Modeling the mechanics of cancer: effect of changes in cellular and extra-cellular mechanical properties

"Patchiness" in mechanical stiffness across a tumor as an early-stage marker for malignancy

Mechanical phenotyping of tumors, either at an individual cell level or tumor cell population level is gaining traction as a diagnostic tool. However, the extent of diagnostic and prognostic information that can be gained through these measurements is still unclear. In this work, we focus on the heterogeneity in mechanical properties of cells obtained from a single source such as a tissue or tumor as a potential novel biomarker. We believe that this heterogeneity is a conventionally overlooked source of information in mechanical phenotyping data. We use mechanics-based in-silico models of cell-cell interactions and cell population dynamics within 3D environments to probe how heterogeneity in cell mechanics drives tissue and tumor dynamics. Our simulations show that the initial heterogeneity in the mechanical properties of individual cells and the arrangement of these heterogenous sub-populations within the environment can dictate overall cell population dynamics and cause a shift towards the growth of malignant cell phenotypes within healthy tissue environments. The overall heterogeneity in the cellular mechanotype and their spatial distributions is quantified by a "patchiness" index, which is the ratio of the global to local heterogeneity in cell populations. We observe that there exists a threshold value of the patchiness index beyond which an overall healthy population of cells will show a steady shift towards a more malignant phenotype. Based on these results, we propose that the "patchiness" of a tumor or tissue sample, can be an early indicator for malignant transformation and cancer occurrence in benign tumors or healthy tissues. Additionally, we suggest that tissue patchiness, measured either by biochemical or biophysical markers, can become an important metric in predicting tissue health and disease likelihood just as landscape patchiness is an important metric in ecology.

Discovery of a septin-4 covalent binder with antimetastatic activity in a mouse model of melanoma

Cancer spreading through metastatic processes is one of the major causes of tumour-related mortality. Metastasis is a complex phenomenon which involves multiple pathways ranging from cell metabolic alterations to changes in the biophysical phenotype of cells and tissues. In the search for new effective anti-metastatic agents, we modulated the chemical structure of the lead compound AA6, in order to find the structural determinants of activity, and to identify the cellular target responsible of the downstream anti-metastatic effects observed. New compounds synthesized were able to inhibit in vitro B16-F10 melanoma cell invasiveness, and one selected compound, CM365, showed in vivo anti-metastatic effects in a lung metastasis mouse model of melanoma. Septin-4 was identified as the most likely molecular target responsible for these effects. This study showed that CM365 is a promising molecule for metastasis prevention, remarkably effective alone or co-administered with drugs normally used in cancer therapy, such as paclitaxel.

Role of galectin-3 in the elastic response of radial growth phase melanoma cancer cells

Melanoma is originated from the malignant transformation of the melanocytes and is characterized by a high rate of invasion, the more serious stage compromising deeper layers of the skin and eventually leading to the metastasis. A high mortality due to melanoma lesion persists because most of melanoma lesions are detected in advanced stages, which decreases the chances of survival. The identification of the principal mechanics implicated in the development and progression of melanoma is essential to devise new early diagnosis strategies. Cell mechanics is related with a lot of cellular functions and processes, for instance motility, differentiation, migration and invasion. In particular, the elastic modulus (Young's modulus) is a very explored parameter to describe the cell mechanical properties; most cancer cells reported in the literature smaller elasticity modulus. In this work, we show that the elastic modulus of melanoma cells lacking galectin-3 is significantly lower than those of melanoma cells expressing galectin-3. More interestingly, the gradient of elastic modulus in cells from the nuclear region towards the cell periphery is more pronounced in shGal3 cells. RESEARCH HIGHLIGHTS: AFM imaging and force spectroscopy were used to investigate the morphology and elasticity properties of healthy HaCaT cells and melanoma cells WM1366, with (shSCR) and without (shGal3) expression of galectin-3. It is shown the effect of galectin-3 protein on the elastic properties of cells: the cells without expression of galectin-3 presents lower elastic modulus. By the results, we suggest here that galectin-3 could be used as an effective biomarker of malignancy in both melanoma diagnostic and prognosis.

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.

Impact of elastic substrate on the dynamic heterogeneity of WC256 Walker carcinosarcoma cells

Cellular heterogeneity is a phenomenon in which cell populations are composed of subpopulations that vary in their behavior. Heterogeneity is particularly pronounced in cancer cells and can affect the efficacy of oncological therapies. Previous studies have considered heterogeneity dynamics to be indicative of evolutionary changes within subpopulations; however, these studies do not consider the short-time morphological plasticity of cells. Physical properties of the microenvironment elasticity have also been poorly investigated within the context of cellular heterogeneity, despite its role in determining cellular behavior. This article demonstrates that cellular heterogeneity can be highly dynamic and dependent on the micromechanical properties of the substrate. During observation, migrating Walker carcinosarcoma WC256 cells were observed to belong to different subpopulations, in which their morphologies and migration strategies differed. Furthermore, the application of an elastic substrate (E = 40 kPa) modified three aspects of cellular heterogeneity: the occurrence of subpopulations, the occurrence of transitions between subpopulations, and cellular migration and morphology. These findings provide a new perspective in the analysis of cellular heterogeneity, whereby it may not be a static feature of cancer cell populations, instead varying over time. This helps further the understanding of cancer cell behavior, including their phenotype and migration strategy, which may help to improve cancer therapies by extending their suitability to investigate tumor heterogeneity.

Encapsulation and adhesion of nanoparticles as a potential biomarker for TNBC cells metastatic propensity

Metastasis is the main cause of cancer-related mortality; therefore, the ability to predict its propensity can remarkably affect survival rate. Metastasis development is predicted nowadays by lymph-node status, tumor size, histopathology, and genetic testing. However, all these methods may have inaccuracies, and some require weeks to complete. Identifying novel prognostic markers will open an essential source for risk prediction, possibly guiding to elevated patient treatment by personalized strategies. Cancer cell invasion is a critical step in metastasis. The cytoskeletal mechanisms used by metastatic cells for the invasion process are very similar to the utilization of actin cytoskeleton in the endocytosis process. In the current study, the adhesion and encapsulation efficiency of low-cost carboxylate-modified fluorescent nanoparticles by breast cancer cells with high (HM) and low metastatic potential (LM) have been evaluated; benign cells were used as control. Using high-content fluorescence imaging and analysis, we have revealed (within a short time of 1 h), that efficiency of nanoparticles adherence and encapsulation is sufficiently higher in HM cells compared to LM cells, while benign cells are not encapsulating or adhering the particles during experiment time at all. We have utilized custom-made automatic image analysis algorithms to find quantitative co-localization (Pearson's coefficients) of the nanoparticles with the imaged cells. The method proposed here is straightforward; it does not require especial equipment or expensive materials nor complicated cell manipulations, it may be potentially applicable for various cells, including patient-derived cells. Effortless and quantitative determination of the metastatic likelihood has the potential to be performed using patient-specific biopsy/surgery sample, which will directly influence the choice of protocols for cancer patient's treatment and, as a result, increase their life expectancy.

Electrospun Drug-Loaded and Gene-Loaded Nanofibres: The Holy Grail of Glioblastoma Therapy?

To date, GBM remains highly resistant to therapies that have shown promising effects in other cancers. Therefore, the goal is to take down the shield that these tumours are using to protect themselves and proliferate unchecked, regardless of the advent of diverse therapies. To overcome the limitations of conventional therapy, the use of electrospun nanofibres encapsulated with either a drug or gene has been extensively researched. The aim of this intelligent biomaterial is to achieve a timely release of encapsulated therapy to exert the maximal therapeutic effect simultaneously eliminating dose-limiting toxicities and activating the innate immune response to prevent tumour recurrence. This review article is focused on the developing field of electrospinning and aims to describe the different types of electrospinning techniques in biomedical applications. Each technique describes how not all drugs or genes can be electrospun with any method; their physico-chemical properties, site of action, polymer characteristics and the desired drug or gene release rate determine the strategy used. Finally, we discuss the challenges and future perspectives associated with GBM therapy.

Challenges and Opportunities Modeling the Dynamic Tumor Matrisome

We need novel strategies to target the complexity of cancer and, particularly, of metastatic disease. As an example of this complexity, certain tissues are particularly hospitable environments for metastases, whereas others do not contain fertile microenvironments to support cancer cell growth. Continuing evidence that the extracellular matrix (ECM) of tissues is one of a host of factors necessary to support cancer cell growth at both primary and secondary tissue sites is emerging. Research on cancer metastasis has largely been focused on the molecular adaptations of tumor cells in various cytokine and growth factor environments on 2-dimensional tissue culture polystyrene plates. Intravital imaging, conversely, has transformed our ability to watch, in real time, tumor cell invasion, intravasation, extravasation, and growth. Because the interstitial ECM that supports all cells in the tumor microenvironment changes over time scales outside the possible window of typical intravital imaging, bioengineers are continuously developing both simple and sophisticated in vitro controlled environments to study tumor (and other) cell interactions with this matrix. In this perspective, we focus on the cellular unit responsible for upholding the pathologic homeostasis of tumor-bearing organs, cancer-associated fibroblasts (CAFs), and their self-generated ECM. The latter, together with tumoral and other cell secreted factors, constitute the "tumor matrisome". We share the challenges and opportunities for modeling this dynamic CAF/ECM unit, the tools and techniques available, and how the tumor matrisome is remodeled (e.g., via ECM proteases). We posit that increasing information on tumor matrisome dynamics may lead the field to alternative strategies for personalized medicine outside genomics.

Gold Nano-Bio-Interaction to Modulate Mechanobiological Responses for Cancer Therapy Applications

In the present study, we investigate the mechanobiological responses of human lung cancer that may occur through their interactions with two different types of gold nanoparticles: nanostars and nanospheres. Hyperspectral images of nanoparticle-treated cells revealed different spatial distributions of nanoparticles in cells depending on their morphology, with nanospheres being more uniformly distributed in cells than nanostars. Gold nanospheres were also found to be more effective in mechanobiological modulations. They significantly suppressed the migratory ability of cells under different incubation times while lowering the bulk stiffness and adhesion of cells. This in vitro study suggests the potential applications of gold nanoparticles to manage cell migration. Nano-bio-interactions appeared to impact the cytoskeletal organization of cells and consequently alter the mechanical properties of cells, which could influence the cellular functions of cells. According to the results and migratory index model, it is thought that nanoparticle-treated cells experience mechanical changes in their body, which largely reduces their migratory potentials. These findings provide a better understanding of nano-bio-interaction in terms of cell mechanics and highlight the importance of mechanobiological responses in designing gold nanoparticles for cancer therapy.

Potential anticancer properties and mechanisms of thymoquinone in osteosarcoma and bone metastasis

Despite great advances, therapeutic approaches of osteosarcoma, the most prevalent class of preliminary pediatric bone tumors, as well as bone-related malignancies, continue to demonstrate insufficient adequacy. In recent years, a growing trend toward applying natural bioactive compounds, particularly phytochemicals, as novel agents for cancer treatment has been observed. Bioactive phytochemicals exert their anticancer features through two main ways: they induce cytotoxic effects against cancerous cells without having any detrimental impact on normal cell macromolecules such as DNA and enzymes, while at the same time combating the oncogenic signaling axis activated in tumor cells. Thymoquinone (TQ), the most abundant bioactive compound of Nigella sativa, has received considerable attention in cancer treatment owing to its distinctive properties, including apoptosis induction, cell cycle arrest, angiogenesis and metastasis inhibition, and reactive oxygen species (ROS) generation, along with inducing immune system responses and reducing side effects of traditional chemotherapeutic drugs. The present review is focused on the characteristics and mechanisms by which TQ exerts its cytotoxic effects on bone malignancies.

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

One of the outstanding challenges of the mathematical modeling of cancer progression is the existence of many unknown parameters. In this work, we develop a data-driven mathematical model of breast cancer progression by deriving a system of ordinary differential equations for the interaction networks of key cell types and molecules in breast tumors. To overcome the limitations of unknown parameters, we utilize a time course data of a PyMT mice model of breast cancer and estimate parameters using an optimization method. Although the predicted dynamics of cancer and necrotic cells using the obtained values of parameters are in good agreement with the data, the predicted values for a few other variables do not match the data. This might indicate that there are some other key interactions that have not been modeled, and/or there is a noise in the data. The sensitivity and bifurcation analyses show that the most important parameters in controlling the cancer cells population are the proliferation and death rates of cancer cells and adipocytes. These results are in agreement with some biological and clinical studies of breast cancer, which have reported a link between adipocytes and breast cancer progression.

Mechanomimetic 3D Scaffolds as a Humanized In Vitro Model for Ovarian Cancer

The mechanical homeostasis of tissues can be altered in response to trauma or disease, such as cancer, resulting in altered mechanotransduction pathways that have been shown to impact tumor development, progression, and the efficacy of therapeutic approaches. Specifically, ovarian cancer progression is parallel to an increase in tissue stiffness and fibrosis. With in vivo models proving difficult to study, tying tissue mechanics to altered cellular and molecular properties necessitate advanced, tunable, in vitro 3D models able to mimic normal and tumor mechanic features. First, we characterized normal human ovary and high-grade serous (HGSC) ovarian cancer tissue stiffness to precisely mimic their mechanical features on collagen I-based sponge scaffolds, soft (NS) and stiff (MS), respectively. We utilized three ovarian cancer cell lines (OVCAR-3, Caov-3, and SKOV3) to evaluate changes in viability, morphology, proliferation, and sensitivity to doxorubicin and liposomal doxorubicin treatment in response to a mechanically different microenvironment. High substrate stiffness promoted the proliferation of Caov-3 and SKOV3 cells without changing their morphology, and upregulated mechanosensors YAP/TAZ only in SKOV3 cells. After 7 days in culture, both OVCAR3 and SKOV3 decreased the MS scaffold storage modulus (stiffness), suggesting a link between cell proliferation and the softening of the matrix. Finally, high matrix stiffness resulted in higher OVCAR-3 and SKOV3 cell cytotoxicity in response to doxorubicin. This study demonstrates the promise of biomimetic porous scaffolds for effective inclusion of mechanical parameters in 3D cancer modeling. Furthermore, this work establishes the use of porous scaffolds for studying ovarian cancer cells response to mechanical changes in the microenvironment and as a meaningful platform from which to investigate chemoresistance and drug response.

Mechanical Properties in the Glioma Microenvironment: Emerging Insights and Theranostic Opportunities

Gliomas represent the most common malignant primary brain tumors, and a high-grade subset of these tumors including glioblastoma are particularly refractory to current standard-of-care therapies including maximal surgical resection and chemoradiation. The prognosis of patients with these tumors continues to be poor with existing treatments and understanding treatment failure is required. The dynamic interplay between the tumor and its microenvironment has been increasingly recognized as a key mechanism by which cellular adaptation, tumor heterogeneity, and treatment resistance develops. Beyond ongoing lines of investigation into the peritumoral cellular milieu and microenvironmental architecture, recent studies have identified the growing role of mechanical properties of the microenvironment. Elucidating the impact of these biophysical factors on disease heterogeneity is crucial for designing durable therapies and may offer novel approaches for intervention and disease monitoring. Specifically, pharmacologic targeting of mechanical signal transduction substrates such as specific ion channels that have been implicated in glioma progression or the development of agents that alter the mechanical properties of the microenvironment to halt disease progression have the potential to be promising treatment strategies based on early studies. Similarly, the development of technology to measure mechanical properties of the microenvironment in vitro and in vivo and simulate these properties in bioengineered models may facilitate the use of mechanical properties as diagnostic or prognostic biomarkers that can guide treatment. Here, we review current perspectives on the influence of mechanical properties in glioma with a focus on biophysical features of tumor-adjacent tissue, the role of fluid mechanics, and mechanisms of mechanical signal transduction. We highlight the implications of recent discoveries for novel diagnostics, therapeutic targets, and accurate preclinical modeling of glioma.

The Effect of Acetylsalicylic Acid (ASA) on the Mechanical Properties of Breast Cancer Epithelial Cells

BACKGROUND

In most communities, the risk of developing breast cancer is increasing. By affecting the cyclooxygenase 1 and 2 (COX-1 and COX-2) enzymes and actin filaments, acetylsalicylic acid (Aspirin) has been shown to reduce the risk of breast cancer and prevent cell migration in both laboratory and clinical studies.

METHODS

The purpose of this study is to determine the mechanical properties of normal and cancerous breast tissue cells, as well as the short-term effect of aspirin on cancer cells. To this end, the mechanical properties and deformation of three cell types were investigated: healthy MCF-10 breast cells, MCF-7 breast cancer cells, and MCF-7 breast cancer cells treated with a 5 µM aspirin solution. Atomic Force Microscopy (AFM) was used to determine the mechanical properties of the cells. Cell deformation was analyzed in all groups, and Young's modulus was calculated using the Hertz model.

RESULT

According to the obtained data, cancer cells deformed at a rate half that of healthy cells. Nonetheless, when aspirin was used, cancer cells deformed similarly to healthy cells. Additionally, healthy cells' Young's modulus was calculated to be approximately three times that of cancer cells, which was placed closer to that of healthy cells by adding aspirin to Young's modulus.

CONCLUSION

Cell strength appears to have increased due to aspirin's intervention on actin filaments and cytoskeletons, and the mechanical properties of breast cancer cells have become more similar to those of normal cells. The likelihood of cell migration and metastasis decreases as cell strength increases.

Mapping Mechanical Properties of the Tumor Microenvironment by Laser Speckle Rheological Microscopy

Altered mechanical properties of the tumor matrix have emerged as both the cause and consequence of breast carcinogenesis. Increased tumor stiffness has traditionally provided a viable metric to screen for malignancies via palpation or imaging. Previous studies have demonstrated that the microscale mechanical properties of the cell substrate influence tumor proliferation and invasive migration in vitro. Nevertheless, the association of the mechanical microenvironment with clinical hallmarks of aggressiveness in human breast tumors, including histopathological subtype, grade, receptor expression status, and lymph node involvement is poorly understood. This is largely due to the lack of tools for mapping tumor viscoelastic properties in clinical specimens with high spatial resolution over a large field of view (FoV). Here we introduce laser Speckle rHEologicAl micRoscopy (SHEAR) that for the first time enables mapping the magnitude viscoelastic or shear modulus, |G*(x,y,ω)|, over a range of frequencies (ω = 1-250 rad/second) in excised tumors within minutes with a spatial resolution of approximately 50 μm, over multiple cm² FoV. Application of SHEAR in a cohort of 251 breast cancer specimens from 148 patients demonstrated that |G*(x,y,ω)| (ω = 2π rad/second) closely corresponds with histological features of the tumor, and that the spatial gradient of the shear modulus, |∇|G*(x,y,ω)||, is elevated at the tumor invasive front. Multivariate analyses established that the metrics, (|G* |) and (|∇|G* ||), measured by SHEAR are associated with prognosis. These findings implicate the viscoelastic properties of the tumor microenvironment in breast cancer prognosis and likely pave the path for identifying new modifiable targets for treatment. SIGNIFICANCE: Laser speckle rheological microscopy establishes the links between microscale heterogeneities of viscoelasticity and histopathological subtype, tumor grade, receptor expression, as well as lymph node status in breast carcinoma.

Mechanical Pressure Driving Proteoglycan Expression in Mammographic Density: a Self-perpetuating Cycle?

Regions of high mammographic density (MD) in the breast are characterised by a proteoglycan (PG)-rich fibrous stroma, where PGs mediate aligned collagen fibrils to control tissue stiffness and hence the response to mechanical forces. Literature is accumulating to support the notion that mechanical stiffness may drive PG synthesis in the breast contributing to MD. We review emerging patterns in MD and other biological settings, of a positive feedback cycle of force promoting PG synthesis, such as in articular cartilage, due to increased pressure on weight bearing joints. Furthermore, we present evidence to suggest a pro-tumorigenic effect of increased mechanical force on epithelial cells in contexts where PG-mediated, aligned collagen fibrous tissue abounds, with implications for breast cancer development attributable to high MD. Finally, we summarise means through which this positive feedback mechanism of PG synthesis may be intercepted to reduce mechanical force within tissues and thus reduce disease burden.

Emerging principles of cancer biophysics

Cancer is a multi-step process where normal cells become transformed, grow, and may disseminate to establish new lesions within the body. In recent years, the physical properties of individual cells and the tissue microenvironment have been shown to be potent determinants of cancer progression. Biophysical tools have long been used to examine cell and tissue mechanics, morphology, and migration. However, exciting developments have linked these physical traits to gene expression changes that drive metastatic seeding, organ selectivity, and tumor growth. Here, we present some vignettes to address recent studies to show progress in harnessing biophysical tools and concepts to gain insights into metastasis.

Non-thermal membrane effects of electromagnetic fields and therapeutic applications in oncology

The temperature-independent effects of electromagnetic fields (EMF) have been controversial for decades. Here, we critically analyze the available literature on non-thermal effects of radiofrequency (RF) and microwave EMF. We present a literature review of preclinical and clinical data on non-thermal antiproliferative effects of various EMF applications, including conventional RF hyperthermia (HT, cRF-HT). Further, we suggest and evaluate plausible biophysical and electrophysiological models to decipher non-thermal antiproliferative membrane effects. Available preclinical and clinical data provide sufficient evidence for the existence of non-thermal antiproliferative effects of exposure to cRF-HT, and in particular, amplitude modulated (AM)-RF-HT. In our model, transmembrane ion channels function like RF rectifiers and low-pass filters. cRF-HT induces ion fluxes and AM-RF-HT additionally promotes membrane vibrations at specific resonance frequencies, which explains the non-thermal antiproliferative membrane effects via ion disequilibrium (especially of Ca²⁺) and/or resonances causing membrane depolarization, the opening of certain (especially Ca²⁺) channels, or even hole formation. AM-RF-HT may be tumor-specific owing to cancer-specific ion channels and because, with increasing malignancy, membrane elasticity parameters may differ from that in normal tissues. Published literature suggests that non-thermal antiproliferative effects of cRF-HT are likely to exist and could present a high potential to improve future treatments in oncology.

Hydrodynamic shear-based purification of cancer cells with enhanced tumorigenic potential

Tumor-initiating cells (TICs), a subpopulation of cancerous cells with high tumorigenic potential and stem-cell-like properties, drive tumor progression and are resistant to conventional therapies. Identification and isolation of TICs are limited by their low frequency and lack of robust markers. Here, we characterize the heterogeneous adhesive properties of a panel of human and murine cancer cells and demonstrate differences in adhesion strength among cells, which exhibit TIC properties and those that do not. These differences in adhesion strength were exploited to rapidly (~10 min) and efficiently isolate cancerous cells with increased tumorigenic potential in a label-free manner by use of a microfluidic technology. Isolated murine and human cancer cells gave rise to larger tumors with increased growth rate and higher frequency in both immunocompetent and immunocompromised mice, respectively. This rapid and label-free TIC isolation technology has the potential to be a valuable tool for facilitating research into TIC biology and the development of more efficient diagnostics and cancer therapies.

Repulsive expansion dynamics in colony growth and gene expression

Spatial expansion of a population of cells can arise from growth of microorganisms, plant cells, and mammalian cells. It underlies normal or dysfunctional tissue development, and it can be exploited as the foundation for programming spatial patterns. This expansion is often driven by continuous growth and division of cells within a colony, which in turn pushes the peripheral cells outward. This process generates a repulsion velocity field at each location within the colony. Here we show that this process can be approximated as coarse-grained repulsive-expansion kinetics. This framework enables accurate and efficient simulation of growth and gene expression dynamics in radially symmetric colonies with homogenous z-directional distribution. It is robust even if cells are not spherical and vary in size. The simplicity of the resulting mathematical framework also greatly facilitates generation of mechanistic insights.

Spatiotemporal dynamics are ubiquitous in biology. To understand these phenomena in nature or to program them using synthetic gene circuits, it is critical to resort to mathematical modeling to deduce mechanistic insights or to explore plausible outcomes. Historically, modeling of spatiotemporal dynamics depends on the use of agent-based models or their continuum counterparts consisting of partial differential equations. Here, we show that a class of colony expansion can be treated as being driven by the steric force generated by growing and diving cells. This approximation leads to a drastically simplified framework consisting of only ordinary differential equations. This framework greatly improves the computational efficiency and facilitates development of mechanistic insights into the dynamics of colony growth and pattern formation.

A Universal Model for the Log-Normal Distribution of Elasticity in Polymeric Gels and Its Relevance to Mechanical Signature of Biological Tissues

Simple Summary

Mechanical properties of biological tissues are increasingly recognized as important in biology. Atomic force microscopy (AFM) is one of the main tools used to assess elastic properties of various types of biological samples. It has been noted that elasticity values frequently follow a log-normal distribution. We propose in this communication a physical model explaining this fact, and we propose that distribution-type analysis could increase the information obtained from AFM studies on biological tissues.

Abstract

The mechanosensitivity of cells has recently been identified as a process that could greatly influence a cell’s fate. To understand the interaction between cells and their surrounding extracellular matrix, the characterization of the mechanical properties of natural polymeric gels is needed. Atomic force microscopy (AFM) is one of the leading tools used to characterize mechanically biological tissues. It appears that the elasticity (elastic modulus) values obtained by AFM presents a log-normal distribution. Despite its ubiquity, the log-normal distribution concerning the elastic modulus of biological tissues does not have a clear explanation. In this paper, we propose a physical mechanism based on the weak universality of critical exponents in the percolation process leading to gelation. Following this, we discuss the relevance of this model for mechanical signatures of biological tissues.

Probing coordinated co-culture cancer related motility through differential micro-compartmentalized elastic substrates

Cell development and behavior are driven by internal genetic programming, but the external microenvironment is increasingly recognized as a significant factor in cell differentiation, migration, and in the case of cancer, metastatic progression. Yet it remains unclear how the microenvironment influences cell processes, especially when examining cell motility. One factor that affects cell motility is cell mechanics, which is known to be related to substrate stiffness. Examining how cells interact with each other in response to mechanically differential substrates would allow an increased understanding of their coordinated cell motility. In order to probe the effect of substrate stiffness on tumor related cells in greater detail, we created hard–soft–hard (HSH) polydimethylsiloxane (PDMS) substrates with alternating regions of different stiffness (200 and 800 kPa). We then cultured WI-38 fibroblasts and A549 epithelial cells to probe their motile response to the substrates. We found that when the 2 cell types were exposed simultaneously to the same substrate, fibroblasts moved at an increased speed over epithelial cells. Furthermore, the HSH substrate allowed us to physically guide and separate the different cell types based on their relative motile speed. We believe that this method and results will be important in a diversity of areas including mechanical microenvironment, cell motility, and cancer biology.

Bacteria Residing at Root Canals Can Induce Cell Proliferation and Alter the Mechanical Properties of Gingival and Cancer Cells

Understanding the importance of oral microbiota in human health and disease also leads to an expansion of the knowledge on functional, metabolic, and molecular alterations directly contributing to oral and systemic pathologies. To date, a compelling number of studies have documented the crucial role of some oral cavity-occurring microbes in the initiation and progression of cancers. Although this effect was noted primarily for Fusobacterium spp., the potential impact of other oral microbes is also worthy of investigation. In this study, we aimed to assess the effect of Enterococcus faecalis, Actinomyces odontolyticus, and Propionibacterium acnes on the proliferation capability and mechanical features of gingival cells and cell lines derived from lung, breast, and ovarian cancers. For this purpose, we incubated selected cell lines with heat-inactivated bacteria and supernatants collected from biofilms, cultured in both anaerobic and aerobic conditions, in the presence of surgically removed teeth and human saliva. The effect of oral bacteria on cell population growth is variable, with the highest growth-promoting abilities observed for E. faecalis in relation to human primary gingival fibroblasts (HGF) and lung cancer A549 cells, and P. acnes in relation to breast cancer MCF-7 and ovarian cancer SKOV-3 cells. Notably, this effect seems to depend on a delicate balance between the pro-stimulatory and toxic effects of bacterial-derived products. Regardless of the diverse effect of bacterial products on cellular proliferation capability, we observed significant alterations in stiffness of gingival and lung cancer cells stimulated with E. faecalis bacteria and corresponding biofilm supernatants, suggesting a novel molecular mechanism involved in the pathogenesis of diseases in oral cavities and tooth tissues. Accordingly, it is proposed that analysis of cancerogenic features of oral cavity bacteria should be multivariable and should include investigation of potential alterations in cell mechanical properties. These findings corroborate the important role of oral hygiene and root canal treatment to assure the healthy stage of oral microbiota.

Evaluation of intercellular communication between breast cancer cells and adipose-derived stem cells via passive diffusion in a two-layer microfluidic device

Breast cancer tumorigenesis and response to therapy is regulated by cancer cell interactions with the tumor microenvironment (TME). Breast cancer signaling to the surrounding TME results in a heterogeneous and diverse tumor microenvironment, which includes the production of cancer-associated fibroblasts, macrophages, adipocytes, and stem cells. The secretory profile of these cancer-associated cell types results in elevated chemokines and growth factors that promote cell survival and proliferation within the tumor. Current co-culture approaches mostly rely on transwell chambers to study intercellular signaling between adipose-derived stem cells (ASCs) and cancer cells; however, these methods are limited to endpoint measurements and lack dynamic control. In this study, a 4-channel, "flow-free" microfluidic device was developed to co-culture triple-negative MDA-MB-231 breast cancer cells and ASCs to study intercellular communication between two distinct cell types found in the TME. The device consists of two layers: a top PDMS layer with four imprinted channels coupled with a bottom agarose slab enclosed in a Plexiglas chamber. For dynamic co-culture, the device geometry contained two centered, flow-free channels, which were supplied with media from two outer flow channels via orthogonal diffusion through the agarose. Continuous fresh media was provided to the cell culture channel via passive diffusion without creating any shearing effect on the cells. The device geometry also allowed for the passive diffusion of cytokines and growth factors between the two cell types cultured in parallel channels to initiate cell-to-cell crosstalk. The device was used to show that MDA-MB-231 cells co-cultured with ASCs exhibited enhanced growth, a more aggressive morphology, and polarization toward the ASCs. The MDA-MB-231 cells were found to exhibit a greater degree of resistance to the drug paclitaxel when co-cultured with ASCs when compared to single culture studies. This microfluidic device is an ideal platform to study intercellular communication for many types of cells during co-culture experiments and allows for new investigations into stromal cell-mediated drug resistance in the tumor microenvironment.

Adhesion modulates cell morphology and migration within dense fibrous networks

One of the most fundamental abilities required for the sustainability of complex life forms is active cell migration, since it is essential in diverse processes from morphogenesis to leukocyte chemotaxis in immune response. The movement of a cell is the result of intricate mechanisms, that involve the coordination between mechanical forces, biochemical regulatory pathways and environmental cues. In particular, epithelial cancer cells have to employ mechanical strategies in order to migrate through the tissue's basement membrane and infiltrate the bloodstream during the invasion stage of metastasis. In this work we explore how mechanical interactions such as spatial restriction and adhesion affect migration of a self-propelled droplet in dense fibrous media. We have performed a systematic analysis using a phase-field model and we propose a novel approach to simulate cell migration with dissipative particle dynamics modelling. With this purpose we have measured in our simulation the cell's velocity and quantified its morphology as a function of the fibre density and of its adhesiveness to the matrix fibres. Furthermore, we have compared our results to a previousin vitromigration assay of fibrosarcoma cells in fibrous matrices. The results show good agreement between the two methodologies and experiments in the literature, which indicates that these minimalist descriptions are able to capture the main features of the system. Our results indicate that adhesiveness is critical for cell migration, by modulating cell morphology in crowded environments and by enhancing cell velocity. In addition, our analysis suggests that matrix metalloproteinases (MMPs) play an important role as adhesiveness modulators. We propose that new assays should be carried out to address the role of adhesion and the effect of different MMPs in cell migration under confined conditions.

The promise of single-cell mechanophenotyping for clinical applications

Cancer is the second leading cause of death worldwide. Despite the immense research focused in this area, one is still not able to predict disease trajectory. To overcome shortcomings in cancer disease study and monitoring, we describe an exciting research direction: cellular mechanophenotyping. Cancer cells must overcome many challenges involving external forces from neighboring cells, the extracellular matrix, and the vasculature to survive and thrive. Identifying and understanding their mechanical behavior in response to these forces would advance our understanding of cancer. Moreover, used alongside traditional methods of immunostaining and genetic analysis, mechanophenotyping could provide a comprehensive view of a heterogeneous tumor. In this perspective, we focus on new technologies that enable single-cell mechanophenotyping. Single-cell analysis is vitally important, as mechanical stimuli from the environment may obscure the inherent mechanical properties of a cell that can change over time. Moreover, bulk studies mask the heterogeneity in mechanical properties of single cells, especially those rare subpopulations that aggressively lead to cancer progression or therapeutic resistance. The technologies on which we focus include atomic force microscopy, suspended microchannel resonators, hydrodynamic and optical stretching, and mechano-node pore sensing. These technologies are poised to contribute to our understanding of disease progression as well as present clinical opportunities.

Low-intensity pulsed ultrasound affects growth, differentiation, migration, and epithelial-to-mesenchymal transition of colorectal cancer cells

Ultrasound (US) offers potentially important opportunities from a therapeutic point of view. Thus, the study of the biological effects of US on cancer cells is important to understand the consequences of these changes on the malignant phenotype. This study aimed to investigate the effects of low-intensity ultrasound (LIPUS) on the phenotype of colorectal cancer cell lines. Cell proliferation was evaluated by viability test and by evaluation of pERK expression, while cell motility using the scratch test. Cell differentiation was evaluated assessing alkaline phosphatase activity. Epithelial mesenchymal transition was assessed by analyzing the expression of Vimentin and E-Cadherin. Release and uptake of extracellular vesicles (EVs) were evaluated by flow cytometry. LIPUS effects on the organization of cytoskeleton were analyzed by confocal microscopy and by evaluation of Rho GTPase expression. No alterations in vitality and clonogenicity were observed when the intermediate (0.4 MPa) and the lowest (0.035 MPa) acoustic intensities were administered while the treatment with high intensity (1 MPa) induced a reduction of both cell viability and clonogenicity in both cell lines in a frequency-dependent manner. LIPUS promoted the differentiation of colon cancer cells, affected epithelial-to-mesenchymal transition, promoted the closure of a wound as well as increased the release of EVs compared with untreated cells. LIPUS-induced increase in cell motility was likely due to a Rho GTPase-dependent mechanism. Overall, the results obtained warrant further studies on the potential combined effect of LIPUS with differentiating agents and on their potential use in a clinical setting.

The Extracellular, Cellular, and Nuclear Stiffness, a Trinity in the Cancer Resistome-A Review

Alterations in mechano-physiological properties of a tissue instigate cancer burdens in parallel to common genetic and epigenetic alterations. The chronological and mechanistic interrelation between the various extra- and intracellular aspects remains largely elusive. Mechano-physiologically, integrins and other cell adhesion molecules present the main mediators for transferring and distributing forces between cells and the extracellular matrix (ECM). These cues are channeled via focal adhesion proteins, termed the focal adhesomes, to cytoskeleton and nucleus and vice versa thereby affecting the pathophysiology of multicellular cancer tissues. In combination with simultaneous activation of diverse downstream signaling pathways, the phenotypes of cancer cells are created and driven characterized by deregulated transcriptional and biochemical cues that elicit the hallmarks of cancer. It, however, remains unclear how elastostatic modifications, i.e., stiffness, in the extracellular, intracellular, and nuclear compartment contribute and control the resistance of cancer cells to therapy. In this review, we discuss how stiffness of unique tumor components dictates therapy response and what is known about the underlying molecular mechanisms.

Switchable and Obedient Interfacial Properties That Grant New Biomedical Applications

Toward imitating the natural smartness and responsivity of biological systems, surface interfacial properties are considered to be responsive and tunable if they show a reactive behavior to an environmental stimulus. This is still quite different from many contemporary biomaterials that lack responsiveness to interact with blood and different body tissues in a physiological manner. Meanwhile it is possible to even go one step further from responsiveness to dual-mode switchability and explore "switchable" or "reversible" responses of synthetic materials. We understand "switchable biomaterials" as materials undergoing a stepwise, structural transformation coupled with considerable changes of interfacial and other surface properties as a response to a stimulus. Therewith, a survey on stimuli-induced dynamic changes of charge, wettability, stiffness, topography, porosity, and thickness/swelling is presented here, as potentially powerful new technologies especially for future biomaterial development. Since living cells constantly sense their environment through a variety of surface receptors and other mechanisms, these obedient interfacial properties were particularly discussed regarding their advantageous multifunctionality for protein adsorption and cell adhesion signaling, which may alter in time and with environmental conditions.

Metabolic reprogramming dynamics in tumor spheroids: Insights from a multicellular, multiscale model

Mathematical modeling provides the predictive ability to understand the metabolic reprogramming and complex pathways that mediate cancer cells’ proliferation. We present a mathematical model using a multiscale, multicellular approach to simulate avascular tumor growth, applied to pancreatic cancer. The model spans three distinct spatial and temporal scales. At the extracellular level, reaction diffusion equations describe nutrient concentrations over a span of seconds. At the cellular level, a lattice-based energy driven stochastic approach describes cellular phenomena including adhesion, proliferation, viability and cell state transitions, occurring on the timescale of hours. At the sub-cellular level, we incorporate a detailed kinetic model of intracellular metabolite dynamics on the timescale of minutes, which enables the cells to uptake and excrete metabolites and use the metabolites to generate energy and building blocks for cell growth. This is a particularly novel aspect of the model. Certain defined criteria for the concentrations of intracellular metabolites lead to cancer cell growth, proliferation or death. Overall, we model the evolution of the tumor in both time and space. Starting with a cluster of tumor cells, the model produces an avascular tumor that quantitatively and qualitatively mimics experimental measurements of multicellular tumor spheroids. Through our model simulations, we can investigate the response of individual intracellular species under a metabolic perturbation and investigate how that response contributes to the response of the tumor as a whole. The predicted response of intracellular metabolites under various targeted strategies are difficult to resolve with experimental techniques. Thus, the model can give novel predictions as to the response of the tumor as a whole, identifies potential therapies to impede tumor growth, and predicts the effects of those therapeutic strategies. In particular, the model provides quantitative insight into the dynamic reprogramming of tumor cells at the intracellular level in response to specific metabolic perturbations. Overall, the model is a useful framework to study targeted metabolic strategies for inhibiting tumor growth.

Cancer cells expertly alter their metabolism in order to sustain growth, a hallmark of cancer. Quantitative details about this metabolic reprogramming are difficult to obtain without the use of predictive mathematical models. Here, we present a robust computational model of avascular tumor growth. The novel aspect of this work lies in the incorporation of a detailed model of the dynamics of metabolism within each individual cell, which directly influence growth of the multicellular tumor as a whole. We apply the model to simulate how the tumor grows in space and time and to predict how the tumor responds to targeted inhibition of specific intracellular metabolic reactions. Our results show, first-hand, the dynamic metabolic reprogramming that occurs in cancer cells. Specifically, the model provides insight into how the cells alter their metabolism to compensate for the loss of a nutrient by exploiting alternative pathways for continued tumor growth. Our work provides a quantitative tool for identifying the impact of cellular and sub-cellular features on the evolution of a tumor. This framework is useful for developing potential cancer therapies, complementing experimental studies.

Predicting cancer cell invasion by single-cell physical phenotyping

The physical properties of cells are promising biomarkers for cancer diagnosis and prognosis. Here we determine the physical phenotypes that best distinguish human cancer cell lines, and their relationship to cell invasion. We use the high throughput, single-cell microfluidic method, quantitative deformability cytometry (q-DC), to measure six physical phenotypes including elastic modulus, cell fluidity, transit time, entry time, cell size, and maximum strain at rates of 102 cells per second. By training a k-nearest neighbor machine learning algorithm, we demonstrate that multiparameter analysis of physical phenotypes enhances the accuracy of classifying cancer cell lines compared to single parameters alone. We also discover a set of four physical phenotypes that predict invasion; using these four parameters, we generate the physical phenotype model of invasion by training a multiple linear regression model with experimental data from a set of human ovarian cancer cells that overexpress a panel of tumor suppressor microRNAs. We validate the model by predicting invasion based on measured physical phenotypes of breast and ovarian human cancer cell lines that are subject to genetic or pharmacologic perturbations. Taken together, our results highlight how physical phenotypes of single cells provide a biomarker to predict the invasion of cancer cells.

Biophysical Phenotyping and Modulation of ALDH+ Inflammatory Breast Cancer Stem-Like Cells

Cancer stem-like cells (CSCs) have been shown to initiate tumorigenesis and cancer metastasis in many cancer types. Although identification of CSCs through specific marker expression helps define the CSC compartment, it does not directly provide information on how or why this cancer cell subpopulation is more metastatic or tumorigenic. In this study, the functional and biophysical characteristics of aggressive and lethal inflammatory breast cancer (IBC) CSCs at the single-cell level are comprehensively profiled using multiple microengineered tools. Distinct functional (cell migration, growth, adhesion, invasion and self-renewal) and biophysical (cell deformability, adhesion strength and contractility) properties of ALDH+ SUM149 IBC CSCs are found as compared to their ALDH- non-CSC counterpart, providing biophysical insights into why CSCs has an enhanced propensity to metastasize. It is further shown that the cellular biophysical phenotype can predict and determine IBC cells' tumorigenic ability. SUM149 and SUM159 IBC cells selected and modulated through biophysical attributes-adhesion and stiffness-show characteristics of CSCs in vitro and enhance tumorigenicity in in vivo murine models of primary tumor growth. Overall, the multiparametric cellular biophysical phenotyping and modulation of IBC CSCs yields a new understanding of IBC's metastatic properties and how they might develop and be targeted for therapeutic interventions.

SS, Paggi M, Bordas SP. Advances in Carbon Based Nanomaterials for Bio-Medical Applications

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The unique mechanical, electrical, thermal, chemical and optical properties of carbon based nanomaterials (CBNs) like: Fullerenes, Graphene, Carbon nanotubes, and their derivatives made them widely used materials for various applications including biomedicine. Few recent applications of the CBNs in biomedicine include: cancer therapy, targeted drug delivery, bio-sensing, cell and tissue imaging and regenerative medicine. However, functionalization renders the toxicity of CBNs and makes them soluble in several solvents including water, which is required for biomedical applications. Hence, this review represents the complete study of development in nanomaterials of carbon for biomedical uses. Especially, CBNs as the vehicles for delivering the drug in carbon nanomaterials is described in particular. The computational modeling approaches of various CBNs are also addressed. Furthermore, prospectus, issues and possible challenges of this rapidly developing field are highlighted.

Fluorescence-Based Nano-Oxygen Particles for Spatiometric Monitoring of Cell Physiological Conditions

Closed-loop artificial pancreas systems have recently been proposed as a solution for treating stage I diabetes by reproducing the function of the pancreas. However, there are many unresolved issues associated with their development, including monitoring and controlling oxygen, immune responses, and the optimization of glucose, all of which need to be monitored and controlled to produce an efficient and viable artificial organ that can become integrated in the patient and maintain homeostasis. This research focused on monitoring the oxygen concentration, specifically achieving this kinetically as the oxygen gradient in an artificial pancreas made of alginate spheres containing islet cells. Functional nanoparticles (NPs) for measuring the oxygen gradient in different hydrogel cellular environments using fluorescence-based (F) microscopy were developed and tested. By the ester bond, a linker Pluronic F127 was conjugated with a carboxylic acid-modified polystyrene NP (510 nm). A hydrophilic/hydrophobic interaction between the commercially available oxygen-sensitive fluorophore and F127 results in fluorescence-based nano-oxygen particles (FNOPs). The in-house synthesized FNOP was calibrated inside electrosprayed alginate-filled hydrogels and demonstrated a good broad dynamic range (2.73-22.23) mg/L as well as a resolution of -0.01 mg/L with an accuracy of ±4%. The calibrated FNOP was utilized for continuous measuring of the oxygen concentration gradient for cell lines RIN-m5F/HeLa for more than 5 days in alginate hydrogel spheres in vitro.

Nonlinear studies of tumor morphological stability using a two-fluid flow model

We consider the nonlinear dynamics of an avascular tumor at the tissue scale using a two-fluid flow Stokes model, where the viscosity of the tumor and host microenvironment may be different. The viscosities reflect the combined properties of cell and extracellular matrix mixtures. We perform a linear morphological stability analysis of the tumors, and we investigate the role of nonlinearity using boundary-integral simulations in two dimensions. The tumor is non-necrotic, although cell death may occur through apoptosis. We demonstrate that tumor evolution is regulated by a reduced set of nondimensional parameters that characterize apoptosis, cell-cell/cell-extracellular matrix adhesion, vascularization and the ratio of tumor and host viscosities. A novel reformulation of the equations enables the use of standard boundary integral techniques to solve the equations numerically. Nonlinear simulation results are consistent with linear predictions for nearly circular tumors. As perturbations develop and grow, the linear and nonlinear results deviate and linear theory tends to underpredict the growth of perturbations. Simulations reveal two basic types of tumor shapes, depending on the viscosities of the tumor and microenvironment. When the tumor is more viscous than its environment, the tumors tend to develop invasive fingers and a branched-like structure. As the relative ratio of the tumor and host viscosities decreases, the tumors tend to grow with a more compact shape and develop complex invaginations of healthy regions that may become encapsulated in the tumor interior. Although our model utilizes a simplified description of the tumor and host biomechanics, our results are consistent with experiments in a variety of tumor types that suggest that there is a positive correlation between tumor stiffness and tumor aggressiveness.

Biophysics of Tumor Microenvironment and Cancer Metastasis - A Mini Review

The role of tumor microenvironment in cancer progression is gaining significant attention. It is realized that cancer cells and the corresponding stroma co-evolve with time. Cancer cells recruit and transform the stromal cells, which in turn remodel the extra cellular matrix of the stroma. This complex interaction between the stroma and the cancer cells results in a dynamic feed-forward/feed-back loop with biochemical and biophysical cues that assist metastatic transition of the cancer cells. Although biochemistry has long been studied for the understanding of cancer progression, biophysical signaling is emerging as a critical paradigm determining cancer metastasis. In this mini review, we discuss the role of one of the biophysical cues, mostly the mechanical stiffness of tumor microenvironment, in cancer progression and its clinical implications.

Lab-on-a-Chip Platforms for Biophysical Studies of Cancer with Single-Cell Resolution

Recent cancer research has more strongly emphasized the biophysical aspects of tumor development, progression, and microenvironment. In addition to genetic modifications and mutations in cancer cells, it is now well accepted that the physical properties of cancer cells such as stiffness, electrical impedance, and refractive index vary with tumor progression and can identify a malignant phenotype. Moreover, cancer heterogeneity renders population-based characterization techniques inadequate, as individual cellular features are lost in the average. Hence, platforms for fast and accurate characterization of biophysical properties of cancer cells at the single-cell level are required. Here, we highlight some of the recent advances in the field of cancer biophysics and the development of lab-on-a-chip platforms for single-cell biophysical analyses of cancer cells.

Cancer Cell Mechanics: Adhesion G Protein-coupled Receptors in Action?

In mammals, numerous organ systems are equipped with adhesion G protein-coupled receptors (aGPCRs) to shape cellular processes including migration, adhesion, polarity and guidance. All of these cell biological aspects are closely associated with tumor cell biology. Consistently, aberrant expression or malfunction of aGPCRs has been associated with dysplasia and tumorigenesis. Mounting evidence indicates that cancer cells comprise viscoelastic properties that are different from that of their non-tumorigenic counterparts, a feature that is believed to contribute to the increased motility and invasiveness of metastatic cancer cells. This is particularly interesting in light of the recent identification of the mechanosensitive facility of aGPCRs. aGPCRs are signified by large extracellular domains (ECDs) with adhesive properties, which promote the engagement with insoluble ligands. This configuration may enable reliable force transmission to the ECDs and may constitute a molecular switch, vital for mechano-dependent aGPCR signaling. The investigation of aGPCR function in mechanosensation is still in its infancy and has been largely restricted to physiological contexts. It remains to be elucidated if and how aGPCR function affects the mechanoregulation of tumor cells, how this may shape the mechanical signature and ultimately determines the pathological features of a cancer cell. This article aims to view known aGPCR functions from a biomechanical perspective and to delineate how this might impinge on the mechanobiology of cancer cells.

Phenotypic Plasticity, Bet-Hedging, and Androgen Independence in Prostate Cancer: Role of Non-Genetic Heterogeneity

It is well known that genetic mutations can drive drug resistance and lead to tumor relapse. Here, we focus on alternate mechanisms-those without mutations, such as phenotypic plasticity and stochastic cell-to-cell variability that can also evade drug attacks by giving rise to drug-tolerant persisters. The phenomenon of persistence has been well-studied in bacteria and has also recently garnered attention in cancer. We draw a parallel between bacterial persistence and resistance against androgen deprivation therapy in prostate cancer (PCa), the primary standard care for metastatic disease. We illustrate how phenotypic plasticity and consequent mutation-independent or non-genetic heterogeneity possibly driven by protein conformational dynamics can stochastically give rise to androgen independence in PCa, and suggest that dynamic phenotypic plasticity should be considered in devising therapeutic dosing strategies designed to treat and manage PCa.

Feeling Stress: The Mechanics of Cancer Progression and Aggression

The tumor microenvironment is a dynamic landscape in which the physical and mechanical properties evolve dramatically throughout cancer progression. These changes are driven by enhanced tumor cell contractility and expansion of the growing tumor mass, as well as through alterations to the material properties of the surrounding extracellular matrix (ECM). Consequently, tumor cells are exposed to a number of different mechanical inputs including cell–cell and cell-ECM tension, compression stress, interstitial fluid pressure and shear stress. Oncogenes engage signaling pathways that are activated in response to mechanical stress, thereby reworking the cell's intrinsic response to exogenous mechanical stimuli, enhancing intracellular tension via elevated actomyosin contraction, and influencing ECM stiffness and tissue morphology. In addition to altering their intracellular tension and remodeling the microenvironment, cells actively respond to these mechanical perturbations phenotypically through modification of gene expression. Herein, we present a description of the physical changes that promote tumor progression and aggression, discuss their interrelationship and highlight emerging therapeutic strategies to alleviate the mechanical stresses driving cancer to malignancy.

In Vitro Modeling of Mechanics in Cancer Metastasis

In addition to a multitude of genetic and biochemical alterations, abnormal morphological, structural, and mechanical changes in cells and their extracellular environment are key features of tumor invasion and metastasis. Furthermore, it is now evident that mechanical cues alongside biochemical signals contribute to critical steps of cancer initiation, progression, and spread. Despite its importance, it is very challenging to study mechanics of different steps of metastasis in the clinic or even in animal models. While considerable progress has been made in developing advanced in vitro models for studying genetic and biological aspects of cancer, less attention has been paid to models that can capture both biological and mechanical factors realistically. This is mainly due to lack of appropriate models and measurement tools. After introducing the central role of mechanics in cancer metastasis, we provide an outlook on the emergence of novel in vitro assays and their combination with advanced measurement technologies to probe and recapitulate mechanics in conditions more relevant to the metastatic disease.

Activation of the HGF/c-Met axis in the tumor microenvironment: A multispecies model

The tumor microenvironment is an integral component in promoting tumor development. Cancer-associated fibroblasts (CAFs), which reside in the tumor stroma, produce Hepatocyte Growth Factor (HGF), an important trigger for invasive and metastatic tumor behavior. HGF contributes to a pro-tumorigenic environment by activating its cognate receptor, c-Met, on tumor cells. Tumor cells, in turn, secrete growth factors that upregulate HGF production in CAFs, thereby establishing a dynamic tumor-host signaling program. Using a spatiotemporal multispecies model of tumor growth, we investigate how the development and spread of a tumor is impacted by the initiation of a dynamic interaction between tumor-derived growth factors and CAF-derived HGF. We show that establishment of such an interaction results in increased tumor growth and morphological instability, the latter due in part to increased cell species heterogeneity at the tumor-host boundary. Invasive behavior is further increased if the tumor lowers responsiveness to paracrine pro-differentiation signals, which is a hallmark of neoplastic development. By modeling anti-HGF and anti-c-Met therapy, we show how disruption of the HGF/c-Met axis can reduce tumor invasiveness and growth, thereby providing theoretical evidence that targeting tumor-microenvironment interactions is a promising avenue for therapeutic development.

The role of the microenvironment in the biophysics of cancer

During the last decades, cell mechanics has been recognized as a quantitative measure to discriminate between many physiological and pathological states of single cells. In the field of biophysics of cancer, a large body of research has been focused on the comparison between normal and cancer mechanics and slowly the hypothesis that cancer cells are softer than their normal counterparts has been accepted, even though in situ tumor tissue is usually stiffer than the surrounding normal tissue. This corroborates the idea that the extra-cellular matrix (ECM) has a critical role in regulating tumor cell properties and behavior. Rearrangements in ECM can lead to changes in cancer cell mechanics and in specific conditions the general assumption about cancer cell softening could be confuted. Here, we highlight the contribution of ECM in cancer cell mechanics and argue that the statement that cancer cells are softer than normal cells should be firmly related to the properties of cell environment and the specific stage of cancer cell progression. In particular, we will discuss that when employing cell mechanics in cancer diagnosis and discrimination, the chemical, the topographical and - last but not least - the mechanical properties of the microenvironment are very important.

Imaging the pharmacology of nanomaterials by intravital microscopy: Toward understanding their biological behavior

Therapeutic nanoparticles (NPs) can deliver cytotoxic chemotherapeutics and other drugs more safely and efficiently to patients; furthermore, selective delivery to target tissues can theoretically be accomplished actively through coating NPs with molecular ligands, and passively through exploiting physiological "enhanced permeability and retention" features. However, clinical trial results have been mixed in showing improved efficacy with drug nanoencapsulation, largely due to heterogeneous NP accumulation at target sites across patients. Thus, a clear need exists to better understand why many NP strategies fail in vivo and not result in significantly improved tumor uptake or therapeutic response. Multicolor in vivo confocal fluorescence imaging (intravital microscopy; IVM) enables integrated pharmacokinetic and pharmacodynamic (PK/PD) measurement at the single-cell level, and has helped answer key questions regarding the biological mechanisms of in vivo NP behavior. This review summarizes progress to date and also describes useful technical strategies for successful IVM experimentation.

Three-dimensional Image-based Mechanical Modeling for Predicting the Response of Breast Cancer to Neoadjuvant Therapy

The use of quantitative medical imaging data to initialize and constrain mechanistic mathematical models of tumor growth has demonstrated a compelling strategy for predicting therapeutic response. More specifically, we have demonstrated a data-driven framework for prediction of residual tumor burden following neoadjuvant therapy in breast cancer that uses a biophysical mathematical model combining reaction-diffusion growth/therapy dynamics and biomechanical effects driven by early time point imaging data. Whereas early work had been based on a limited dimensionality reduction (two-dimensional planar modeling analysis) to simplify the numerical implementation, in this work, we extend our framework to a fully volumetric, three-dimensional biophysical mathematical modeling approach in which parameter estimates are generated by an inverse problem based on the adjoint state method for numerical efficiency. In an in silico performance study, we show accurate parameter estimation with error less than 3% as compared to ground truth. We apply the approach to patient data from a patient with pathological complete response and a patient with residual tumor burden and demonstrate technical feasibility and predictive potential with direct comparisons between imaging data observation and model predictions of tumor cellularity and volume. Comparisons to our previous two-dimensional modeling framework reflect enhanced model prediction of residual tumor burden through the inclusion of additional imaging slices of patient-specific data.

Nano-mechanical signature of brain tumours

Glioblastoma (GBM) and meningothelial meningioma (MM) are the most frequent malignant and benign brain lesions, respectively. Mechanical cues play a major role in the progression of both malignancies that is modulated by the occurrence of aberrant physical interactions between neoplastic cells and the extracellular matrix (ECM). Here we investigate the nano-mechanical properties of human GBM and MM tissues by atomic force microscopy. Our measures unveil the mechanical fingerprint of the main hallmark features of both lesions, such as necrosis in GBM and dural infiltration in MM. These findings have the potential to positively impact on the development of novel AFM-based diagnostic methods to assess the tumour grade. Most importantly, they provide a quantitative description of the tumour-induced mechanical modifications in the brain ECM, thus being of potential help in the search for novel ECM targets for brain tumours and especially for GBM that, despite years of intense research, has still very limited therapeutic options.