Cell motility and drug gradients in the emergence of resistance to chemotherapy

Deciphering population-level response under spatial drug heterogeneity on microhabitat structures

Bacteria and cancer cells live in a spatially heterogeneous environment, where migration shapes the microhabitat structures critical for colonization and metastasis. The interplay between growth, migration, and microhabitat structure complicates the prediction of population responses to drugs, such as clearance or sustained growth, posing a longstanding challenge. Here, we disentangle growth-migration dynamics and identify that population decline is determined by two decoupled terms: a spatial growth variation term and a microhabitat structure term. Notably, the microhabitat structure term can be interpreted as a dynamic-related centrality measure. For fixed spatial drug arrangements, we show that interpreting these centralities reveals how different network structures, even with identical edge densities, microhabitat numbers, and spatial heterogeneity, can lead to distinct population-level responses. Increasing edge density shifts the population response from growth to clearance, supporting an inversed centrality-connectivity relationship, and mirroring the effects of higher migration rates. Furthermore, we derive a sufficient condition for robust population decline across various spatial growth rate arrangements, regardless of spatial-temporal fluctuations induced by drugs. Additionally, we demonstrate that varying the maximum growth-to-death ratio, determined by drug-bacteria interactions, can lead to distinct population decline profiles and a minimal decline phase emerges. These findings address key challenges in predicting population-level responses and provide insights into divergent clinical outcomes under identical drug dosages. This work may offer a new method of interpreting treatment dynamics and potential approaches for optimizing spatially explicit drug dosing strategies.

The development of drug resistance in metastatic tumours under chemotherapy: An evolutionary perspective

We present a mathematical model of the evolutionary dynamics of a metastatic tumour under chemotherapy, comprising non-local partial differential equations for the phenotype-structured cell populations in the primary tumour and its metastasis. These equations are coupled with a physiologically-based pharmacokinetic model of drug administration and distribution, implementing a realistic delivery schedule. The model is carefully calibrated from the literature, focusing on BRAF-mutated melanoma treated with Dabrafenib as a case study. By means of long-time asymptotic and global sensitivity analyses, as well as numerical simulations, we explore the impact of cell migration from the primary to the metastatic site, physiological aspects of the tumour tissues and drug dose on the development of chemoresistance and treatment efficacy. Our findings provide a possible explanation for empirical evidence indicating that chemotherapy may foster metastatic spread and that metastases may be less impacted by the chemotherapeutic agent.

Linking spatial drug heterogeneity to microbial growth dynamics in theory and experiment

Diffusion and migration play pivotal roles in microbial communities - shaping, for example, colonization in new environments and the maintenance of spatial structures of biodiversity. While previous research has extensively studied free diffusion, such as range expansion, there remains a gap in understanding the effects of biologically or physically deleterious confined environments. In this study, we examine the interplay between migration and spatial drug heterogeneity within an experimental meta-community of E. faecalis, a Gram-positive opportunistic pathogen. When the community is confined to spatially-extended habitats ('islands') bordered by deleterious conditions, we find that the population level response depends on the trade-off between the growth rate within the island and the rate of transfer into regions with harsher conditions, a phenomenon we explore by modulating antibiotic concentration within the island. In heterogeneous islands, composed of spatially patterned patches that support varying levels of growth, the population's fate depends critically on the specific spatial arrangement of these patches - the same spatially averaged growth rate leads to diverging responses. These results are qualitatively captured by simple simulations, and analytical expressions which we derive using first-order perturbation approximations to reaction-diffusion models with explicit spatial dependence. Among all possible spatial arrangements, our theoretical and experimental findings reveal that the arrangement with the highest growth rates at the center most effectively mitigates population decline, while the arrangement with the lowest growth rates at the center is the least effective. Extending this approach to more complex experimental communities with varied spatial structures, such as a ring-structured community, further validates the impact of spatial drug arrangement. Our findings suggest new approaches to interpreting diverging clinical outcomes when applying identical drug doses and inform the possible optimization of spatially-explicit dosing strategies.

Bacterial motility can govern the dynamics of antibiotic resistance evolution

Spatial heterogeneity in antibiotic concentrations is thought to accelerate the evolution of antibiotic resistance, but current theory and experiments have overlooked the effect of cell motility on bacterial adaptation. Here, we study bacterial evolution in antibiotic landscapes with a quantitative model where bacteria evolve under the stochastic processes of proliferation, death, mutation and migration. Numerical and analytical results show that cell motility can both accelerate and decelerate bacterial adaptation by affecting the degree of genotypic mixing and ecological competition. Moreover, we find that for sufficiently high rates, cell motility can limit bacterial survival, and we derive conditions for all these regimes. Similar patterns are observed in more complex scenarios, namely where bacteria can bias their motion in chemical gradients (chemotaxis) or switch between motility phenotypes either stochastically or in a density-dependent manner. Overall, our work reveals limits to bacterial adaptation in antibiotic landscapes that are set by cell motility.

Diverse mutant selection windows shape spatial heterogeneity in evolving populations

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N*2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more accurately reflect the selection fo drug resistant genotypes. Furthermore, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

Counterintuitive properties of evolutionary measures: A stochastic process study in cyclic population structures with periodic environments

Local environmental interactions are a major factor in determining the success of a new mutant in structured populations. Spatial variations in the concentration of genotype-specific resources change the fitness of competing strategies locally and thus can drastically change the outcome of evolutionary processes in unintuitive ways. The question is how such local environmental variations in network population structures change the condition for selection and fixation probability of an advantageous (or deleterious) mutant. We consider linear graph structures and focus on the case where resources have a spatial periodic pattern. This is the simplest model with two parameters, length scale and fitness scales, representing heterogeneity. We calculate fixation probability and fixation times for a constant population birth-death process as fitness heterogeneity and period vary. Fixation probability is affected by not only the level of fitness heterogeneity but also spatial scale of resources variations set by period of distribution T. We identify conditions for which a previously a deleterious mutant (in a uniform environment) becomes beneficial as fitness heterogeneity is increased. We observe cases where the fixation probability of both mutant and resident types are more than their neutral value, 1/N, simultaneously. This coincides with exponential increase in time to fixation which points to potential coexistence of resident and mutant types. Finally, we discuss the effect of the 'fitness shift' where the fitness function of two types has a phase difference. We observe significant increases (or decreases) in the fixation probability of the mutant as a result of such phase shift.

Discovery of Proteins Responsible for Resistance to Three Chemotherapy Drugs in Breast Cancer Cells Using Proteomics and Bioinformatics Analysis

Chemoresistance is a daunting obstacle to the effective treatment of breast cancer patients receiving chemotherapy. Although the mechanism of chemotherapy drug resistance has been explored broadly, the precise mechanism at the proteome level remains unclear. Especially, comparative studies between widely used anticancer drugs in breast cancer are very limited. In this study, we employed proteomics and bioinformatics approaches on chemoresistant breast cancer cell lines to understand the underlying resistance mechanisms that resulted from doxorubicin (DR), paclitaxel (PR), and tamoxifen (TAR). In total, 10,385 proteins were identified and quantified from three TMT 6-plex and one TMT 10-plex experiments. Bioinformatics analysis showed that Notch signaling, immune response, and protein re-localization processes were uniquely associated with DR, PR, and TAR resistance, respectively. In addition, proteomic signatures related to drug resistance were identified as potential targets of many FDA-approved drugs. Furthermore, we identified potential prognostic proteins with significant effects on overall survival. Representatively, PLXNB2 expression was associated with a highly significant increase in risk, and downregulation of ACOX3 was correlated with a worse overall survival rate. Consequently, our study provides new insights into the proteomic aspects of the distinct mechanisms underlying chemoresistance in breast cancer.

Mathematical modeling of therapeutic neural stem cell migration in mouse brain with and without brain tumors

Neural stem cells (NSCs) offer a potential solution to treating brain tumors. This is because NSCs can circumvent the blood-brain barrier and migrate to areas of damage in the central nervous system, including tumors, stroke, and wound injuries. However, for successful clinical application of NSC treatment, a sufficient number of viable cells must reach the diseased or damaged area(s) in the brain, and evidence suggests that it may be affected by the paths the NSCs take through the brain, as well as the locations of tumors. To study the NSC migration in brain, we develop a mathematical model of therapeutic NSC migration towards brain tumor, that provides a low cost platform to investigate NSC treatment efficacy. Our model is an extension of the model developed in Rockne et al. (PLoS ONE 13, e0199967, 2018) that considers NSC migration in non-tumor bearing naive mouse brain. Here we modify the model in Rockne et al. in three ways: (i) we consider three-dimensional mouse brain geometry, (ii) we add chemotaxis to model the tumor-tropic nature of NSCs into tumor sites, and (iii) we model stochasticity of migration speed and chemosensitivity. The proposed model is used to study migration patterns of NSCs to sites of tumors for different injection strategies, in particular, intranasal and intracerebral delivery. We observe that intracerebral injection results in more NSCs arriving at the tumor site(s), but the relative fraction of NSCs depends on the location of injection relative to the target site(s). On the other hand, intranasal injection results in fewer NSCs at the tumor site, but yields a more even distribution of NSCs within and around the target tumor site(s).

Design and implementation of a microfluidic device capable of temporal growth factor delivery reveal filtering capabilities of the EGFR/ERK pathway

Utilizing microfluidics to mimic the dynamic temporal changes of growth factor and cytokine concentrations in vivo has greatly increased our understanding of how signal transduction pathways are structured to encode extracellular stimuli. To date, these devices have focused on delivering pulses of varying frequency, and there are limited cell culture models for delivering slowly increasing concentrations of stimuli that cells may experience in vivo. To examine this setting, we developed and validated a microfluidic device that can deliver increasing concentrations of growth factor over periods ranging from 6 to 24 h. Using this device and a fluorescent biosensor of extracellular-regulated kinase (ERK) activity, we delivered a slowly increasing concentration of epidermal growth factor (EGF) to human mammary epithelial cells and surprisingly observed minimal ERK activation, even at concentrations that stimulate robust activity in bolus delivery. The cells remained unresponsive to subsequent challenges with EGF, and immunocytochemistry suggested that the loss of an epidermal growth factor receptor was responsible. Cells were then challenged with faster rates of change of EGF, revealing an increased ERK activity as a function of rate of change. Specifically, both the fraction of cells that responded and the length of ERK activation time increased with the rate of change. This microfluidic device fills a gap in the current repertoire of in vitro microfluidic devices and demonstrates that slower, more physiological changes in growth factor presentation can reveal new regulatory mechanisms for how signal transduction pathways encode changes in the extracellular growth factor milieu.

The role of chemotaxis and efflux pumps on nitrate reduction in the toxic regions of a ciprofloxacin concentration gradient

Spatial concentration gradients of antibiotics are prevalent in the natural environment. Yet, the microbial response in these heterogeneous systems remains poorly understood. We used a microfluidic reactor to create an artificial microscopic ecosystem that generates diffusive gradients of solutes across interconnected microenvironments. With this reactor, we showed that chemotaxis toward a soluble electron acceptor (nitrate) allowed Shewanella oneidensis MR-1 to inhabit and sustain metabolic activity in highly toxic regions of the antibiotic ciprofloxacin (>80× minimum inhibitory concentration, MIC). Acquired antibiotic resistance was not observed for cells extracted from the reactor, so we explored the role of transient adaptive resistance by probing multidrug resistance (MDR) efflux pumps, ancient elements that are important for bacterial physiology and virulence. Accordingly, we constructed an efflux pump deficient mutant (∆mexF) and used resistance-nodulation-division (RND) efflux pump inhibitors (EPIs). While batch results showed the importance of RND efflux pumps for microbial survival, microfluidic studies indicated that these pumps were not necessary for survival in antibiotic gradients. Our work contributes to an emerging body of knowledge deciphering the effects of antibiotic spatial heterogeneity on microorganisms and highlights differences of microbial response in these systems versus well-mixed batch conditions.

Breast tumor-on-chip models: From disease modeling to personalized drug screening

Breast cancer is one of the leading causes of mortality worldwide being the most common cancer among women. Despite the significant progress obtained during the past years in the understanding of breast cancer pathophysiology, women continue to die from it. Novel tools and technologies are needed to develop better diagnostic and therapeutic approaches, and to better understand the molecular and cellular players involved in the progression of this disease. Typical methods employed by the pharmaceutical industry and laboratories to investigate breast cancer etiology and evaluate the efficiency of new therapeutic compounds are still based on traditional tissue culture flasks and animal models, which have certain limitations. Recently, tumor-on-chip technology emerged as a new generation of in vitro disease model to investigate the physiopathology of tumors and predict the efficiency of drugs in a native-like microenvironment. These microfluidic systems reproduce the functional units and composition of human organs and tissues, and importantly, the rheological properties of the native scenario, enabling precise control over fluid flow or local gradients. Herein, we review the most recent works related to breast tumor-on-chip for disease modeling and drug screening applications. Finally, we critically discuss the future applications of this emerging technology in breast cancer therapeutics and drug development.

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.

3D Scaffolds to Model the Hematopoietic Stem Cell Niche: Applications and Perspectives

Hematopoietic stem cells (HSC) are responsible for the production of blood and immune cells during life. HSC fate decisions are dependent on signals from specialized microenvironments in the bone marrow, termed niches. The HSC niche is a tridimensional environment that comprises cellular, chemical, and physical elements. Introductorily, we will revise the current knowledge of some relevant elements of the niche. Despite the importance of the niche in HSC function, most experimental approaches to study human HSCs use bidimensional models. Probably, this contributes to the failure in translating many in vitro findings into a clinical setting. Recreating the complexity of the bone marrow microenvironment in vitro would provide a powerful tool to achieve in vitro production of HSCs for transplantation, develop more effective therapies for hematologic malignancies and provide deeper insight into the HSC niche. We previously demonstrated that an optimized decellularization method can preserve with striking detail the ECM architecture of the bone marrow niche and support HSC culture. We will discuss the potential of this decellularized scaffold as HSC niche model. Besides decellularized scaffolds, several other methods have been reported to mimic some characteristics of the HSC niche. In this review, we will examine these models and their applications, advantages, and limitations.

Advanced Multi-Dimensional Cellular Models as Emerging Reality to Reproduce In Vitro the Human Body Complexity

A hot topic in biomedical science is the implementation of more predictive in vitro models of human tissues to significantly improve the knowledge of physiological or pathological process, drugs discovery and screening. Bidimensional (2D) culture systems still represent good high-throughput options for basic research. Unfortunately, these systems are not able to recapitulate the in vivo three-dimensional (3D) environment of native tissues, resulting in a poor in vitro–in vivo translation. In addition, intra-species differences limited the use of animal data for predicting human responses, increasing in vivo preclinical failures and ethical concerns. Dealing with these challenges, in vitro 3D technological approaches were recently bioengineered as promising platforms able to closely capture the complexity of in vivo normal/pathological tissues. Potentially, such systems could resemble tissue-specific extracellular matrix (ECM), cell–cell and cell–ECM interactions and specific cell biological responses to mechanical and physical/chemical properties of the matrix. In this context, this review presents the state of the art of the most advanced progresses of the last years. A special attention to the emerging technologies for the development of human 3D disease-relevant and physiological models, varying from cell self-assembly (i.e., multicellular spheroids and organoids) to the use of biomaterials and microfluidic devices has been given.

The Moran process on 2-chromatic graphs

Resources are rarely distributed uniformly within a population. Heterogeneity in the concentration of a drug, the quality of breeding sites, or wealth can all affect evolutionary dynamics. In this study, we represent a collection of properties affecting the fitness at a given location using a color. A green node is rich in resources while a red node is poorer. More colors can represent a broader spectrum of resource qualities. For a population evolving according to the birth-death Moran model, the first question we address is which structures, identified by graph connectivity and graph coloring, are evolutionarily equivalent. We prove that all properly two-colored, undirected, regular graphs are evolutionarily equivalent (where “properly colored” means that no two neighbors have the same color). We then compare the effects of background heterogeneity on properly two-colored graphs to those with alternative schemes in which the colors are permuted. Finally, we discuss dynamic coloring as a model for spatiotemporal resource fluctuations, and we illustrate that random dynamic colorings often diminish the effects of background heterogeneity relative to a proper two-coloring.

Heterogeneity in environmental conditions can have profound effects on long-term evolutionary outcomes in structured populations. We consider a population evolving on a colored graph, wherein the color of a node represents the resources at that location. Using a combination of analytical and numerical methods, we quantify the effects of background heterogeneity on a population’s dynamics. In addition to considering the notion of an “optimal” coloring with respect to mutant invasion, we also study the effects of dynamic spatial redistribution of resources as the population evolves. Although the effects of static background heterogeneity can be quite striking, these effects are often attenuated by the movement (or “flow”) of the underlying resources.

Superparamagnetic Iron Oxide Nanoparticles Carrying Chemotherapeutics Improve Drug Efficacy in Monolayer and Spheroid Cell Culture by Enabling Active Accumulation

Cytotoxic and cytostatic chemotherapeutics act by attacking rapidly dividing tumor cells, predominantly affecting malignant tissue and to a certain degree preserving healthy cells. Nonetheless, severe side effects are caused as quickly proliferating healthy cells such as hematopoietic precursors and mucous membranes are impaired as well. This limits the administered dose and eventually allows tumor cells to escape treatment. In order to increase intratumoral drug concentration and simultaneously reduce systemic side effects, nanoparticles have come into focus as drug carriers. The functionalization of superparamagnetic iron oxide nanoparticles (SPIONs) with chemotherapeutics such as mitoxantrone (MTO) enables targeted drug transport by using magnetic forces. Here, we investigate SPIONs consisting of individual iron oxide cores of 10 nm in diameter and a total hydrodynamic diameter of 53 ± 0.8 nm as a transporting system for MTO. Comparing the killing efficacy in monolayer cell culture and multicellular tumor spheroids of HT-29 cells, we show that spheroids tolerate considerably higher doses of nanoparticle-loaded MTO. Therefore, dose predictions from conventional monolayer cell cultures are often misleading for in vivo applications. This was true for both soluble and nanoparticle-bound MTO. Using flow chambers mimicking in vivo blood flow, we furthermore demonstrate that SPIONs can magnetically accumulate MTO. We conclude that SPIONs can function as an effective delivery platform to increase local drug concentrations, thereby potentially overcoming chemotherapy resistance of cells.

An in vitro tumor swamp model of heterogeneous cellular and chemotherapeutic landscapes

The heterogenous, highly metabolic stressed, poorly irrigated, solid tumor microenvironment - the tumor swamp - is widely recognized to play an important role in cancer progression as well as the development of therapeutic resistance. It is thus important to create realistic in vitro models within the therapeutic pipeline that can recapitulate the fundamental stress features of the tumor swamp. Here we describe a microfluidic system which generates a chemical gradient within connected microenvironments achieved through a static diffusion mechanism rather than active pumping. We show that the gradient can be stably maintained for over a week. Due to the accessibility and simplicity of the experimental platform, the system allows for not only well-controlled continuous studies of the interactions among various cell types at single-cell resolution, but also parallel experimentation for time-resolved downstream cellular assays on the time scale of weeks. This approach enables simple, compact implementation and is compatible with existing 6-well imaging technology for simultaneous experiments. As a proof-of-concept, we report the co-culture of a human bone marrow stromal cell line and a bone-metastatic prostate cancer cell line using the presented device, revealing on the same chip a transition in cancer cell survival as a function of drug concentration on the population level while exhibiting an enrichment of poly-aneuploid cancer cells (PACCs) as an evolutionary consequence of high stress. The device allows for the quantitative study of cancer cell dynamics on a stress landscape by real-time monitoring of various cell types with considerable experimental throughput.

Characterizing the Motility of Chemotherapeutics-Treated Acute Lymphoblastic Leukemia Cells by Time-Lapse Imaging

Drug resistance is an obstacle in the therapy of acute lymphoblastic leukemia (ALL). Whether the physical properties such as the motility of the cells contribute to the survival of ALL cells after drug treatment has recently been of increasing interest, as they could potentially allow the metastasis of solid tumor cells and the migration of leukemia cells. We hypothesized that chemotherapeutic treatment may alter these physical cellular properties. To investigate the motility of chemotherapeutics-treated B-cell ALL (B-ALL) cells, patient-derived B-ALL cells were treated with chemotherapy for 7 days and left for 12 h without chemotherapeutic treatment. Two parameters of motility were studied, velocity and migration distance, using a time-lapse imaging system. The study revealed that compared to non-chemotherapeutically treated B-ALL cells, B-ALL cells that survived chemotherapy treatment after 7 days showed reduced motility. We had previously shown that Tysabri and P5G10, antibodies against the adhesion molecules integrins α4 and α6, respectively, may overcome drug resistance mediated through leukemia cell adhesion to bone marrow stromal cells. Therefore, we tested the effect of integrin α4 or α6 blockade on the motility of chemotherapeutics-treated ALL cells. Only integrin α4 blockade decreased the motility and velocity of two chemotherapeutics-treated ALL cell lines. Interestingly, integrin α6 blockade did not affect the velocity of chemoresistant ALL cells. This study explores the physical properties of the movements of chemoresistant B-ALL cells and highlights a potential link to integrins. Further studies to investigate the underlying mechanism are warranted.

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.

Drug-Induced Resistance in Micrometastases: Analysis of Spatio-Temporal Cell Lineages

Resistance to anti-cancer drugs is a major cause of treatment failure. While several intracellular mechanisms of resistance have been postulated, the role of extrinsic factors in the development of resistance in individual tumor cells is still not fully understood. Here we used a hybrid agent-based model to investigate how sensitive tumor cells develop drug resistance in the heterogeneous tumor microenvironment. We characterized the spatio-temporal evolution of lineages of the resistant cells and examined how resistance at the single-cell level contributes to the overall tumor resistance. We also developed new methods to track tumor cell adaptation, to trace cell viability trajectories and to examine the three-dimensional spatio-temporal lineage trees. Our findings indicate that drug-induced resistance can result from cells adaptation to the changes in drug distribution. Two modes of cell adaptation were identified that coincide with microenvironmental niches—areas sheltered by cell micro-communities (protectorates) or regions with limited drug penetration (refuga or sanctuaries). We also recognized that certain cells gave rise to lineages of resistant cells (precursors of resistance) and pinpointed three temporal periods and spatial locations at which such cells emerged. This supports the hypothesis that tumor micrometastases do not need to harbor cell populations with pre-existing resistance, but that individual tumor cells can adapt and develop resistance induced by the drug during the treatment.

Preparation and anti-cancer activity of transferrin/folic acid double-targeted graphene oxide drug delivery system

In this study, a transferrin/folic acid double-targeting graphene oxide drug delivery system loaded with doxorubicin was designed. Graphene oxide was prepared by ultrasound improved Hummers method and was modified with Pluronic F68, folic acid, and transferrin to decrease its toxicity and to allow dual-targeting. The results show that the double target drug delivery system (TFGP*DOX) has good and controllable drug delivery performance with no toxicity. Moreover, TFGP*DOX has a better inhibitory effect on SMMC-7721 cells than does a single target drug delivery system (FGP*DOX). The results of drug release analysis and cell inhibition studies showed that TFGP*DOX has a good sustained release function that can reduce the drug release rate in blood circulation over time and improve the local drug concentration in or near a targeted tumor. Therefore, the drug loading system (TFGP*DOX) has potential application value in the treatment of hepatocellular carcinoma.

High-Throughput Cell Motility Studies on Surface-Bound Protein Nanoparticles with Diverse Structural and Compositional Characteristics

Eighty areas with different structural and compositional characteristics made of bacterial inclusion bodies formed by the fibroblast growth factor (FGF-IBs) were simultaneously patterned on a glass surface with an evaporation-assisted method that relies on the coffee-drop effect. The resulting surface patterned with these protein nanoparticles enabled to perform a high-throughput study of the motility of NIH-3T3 fibroblasts under different conditions including the gradient steepness, particle concentrations, and area widths of patterned FGF-IBs, using for the data analysis a methodology that includes "heat maps". From this analysis, we observed that gradients of concentrations of surface-bound FGF-IBs stimulate the total cell movement but do not affect the total net distances traveled by cells. Moreover, cells tend to move toward an optimal intermediate FGF-IB concentration (i.e., cells seeded on areas with high IB concentrations moved toward areas with lower concentrations and vice versa, reaching the optimal concentration). Additionally, a higher motility was obtained when cells were deposited on narrow and highly concentrated areas with IBs. FGF-IBs can be therefore used to enhance and guide cell migration, confirming that the decoration of surfaces with such IB-like protein nanoparticles is a promising platform for regenerative medicine and tissue engineering.

Systems biology approaches to measure and model phenotypic heterogeneity in cancer

The recent wide-spread adoption of single cell profiling technologies has revealed that individual cancers are not homogenous collections of deregulated cells, but instead are comprised of multiple genetically and phenotypically distinct cell subpopulations that exhibit a wide range of responses to extracellular signals and therapeutic insult. Such observations point to the urgent need to understand cancer as a complex, adaptive system. Cancer systems biology studies seek to develop the experimental and theoretical methods required to understand how biological components work together to determine how cancer cells function. Ultimately, such approaches will lead to improvements in how cancer is managed and treated. In this review, we discuss recent advances in cancer systems biology approaches to quantify, model, and elucidate mechanisms of heterogeneity.

Bi-layer blood vessel mimicking microfluidic platform for antitumor drug screening based on co-culturing 3D tumor spheroids and endothelial layers

Two-dimensional (2D) cell culture is not ideal for traditional drug screening, because 2D culture does not accurately mimic the physiological microenvironment of tumor cells. Thus, a drug-screening system which more closely mimics the microenvironment of in vivo tumors is necessary. Here, we present a biomimicking bilayer microfluidic device that can facilitate antitumor drug screening. The microfluidic device consists of two polydimethylsiloxane (PDMS) pieces with channels which are separated by a semipermeable membrane to allow water, oxygen, and nutrition supply, while preventing cell migration. The channels embedded on the two PDMS pieces overlap each other over a long distance to ensure a larger exchange area to mimic the blood vessel-tumor model. High concentrations of endothelial cells (EC) are first seeded onto the membrane through the apical channel, and after a two-day culture, a confluent EC monolayer forms. Tumor spheroid-laden Matrigel is then seeded into the basal channel. After the Matrigel is cured, the device is ready for drug testing. Paclitaxel is used as the model drug for testing. Confocal microscopy and ImageJ are used to assess the efficacy of different concentrations of paclitaxel, and optical coherence tomography (OCT) is employed to determine the tumor volumetric change after the drug treatment. The results indicate that the proposed bilayer microfluidic device in combination with confocal and OCT optical characterization provide an efficient platform for antitumor drug testing.

Motility of Shewanella oneidensis MR-1 Allows for Nitrate Reduction in the Toxic Region of a Ciprofloxacin Concentration Gradient in a Microfluidic Reactor

Subsurface environments often contain mixtures of contaminants in which the microbial degradation of one pollutant may be inhibited by the toxicity of another. Agricultural settings exemplify these complex environments, where antimicrobial leachates may inhibit nitrate bioreduction, and are the motivation to address this fundamental ecological response. In this study, a microfluidic reactor was fabricated to create diffusion-controlled concentration gradients of nitrate and ciprofloxacin under anoxic conditions in order to evaluate the ability of Shewanella oneidenisis MR-1 to reduce the former in the presence of the latter. Results show a surprising ecological response, where swimming motility allow S. oneidensis MR-1 to accumulate and maintain metabolic activity for nitrate reduction in regions with toxic ciprofloxacin concentrations (i.e., 50× minimum inhibitory concentration, MIC), despite the lack of observed antibiotic resistance. Controls with limited nutrient flux and a nonmotile mutant (Δ flag) show that cells cannot colonize antibiotic rich microenvironments, and this results in minimal metabolic activity for nitrate reduction. These results demonstrate that under anoxic, nitrate-reducing conditions, motility can control microbial habitability and metabolic activity in spatially heterogeneous toxic environments.

Delays in Fitness Adjustment Can Lead to Coexistence of Hierarchically Interacting Species

Organisms that exploit different environments may experience a stochastic delay in adjusting their fitness when they switch habitats. We study two such organisms whose fitness is determined by the species composition of the local environment, as they interact through a public good. We show that a delay in the fitness adjustment can lead to the coexistence of the two species in a metapopulation, although the faster-growing species always wins in well-mixed competition experiments. Coexistence is favored over wide parameter ranges and is independent of spatial clustering. It arises when species are heterogeneous in their fitness and can keep each other balanced.

Liposomal borrelidin for treatment of metastatic breast cancer

Borrelidin is an inhibitor of threonyl-tRNA synthetase with both anticancer and antiangiogenic activities. Although borrelidin could be a potent drug that can treat metastatic cancer through synergistic therapeutic effects, its severe liver toxicity has limited the use for cancer therapeutics. In this study, we developed a liposomal formulation of borrelidin to treat metastatic breast cancer effectively through its combined anticancer and antiangiogenic effects while reducing the potential liver toxicity. The liposomal formulation was optimized to maximize loading stability and efficiency of lipophilic borrelidin in the liposomal membrane and its delivery efficiency to primary tumor in a mouse model of metastatic breast cancer. Liposomal borrelidin showed significant in vitro therapeutic effects on proliferation and migration of tumor cells and angiogenesis of endothelial cells. Furthermore, liposomal borrelidin exhibited superior inhibitory effects on primary tumor growth and lung metastasis in vivo compared to free borrelidin. More importantly, liposomal borrelidin did not induce any significant systemic toxicity in the mouse model after multiple injections.

Polymer-Temozolomide Conjugates as Therapeutics for Treating Glioblastoma

A series of polymer-drug conjugates based on 2-methacryloyloxyethyl phosphorylcholine (MPC) was prepared with the glioblastoma drug temozolomide (TMZ) as pendent groups. Random and block copolymers were synthesized by reversible addition-fragmentation chain-transfer (RAFT) polymerization using a TMZ-containing methacrylate monomer. The solution properties of the polyMPC-TMZ copolymers were investigated by dynamic light scattering and transmission electron microscopy, revealing well-defined nanostructures from the block copolymers. Conjugation of TMZ to polyMPC enhanced drug stability, with decomposition half-life values ranging from 2- to 19-times longer than that of free TMZ. The cytotoxicity of polyMPC-TMZ was evaluated in both chemosensitive (U87MG) and chemoresistant (T98G) glioblastoma cell lines. Furthermore, the polyMPC-TMZ platform was expanded considerably by the preparation of redox-sensitive polyMPC-TMZ copolymers utilizing disulfides as the polymer-to-drug linker.

Surface-Bound Gradient Deposition of Protein Nanoparticles for Cell Motility Studies

A versatile evaporation-assisted methodology based on the coffee-drop effect is described to deposit nanoparticles on surfaces, obtaining for the first time patterned gradients of protein nanoparticles (pNPs) by using a simple custom-made device. Fully controllable patterns with specific periodicities consisting of stripes with different widths and distinct nanoparticle concentration as well as gradients can be produced over large areas (∼10 cm²) in a fast (up to 10 mm²/min), reproducible, and cost-effective manner using an operational protocol optimized by an evolutionary algorithm. The developed method opens the possibility to decorate surfaces "a-la-carte" with pNPs enabling different categories of high-throughput studies on cell motility.

The Role of Desmoplasia and Stromal Fibroblasts on Anti-cancer Drug Resistance in a Microengineered Tumor Model

Introduction

Cancer associated fibroblasts (CAFs) are known to participate in anti-cancer drug resistance by upregulating desmoplasia and pro-survival mechanisms within the tumor microenvironment. In this regard, anti-fibrotic drugs (i.e., tranilast) have been repurposed to diminish the elastic modulus of the stromal matrix and reduce tumor growth in presence of chemotherapeutics (i.e., doxorubicin). However, the quantitative assessment on impact of these stromal targeting drugs on matrix stiffness and tumor progression is still missing in the sole presence of CAFs.

Methods

We developed a high-density 3D microengineered tumor model comprised of MDA-MB-231 (highly invasive breast cancer cells) embedded microwells, surrounded by CAFs encapsulated within collagen I hydrogel. To study the influence of tranilast and doxorubicin on fibrosis, we probed the matrix using atomic force microscopy (AFM) and assessed matrix protein deposition. We further studied the combinatorial influence of the drugs on cancer cell proliferation and invasion.

Results

Our results demonstrated that the combinatorial action of tranilast and doxorubicin significantly diminished the stiffness of the stromal matrix compared to the control. The two drugs in synergy disrupted fibronectin assembly and reduced collagen fiber density. Furthermore, the combination of these drugs, condensed tumor growth and invasion.

Conclusion

In this work, we utilized a 3D microengineered model to tease apart the role of tranilast and doxorubicin in the sole presence of CAFs on desmoplasia, tumor growth and invasion. Our study lay down a ground work on better understanding of the role of biomechanical properties of the matrix on anti-cancer drug efficacy in the presence of single class of stromal cells.

Bacterial cellulose hydrogel loaded with lipid nanoparticles for localized cancer treatment

The use of hybrid materials, where a matrix sustains nanoparticles controlling the release of the chemotherapeutic drug, could be beneficial for the treatment of primary tumors prior or after surgery. This localized chemotherapy would guarantee high drug concentrations at the tumor site while precluding systemic drug exposure minimizing undesirable side effects. We combined bacterial cellulose hydrogel (BC) and nanostructured lipid carriers (NLCs) including doxorubicin (Dox) as a drug model. NLCs loaded with cationic Dox (NLCs-H) or neutral Dox (NLCs-N) were fully characterized and their cell internalization and cytotoxic efficacy were evaluated in vitro against MDA-MB-231 cells. Thereafter, a fixed combination of NLCs-H and NLCs-N loaded into BC (BC-NLCs-NH) was assayed in vivo into an orthotopic breast cancer mouse model. NLCs-H showed low encapsulation efficiency (48%) and fast release of the drug while NLCs-N showed higher encapsulation (97%) and sustained drug release. Both NLCs internalized via endocytic pathway, while allowing a sustained release of the Dox, which in turn rendered IC50 values below of those of free Dox. Taking advantage of the differential drug release, a mixture of NLCs-N and NLCs-H was encapsulated into BC matrix (BC-NLCs-NH) and assayed in vivo, showing a significant reduction of tumor growth, metastasis incidence and local drug toxicities.

Microfluidics in Malignant Glioma Research and Precision Medicine

Glioblastoma multiforme (GBM) is an aggressive form of brain cancer that has no effective treatments and a prognosis of only 12-15 months. Microfluidic technologies deliver microscale control of fluids and cells, and have aided cancer therapy as point-of-care devices for the diagnosis of breast and prostate cancers. However, a few microfluidic devices are developed to study malignant glioma. The ability of these platforms to accurately replicate the complex microenvironmental and extracellular conditions prevailing in the brain and facilitate the measurement of biological phenomena with high resolution and in a high-throughput manner could prove useful for studying glioma progression. These attributes, coupled with their relatively simple fabrication process, make them attractive for use as point-of-care diagnostic devices for detection and treatment of GBM. Here, the current issues that plague GBM research and treatment, as well as the current state of the art in glioma detection and therapy, are reviewed. Finally, opportunities are identified for implementing microfluidic technologies into research and diagnostics to facilitate the rapid detection and better therapeutic targeting of GBM.

Systems for localized release to mimic paracrine cell communication in vitro

Paracrine cell communication plays a pivotal role for signal exchange between proximal cells in vivo. However, this localized, gradient type release of mediators at very low concentrations (pg/ml), relevant during physiological and pathological processes, is rarely reflected within in vitro approaches. This review gives an overview on state-of-the-art approaches, which transfer the paracrine cell-to-cell communication into in vitro cell culture model setups. The traditional methods like trans-well assays and more advanced microfluidic approaches are included. The review focusses on systems for localized release, mostly based on microparticles, which tightly mimic the paracrine interaction between single cells in 3D microenvironments. Approaches based on single microparticles, with the main focus on affinity-controlled storage and release of cytokines, are reviewed and their importance for understanding paracrine communication is highlighted. Various methods to study the cytokine release and their advantages and disadvantages are discussed. Basic principles of the release characteristics, like diffusion mechanisms, are quantitatively described, including the formation of resulting gradients around the local sources. In vitro cell experiments using such localized microparticle release systems in approaches to increase understanding of stem cell behavior within their niches and regulation of wound healing are highlighted as examples of successful localized release systems for mimicking paracrine cell communication.

Relevance of small GTPase Rac1 pathway in drug and radio-resistance mechanisms: Opportunities in cancer therapeutics

Rac1 GTPase signaling pathway has a critical role in the regulation of a plethora of cellular functions governing cancer cell behavior. Recently, it has been shown a critical role of Rac1 in the emergence of resistance mechanisms to cancer therapy. This review describes the current knowledge regarding Rac1 pathway deregulation and its association with chemoresistance, radioresistance, resistance to targeted therapies and immune evasion. This supports the idea that interfering Rac1 signaling pathway could be an interesting approach to tackle cancer resistance.

Mimicking Embedded Vasculature Structure for 3D Cancer on a Chip Approaches through Micromilling

The ability for cells to sense and respond to microenvironmental signals is influenced by their three dimensional (3D) surroundings, which includes the extracellular matrix (ECM). In the 3D environment, vascular structures supply cells with nutrients and oxygen thus affecting cell responses such as motility. Interpretation of cell motility studies though is often restricted by the applied approaches such as 2D conventional soft lithography methods that have rectangular channel cross-sectional morphology. To better simulate cell responses to vascular supply in 3D, we developed a cell on a chip system with microfluidic channels with curved cross-sections embedded within a 3D collagen matrix that emulates anatomical vasculature more closely than inorganic polymers, thus to mimic a more physiologically relevant 3D cellular environment. To accomplish this, we constructed perfusable microfluidic channels by embedding sacrificial circular gelatin vascular templates in collagen, which were removed through temperature control. Motile breast cancer cells were pre-seeded into the collagen matrix and when presented with a controlled chemical stimulation from the artificial vasculature, they migrated towards the vasculature structure. We believe this innovative vascular 3D ECM system can be used to provide novel insights into cellular dynamics during multidirectional chemokineses and chemotaxis that exist in cancer and other diseases.

Exploiting ecology in drug pulse sequences in favour of population reduction

A deterministic population dynamics model involving birth and death for a two-species system, comprising a wild-type and more resistant species competing via logistic growth, is subjected to two distinct stress environments designed to mimic those that would typically be induced by temporal variation in the concentration of a drug (antibiotic or chemotherapeutic) as it permeates through the population and is progressively degraded. Different treatment regimes, involving single or periodical doses, are evaluated in terms of the minimal population size (a measure of the extinction probability), and the population composition (a measure of the selection pressure for resistance or tolerance during the treatment). We show that there exist timescales over which the low-stress regime is as effective as the high-stress regime, due to the competition between the two species. For multiple periodic treatments, competition can ensure that the minimal population size is attained during the first pulse when the high-stress regime is short, which implies that a single short pulse can be more effective than a more protracted regime. Our results suggest that when the duration of the high-stress environment is restricted, a treatment with one or multiple shorter pulses can produce better outcomes than a single long treatment. If ecological competition is to be exploited for treatments, it is crucial to determine these timescales, and estimate for the minimal population threshold that suffices for extinction. These parameters can be quantified by experiment.

A novel 3-D bio-microfluidic system mimicking in vivo heterogeneous tumour microstructures reveals complex tumour-stroma interactions

A 3-D microfluidic system consisting of microchamber arrays embedded in a collagen hydrogel with tuneable biochemical gradients that mimics the tumour microenvironment of mammary glands was constructed for the investigation on the interactions between invasive breast cancer cells and stromal cells. The hollow microchambers in collagen provide a very similar 3-D environment to that in vivo that regulates collective cellular dynamics and behaviour, while the microfluidic channels surrounding the collagen microchamber arrays allow one to impose complex concentration gradients of specific biological molecules or drugs. We found that breast epithelial cells (MCF-10A) seeded in the microchambers formed lumen-like structures similar to those in epithelial layers. When MCF-10A cells were co-cultured with invasive breast cancer cells (MDA-MB-231), the formation of lumen-like structures in the microchambers was inhibited, indicating the capability of cancer cells to disrupt the structures formed by surrounding cells for further invasion and metastasis. Subsequent mechanism studies showed that down regulation of E-cad expression due to MMPs produced by the cancer cells plays a dominant role in determining the cellular behaviour. Our microfluidic system offers a robust platform for high throughput studies that aim to understand combinatorial effects of multiple biochemical and microenvironmental factors.

A hybrid discrete-continuous model of in vitro spheroid tumor growth and drug response

Anti-cancer therapy efficacy in solid tumors mainly depends on drug transportation through the vasculature system and the extracellular matrix, on diffusion gradients and clonal heterogeneity within the tumor mass, as well as on the responses of the individual tumor cells to drugs and their interactions with each other and their local microenvironment. In this work, we develop a mathematical predictive model for tumor growth and drug response based on 3D spheroids experiments that possess several in vivo features of tumors and are considered better for drug screening. The model takes into account the diffusion gradients of both oxygen and drug through the tumor volume, describes the tumor population at cell level and assumes a simple underlying cellular dose-response curve that is translated to a cell death probability. The model shows that although the endpoint tumor regression can be well approximated, the effects of the drug on cell fate necessitate a more sophisticated model to explain the temporal evolution of tumor regression and more quantitative information regarding the number and topology of dead and living cells, which is highly important for in vivo clinical relevant predictions. The model is built in a way that can be constrained by experimentally derived set of parameters and is capable of accommodating cell heterogeneity, sub-cellular regulatory mechanisms and drug-induced signaling cascades, as well as additional mechanisms of adapted resistance.

Evolutionary scalpels for dissecting tumor ecosystems

Amidst the growing literature on cancer genomics and intratumor heterogeneity, essential principles in evolutionary biology recur time and time again. Here we use these principles to guide the reader through major advances in cancer research, highlighting issues of "hit hard, hit early" treatment strategies, drug resistance, and metastasis. We distinguish between two frameworks for understanding heterogeneous tumors, both of which can inform treatment strategies: (1) The tumor as diverse ecosystem, a Darwinian population of sometimes-competing, sometimes-cooperating cells; (2) The tumor as tightly integrated, self-regulating organ, which may hijack developmental signals to restore functional heterogeneity after treatment. While the first framework dominates literature on cancer evolution, the second framework enjoys support as well. Throughout this review, we illustrate how mathematical models inform understanding of tumor progression and treatment outcomes. Connecting models to genomic data faces computational and technical hurdles, but high-throughput single-cell technologies show promise to clear these hurdles. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Limiting the development of anti-cancer drug resistance in a spatial model of micrometastases

While chemoresistance in primary tumors is well-studied, much less is known about the influence of systemic chemotherapy on the development of drug resistance at metastatic sites. In this work, we use a hybrid spatial model of tumor response to a DNA damaging drug to study how the development of chemoresistance in micrometastases depends on the drug dosing schedule. We separately consider cell populations that harbor pre-existing resistance to the drug, and those that acquire resistance during the course of treatment. For each of these independent scenarios, we consider one hypothetical cell line that is responsive to metronomic chemotherapy, and another that with high probability cannot be eradicated by a metronomic protocol. Motivated by experimental work on ovarian cancer xenografts, we consider all possible combinations of a one week treatment protocol, repeated for three weeks, and constrained by the total weekly drug dose. Simulations reveal a small number of fractionated-dose protocols that are at least as effective as metronomic therapy in eradicating micrometastases with acquired resistance (weak or strong), while also being at least as effective on those that harbor weakly pre-existing resistant cells. Given the responsiveness of very different theoretical cell lines to these few fractionated-dose protocols, these may represent more effective ways to schedule chemotherapy with the goal of limiting metastatic tumor progression.

Rapid emergence and mechanisms of resistance by U87 glioblastoma cells to doxorubicin in an in vitro tumor microfluidic ecology

In vitro prediction of the probable rapid emergence of resistance to a drug in tumors could act to winnow out potential candidates for further costly development. We have developed a microfluidic device consisting of ∼500 hexagonal microcompartments that provides a complex ecology with wide ranges of drug and nutrient gradients and local populations. This ecology of a fragmented metapopulation induced the drug resistance in stage IV U87 glioblastoma cells to doxorubicin in 7 d. Exome and transcriptome sequencing of the resistant cells identified mutations and differentially expressed genes. Gene ontology and pathway analyses of the genes identified showed that they were functionally relevant to the established mechanisms of doxorubicin action. Specifically, we identified (i) a frame-shift insertion in the filamin-A gene, which regulates the influx and efflux of topoisomerase II poisons; (ii) the overexpression of aldo-keto reductase enzymes, which convert doxorubicin into doxorubicinol; and (iii) activation of NF-κB via alterations in the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway from mutations in three genes (CARD6, NSD1, and NLRP13) and the overexpression of inflammatory cytokines. Functional experiments support the in silico analyses and, together, demonstrate the effects of these genetic changes. Our findings suggest that, given the rapid evolution of resistance and the focused response, this technology could act as a rapid screening modality for genetic aberrations leading to resistance to chemotherapy as well as counter selection of drugs unlikely to be successful ultimately.

Long range personalized cancer treatment strategies incorporating evolutionary dynamics

Background

Current cancer precision medicine strategies match therapies to static consensus molecular properties of an individual’s cancer, thus determining the next therapeutic maneuver. These strategies typically maintain a constant treatment while the cancer is not worsening. However, cancers feature complicated sub-clonal structure and dynamic evolution. We have recently shown, in a comprehensive simulation of two non-cross resistant therapies across a broad parameter space representing realistic tumors, that substantial improvement in cure rates and median survival can be obtained utilizing dynamic precision medicine strategies. These dynamic strategies explicitly consider intratumoral heterogeneity and evolutionary dynamics, including predicted future drug resistance states, and reevaluate optimal therapy every 45 days. However, the optimization is performed in single 45 day steps (“single-step optimization”).

Results

Herein we evaluate analogous strategies that think multiple therapeutic maneuvers ahead, considering potential outcomes at 5 steps ahead (“multi-step optimization”) or 40 steps ahead (“adaptive long term optimization (ALTO)”) when recommending the optimal therapy in each 45 day block, in simulations involving both 2 and 3 non-cross resistant therapies. We also evaluate an ALTO approach for situations where simultaneous combination therapy is not feasible (“Adaptive long term optimization: serial monotherapy only (ALTO-SMO)”). Simulations utilize populations of 764,000 and 1,700,000 virtual patients for 2 and 3 drug cases, respectively. Each virtual patient represents a unique clinical presentation including sizes of major and minor tumor subclones, growth rates, evolution rates, and drug sensitivities.

While multi-step optimization and ALTO provide no significant average survival benefit, cure rates are significantly increased by ALTO. Furthermore, in the subset of individual virtual patients demonstrating clinically significant difference in outcome between approaches, by far the majority show an advantage of multi-step or ALTO over single-step optimization. ALTO-SMO delivers cure rates superior or equal to those of single- or multi-step optimization, in 2 and 3 drug cases respectively.

Conclusion

In selected virtual patients incurable by dynamic precision medicine using single-step optimization, analogous strategies that “think ahead” can deliver long-term survival and cure without any disadvantage for non-responders. When therapies require dose reduction in combination (due to toxicity), optimal strategies feature complex patterns involving rapidly interleaved pulses of combinations and high dose monotherapy.

Reviewers

This article was reviewed by Wendy Cornell, Marek Kimmel, and Andrzej Swierniak. Wendy Cornell and Andrzej Swierniak are external reviewers (not members of the Biology Direct editorial board). Andrzej Swierniak was nominated by Marek Kimmel.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-016-0153-2) contains supplementary material, which is available to authorized users.

Polymeric Biomaterials for In Vitro Cancer Tissue Engineering and Drug Testing Applications

Biomimetic polymers and materials have been widely used in tissue engineering for regeneration and replication of diverse types of both normal and diseased tissues. Cancer, being a prevalent disease throughout the world, has initiated substantial interest in the creation of tissue-engineered models for anticancer drug testing. The development of these in vitro three-dimensional (3D) culture models using novel biomaterials has facilitated the investigation of tumorigenic and associated biological phenomena with a higher degree of complexity and physiological context than that provided by established two-dimensional culture models. In this review, an overview of a wide range of natural, synthetic, and hybrid biomaterials used for 3D cancer cell culture and investigation of cancer cell behavior is presented. The role of these materials in modulating cell-matrix interactions and replicating specific tumorigenic characteristics is evaluated. In addition, recent advances in biomaterial design, synthesis, and fabrication are also assessed. Finally, the advantages of incorporating polymeric biomaterials in 3D cancer models for obtaining efficacy data in anticancer drug testing applications are highlighted.

Evolutionary Phase Transitions in Random Environments

We present analytical results for long-term growth rates of structured populations in randomly fluctuating environments, which we apply to predict how cellular response networks evolve. We show that networks which respond rapidly to a stimulus will evolve phenotypic memory exclusively under random (i.e., nonperiodic) environments. We identify the evolutionary phase diagram for simple response networks, which we show can exhibit both continuous and discontinuous transitions. Our approach enables exact analysis of diverse evolutionary systems, from viral epidemics to emergence of drug resistance.