence on fibroblasts or macrophages on growth and morphology, and the contributions of macrophage infiltration on tumor growth. We find that while the presence of macrophages increases overall tumor growth, the increase in macrophage infiltration does not substantially increase tumor growth and can even stifle tumor growth at excessive rates.

Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models

We offer a critique of what constitutes a suitable dosage limit, in both clinical and preclinical studies, for interstitially administered magnetic nanoparticles in order to enable therapeutic hyperthermia under the action of an externally applied alternating magnetic field. We approach this first from the perspective of the currently approved clinical dosages of magnetic nanoparticles in the fields of MRI contrast enhancement, sentinel node detection, iron replacement therapy and magnetic thermoablation. We compare this to a simple analytical model of the achievable hyperthermia temperature rise in both humans and animals based on the interstitially administered dose, the heating and dispersion characteristics of the injected fluid, and the strength and frequency of the applied magnetic field. We show that under appropriately chosen conditions a therapeutic temperature rise is achievable in clinically relevant situations. We also show that in such cases it may paradoxically be harder to achieve the same therapeutic temperature rise in a preclinical model. We comment on the implications for the evidence-based translation of hyperthermia based interventions from the laboratory to the clinic.

Nanoformulations for combination or cascade anticancer therapy

Nanoparticle drug formulations have been extensively investigated, developed, and in some cases, approved by the Food and Drug Administration (FDA). Synergistic combinations of drugs having distinct tumor-inhibiting mechanisms and non-overlapping toxicity can circumvent the issue of treatment resistance and may be essential for effective anti-cancer therapy. At the same time, co-delivery of a combined regimen by a single nanocarrier presents a challenge due to differences in solubility, molecular weight, functional groups and encapsulation conditions between the two drugs. This review discusses cellular and microenvironment mechanisms behind treatment resistance and nanotechnology-based solutions for effective anti-cancer therapy. Co-loading or cascade delivery of multiple drugs using of polymeric nanoparticles, polymer-drug conjugates and lipid nanoparticles will be discussed along with lipid-coated drug nanoparticles developed by our lab and perspectives on combination therapy.