Predicting DNA-mediated drug delivery in interior carcinoma using electromagnetically excited nanoparticles

Abstract

Tumor-site-specific delivery of anti-cancer drugs remains one of the most prevailing problems in cancer treatment. While conventional means of chemo-delivery invariably leave different degrees of side-effects on healthy tissues, in recent times, intelligent chemical designs have been exploited to reduce the cross-consequences. In particular, the strategies involving superparamaganetic nanoparticles with surface assembled oligonucleotides as therapeutic carrier have raised affirmative promises. Process is designed in such a way that the therapeutic molecules are released preferentially at target site as the complementary oligonucleotide chains dissociate over the heat generated by the nanoparticles under the excitation of low frequency electromagnetic energy. In spite of the preliminary demonstrations, analytical comprehension of the entire process especially on the purview of non-trivial interactions between stochastic phase-transition phenomena of oligonucleotide chains and hierarchical organization of in vivo transport processes remains unknown. Here, we propose an integrated computational predictive model to interpret the efficacy of drug delivery in the aforementioned process. The basic physics of heat generation by superparamagnetic nanoparticles in presence of external electromagnetic field has been coupled with transient biological heat transfer model and the statistical mechanics based oligonucleotide denaturation dynamics. Conjunctionally, we have introduced a set of hierarchically appropriate transport processes to mimic the in vivo drug delivery system. The subsequent interstitial diffusion and convection of the various species involved in the process over time was simulated assuming a porous media model of the carcinoma. As a result, the model predictions exhibit excellent congruence with available experimental results. To delineate a broader spectrum of a priori speculations, we have investigated the effects of different tunable parameters such as magnetizing field strength, nanoparticle size, diffusion coefficients, porous media parameters and different oligonucleotide sequences on temperature rise and site-specific drug release. The proposed model, thus, provides a generic framework for the betterment of nanoparticle mediated drug delivery, which is expected to impart significant impact on cancer therapy.

Introduction

Targeting specific tumor site is a pivotal theme in modern medicine towards designing improved diagnosis and treatment of cancer. Pertinently, nanotechnology based drug delivery systems possess the ability of localized, controlled and targeted release of therapeutic chemicals with minimal perturbation to the neighboring normal cells [1], [2]. To this purpose, of diverse types of materials being experimented over the years, magnetic elements and alloys have been most effective, predominantly due to their easily modifiable surface chemistry, visibility to non-invasive methods such as magnetic resonance imaging (MRI) and most notably, exclusive efficacy in converting weak electromagnetic waves to extremely concentrated heat energy. The heating of magnetic nanoparticles arises due to different processes of magnetization reversal in the particle system [3], [4]. If the characteristics length scale of particle is reduced to few nanometers, intrinsic M–H curve becomes sigmoidal and, importantly, non-hysteretic. In this state, the magnetic moment of the particle is, as a whole, free to fluctuate in response to radiative energy, maintaining the individual atomic moments in their ordered state relative to each other. Simultaneously, the energy barrier for magnetization reversal also diminishes to such extent that thermal fluctuations can lead to relaxation phenomena. These effects, in juxtaposition, induce the heat generation process. It is pertinent to mention that the frequency range used (350–400 kHz) to activate the magnetic nanoparticles, produces insignificant heating in healthy tissue [5].

Previously, researchers have extensively utilized magnetic neodymium-iron-bor capsules [6], magnetic microspheres [7], [8], activated carbonated iron [9], [10] and magnetoliposomes [11], [12] as potential drug carriers. However, a recently invented strategy [13], as described in Fig. 1(a) exploiting superparamaganetic nanoparticles with surface assembled oligonucleotides (a short chain of nucleotides; n<100), has been perceived to possess the ability of localized release possibly to most superior extent. In this method, instead of coupling the drug directly to nanoparticle, an intermediate heat-labile linker in the form of double stranded short nucleic acid chain is introduced, which under a rise in temperature field facilitates the release process in a very confined way. While one strand of the oligonucleotide chain is covalently linked with a multivalent superparamagnetic nanoparticle, the complementary strand is coupled with the therapeutic medicine. As imaged non-invasively by MRI, these multivalent nanoparticles invade the fenestrations of the angiogenic vasculature to extravasate into the tumor stroma [13]. The antibodies carried by the nanoparticles target the epitopes either exclusive or overexpressed in cancer cells. Once the target is reached, the nanoparticles are excited with low frequency electromagnetic energy, which raises the local temperature (42–45 °C) enough to disrupt hydrogen bonding between complementary strands and facilitate site-specific release of the therapeutic agent. After the drug gets released, it is transported through the tumor interstitial space, diffuses inside the cancer cells and culminates into gross necrosis of malignant tissues.

Assimilating the aforementioned facts, it becomes readily evident that the entire process is composed of three critical thermofluidic steps namely the heat generation by nanoparticles, dissociation of oligonucleotide strands and transport of drug molecules inside the tumor site, culminating into tissue necrosis. Though these processes have been subjected to extensive experimental investigations either in isolation or in combination [14], [15], [16], [17] there has not been much effort towards theoretical elucidation of entangled and intricate thermo-fluidic-biological processes. On the ground of largely varying experimental results, we intent to emphasize the need for extensive analysis of the governing processes, which should endow us with more rational view and optimized parametric control of this specific cancer treatment method. In the present work, we have proposed an integrated computational predictive model to interpret the efficacy of drug delivery in the process. The basic physics of heat generation by superparamagnetic nanoparticles in presence of external electromagnetic field has been coupled with transient biological heat transfer model and the statistical thermodynamics based generalized Langevin formalism [18] of complete oligonucleotide denaturation to delineate a simulation tool in order to find out the amount of drug released. With respect to the transport of drug molecules, it is important to conceive that no uniform dogma of fluid dynamics exists as different forces prevails at different strata of physiological architecture ranging from the whole tissue to single cell. Hence, we resort to a hierarchically adaptive model approach. In this purview, first, the interstitial diffusion and convection of the various species involved in the process over time has been simulated assuming a porous media model of the tumor [19]. The transvascular migration of nanoparticle-oligo-drug assembly dictated by both hydraulic and osmotic pressure along with the drag force on the diffusing DNA strands has also been accounted to incorporate the in vivo complexities of the integrated process. We have also included the temperature dependence of diffusion coefficients, blood perfusion rate and other physical parameters. Importantly, our model retains numerous process parameters unchanged to the values quantified by previous researchers. Subsequently, the model has been validated with existing experimental results and good congruencies have been obtained even in the presence of utmost uncertainties in complex biological processes.