Avascular Tumor Research Articles

A mathematical model for the nutrient distribution of a spheroidal avascular cancer tumour within an inhomogeneous environment

A mathematical model for the nutrient distribution of a spheroidal avascular cancer tumour within an inhomogeneous environment

Using Spheroids as Building Blocks Towards 3D Bioprinting of Tumor Microenvironment.

Cancer still ranks as a leading cause of mortality worldwide. Although considerable efforts have been dedicated to anticancer therapeutics, progress is still slow, partially due to the absence of robust prediction models. Multicellular tumor spheroids, as a major three-dimensional (3D) culture model exhibiting features of avascular tumors, gained great popularity in pathophysiological studies and high throughput drug screening. However, limited control over cellular and structural organization is still the key challenge in achieving in vivo like tissue microenvironment. 3D bioprinting has made great strides toward tissue/organ mimicry, due to its outstanding spatial control through combining both cells and materials, scalability, and reproducibility. Prospectively, harnessing the power from both 3D bioprinting and multicellular spheroids would likely generate more faithful tumor models and advance our understanding on the mechanism of tumor progression. In this review, the emerging concept on using spheroids as a building block in 3D bioprinting for tumor modeling is illustrated. We begin by describing the context of the tumor microenvironment, followed by an introduction of various methodologies for tumor spheroid formation, with their specific merits and drawbacks. Thereafter, we present an overview of existing 3D printed tumor models using spheroids as a focus. We provide a compilation of the contemporary literature sources and summarize the overall advancements in technology and possibilities of using spheroids as building blocks in 3D printed tissue modeling, with a particular emphasis on tumor models. Future outlooks about the wonderous advancements of integrated 3D spheroidal printing conclude this review.

Computational model of the cancer necrotic core formation in a tumor-on-a-chip device

The mechanisms underlying the formation of necrotic regions within avascular tumors are complex and poorly understood. In this paper, we investigate the formation of a necrotic core in a 3D tumor cell culture within a microfluidic device, considering oxygen, nutrients, and the microenvironment acidification by means of a computational-mathematical model. Our objective is to simulate cell processes, including proliferation and death inside a microfluidic device, according to the microenvironmental conditions. We employed approximation utilizing finite element models taking into account glucose, oxygen, and hydrogen ions diffusion, consumption and production, as well as cell proliferation, migration and death, addressing how tumor cells evolve under different conditions. The resulting mathematical model was examined under different scenarios, being capable of reproducing cell death and proliferation under different cell concentrations, and the formation of a necrotic core, in good agreement with experimental data reported in the literature. This approach not only advances our fundamental understanding of necrotic core formation but also provides a robust computational platform to study personalized therapeutic strategies, offering an important tool in cancer research and treatment design.

Spheroid Model of Mammary Tumor Cells: Epithelial-Mesenchymal Transition and Doxorubicin Response.

Breast cancer is the most prevalent cancer among women worldwide. Therapeutic strategies to control tumors and metastasis are still challenging. Three-dimensional (3D) spheroid-type systems more accurately replicate the features of tumors in vivo, working as a better platform for performing therapeutic response analysis. This work aimed to characterize the epithelial-mesenchymal transition and doxorubicin (dox) response in a mammary tumor spheroid (MTS) model. We evaluated the doxorubicin treatment effect on MCF-7 spheroid diameter, cell viability, death, migration and proteins involved in the epithelial-mesenchymal transition (EMT) process. Spheroids were also produced from tumors formed from 4T1 and 67NR cell lines. MTSs mimicked avascular tumor characteristics, exhibited adherens junction proteins and independently produced their own extracellular matrix. Our spheroid model supports the 3D culturing of cells isolated from mice mammary tumors. Through the migration assay, we verified a reduction in E-cadherin expression and an increase in vimentin expression as the cells became more distant from spheroids. Dox promoted cytotoxicity in MTSs and inhibited cell migration and the EMT process. These results suggest, for the first time, that this model reproduces aspects of the EMT process and describes the potential of dox in inhibiting the metastatic process, which can be further explored.

A bioprinted sea-and-island multicellular model for dissecting human pancreatic tumor-stroma reciprocity and adaptive metabolism

Pancreatic ductal adenocarcinoma (PDAC) presents a formidable clinical challenge due to its intricate microenvironment characterized by desmoplasia and complex tumor-stroma interactions. Conventional models hinder studying cellular crosstalk for therapeutic development. To recapitulate key features of PDAC masses, this study creates a novel sea-and-island PDAC tumor construct (s&i PTC). The s&i PTC consists of 3D-printed islands of human PDAC cells positioned within an interstitial extracellular matrix (ECM) populated by human cancer-associated fibroblasts (CAFs). This design closely mimics the in vivo desmoplastic architecture and nutrient-poor conditions. The model enables studying dynamic tumor-stroma crosstalk and signaling reciprocity, revealing both known and yet-to-be-discovered multicellular metabolic adaptations. Using the model, we discovered the orchestrated dynamic alterations of CAFs under nutrient stress, resembling critical in vivo human tumor niches, such as the secretion of pro-tumoral inflammatory factors. Additionally, nutrient scarcity induces dynamic alterations in the ECM composition and exacerbates poor cancer cell differentiation—features well-established in PDAC progression. Proteomic analysis unveiled the enrichment of proteins associated with aggressive tumor behavior and ECM remodeling in response to poor nutritional conditions, mimicking the metabolic stresses experienced by avascular pancreatic tumor cores. Importantly, the model's relevance to patient outcomes is evident through an inverse correlation between biomarker expression patterns in the s&i PTCs and PDAC patient survival rates. Key findings include upregulated MMPs and key ECM proteins (such as collagen 11 and TGFβ) under nutrient-avid conditions, known to be regulated by CAFs, alongside the concomitant reduction in E-cadherin expression associated with a poorly differentiated PDAC state under nutrient deprivation. Furthermore, elevated levels of hyaluronic acid (HA) and integrins in response to nutrient deprivation underscore the model's fidelity to the PDAC microenvironment. We also observed increased IL-6 and reduced α-SMA expression under poor nutritional conditions, suggesting a transition of CAFs from myofibroblastic to inflammatory phenotypes under a nutrient stress akin to in vivo niches. In conclusion, the s&i PTC represents a significant advancement in engineering clinically relevant 3D models of PDAC masses. It offers a promising platform for elucidating tumor-stroma interactions and guiding future therapeutic strategies to improve patient outcomes.

Morphological Stability for in silico Models of Avascular Tumors

The landscape of computational modeling in cancer systems biology is diverse, offering a spectrum of models and frameworks, each with its own trade-offs and advantages. Ideally, models are meant to be useful in refining hypotheses, to sharpen experimental procedures and, in the longer run, even for applications in personalized medicine. One of the greatest challenges is to balance model realism and detail with experimental data to eventually produce useful data-driven models. We contribute to this quest by developing a transparent, highly parsimonious, first principle in silico model of a growing avascular tumor. We initially formulate the physiological considerations and the specific model within a stochastic cell-based framework. We next formulate a corresponding mean-field model using partial differential equations which is amenable to mathematical analysis. Despite a few notable differences between the two models, we are in this way able to successfully detail the impact of all parameters in the stability of the growth process and on the eventual tumor fate of the stochastic model. This facilitates the deduction of Bayesian priors for a given situation, but also provides important insights into the underlying mechanism of tumor growth and progression. Although the resulting model framework is relatively simple and transparent, it can still reproduce the full range of known emergent behavior. We identify a novel model instability arising from nutrient starvation and we also discuss additional insight concerning possible model additions and the effects of those. Thanks to the framework’s flexibility, such additions can be readily included whenever the relevant data become available.

PAPILLARY FIBROELASTOMA: AN UNUSUAL CAUSE OF TRANSIENT ISCHEMIC ATTACK

Abstract Papillary fibroelastomas (PFEs) are small, avascular benign tumors. Despite that, PFEs could lead to important clinical consequences such as transient ischemic attack and myocardial infarction. A 65–year–old female patient was admitted to our ER presenting a transient ischemic attack characterized by retrograde amnesia lasting about an hour. She had a history of systemic scleroderma and left breast cancer treated with local radiotherapy. In our hospital she underwent a neurological examination and a head CT which were negative for ongoing acute pathologies. An electrocardiogram was performed which showed sinus rhythm at 65 bpm. A transthoracic echocardiogram was also performed revealing a floating mass arising from left ventricular outflow tract between aortic and mitral valves. The transesophageal echocardiogram confirmed a solitary lesion approximately 2 centimeters long localized between A2 and A3 mitral valve scallops. The patient was therefore referred for surgery. During surgery the mass was found to arise from anterior mitral annulus and was resected. The histopathological examination of the mass confirmed the morphologic diagnosis of papillary fibroelastoma. Histologically PFEs are made up of a single layer of endocardial cells covering a matrix of collagen. The main risk factors for the development of PFEs are iatrogenic causes, such as radiotherapy, and autoimmune diseases such as systemic scleroderma. In 54% of cases PFEs are asymptomatic at the time of diagnosis. Since over 95% of PFEs present on the left side of the heart, systemic embolism is the most frequent presentation typically as transient ischemic attacks. Initial evaluation is accomplished with echocardiography. PFEs appear as echo–dense and pedunculated masses. Cardiac computed tomography and magnetic resonance imaging are second line modalities in PFEs evaluation. Definitive diagnosis of PFE requires pathological confirmation. Surgical resection remains the treatment of choice for all symptomatic patients. For symptomatic patients who are not surgical candidate, long term antiplatelets or anticoagulation therapy should be initiated. Asymptomatic patients should have surgical resection if the size of the tumor is > 1 cm. PFEs are associated with significant morbidity and mortality. Echocardiography remains the most utilized diagnostic modality. Surgical treatment should always be considered. Antithrombotic therapy should be considered in non–surgical candidates.

Simulation of avascular tumor growth and drug response in a microfluidic device with a cellular automaton model

Simulation of avascular tumor growth and drug response in a microfluidic device with a cellular automaton model

Hip Arthroplasty in Young Patients: Analysis of the New Zealand Joint Registry

Purpose: The aim of this study was to look into the New Zealand Joint Registry (NZJR) data on total hip arthroplasty (THA) in paediatric and adolescent patients aged 20 and under. Specifically, indications for THA, trends in implants and outcome data. Methods: An analysis of all patients aged 20 and under, recorded in the NZJR from December 1999 until January 2021. Review of similar international reports and NZ adult data undertaken. Results: We identified 115 THA performed in patients aged 20 and under in the NZJR. Mean age at primary surgery is 17.9 years. Indications included avascular necrosis (24%), fracture (6%), tumour (3.5%), inflammatory conditions (16.4%), post-infective (6.1%), SUFE (8.7%) and various other disorders. A total of 9/115 THA were reported as being revised in the study period with a revision rate per 100 component years of 0.69. Bearing surface has trended towards ceramic heads. Cementless implants have been the most commonly utilized. The approach is almost exclusively posterior (79%). Head size has increased from formerly being 28 or less to now 32 and above. Conclusions: Rates of THA in this population remain very low, in keeping with international data. Indications are similar to those seen in other registry studies. Trends mimic those seen internationally and in adult cohorts with cementless implants and larger ceramic heads being favored. Revisions were recorded in 9/115 patients with polywear being the most common indication. Outcome measures were excellent with a mean Oxford hip score of 37.4 at 6 months post operatively.

Examining avascular tumour growth dynamics: A variable-order non-local modelling perspective

This study investigates the growth of an avascular tumour described through the interchange of mass among its constituents and the production of inelastic distortions induced by growth itself. A key contribution of this research examines the role of non-local diffusion arising from the complex and heterogeneous tumour micro-environment. In our context, the non-local diffusion is enhanced by a variable-order fractional operator that incorporates crucial information about regions of limited nutrient availability within the tissue. Our research also focuses on the identification of an evolution law for the growth-induced inelastic distortions recast through the identification of non-conventional forces dual to suitable kinematic descriptors associated with the growth tensor. The establishment of such evolution law stems from examining the dissipation inequality and subsequently determining a posteriori connections between the inelastic distortions and the source/sink terms in the mass balance laws. To gain insights into the dynamics of tumour growth and its response to the proposed modelling framework, we first study how the variables governing the tissue evolution are affected by the introduction of the new growth law. Second, we investigate how regions of limited diffusion within the tumour, encoded into a fractional operator of variable-order, influence its growth.

Selected aspects of avascular tumor growth reproduced by a hybrid model of cell dynamics and chemical kinetics

We here propose a hybrid computational framework to reproduce and analyze aspects of the avascular progression of a generic solid tumor. Our method first employs an individual-based approach to represent the population of tumor cells, which are distinguished in viable and necrotic agents. The active part of the disease is in turn differentiated according to a set of metabolic states. We then describe the spatio-temporal evolution of the concentration of oxygen and of tumor-secreted proteolytic enzymes using partial differential equations (PDEs). A differential equation finally governs the local degradation of the extracellular matrix (ECM) by the malignant mass. Numerical realizations of the model are run to reproduce tumor growth and invasion in a number scenarios that differ for cell properties (adhesiveness, duplication potential, proteolytic activity) and/or environmental conditions (level of tissue oxygenation and matrix density pattern). In particular, our simulations suggest that tumor aggressiveness, in terms of invasive depth and extension of necrotic tissue, can be reduced by (i) stable cell–cell contact interactions, (ii) poor tendency of malignant agents to chemotactically move upon oxygen gradients, and (iii) presence of an overdense matrix, if coupled by a disrupted proteolytic activity of the disease.

Antiangiogenic Therapy Efficacy Can Be Tumor-Size Dependent, as Mathematical Modeling Suggests

Antiangiogenic therapy (AAT) is an indirect oncological modality that is aimed at the disruption of cancer cell nutrient supply. Invasive tumors have been shown to possess inherent resistance to this treatment, while compactly growing benign tumors react to it by shrinking. It is generally accepted that AAT by itself is not curative. This study presents a mathematical model of non-invasive tumor growth with a physiologically justified account of microvasculature alteration and the biomechanical aspects of importance during tumor growth and AAT. In the untreated setting, the model reproduces tumor growth with saturation, where the maximum tumor volume depends on the level of angiogenesis. The outcomes of the AAT simulations depend on the tumor size at the moment of treatment initiation. If it is close to the stable size of an avascular tumor grown in the absence of angiogenesis, then the tumor is rapidly stabilized by AAT. The treatment of large tumors is accompanied by the displacement of normal tissue due to tumor shrinkage. During this, microvasculature undergoes distortion, the degree of which depends on the displacement distance. As it affects tumor nutrient supply, the stable size of a tumor that undergoes AAT negatively correlates with its size at the beginning of treatment. For sufficiently large initial tumors, the long-term survival of tumor cells is compromised by competition with normal cells for the severely limited inflow of nutrients, which makes AAT effectively curative.

Evaluation of a targeted drug delivery system on breast tumor spheroids on a chip

Targeted combination nanomedicine can be employed as a potent approach for cancer treatment. However, the inadequacy of most preclinical tumor models for drug/nanotherapeutic screening has limited their clinical translation. As promising in vitro models, three-dimensional (3D)-printed microfluidic devices can be fabricated in a high-throughput cost-effective manner for various biomedical applications. In this study, using a 3D printed mold, a microwell-based breast tumor-on-a-chip was developed. A modified protocol was devised for the surface treatment of the resin-based 3D-printed template making it suitable for repeated long-term polydimethylsiloxane (PDMS) casting. The versatility of the chip was demonstrated through both biorelevant scaffold-free 3D tumor spheroid culture and nanomedicine screening. Representative of avascular tumor tissues, tumor spheroids were generated in this platform and exhibited tight structure with a size range of 300–500 μm, internal cellular layers, and in vivo pathophysiology conditions. A targeted drug delivery system of 5-fluorouracil, curcumin, and piperine co-loaded folate-conjugated human serum albumin nanoparticles (FA-5FU-CUR-PIP-HSA-NPs) was synthesized by the self-assembly method and both hydrophobic and hydrophilic drugs were encapsulated in the NPs. The transport mechanism and efficacy of the NPs were investigated on the tumor model tissue. Possessing proper physical, biological, and pharmaceutical drug combination, the targeted NPs formulation with the potential of cancer theranostics demonstrated enhanced internalization and accumulation into triple-negative MDA-MB-231 breast cancer microtissues upon both passive and active targeting. The increased penetration and uptake of the targeted NPs in tumor spheroids were translated into boosted anticancer activity. Compatible with the uptake and cytotoxicity test, higher cell apoptosis was observed for the targeted nanomedicine than for the non-targeted NPs. Together, the combination of microfluidics and nanomedicine approaches can benefit basic research related to human disease.

Modeling and analysis of a multilayer solid tumour with cell physiological age and resource limitations

We study an avascular spherical solid tumour model with cell physiological age and resource constraints in vivo. We divide the tumour cells into three components: proliferating cells, quiescent cells and dead cells in necrotic core. We assume that the division rate of proliferating cells is nonlinear due to the nutritional and spatial constraints. The proportion of newborn tumour cells entering directly into quiescent state is considered, since this proportion can respond to the therapeutic effect of drug. We establish a nonlinear age-structured tumour cell population model. We investigate the existence and uniqueness of the model solution and explore the local and global stabilities of the tumour-free steady state. The existence and local stability of the tumour steady state are studied. Finally, some numerical simulations are performed to verify the theoretical results and to investigate the effects of different parameters on the model.

A multiscale model of the role of microenvironmental factors in cell segregation and heterogeneity in breast cancer development.

We analyzed a quantitative multiscale model that describes the epigenetic dynamics during the growth and evolution of an avascular tumor. A gene regulatory network (GRN) formed by a set of ten genes that are believed to play an important role in breast cancer development was kinetically coupled to the microenvironmental agents: glucose, estrogens, and oxygen. The dynamics of spontaneous mutations was described by a Yule-Furry master equation whose solution represents the probability that a given cell in the tissue undergoes a certain number of mutations at a given time. We assumed that the mutation rate is modified by a spatial gradient of nutrients. The tumor mass was simulated by means of cellular automata supplemented with a set of reaction diffusion equations that described the transport of microenvironmental agents. By analyzing the epigenetic state space described by the GRN dynamics, we found three attractors that were identified with cellular epigenetic states: normal, precancer and cancer. For two-dimensional (2D) and three-dimensional (3D) tumors we calculated the spatial distribution of the following quantities: (i) number of mutations, (ii) mutation of each gene and, (iii) phenotypes. Using estrogen as the principal microenvironmental agent that regulates cell proliferation process, we obtained tumor shapes for different values of estrogen consumption and supply rates. It was found that he majority of mutations occurred in cells that were located close to the 2D tumor perimeter or close to the 3D tumor surface. Also, it was found that the occurrence of different phenotypes in the tumor are controlled by estrogen concentration levels since they can change the individual cell threshold and gene expression levels. All results were consistently observed for 2D and 3D tumors.

Proceedings of the 2022 Computational Techniques and Applications Conference

CTAC 2022 Queensland University of Technology, Brisbane, Australia 29 November – 2 December, 2022 The 21st Biennial Computational Techniques and Appli- cations Conference (CTAC-2022) was hosted by the School of Mathematical Sciences and Centre for Data Science at Queensland University of Technology in Brisbane. The ANZIAM Special Interest Group in Computational Mathematics is responsible for this series of conferences, the first of which was held in 1981. The meeting provides an interactive forum for researchers interested in the de- velopment and use of computational methods applied to engineering, scientific and other problems. Participants of the conference are able to submit a short article based on their presentation for publication in this special section of the ANZIAM Journal (Electronic Supplement). The ed- itors, Tim Moroney, Qianqian Yang, Vivien Challis and Elliot Carr, thank the referees whose efforts have helped improve the quality of these conference proceedings. This Special Section of the ANZIAM Journal (Electronic Supplement) contains the refereed conference papers. The eight keynote presentations were as follows. Chris Drovandi, Queensland University of TechnologyLikelihood-Free Bayesian Inference and Model Mis- specification Jennifer Flegg, The University of Melbourne Mathematical Modelling of Avascular Tumour Growth Frances Kuo, The University of New South Wales Lattice Meets Lattice—Application of Lattice Cuba- ture to Models in Lattice Gauge Theory Christian Lubich, University of Tuebingen Convergent evolving surface finite element algo- rithms for geometric evolution equations Marco Palombo, Cardiff University Perspectives on AI-powered brain microstructure imaging Emilie Sauret, Queensland University of TechnologyA hybrid Lattice Boltzmann approach for simulating viscoelastic instabilities and elastic turbulence Karen E Willcox, The University of Texas at Austin Predictive Digital Twins: From Aerospace Engineer- ing to Computational Oncology Andy Wilkins, CSIROThe Importance of Mathematics The presentation by Andy Wilkins was a public lecture. The conference attracted 76 registered participants, and featured a total of 54 contributed talks. CTAC2022 Organising Committee (QUT) • Tim Moroney • Qianqian Yang • Ian Turner• Vivien Challis • Elliot Carr• Sarie Gould CTAC2022 Scientific Committee • Kevin Burrage (QUT)• Vivien Challis (QUT)• Frances Kuo (UNSW)• Bishnu Lamichhane (Newcastle) • Quoc Thong Le Gia (UNSW) • Fawang Liu (QUT)• William Mclean (UNSW) • Tim Moroney (QUT)• Linda Stals (ANU)• Ian Turner (QUT)• Qianqian Yang (QUT) Acknowledgements QUT acknowledges the Turrbal and Yugara, as the First Nations owners of the lands where QUT now stands. We pay respect to their Elders, lores, customs and creation spirits. We recognise that these lands have always been places of teaching, research and learning. QUT acknowledges the important role Aborigi- nal and Torres Strait Islander people play within the QUT community. We gratefully acknowledge support from the following sponsors: School of Mathematical Sciences, QUT Centre for Data Science, QUT Modelling and Simulation Society of Australia and New Zealand Inc Mathematics of Computation and Optimization (MoCaO) special interest group of the Australian Mathematical Society The ANZIAM Student Support Scheme

Effect of Polyplex Size on Penetration into Tumor Spheroids.

Ovarian cancer is one of the most lethal gynecological cancers in the world. In recent years, nucleic acid (NA)-based formulations have been shown to be promising treatments for ovarian cancer, including tumor nodules. However, gene therapy is not that far advanced in clinical reality due to unfavorable physicochemical properties of the NAs, such as high molecular weight, poor cellular uptake, rapid degradation by nucleases, etc. One of the strategies used to overcome these drawbacks is the complexation of anionic NAs via electrostatic interactions with cationic polymers, resulting in the formation of so-called polyplexes. In this work, the role of the size of pDNA and siRNA polyplexes on their penetration into ovarian-cancer-based tumor spheroids was investigated. For this, a methoxypoly(ethylene glycol) poly(2-(dimethylamino)ethyl methacrylate) (mPEG-pDMAEMA) diblock copolymer was synthesized as a polymeric carrier for NA binding and condensation with either plasmid DNA (pDNA) or short interfering RNA (siRNA). When prepared in HEPES buffer (10 mM, pH 7.4) at a nitrogen/phosphate (N/P) charge ratio of 5 and pDNA polyplexes were formed with a size of 162 ± 11 nm, while siRNA-based polyplexes displayed a size of 25 ± 2 nm. The polyplexes had a slightly positive zeta potential of +7-8 mV in the same buffer. SiRNA and pDNA polyplexes were tracked in vitro into tumor spheroids, resembling in vivo avascular ovarian tumor nodules. For this purpose, reproducible spheroids were obtained by coculturing ovarian carcinoma cells with primary mouse embryonic fibroblasts in different ratios (5:2, 1:1, and 2:5). Penetration studies revealed that after 24 h of incubation, siRNA polyplexes were able to penetrate deeper into the homospheroids (composed of only cancer cells) and heterospheroids (cancer cells cocultured with fibroblasts) compared to pDNA polyplexes which were mainly located in the rim. The penetration of the polyplexes was slowed when increasing the fraction of fibroblasts present in the spheroids. Furthermore, in the presence of serum siRNA polyplexes encoding for luciferase showed a high cellular uptake in 2D cells resulting in ∼50% silencing of luciferase expression. Taken together, these findings show that self-assembled small siRNA polyplexes have good potential as a platform to test ovarian tumor nodulus penetration..

The Efficacy of Zinc Phthalocyanine Nanoconjugate on Melanoma Cells Grown as Three-Dimensional Multicellular Tumour Spheroids.

Melanoma remains a major public health concern that is highly resistant to standard therapeutic approaches. Photodynamic therapy (PDT) is an underutilised cancer therapy with an increased potency and negligible side effects, and it is non-invasive compared to traditional treatment modalities. Three-dimensional multicellular tumour spheroids (MCTS) closely resemble in vivo avascular tumour features, allowing for the more efficient and precise screening of novel anticancer agents with various treatment combinations. In this study, we utilised A375 human melanoma spheroids to screen the phototoxic effect of zinc phthalocyanine tetrasulfonate (ZnPcS4) conjugated to gold nanoparticles (AuNP). The nanoconjugate was synthesised and characterised using ultraviolet-visible spectroscopy, a high-resolution transmission electron microscope (TEM), dynamic light scattering (DLS), and zeta potential (ZP). The phototoxicity of the nanoconjugate was tested on the A375 MCTS using PDT at a fluency of 10 J/cm2. After 24 h, the cellular responses were evaluated via microscopy, an MTT viability assay, an ATP luminescence assay, and cell death induction using annexin propidium iodide. The MTT viability assay demonstrated that the photoactivated ZnPcS4, at a concentration of 12.73 µM, caused an approximately 50% reduction in the cell viability of the spheroids. When conjugated to AuNPs, the latter significantly increased the cellular uptake and cytotoxicity in the melanoma spheroids via the induction of apoptosis. This novel Zinc Phthalocyanine Nanoconjugate shows promise as a more effective PDT treatment modality.

Analytical Models of Intra- and Extratumoral Cell Interactions at Avascular Stage of Growth in the Presence of Targeted Chemotherapy.

In this study, we propose a set of nonlinear differential equations to model the dynamic growth of avascular stage tumors, considering nutrient supply from underlying tissue, innate immune response, contact inhibition of cell migration, and interactions with a chemotherapeutic agent. The model has been validated against available experimental data from the literature for tumor growth. We assume that the size of the modeled tumor is already detectable, and it represents all clinically observed existent cell populations; initial conditions are selected accordingly. Numerical results indicate that the tumor size and regression significantly depend on the strength of the host immune system. The effect of chemotherapy is investigated, not only within the malignancy, but also in terms of the responding immune cells and healthy tissue in the vicinity of a tumor.

How do cell crowding and starvation affect avascular tumor growth of the EMT6/Ro tumor?

Here we re-examine experimental in vitro data for the EMT6/Ro tumor volume and viable rim thickness. This shows that the growth speed is constant in time, and independent of nutrient concentration at large concentrations, but that the viable rim thickness increases in this high concentration regime. We then present a simple mechanistic reaction-diffusion equation that includes crowding and starvation effects, and show that the model qualitatively captures the experimental observations. Moreover, the model predicts that the cancer cell concentration is characterised by a wave pulse (soliton), and the pulse shape is explored through zero’th order perturbation analysis corresponding to large wave speeds. It is shown that this zero’th order term is dominant for the experimental condition, further indicating that the non-linear reaction governs the pulse characteristic shape. Finally, at low nutrient concentrations we find that the front is a pulled-front, that is, the growth speed is determined by the cell multiplication at the wave front edge in accordance with earlier modelling approaches.