What does physics have to do with cancer?

Integrating frontiers: a holistic, quantum and evolutionary approach to conquering cancer through systems biology and multidisciplinary synergy

Cancer therapy is facing increasingly significant challenges, marked by a wide range of techniques and research efforts centered around somatic mutations, precision oncology, and the vast amount of big data. Despite this abundance of information, the quest to cure cancer often seems more elusive, with the "war on cancer" yet to deliver a definitive victory. A particularly pressing issue is the development of tumor treatment resistance, highlighting the urgent need for innovative approaches. Evolutionary, Quantum Biology and System Biology offer a promising framework for advancing experimental cancer research. By integrating theoretical studies, translational methods, and flexible multidisciplinary clinical research, there's potential to enhance current treatment strategies and improve outcomes for cancer patients. Establishing stronger links between evolutionary, quantum, entropy and chaos principles and oncology could lead to more effective treatments that leverage an understanding of the tumor's evolutionary dynamics, paving the way for novel methods to control and mitigate cancer. Achieving these objectives necessitates a commitment to multidisciplinary and interprofessional collaboration at the heart of both research and clinical endeavors in oncology. This entails dismantling silos between disciplines, encouraging open communication and data sharing, and integrating diverse viewpoints and expertise from the outset of research projects. Being receptive to new scientific discoveries and responsive to how patients react to treatments is also crucial. Such strategies are key to keeping the field of oncology at the forefront of effective cancer management, ensuring patients receive the most personalized and effective care. Ultimately, this approach aims to push the boundaries of cancer understanding, treating it as a manageable chronic condition, aiming to extend life expectancy and enhance patient quality of life.

Macrophage mediated mesoscale brain mechanical homeostasis mechanically imaged via optical tweezers and Brillouin microscopy in vivo

Tissues are active materials where epithelial turnover, immune surveillance, and remodeling of stromal cells such as macrophages all regulate form and function. Scattering modalities such as Brillouin microscopy (BM) can non-invasively access mechanical signatures at GHz. However, our traditional understanding of tissue material properties is derived mainly from modalities which probe mechanical properties at different frequencies. Thus, reconciling measurements amongst these modalities remains an active area. Here, we compare optical tweezer active microrheology (OT-AMR) and Brillouin microscopy (BM) to longitudinally map brain development in the larval zebrafish. We determine that each measurement is able to detect a mechanical signature linked to functional units of the brain. We demonstrate that the corrected BM-Longitudinal modulus using a density factor correlates well with OT-AMR storage modulus at lower frequencies. We also show that the brain tissue mechanical properties are dependent on both the neuronal architecture and the presence of macrophages. Moreover, the BM technique is able to delineate the contributions to mechanical properties of the macrophage from that due to colony stimulating factor 1 receptor (CSF1R) mediated stromal remodeling. Here, our data suggest that macrophage remodeling is instrumental in the maintenance of tissue mechanical homeostasis during development. Moreover, the strong agreement between the OT-AM and BM further demonstrates that scattering-based technique is sensitive to both large and minute structural modification in vivo.

Hydrodynamic shear stress' impact on mammalian cell properties and its applications in 3D bioprinting

As an effective cell assembly method, three-dimensional bioprinting has been widely used in building organ models and tissue repair over the past decade. However, different shear stresses induced throughout the entire printing process can cause complex impacts on cell integrity, including reducing cell viability, provoking morphological changes and altering cellular functionalities. The potential effects that may occur and the conditions under which these effects manifest are not clearly understood. Here, we review systematically how different mammalian cells respond under shear stress. We enumerate available experimental apparatus, and we categorise properties that can be affected under disparate stress patterns. We also summarise cell damaging mathematical models as a predicting reference for the design of bioprinting systems. We concluded that it is essential to quantify specific cell resistance to shear stress for the optimisation of bioprinting systems. Besides, as substantial positive impacts, including inducing cell alignment and promoting cell motility, can be generated by shear stress, we suggest that we find the proper range of shear stress and actively utilise its positive influences in the development of future systems.

Targeting Translation and the Cell Cycle Inversely Affects CTC Metabolism but Not Metastasis

Melanoma brain metastasis (MBM) is significantly associated with poor prognosis and is diagnosed in 80% of patients at autopsy. Circulating tumor cells (CTCs) are "seeds" of metastasis and the smallest functional units of cancer. Our multilevel approach has previously identified a CTC RPL/RPS gene signature directly linked to MBM onset. We hypothesized that targeting ribogenesis prevents MBM/metastasis in CTC-derived xenografts. We treated parallel cohorts of MBM mice with FDA-approved protein translation inhibitor omacetaxine with or without CDK4/CDK6 inhibitor palbociclib, and monitored metastatic development and cell proliferation. Necropsies and IVIS imaging showed decreased MBM/extracranial metastasis in drug-treated mice, and RNA-Seq on mouse-blood-derived CTCs revealed downregulation of four RPL/RPS genes. However, mitochondrial stress tests and RT-qPCR showed that omacetaxine and palbociclib inversely affected glycolytic metabolism, demonstrating that dual targeting of cell translation/proliferation is critical to suppress plasticity in metastasis-competent CTCs. Equally relevant, we provide the first-ever functional metabolic characterization of patient-derived circulating neoplastic cells/CTCs.

Strategy of targeting the tumor microenvironment via inhibition of fibroblast/fibrosis remodeling new era to cancer chemo-immunotherapy resistance

The use of repurposing drugs that may have neoplastic and anticancer effects increases the efficiency and decrease resistance to chemotherapy drugs through a biochemical and mechanical transduction mechanisms through modulation of fibroblast/fibrosis remodeling in tumor microenvironment (TME). Interestingly, fibroblast/fibrosis remodeling plays a vital role in mediating cancer metastasis and drug resistance after immune chemotherapy. The most essential hypothesis for induction of chemo-immunotherapy resistance is via activation of fibroblast/fibrosis remodeling and preventing the infiltration of T cells after is mainly due to the interference between cytoskeleton, mechanical, biochemical, metabolic, vascular, and remodeling signaling pathways in TME. The structural components of the tumor that can be targeted in the fibroblast/fibrosis remodeling include the depletion of the TME components, targeting the cancer-associated fibroblasts and tumor associated macrophages, alleviating the mechanical stress within the ECM, and normalizing the blood vessels. It has also been found that during immune-chemotherapy, TME injury and fibroblast/fibrosis remodeling causes the up-regulation of inhibitory signals and down-regulation of activated signals, which results in immune escape or chemo-resistance of the tumor. In this regard, repurposing or neo-adjuvant drugs with various transduction signaling mechanisms, including anti-fibrotic effects, are used to target the TME and fibroblast/fibrosis signaling pathway such as angiotensin 2, transforming growth factor-beta, physical barriers of the TME, cytokines and metabolic factors which finally led to the reverse of the chemo-resistance. Consistent to many repurposing drugs such as pirfenidone, metformin, losartan, tranilast, dexamethasone and pentoxifylline are used to decrease immune-suppression by abrogation of TME inhibitory signal that stimulates the immune system and increases efficiency and reduces resistance to chemotherapy drugs. To overcome immunosuppression based on fibroblast/fibrosis remodeling, in this review, we focus on inhibitory signal transduction, which is the physical barrier, alleviates mechanical stress and prevents mechano-metabolic activation.

Travelling under pressure - hypoxia and shear stress in the metastatic journey

Cancer cell invasion, intravasation and survival in the bloodstream are early steps of the metastatic process, pivotal to enabling the spread of cancer to distant tissues. Circulating tumor cells (CTCs) represent a highly selected subpopulation of cancer cells that tamed these critical steps, and a better understanding of their biology and driving molecular principles may facilitate the development of novel tools to prevent metastasis. Here, we describe key research advances in this field, aiming at describing early metastasis-related processes such as collective invasion, shedding, and survival of CTCs in the bloodstream, paying particular attention to microenvironmental factors like hypoxia and mechanical stress, considered as important influencers of the metastatic journey.

Predicting cancer stages from tissue energy dissipation

Understanding cancer staging in order to predict its progression is vital to determine its severity and to plan the most appropriate therapies. This task has attracted interest from different fields of science and engineering. We propose a computational model that predicts the evolution of cancer in terms of the intimate structure of the tissue, considering that this is a self-organised structure that undergoes transformations governed by non-equilibrium thermodynamics laws. Based on experimental data on the dependence of tissue configurations on their elasticity and porosity, we relate the cancerous tissue stages with the energy dissipated, showing quantitatively that tissues in more advanced stages dissipate more energy. The knowledge of this energy allows us to know the probability of observing the tissue in its different stages and the probability of transition from one stage to another. We validate our results with experimental data and statistics from the World Health Organisation. Our quantitative approach provides insights into the evolution of cancer through its different stages, important as a starting point for new and integrative research to defeat cancer.

Immune-checkpoint inhibitor therapy response evaluation using oncophysics-based mathematical models

The field of oncology has transformed with the advent of immunotherapies. The standard of care for multiple cancers now includes novel drugs that target key checkpoints that function to modulate immune responses, enabling the patient's immune system to elicit an effective anti-tumor response. While these immune-based approaches can have dramatic effects in terms of significantly reducing tumor burden and prolonging survival for patients, the therapeutic approach remains active only in a minority of patients and is often not durable. Multiple biological investigations have identified key markers that predict response to the most common form of immunotherapy-immune checkpoint inhibitors (ICI). These biomarkers help enrich patients for ICI but are not 100% predictive. Understanding the complex interactions of these biomarkers with other pathways and factors that lead to ICI resistance remains a major goal. Principles of oncophysics-the idea that cancer can be described as a multiscale physical aberration-have shown promise in recent years in terms of capturing the essence of the complexities of ICI interactions. Here, we review the biological knowledge of mechanisms of ICI action and how these are incorporated into modern oncophysics-based mathematical models. Building on the success of oncophysics-based mathematical models may help to discover new, rational methods to engineer immunotherapy for patients in the future. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

The Sub-Molecular and Atomic Theory of Cancer Beginning: The Role of Mitochondria

Life as we know it is made of strict interaction of atom, metabolism, and genetics, made around the chemistry of the most common elements of the universe: hydrogen, oxygen, nitrogen, sulfur, phosphorus, and carbon. The interaction of atomic, metabolic, and genetic cycles results in the organization and de-organization of chemical information of what we consider living entities, including cancer cells. In order to approach the problem of the origin of cancer, it is therefore reasonable to start from the assumption that the atomic structure, metabolism, and genetics of cancer cells share a common frame with prokaryotic mitochondria, embedded in conditions favorable for the onset of both. Despite years of research, cancer in its general acceptation remains enigmatic. Despite the increasing efforts to investigate the complexity of tumorigenesis, complementing the research on genetic and biochemical changes, researchers face insurmountable limitations due to the huge presence of variabilities in cancer and metastatic behavior. The atomic level of all biological activities it seems confirmed the electron behavior, especially within the mitochondria. The electron spin may be considered a key factor in basic biological processes defining the structure, reactivity, spectroscopic, and magnetic properties of a molecule. The use of magnetic fields (MF) has allowed a better understanding of the grade of influence on different biological systems, clarifying the multiple effects on electron behavior and consequently on cellular changes. Scientific advances focused on the mechanics of the cytoskeleton and the cellular microenvironment through mechanical properties of the cell nucleus and its connection to the cytoskeleton play a major role in cancer metastasis and progression. Here, we present a hypothesis regarding the changes that take place at the atomic and metabolic levels within the human mitochondria and the modifications that probably drive it in becoming cancer cell. We propose how atomic and metabolic changes in structure and composition could be considered the unintelligible reason of many cancers’ invulnerability, as it can modulate nuclear mechanics and promote metastatic processes. Improved insights into this interplay between this sub-molecular organized dynamic structure, nuclear mechanics, and metastatic progression may have powerful implications in cancer diagnostics and therapy disclosing innovation in targets of cancer cell invasion.

Aperiodic crystals in biology

Biological systems display a broad palette of hierarchically ordered designs spanning over many orders of magnitude in size. Remarkably enough, periodic order, which profusely shows up in non-living ordered compounds, plays a quite subsidiary role in most biological structures, which can be appropriately described in terms of the more general aperiodic crystal notion instead. In this topical review I shall illustrate this issue by considering several representative examples, including botanical phyllotaxis, the geometry of cell patterns in tissues, the morphology of sea urchins, or the symmetry principles underlying virus architectures. In doing so, we will realize that albeit the currently adopted quasicrystal notion is not general enough to properly account for the rich structural features one usually finds in biological arrangements of matter, several mathematical tools and fundamental notions belonging to the aperiodic crystals science toolkit can provide a useful modeling framework to this end.

Spectroscopic and microscopic comparisons of cell topology and chemistry analysis of mouse embryonic stem cell, somatic cell and cancer cell

While embryonic stem cells and cancer cells are known to have many similarities in signalling pathways, healthy somatic cells are known to be different in many ways. Characterization of embryonic stem cell is crucial for cancer development and cancer recurrence due to the shared signalling pathways and life course with cancer initiator and cancer stem cells. Since embryonic stem cells are the sources of the somatic and cancer cells, it is necessary to reveal the relevance between them. The past decade has seen the importance of interdisciplinary studies and it is obvious that the reflection of the physical/chemical phenomena occurring on the cell biology has attracted much more attention. For this reason, the aim of this study is to elementally and topologically characterize the mouse embryonic stem cells, mouse lung squamous cancer cells, and mouse skin fibroblast cells by using Atomic Force Microscopy (AFM), X-ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscopy (SEM) supported with Electron Dispersive Spectroscopy (EDS) techniques in a complementary way. Our AFM findings revealed that roughness data of the mouse embryonic stem cells and cancer cells were similar and somatic cells were found to be statistically different from these two cell types. However, based on both XPS and SEM-EDS results, surface elemental ratios vary in mouse embryonic stem cells, cancer cells and somatic cells. Our results showed that these complementary spectroscopic and microscopic techniques used in this work are very effective in cancer and stem cell characterization and have the potential to gather more detailed information on relevant biological samples.

The functional cross talk between cancer cells and cancer associated fibroblasts from a cancer mechanics perspective

The function of biological tissues in health and disease is regulated at cellular level and is highly influenced by the physical microenvironment, through the interaction of forces between cells and ECM, which are perceived through mechanosensing pathways. In cancer, both chemical and physical signaling cascades and their interactions are involved during cell-cell and cell-ECM communications to meet requirements of tumor growth. Among stroma cells, cancer associated fibroblasts (CAFs) play key role in tumor growth and pave the way for cancer cells to initiate metastasis and invasion to other tissues, and without recruitment of CAFs, the process of cancer invasion is dysfunctional. This is through an intense chemical and physical cross talks with tumor cells, and interactive remodeling of ECM. During such interaction CAFs apply traction forces and depending on the mechanical properties, deform ECM and in return receive physical signals from the micromechanical environment. Such interaction leads to ECM remodeling by manipulating ECM structure and its mechanical properties. The results are in form of deposition of extra fibers, stiffening, rearrangement and reorganization of fibrous structure, and degradation which are due to a complex secretion and expression of different markers triggered by mechanosensing of tumor cells, specially CAFs. Such events define cancer progress and invasion of cancer cells. A systemic knowledge of chemical and physical factors provides a holistic view of how cancer process and enhances the current treatment methods to provide more diversity among targets that involves tumor cells and ECM structure.

Surface Engineering and Multimodal Imaging of Multistage Delivery Vectorsin Metastatic Breast Cancer

The design of effective nanoformulations that target metastatic breast cancers is challenging due to a lack of competent imaging and image analysis protocols that can capture the interactions between the injected nanoparticles and metastatic lesions. Here, we describe the integration of in vivo whole-body PET-CT with high temporal resolution, ex vivo whole-organ optical imaging and high spatial resolution confocal microscopy to deconstruct the trafficking of injectable nanoparticle generators encapsulated with polymeric doxorubicin (iNPG-pDox) in pulmonary metastases of triple-negative breast cancer. We describe the details of image acquisition and analysis in a step-wise manner along with the development of a mouse model for metastatic breast cancer. The methods described herein can be easily adapted to any nanoparticle or disease model, allowing a standardized pipeline for in vivo preclinical studies that focus on delineating nanoparticle kinetics and interactions within metastases.

The prognostic value of Piezo1 in breast cancer patients with various clinicopathological features

The effects of piezo-type mechanosensitive ion channel component 1 (Piezo1) in sensing extracellular mechanical stress have been well investigated. Recently, Piezo1's vital role in cancerogenesis has been demonstrated by many studies. Nonetheless, the prognostic value of Piezo1 in cancer still remains unexplored and unclear. This article aims to investigate the prognostic value of Piezo1 in breast cancer. Human Protein Atlas and the Cancer Genome Atlas (TCGA) databases were used to examine Piezo1 expression in different human tissues and human cell lines. The discrepancies of Piezo1 mRNA expression in breast cancer patients with different clinicopathological features were assessed using bc-GenExMiner. The prognostic value of Piezo1 in breast cancer patients was evaluated using Kaplan-Meier plotter. Piezo1 mRNA was extensively expressed in human tissues and cell lines, particularly in breast and cancerous breast cancer cell line MCF7. High Piezo1 expression was found correlated with poor prognosis of breast cancer. Survival analysis further confirmed unfavorable prognosis of high Piezo1 expression in breast cancer patients with lymph node positive, estrogen receptor positive, Grade 2 (Scarff-Bloom-Richardson grading system), luminal A, and human epidermal growth factor receptor 2 overexpression, respectively. This study suggested that Piezo1 can serve as a prognostic indicator of breast cancer.

Physics approaches to the spatial distribution of immune cells in tumors

The goal of immunotherapy is to mobilize the immune system to kill cancer cells. Immunotherapy is more effective and, in general, the prognosis is better, when more immune cells infiltrate the tumor. We explore the question of whether the spatial distribution rather than just the density of immune cells in the tumor is important in forecasting whether cancer recurs. After reviewing previous work on this issue, we introduce a novel application of maximum entropy to quantify the spatial distribution of discrete point-like objects. We apply our approach to B and T cells in images of tumor tissue taken from triple negative breast cancer patients. We find that the immune cells are more spatially dispersed in good clinical outcome (no recurrence of cancer within at least 5 years of diagnosis) compared to poor clinical outcome (recurrence within 3 years of diagnosis). Our results highlight the importance of spatial distribution of immune cells within tumors with regard to clinical outcome, and raise new questions on their role in cancer recurrence.

Modeling iontophoretic drug delivery in a microfluidic device

Iontophoresis employs low-intensity electrical voltage and continuous constant current to direct a charged drug into a tissue. Iontophoretic drug delivery has recently been used as a novel method for cancer treatment in vivo. There is an urgent need to precisely model the low-intensity electric fields in cell culture systems to optimize iontophoretic drug delivery to tumors. Here, we present an iontophoresis-on-chip (IOC) platform to precisely quantify carboplatin drug delivery and its corresponding anti-cancer efficacy under various voltages and currents. In this study, we use an in vitro heparin-based hydrogel microfluidic device to model the movement of a charged drug across an extracellular matrix (ECM) and in MDA-MB-231 triple-negative breast cancer (TNBC) cells. Transport of the drug through the hydrogel was modeled based on diffusion and electrophoresis of charged drug molecules in the direction of an oppositely charged electrode. The drug concentration in the tumor extracellular matrix was computed using finite element modeling of transient drug transport in the heparin-based hydrogel. The model predictions were then validated using the IOC platform by comparing the predicted concentration of a fluorescent cationic dye (Alexa Fluor 594®) to the actual concentration in the microfluidic device. Alexa Fluor 594® was used because it has a molecular weight close to paclitaxel, the gold standard drug for treating TNBC, and carboplatin. Our results demonstrated that a 50 mV DC electric field and a 3 mA electrical current significantly increased drug delivery and tumor cell death by 48.12% ± 14.33 and 39.13% ± 12.86, respectively (n = 3, p-value <0.05). The IOC platform and mathematical drug delivery model of iontophoresis are promising tools for precise delivery of chemotherapeutic drugs into solid tumors. Further improvements to the IOC platform can be made by adding a layer of epidermal cells to model the skin.

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.

Anlar G, A. Hussein E, Elzatahry A, C. Yalcin H. Effect of Flow-Induced Shear Stress in Nanomaterial Uptake by Cells: Focus on Targeted Anti-Cancer Therapy

Recently, nanomedicines have gained a great deal of attention in diverse biomedical applications, including anti-cancer therapy. Being different from normal tissue, the biophysical microenvironment of tumor cells and cancer cell mechanics should be considered for the development of nanostructures as anti-cancer agents. Throughout the last decades, many efforts devoted to investigating the distinct cancer environment and understanding the interactions between tumor cells and have been applied bio-nanomaterials. This review highlights the microenvironment of cancer cells and how it is different from that of healthy tissue. We gave special emphasis to the physiological shear stresses existing in the cancerous surroundings, since these stresses have a profound effect on cancer cell/nanoparticle interaction. Finally, this study reviews relevant examples of investigations aimed at clarifying the cellular nanoparticle uptake behavior under both static and dynamic conditions.

Drug delivery: Experiments, mathematical modelling and machine learning

We address the problem of determining from laboratory experiments the data necessary for a proper modeling of drug delivery and efficacy in anticancer therapy. There is an inherent difficulty in extracting the necessary parameters, because the experiments often yield an insufficient quantity of information. To overcome this difficulty, we propose to combine real experiments, numerical simulation, and Machine Learning (ML) based on Artificial Neural Networks (ANN), aiming at a reliable identification of the physical model factors, e.g. the killing action of the drug. To this purpose, we exploit the employed mathematical-numerical model for tumor growth and drug delivery, together with the ANN - ML procedure, to integrate the results of the experimental tests and feed back the model itself, thus obtaining a reliable predictive tool. The procedure represents a hybrid data-driven, physics-informed approach to machine learning. The physical and mathematical model employed for the numerical simulations is without extracellular matrix (ECM) and healthy cells because of the experimental conditions we reproduce.

Neutrophils, as "Trojan horses", participate in the delivery of therapeutical PLGA nanoparticles into a tumor based on the chemotactic effect

Inspired by the fact that leukocytes have innate phagocytic functions and oriented migration capabilities in response to chemoattractants, we have unveiled that endogenous neutrophils as “Trojan horses”, participate in the delivery of nanoparticles in an “in vivo self-armed assembly” manner. Neutrophils were the main population to preferentially sequester the intravenous administrated nanoparticles with an average size of 260 nm. The pre-implantation of CXCL1-laden hydrogels could trigger and induce a targeted signal to attract an influx of neutrophils carrying the therapeutic goods to the desired position. In mouse models of melanoma, the combinatorial regimen of using the PLGA nanoparticles with the CXCL1 hydrogels exhibited superior tumor inhibition capability. This work leveraged the natural phagocytosis of neutrophile and the chemotactic effect of chemokines for targeted delivery. We believe this strategy will improve the therapeutic efficiency of nanoparticle-based delivery systems, especially when the chemokines are implanted at sites of surgical tumor removal, during cancer treatment at the clinic.

Sequential deconstruction of composite drug transport in metastatic breast cancer

It is challenging to design effective drug delivery systems (DDS) that target metastatic breast cancers (MBC) because of lack of competent imaging and image analysis protocols that suitably capture the interactions between DDS and metastatic lesions. Here, we integrate high temporal resolution of in vivo whole-body PET-CT, ex vivo whole-organ optical imaging, high spatial resolution of confocal microscopy, and mathematical modeling, to systematically deconstruct the trafficking of injectable nanoparticle generators encapsulated with polymeric doxorubicin (iNPG-pDox) in pulmonary MBC. iNPG-pDox accumulated substantially in metastatic lungs, compared to healthy lungs. Intratumoral distribution and retention of iNPG-pDox varied with lesion size, possibly induced by locally remodeled microenvironment. We further used multiscale imaging and mathematical simulations to provide improved drug delivery strategies for MBC. Our work presents a multidisciplinary translational toolbox to evaluate transport and interactions of DDS within metastases. This knowledge can be recursively applied to rationally design advanced therapies for metastatic cancers.

Meeting the Needs of A Changing Landscape: Advances and Challenges in Undergraduate Biology Education

Over the last 25 years, reforms in undergraduate biology education have transformed the way biology is taught at many institutions of higher education. This has been fueled in part by a burgeoning discipline-based education research community, which has advocated for evidence-based instructional practices based on findings from research. This perspective will review some of the changes to undergraduate biology education that have gained or are currently gaining momentum, becoming increasingly common in undergraduate biology classrooms. However, there are still areas in need of improvement. Although more underrepresented minority students are enrolling in and graduating from biology programs than in the past, there is a need to understand the experiences and broaden participation of other underserved groups in biology and ensure biology classroom learning environments are inclusive. Additionally, although understanding biology relies on understanding concepts from the physical sciences and mathematics, students still rarely connect the concepts they learn from other STEM disciplines to biology. Integrating concepts and practices across the STEM disciplines will be critical for biology graduates as they tackle the biological problems of the twenty-first century.

Role of mechanical cues and hypoxia on the growth of tumor cells in strong and weak confinement: A dual in vitro-in silico approach

Characterization of tumor growth dynamics is of major importance for cancer understanding. By contrast with phenomenological approaches, mechanistic modeling can facilitate disclosing underlying tumor mechanisms and lead to identification of physical factors affecting proliferation and invasive behavior. Current mathematical models are often formulated at the tissue or organ scale with the scope of a direct clinical usefulness. Consequently, these approaches remain empirical and do not allow gaining insight into the tumor properties at the scale of small cell aggregates. Here, experimental and numerical studies of the dynamics of tumor aggregates are performed to propose a physics-based mathematical model as a general framework to investigate tumor microenvironment. The quantitative data extracted from the cellular capsule technology microfluidic experiments allow a thorough quantitative comparison with in silico experiments. This dual approach demonstrates the relative impact of oxygen and external mechanical forces during the time course of tumor model progression.

Brome mosaic virus-like particles as siRNA nanocarriers for biomedical purposes

There is an increasing interest in the use of plant viruses as vehicles for anti-cancer therapy. In particular, the plant virus brome mosaic virus (BMV) and cowpea chlorotic mottle virus (CCMV) are novel potential nanocarriers for different therapies in nanomedicine. In this work, BMV and CCMV were loaded with a fluorophore and assayed on breast tumor cells. The viruses BMV and CCMV were internalized into breast tumor cells. Both viruses, BMV and CCMV, did not show cytotoxic effects on tumor cells in vitro. However, only BMV did not activate macrophages in vitro. This suggests that BMV is less immunogenic and may be a potential carrier for therapy delivery in tumor cells. Furthermore, BMV virus-like particles (VLPs) were efficiently loaded with small interfering RNA (siRNA) without packaging signal. The gene silencing was demonstrated by VLPs loaded with siGFP and tested on breast tumor cells that constitutively express the green fluorescent protein (GPF). After VLP-siGFP treatment, GFP expression was efficiently inhibited corroborating the cargo release inside tumor cells and the gene silencing. In addition, BMV VLP carring siAkt1 inhibited the tumor growth in mice. These results show the attractive potential of plant virus VLPs to deliver molecular therapy to tumor cells with low immunogenic response.

Field cancerization in the understanding of parenchymal analysis of mammograms for breast cancer risk assessment

In recent years, mammographic image analysis has shown great potential for breast cancer risk assessment. The aim of risk assessment is to predict how likely a woman is to develop breast cancer in the future. Several studies suggest that computerized parenchymal analysis of mammograms can be utilized as an independent imaging biomarker of breast cancer. Parenchymal analysis consists of the quantitative assessment of visual texture patterns in mammograms to infer the level of risk. In spite of substantial evidence of the association between parenchymal patterns and breast cancer risk, its biological foundations remain poorly understood. In this work, we draw a hypothesis that links the field cancerization (FC) with breast cancer risk assessment based on the parenchymal analysis. In the literature, the FC is interpreted as a biochemical anomaly amplification in otherwise healthy cells due to the effect of pre-cancerous transformed cells in surrounding regions. Our hypothesis is that these biochemical anomaly amplifications change the cellular micro-environment which, in turn, alter tissue responses to X-ray radiation. As a result, it is reasonable to think that these changes influence the interaction of X-rays with parenchymal - the functional - breast tissue thus enabling cancer prediction by analyzing X-ray images of the breast. We believe that our hypothesis provides an actionable explanation as to how computerized parenchymal analysis of apparently normal mammograms can be successfully utilized for the stratification of breast cancer risk.

Effect of heterogeneity and spatial correlations on the structure of a tumor invasion front in cellular environments

Analysis of invasion front has been widely used to decipher biological properties, as well as the growth dynamics of the corresponding populations. Likewise, the invasion front of tumors has been investigated, from which insights into the biological mechanisms of tumor growth have been gained. We develop a model to study how tumors' invasion front depends on the relevant properties of a cellular environment. To do so, we develop a model based on a nonlinear reaction-diffusion equation, the Fisher-Kolmogorov-Petrovsky-Piskunov equation, to model tumor growth. Our study aims to understand how heterogeneity in the cellular environment's stiffness, as well as spatial correlations in its morphology, the existence of both of which has been demonstrated by experiments, affects the properties of tumor invasion front. It is demonstrated that three important factors affect the properties of the front, namely the spatial distribution of the local diffusion coefficients, the spatial correlations between them, and the ratio of the cells' duplication rate and their average diffusion coefficient. Analyzing the scaling properties of tumor invasion front computed by solving the governing equation, we show that, contrary to several previous claims, the invasion front of tumors and cancerous cell colonies cannot be described by the well-known models of kinetic growth, such as the Kardar-Parisi-Zhang equation.

Assessing the interactions between radiotherapy and antitumour immunity

Immunotherapy, specifically the introduction of immune checkpoint inhibitors, has transformed the treatment of cancer, enabling long-term tumour control even in individuals with advanced-stage disease. Unfortunately, only a small subset of patients show a response to currently available immunotherapies. Despite a growing consensus that combining immune checkpoint inhibitors with radiotherapy can increase response rates, this approach might be limited by the development of persistent radiation-induced immunosuppression. The ultimate goal of combining immunotherapy with radiotherapy is to induce a shift from an ineffective, pre-existing immune response to a long-lasting, therapy-induced immune response at all sites of disease. To achieve this goal and enable the adaptation and monitoring of individualized treatment approaches, assessment of the dynamic changes in the immune system at the patient level is essential. In this Review, we summarize the available clinical data, including forthcoming methods to assess the immune response to radiotherapy at the patient level, ranging from serum biomarkers to imaging techniques that enable investigation of immune cell dynamics in patients. Furthermore, we discuss modelling approaches that have been developed to predict the interaction of immunotherapy with radiotherapy, and highlight how they could be combined with biomarkers of antitumour immunity to optimize radiotherapy regimens and maximize their synergy with immunotherapy.

An approach for vascular tumor growth based on a hybrid embedded/homogenized treatment of the vasculature within a multiphase porous medium model

The aim of this work is to develop a novel computational approach to facilitate the modeling of angiogenesis during tumor growth. The preexisting vasculature is modeled as a 1D inclusion and embedded into the 3D tissue through a suitable coupling method, which allows for nonmatching meshes in 1D and 3D domain. The neovasculature, which is formed during angiogenesis, is represented in a homogenized way as a phase in our multiphase porous medium system. This splitting of models is motivated by the highly complex morphology, physiology, and flow patterns in the neovasculature, which are challenging and computationally expensive to resolve with a discrete, 1D angiogenesis and blood flow model. Moreover, it is questionable if a discrete representation generates any useful additional insight. By contrast, our model may be classified as a hybrid vascular multiphase tumor growth model in the sense that a discrete, 1D representation of the preexisting vasculature is coupled with a continuum model describing angiogenesis. It is based on an originally avascular model which has been derived via the thermodynamically constrained averaging theory. The new model enables us to study mass transport from the preexisting vasculature into the neovasculature and tumor tissue. We show by means of several illustrative examples that it is indeed capable of reproducing important aspects of vascular tumor growth phenomenologically.

3D Microfluidic Bone Tumor Microenvironment Comprised of Hydroxyapatite/Fibrin Composite

Bone is one of the most common sites of cancer metastasis, as its fertile microenvironment attracts tumor cells. The unique mechanical properties of bone extracellular matrix (ECM), mainly composed of hydroxyapatite (HA) affect a number of cellular responses in the tumor microenvironment (TME) such as proliferation, migration, viability, and morphology, as well as angiogenic activity, which is related to bone metastasis. In this study, we engineered a bone-mimetic microenvironment to investigate the interactions between the TME and HA using a microfluidic platform designed for culturing tumor cells in 3D bone-mimetic composite of HA and fibrin. We developed a bone metastasis TME model from colorectal cancer (SW620) and gastric cancer (MKN74) cells, which has very poor prognosis but rarely been investigated. The microfluidic platform enabled straightforward formation of 3D TME composed the hydrogel and multiple cell types. This facilitated monitoring of the effect of HA concentration and culture time on the TME. In 3D bone mimicking culture, we found that HA rich microenvironment affects cell viability, proliferation and cancer cell cytoplasmic volume in a manner dependent on the different metastatic cancer cell types and culture duration indicating the spatial heterogeneity (different origin of metastatic cancer) and temporal heterogeneity (growth time of cancer) of TME. We also found that both SW620 and MKN72 cells exhibited significantly reduced migration at higher HA concentration in our platform indicating inhibitory effect of HA in both cancer cells migration. Next, we quantitatively analyzed angiogenic sprouts induced by paracrine factors that secreted by TME and showed paracrine signals from tumor and stromal cell with a high HA concentration resulted in the formation of fewer sprouts. Finally we reconstituted vascularized TME allowing direct interaction between angiogenic sprouts and tumor-stroma microspheroids in a bone-mimicking microenvironment composing a tunable HA/fibrin composite. Our multifarious approach could be applied to drug screening and mechanistic studies of the metastasis, growth, and progression of bone tumors.

Minimal dosing of leukocyte targeting TRAIL decreases triple-negative breast cancer metastasis following tumor resection

Surgical removal of the primary tumor is a common practice in breast cancer treatment. However, postsurgical metastasis poses an immense setback in cancer therapy. Considering that 90% of cancer-related deaths are due to metastasis, antimetastatic therapeutic strategies that can target disseminating tumor cells in the circulation before they can form secondary tumors hold preclinical and clinical potential for cancer patients. Our current work uses a liposomal formulation functionalized with the adhesion receptor E-selectin and the apoptosis-inducing ligand TNF (tumor necrosis factor)-related apoptosis-inducing ligand (TRAIL) to reduce metastasis following tumor resection in an aggressive triple-negative breast cancer (TNBC) mouse model. We demonstrate that minimal administration of E-selectin-TRAIL liposomes can target metastasis in a TNBC model, with primary tumor resection to mimic clinical settings. Our study indicates that TRAIL liposomes, alone or in combination with existing clinically approved therapies, may neutralize distant metastasis of a broad range of tumor types systemically.

Tumor Site-Dependent Transport Properties Determine Nanotherapeutics Delivery and Its Efficacy

Insufficient delivery of systemically administered anticancer drugs to tumors can compromise therapeutic efficacy and develop drug delivery-based therapeutic resistance. Nanotherapeutics such as PEGylated liposomal doxorubicin (PLD) are designed to preferentially accumulate in tumors utilizing enhanced permeation and retention effect. However, their antitumor effects and resulting clinical outcomes are modest and heterogeneous among tumors. Here, we aimed to investigate whether the amount and efficacy of PLD delivered to tumors are tumor site dependent. We established orthotopic primary tumor or liver metastases models of murine breast cancer using 4 T1 cells. PLD showed significant therapeutic effects against tumors that grew in primary mammary sites but not in the liver. We found that differences in therapeutic efficacy were not because of the intrinsic biological resistance of cancer cells but rather were associated with tumor site-dependent differences in transport properties, such as the amount of PLD delivery, blood vessel function, relative vascular permeability, and mechanical pressure in tumors. Thus, transport properties in tumor is site dependent and can be used as phenotypic surrogate markers for tumor drug delivery and therapeutic efficacy.

Clinical Cancer Nanomedicine

Nanotechnology offers new solutions for the development of cancer therapeutics that display improved efficacy and safety. Although several nanotherapeutics have received clinical approval, the most promising nanotechnology applications for patients still lie ahead. Nanoparticles display unique transport, biological, optical, magnetic, electronic, and thermal properties that are not apparent on the molecular or macroscale, and can be utilized for therapeutic purposes. These characteristics arise because nanoparticles are in the same size range as the wavelength of light and display large surface area to volume ratios. The large size of nanoparticles compared to conventional chemotherapeutic agents or biological macromolecule drugs also enables incorporation of several supportive components in addition to active pharmaceutical ingredients. These components can facilitate solubilization, protection from degradation, sustained release, immunoevasion, tissue penetration, imaging, targeting, and triggered activation. Nanoparticles are also processed differently in the body compared to conventional drugs. Specifically, nanoparticles display unique hemodynamic properties and biodistribution profiles. Notably, the interactions that occur at the bio-nano interface can be exploited for improved drug delivery. This review discusses successful clinically approved cancer nanodrugs as well as promising candidates in the pipeline. These nanotherapeutics are categorized according to whether they predominantly exploit multifunctionality, unique electromagnetic properties, or distinct transport characteristics in the body. Moreover, future directions in nanomedicine such as companion diagnostics, strategies for modifying the microenvironment, spatiotemporal nanoparticle transitions, and the use of extracellular vesicles for drug delivery are also explored.

Coupling tumor growth and bio distribution models

We couple a tumor growth model embedded in a microenvironment, with a bio distribution model able to simulate a whole organ. The growth model yields the evolution of tumor cell population, of the differential pressure between cell populations, of porosity of ECM, of consumption of nutrients due to tumor growth, of angiogenesis, and related growth factors as function of the locally available nutrient. The bio distribution model on the other hand operates on a frozen geometry but yields a much refined distribution of nutrient and other molecules. The combination of both models will enable simulating the growth of a tumor in a whole organ, including a realistic distribution of therapeutic agents and allow hence to evaluate the efficacy of these agents.

Mathematical modeling of tumor-immune cell interactions

The anti-tumor activity of the immune system is increasingly recognized as critical for the mounting of a prolonged and effective response to cancer growth and invasion, and for preventing recurrence following resection or treatment. As the knowledge of tumor-immune cell interactions has advanced, experimental investigation has been complemented by mathematical modeling with the goal to quantify and predict these interactions. This succinct review offers an overview of recent tumor-immune continuum modeling approaches, highlighting spatial models. The focus is on work published in the past decade, incorporating one or more immune cell types and evaluating immune cell effects on tumor progression. Due to their relevance to cancer, the following immune cells and their combinations are described: macrophages, Cytotoxic T Lymphocytes, Natural Killer cells, dendritic cells, T regulatory cells, and CD4+ T helper cells. Although important insight has been gained from a mathematical modeling perspective, the development of models incorporating patient-specific data remains an important goal yet to be realized for potential clinical benefit.

Tyrosinase-Loaded Multicompartment Microreactor toward Melanoma Depletion

Melanoma is malignant skin cancer occurring with increasing prevalence with no effective treatment. A unique feature of melanoma cells is that they require higher concentrations of ltyrosine (l-tyr) for expansion than normal cells. As such, it has been demonstrated that dietary l-tyr restriction lowers systemic l-tyr and suppresses melanoma advancement in mice. Unfortunately, this diet is not well tolerated by humans. An alternative approach to impede melanoma progression will be to administer the enzyme tyrosinase (TYR), which converts l-tyr into melanin. Herein, a multicompartment carrier consisting of a polymer shell entrapping thousands of liposomes is employed to act as a microreactor depleting l-tyr in the presence of melanoma cells. It is shown that the TYR enzyme can be incorporated within the liposomal subunits with preserved catalytic activity. Aiming to mimic the dynamic environment at the tumor site, l-tyr conversion is conducted by co-culturing melanoma cells and microreactors in a microfluidic setup with applied intratumor shear stress. It is demonstrated that the microreactors are concurrently depleting l-tyr, which translates into inhibited melanoma cell growth. Thus, the first microreactor where the depletion of a substrate translates into antitumor properties in vitro is reported.

3D Microfluidic Bone Tumor Microenvironment Comprised of Hydroxyapatite/Fibrin Composite

Bone is one of the most common sites of cancer metastasis, as its fertile microenvironment attracts tumor cells. The unique mechanical properties of bone extracellular matrix (ECM), mainly composed of hydroxyapatite (HA) affect a number of cellular responses in the tumor microenvironment (TME) such as proliferation, migration, viability, and morphology, as well as angiogenic activity, which is related to bone metastasis. In this study, we engineered a bone-mimetic microenvironment to investigate the interactions between the TME and HA using a microfluidic platform designed for culturing tumor cells in 3D bone-mimetic composite of HA and fibrin. We developed a bone metastasis TME model from colorectal cancer (SW620) and gastric cancer (MKN74) cells, which has very poor prognosis but rarely been investigated. The microfluidic platform enabled straightforward formation of 3D TME composed the hydrogel and multiple cell types. This facilitated monitoring of the effect of HA concentration and culture time on the TME. In 3D bone mimicking culture, we found that HA rich microenvironment affects cell viability, proliferation and cancer cell cytoplasmic volume in a manner dependent on the different metastatic cancer cell types and culture duration indicating the spatial heterogeneity (different origin of metastatic cancer) and temporal heterogeneity (growth time of cancer) of TME. We also found that both SW620 and MKN72 cells exhibited significantly reduced migration at higher HA concentration in our platform indicating inhibitory effect of HA in both cancer cells migration. Next, we quantitatively analyzed angiogenic sprouts induced by paracrine factors that secreted by TME and showed paracrine signals from tumor and stromal cell with a high HA concentration resulted in the formation of fewer sprouts. Finally we reconstituted vascularized TME allowing direct interaction between angiogenic sprouts and tumor-stroma microspheroids in a bone-mimicking microenvironment composing a tunable HA/fibrin composite. Our multifarious approach could be applied to drug screening and mechanistic studies of the metastasis, growth, and progression of bone tumors.

A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal Adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology.

EXPERIMENTAL DESIGN

We developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology.

RESULTS

In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth.

CONCLUSIONS

At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.

Chemoresistance of Cancer Cells: Requirements of Tumor Microenvironment-mimicking In Vitro Models in Anti-Cancer Drug Development

For decades, scientists have been using two-dimensional cell culture platforms for high-throughput drug screening of anticancer drugs. Growing evidence indicates that the results of anti-cancer drug screening vary with the cell culture microenvironment, and this variation has been proposed as a reason for the high failure rate of clinical trials. Since the culture condition-dependent drug sensitivity of anti-cancer drugs may negatively impact the identification of clinically effective drug candidates, more reliable in vitro cancer platforms are urgently needed. In this review article, we provide an overview of how cell culture conditions can alter drug efficacy and highlight the importance of developing more reliable cancer drug testing platforms for use in the drug discovery process. The environmental factors that can alter drug delivery and efficacy are reviewed. Based on these observations of chemoresistant tumor physiology, we summarize the recent advances in the fabrication of in vitro cancer models and the model-dependent cytotoxicity of anti-cancer drugs, with a particular focus on engineered environmental factors in these platforms. It is believed that more physiologically relevant cancer models can revolutionize the drug discovery process.

Temporary suppression the sequestrated function of host macrophages for better nanoparticles tumor delivery

Orchestration of nanoparticles to achieve targeting has become the mainstream for efficient delivery of antitumor drugs. However, the low delivery efficiency becomes the biggest barrier for clinical translation of cancer nanomedicines, as most of them are sequestrated in the liver where more macrophages located in are responsible for capture of systemic administrated nanoparticles. In this study, we found that the depletion of the liver macrophages could lead to a superior improvement in the nanoparticles delivery. Firstly, we developed clodronate-containing liposomes (clodrolip) to transiently suppress the phagocytic function of macrophages, the residual macrophages in liver only accounted for less than 1% when the mice were treated with clodrolip in advance. In addition, the pharmacokinetics results of treatment with paclitaxel-poly(lactic-co-glycolic acid) (PTX-PLGA) nanoparticles disclosed that the AUC of PTX in the macrophages depletion group increased 2.11-fold. These results meant that the removal of macrophages would decrease the nanoparticles accumulation in the liver and better the biodistribution and bioavailability of nanoparticles delivery systems. Moreover, treatment of mice with melanoma by the combination of clodrolip and PTX-PLGA nanoparticles resulted in an elevated anti-tumor efficacy, the tumor inhibition ratio was nearly reached to 80%. Furthermore, these combinatorial regimens have demonstrated negligible toxicity in incidence of adverse effects. In conclusion, the encouraging results from this study inspire the generation of a rational strategy to focus on microenvironmental priming for modulation of innate immunity and to improve delivery efficiency of nanoparticles.

A monolithic multiphase porous medium framework for (a-)vascular tumor growth

We present a dynamic vascular tumor model combining a multiphase porous medium framework for avascular tumor growth in a consistent Arbitrary Lagrangian Eulerian formulation and a novel approach to incorporate angiogenesis. The multiphase model is based on Thermodynamically Constrained Averaging Theory and comprises the extracellular matrix as a porous solid phase and three fluid phases: (living and necrotic) tumor cells, host cells and the interstitial fluid. Angiogenesis is modeled by treating the neovasculature as a proper additional phase with volume fraction or blood vessel density. This allows us to define consistent inter-phase exchange terms between the neovasculature and the interstitial fluid. As a consequence, transcapillary leakage and lymphatic drainage can be modeled. By including these important processes we are able to reproduce the increased interstitial pressure in tumors which is a crucial factor in drug delivery and, thus, therapeutic outcome. Different coupling schemes to solve the resulting five-phase problem are realized and compared with respect to robustness and computational efficiency. We find that a fully monolithic approach is superior to both the standard partitioned and a hybrid monolithic-partitioned scheme for a wide range of parameters. The flexible implementation of the novel model makes further extensions (e.g., inclusion of additional phases and species) straightforward.

Rethinking Causation in Cancer with Evolutionary Developmental Biology

Despite the productivity of basic cancer research, cancer continues to be a health burden to society because this research has not yielded corresponding clinical applications. Many proposed solutions to this dilemma have revolved around implementing organizational and policy changes related to cancer research. Here I argue for a different solution: a new conceptualization of causation in cancer. Neither the standard molecular biomarker approaches nor evolutionary biology approaches to cancer fully capture its complex causal dynamics, even when considered jointly. These approaches map on to Ernst Mayr's proximate-ultimate distinction, which is an inadequate conceptualization of causation in biological systems and makes it difficult to connect developmental and evolutionary viewpoints. I propose looking to evolutionary developmental biology (EvoDevo) to overcome the distinction and integrate the proximate and ultimate causal frameworks. I use the concepts of modularity and evolvability to show how an EvoDevo perspective can be manifested in cancer translational research. This perspective on causation in cancer is better suited for integrating the complexity of current empirical results and can facilitate novel developments in the investigation and clinical treatment of cancer.

Shear stress regulated uptake of liposome-decorated microgels coated with a poly(dopamine) shell

Advanced multicompartment drug delivery platforms ensure the co-localization of several drugs within the same carrier, thus making it possible to achieve a more effective and safe therapeutic outcome. Herein, we report a novel multicompartment architecture by combining two intrinsically different systems, i.e., polymeric microgels and liposomes, with the aim to achieve different release kinetics for model compounds. We assemble poly(N-isopropylacrylamide-co-acrylic acid) microgels decorated with liposomes which are subsequently coated with a protective poly(dopamine) shell and a poly(ethylene glycol) (PEG) layer. Since any intravenous administered drug delivery vehicle will get in contact with the dynamics of the blood flow, we evaluate the stealth properties of this novel multicompartment carrier towards protein adsorption and cellular uptake by three relevant cell lines (macrophages, endothelial and cancer cells) under physiological shear stress conditions. Our results demonstrate less protein adsorption for the PEGylated carriers and differences in the extent of internalized carriers depending on the presence of a PEG coating, the studied cell line and the intensity of the applied shear stress. Additionally, we demonstrate that, for all three tested cell lines, shear stress results in the activation of different cell entry pathways as compared to static conditions. All in all, we report a thorough study about the effect of shear stress on the cell association/uptake with a novel multicompartment carrier.

Simulation of Multispecies Desmoplastic Cancer Growth via a Fully Adaptive Non-linear Full Multigrid Algorithm

A fully adaptive non-linear full multigrid (FMG) algorithm is implemented to computationally simulate a model of multispecies desmoplastic tumor growth in three spatial dimensions. The algorithm solves a thermodynamic mixture model employing a diffuse interface approach with Cahn-Hilliard-type fourth-order equations that are coupled, non-linear, and numerically stiff. The tumor model includes extracellular matrix (ECM) as a major component with elastic energy contribution in its chemical potential term. Blood and lymphatic vasculatures are simulated via continuum representations. The model employs advection-reaction-diffusion partial differential equations (PDEs) for the cell, ECM, and vascular components, and reaction-diffusion PDEs for the elements diffusing from the vessels. This study provides the details of the numerical solution obtained by applying the fully adaptive non-linear FMG algorithm with finite difference method to solve this complex system of PDEs. The results indicate that this type of computational model can simulate the extracellular matrix-rich desmoplastic tumor microenvironment typical of fibrotic tumors, such as pancreatic adenocarcinoma.