Cancer Stem Cells: A Minor Cancer Subpopulation that Redefines Global Cancer Features

Imaging cellular forces with photonic crystals

Current techniques for visualizing and quantifying cellular forces have limitations in live cell imaging, throughput, and multi-scale analysis, which impede progress in cell force research and its practical applications. We developed a photonic crystal cellular force microscopy (PCCFM) to image vertical cell forces over a wide field of view (1.3 mm ⨯ 1.0 mm, a 10 ⨯ objective image) at high speed (about 20 frames per second) without references. The photonic crystal hydrogel substrate (PCS) converts micro-nano deformations into perceivable color changes, enabling in situ visualization and quantification of tiny vertical cell forces with high throughput. It enabled long-term, cross-scale monitoring from subcellular focal adhesions to tissue-level cell sheets and aggregates.

Tumor matrix stiffness provides fertile soil for cancer stem cells

Matrix stiffness is a mechanical characteristic of the extracellular matrix (ECM) that increases from the tumor core to the tumor periphery in a gradient pattern in a variety of solid tumors and can promote proliferation, invasion, metastasis, drug resistance, and recurrence. Cancer stem cells (CSCs) are a rare subpopulation of tumor cells with self-renewal, asymmetric cell division, and differentiation capabilities. CSCs are thought to be responsible for metastasis, tumor recurrence, chemotherapy resistance, and consequently poor clinical outcomes. Evidence suggests that matrix stiffness can activate receptors and mechanosensor/mechanoregulator proteins such as integrin, FAK, and YAP, modulating the characteristics of tumor cells as well as CSCs through different molecular signaling pathways. A deeper understanding of the effect of matrix stiffness on CSCs characteristics could lead to development of innovative cancer therapies. In this review, we discuss how the stiffness of the ECM is sensed by the cells and how the cells respond to this environmental change as well as the effect of matrix stiffness on CSCs characteristics and also the key malignant processes such as proliferation and EMT. Then, we specifically focus on how increased matrix stiffness affects CSCs in breast, lung, liver, pancreatic, and colorectal cancers. We also discuss how the molecules responsible for increased matrix stiffness and the signaling pathways activated by the enhanced stiffness can be manipulated as a therapeutic strategy for cancer.

Practical Understanding of Cancer Model Identifiability in Clinical Applications

Mathematical models are a core component in the foundation of cancer theory and have been developed as clinical tools in precision medicine. Modeling studies for clinical applications often assume an individual's characteristics can be represented as parameters in a model and are used to explain, predict, and optimize treatment outcomes. However, this approach relies on the identifiability of the underlying mathematical models. In this study, we build on the framework of an observing-system simulation experiment to study the identifiability of several models of cancer growth, focusing on the prognostic parameters of each model. Our results demonstrate that the frequency of data collection, the types of data, such as cancer proxy, and the accuracy of measurements all play crucial roles in determining the identifiability of the model. We also found that highly accurate data can allow for reasonably accurate estimates of some parameters, which may be the key to achieving model identifiability in practice. As more complex models required more data for identification, our results support the idea of using models with a clear mechanism that tracks disease progression in clinical settings. For such a model, the subset of model parameters associated with disease progression naturally minimizes the required data for model identifiability.

Effect of feedback regulation on stem cell fractions in tissues and tumors: Understanding chemoresistance in cancer

While resistance mutations are often implicated in the failure of cancer therapy, lack of response also occurs without such mutants. In bladder cancer mouse xenografts, repeated chemotherapy cycles have resulted in cancer stem cell (CSC) enrichment, and consequent loss of therapy response due to the reduced susceptibility of CSCs to drugs. A particular feedback loop present in the xenografts has been shown to promote CSC enrichment in this system. Yet, many other regulatory loops might also be operational and might promote CSC enrichment. Their identification is central to improving therapy response. Here, we perform a comprehensive mathematical analysis to define what types of regulatory feedback loops can and cannot contribute to CSC enrichment, providing guidance to the experimental identification of feedback molecules. We derive a formula that reveals whether or not the cell population experiences CSC enrichment over time, based on the properties of the feedback. We find that negative feedback on the CSC division rate or positive feedback on differentiated cell death rate can lead to CSC enrichment. Further, the feedback mediators that achieve CSC enrichment can be secreted by either CSCs or by more differentiated cells. The extent of enrichment is determined by the CSC death rate, the CSC self-renewal probability, and by feedback strength. Defining these general characteristics of feedback loops can guide the experimental screening for and identification of feedback mediators that can promote CSC enrichment in bladder cancer and potentially other tumors. This can help understand and overcome the phenomenon of CSC-based therapy resistance.

One stem cell program to rule them all?

Many species of animals have stem cells that they maintain throughout their lives, which suggests that stem cells are an ancestral feature of all animals. From this, we take the viewpoint that cells with the biological properties of 'stemness'-self-renewal and multipotency-may share ancestral genetic circuitry. However, in practice is it very difficult to identify and compare stemness gene signatures across diverse animals and large evolutionary distances? First, it is critical to experimentally demonstrate self-renewal and potency. Second, genomic methods must be used to determine specific gene expression in stem cell types compared with non-stem cell types to determine stem cell gene enrichment. Third, gene homology must be mapped between diverse animals across large evolutionary distances. Finally, conserved genes that fulfill these criteria must be tested for role in stem cell function. It is our viewpoint that by comparing stem cell-specific gene signatures across evolution, ancestral programs of stemness can be uncovered, and ultimately, the dysregulation of stemness programs drives the state of cancer stem cells.

Isorhapontigenin (ISO) inhibits stem cell-like properties and invasion of bladder cancer cell by attenuating CD44 expression

Cancer stem cells (CSC) are highly associated with poor prognosis in cancer patients. Our previous studies report that isorhapontigenin (ISO) down-regulates SOX2-mediated cyclin D1 induction and stem-like cell properties in glioma stem-like cells. The present study revealed that ISO could inhibit stem cell-like phenotypes and invasivity of human bladder cancer (BC) by specific attenuation of expression of CD44 but not SOX-2, at both the protein transcription and degradation levels. On one hand, ISO inhibited cd44 mRNA expression through decreases in Sp1 direct binding to its promoter region-binding site, resulting in attenuation of its transcription. On the other hand, ISO also down-regulated USP28 expression, which in turn reduced CD44 protein stability. Further studies showed that ISO treatment induced miR-4295, which specific bound to 3'-UTR activity of usp28 mRNA and inhibited its translation and expression, while miR-4295 induction was mediated by increased Dicer protein to enhance miR-4295 maturation upon ISO treatment. Our results provide the first evidence that ISO has a profound inhibitory effect on human BC stem cell-like phenotypes and invasivity through the mechanisms distinct from those previously noted in glioma stem-like cells.

A Potential Application of Triangular Microwells to Entrap Single Cancer Cells: A Canine Cutaneous Mast Cell Tumor Model

Cellular heterogeneity is a major hindrance, leading to the misunderstanding of dynamic cell biology. However, single cell analysis (SCA) has been used as a practical means to overcome this drawback. Many contemporary methodologies are available for single cell analysis; among these, microfluidics is the most attractive and effective technology, due to its advantages of low-volume specimen consumption, label-free evaluation, and real-time monitoring, among others. In this paper, a conceptual application for microfluidic single cell analysis for veterinary research is presented. A microfluidic device is fabricated with an elastomer substrate, polydimethylsiloxane (PDMS), under standard soft lithography. The performance of the microdevice is high-throughput, sensitive, and user-friendly. A total of 53.1% of the triangular microwells were able to trap single canine cutaneous mast cell tumor (MCT) cells. Of these, 38.82% were single cell entrapments, while 14.34% were multiple cell entrapments. The ratio of single-to-multiple cell trapping was high, at 2.7:1. In addition, 80.5% of the trapped cells were viable, indicating that the system was non-lethal. OCT4A-immunofluorescence combined with the proposed system can assess OCT4A expression in trapped single cells more precisely than OCT4A-immunohistochemistry. Therefore, the results suggest that microfluidic single cell analysis could potentially reduce the impact of cellular heterogeneity.

Mathematical modeling reveals the factors involved in the phenomena of cancer stem cells stabilization

Cancer Stem Cells (CSC), a subset of cancer cells resembling normal stem cells with self-renewal and asymmetric division capabilities, are present at various but low proportions in many tumors and are thought to be responsible for tumor relapses following conventional cancer therapies. In vitro, most intriguingly, isolated CSCs rapidly regenerate the original population of stem and non-stem cells (non-CSCs) as shown by various investigators. This phenomenon still remains to be explained. We propose a mathematical model of cancer cell population dynamics, based on the main parameters of cell population growth, including the proliferation rates, the rates of cell death and the frequency of symmetric and asymmetric cell divisions both in CSCs and non-CSCs sub-populations, and taking into account the stabilization phenomenon. The analysis of the model allows determination of time-varying corridors of probabilities for different cell fates, given the particular dynamics of cancer cells populations; and determination of a cell-cell communication factors influencing these time-varying probabilities of cell behavior (division, transition) scenarios. Though the results of the model have to be experimentally confirmed, we can anticipate the development of several fundamental and practical applications based on the theoretical results of the model.

Clonal pattern dynamics in tumor: the concept of cancer stem cells

We present a multiphase model for solid tumor initiation and progression focusing on the properties of cancer stem cells (CSC). CSCs are a small and singular cell sub-population having outstanding capacities: high proliferation rate, self-renewal and extreme therapy resistance. Our model takes all these factors into account under a recent perspective: the possibility of phenotype switching of differentiated cancer cells (DC) to the stem cell state, mediated by chemical activators. This plasticity of cancerous cells complicates the complete eradication of CSCs and the tumor suppression. The model in itself requires a sophisticated treatment of population dynamics driven by chemical factors. We analytically demonstrate that the rather important number of parameters, inherent to any biological complexity, is reduced to three pivotal quantities.Three fixed points guide the dynamics, and two of them may lead to an optimistic issue, predicting either a control of the cancerous cell population or a complete eradication. The space environment, critical for the tumor outcome, is introduced via a density formalism. Disordered patterns are obtained inside a stable growing contour driven by the CSC. Somewhat surprisingly, despite the patterning instability, the contour maintains its circular shape but ceases to grow for a typical size independently of segregation patterns or obstacles located inside.

Bioengineered adipose-derived stem cells for targeted enzyme-prodrug therapy of ovarian cancer intraperitoneal metastasis

The objective of this study was to develop a stem cell-based system for targeted suicide gene therapy of recurrent, metastatic, and unresectable ovarian cancer. Malignant cells were obtained from the ascites of a patient with advanced recurrent epithelial ovarian cancer (named OVASC-1). Cancer cells were characterized to determine the percentages of drug-resistant ALDH+ cells, MDR-1/ABCG2 overexpressing cells, and cancer stem-like cells. The sensitivity and resistance of the OVASC-1 cells and spheroids to the metabolites of three different enzyme/prodrug systems were assessed, and the most effective one was selected. Adipose-derived stem cells (ASCs) were genetically engineered to express recombinant secretory human carboxylesterase-2 and nanoluciferase genes for simultaneous disease therapy and quantitative imaging. Bioluminescent imaging, magnetic resonance imaging and immuno/histochemistry results show that the engineered ASCs actively targeted and localized at both tumor stroma and necrotic regions. This created the unique opportunity to deliver drugs to not only tumor supporting cells in the stroma, but also to cancer stem-like cells in necrotic/hypoxic regions. The statistical analysis of intraperitoneal OVASC-1 tumor burden and survival rates in mice shows that the administration of the bioengineered ASCs in combination with irinotecan prodrug in the designed sequence and timeline eradicated all intraperitoneal tumors and provided survival benefits. In contrast, treatment of the drug-resistant OVASC-1 tumors with cisplatin/paclitaxel (standard-of-care) did not have any statistically significant benefit. The histopathology and hematology results do not show any toxicity to major peritoneal organs. Our toxicity data in combination with efficacy outcomes delineate a nonsurgical and targeted stem cell-based approach to overcoming drug resistance in recurrent metastatic ovarian cancer.

Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy

Background

Standard radiobiology theory of radiation response assumes a uniform innate radiosensitivity of tumors. However, experimental data show that there is significant intratumoral heterogeneity of radiosensitivity. Therefore, a model with heterogeneity was developed and tested using existing experimental data to show the potential effects from the presence of an intratumoral distribution of radiosensitivity on radiation therapy response over a protracted radiation therapy treatment course.

Methods

The standard radiation response curve was modified to account for a distribution of radiosensitivity, and for variations in the repopulation rates of the tumor cell subpopulations. Experimental data from the literature were incorporated to determine the boundaries of the model. The proposed model was then used to show the changes in radiosensitivity of the tumor during treatment, and the effects of fraction size, α/β ratio and variation of the repopulation rates of tumor cells.

Results

In the presence of an intratumoral distribution of radiosensitivity, there is rapid selection of radiation-resistant cells over a course of fractionated radiation therapy. Standard treatment fractionation regimes result in the near-complete replacement of the initial population of sensitive cells with a population of more resistant cells. Further, as treatment progresses, the tumor becomes more resistant to further radiation treatment, making each fractional dose less efficacious. A wider initial distribution induces increased radiation resistance. Hypofractionation is more efficient in a heterogeneous tumor, with increased cell kill for biologically equivalent doses, while inducing less resistance. The model also shows that a higher growth rate in resistant cells can account for the accelerated repopulation that is seen during the clinical treatment of patients.

Conclusions

Modeling of tumor cell survival with radiosensitivity heterogeneity alters the predicted tumor response, and explains the induction of radiation resistance by radiation treatment, the development of accelerated repopulation, and the potential beneficial effects of hypofractionation. Tumor response to treatment may be better predicted by assaying for the distribution of radiosensitivity, or the extreme of the radiosensitivity, rather than measuring the initial, general radiation sensitivity of the untreated tumor.

Krüppel-like factor 9 and histone deacetylase inhibitors synergistically induce cell death in glioblastoma stem-like cells

Background

The dismal prognosis of patients with glioblastoma (GBM) is attributed to a rare subset of cancer stem cells that display characteristics of tumor initiation, growth, and resistance to aggressive treatment involving chemotherapy and concomitant radiation. Recent research on the substantial role of epigenetic mechanisms in the pathogenesis of cancers has prompted the investigation of the enzymatic modifications of histone proteins for therapeutic drug targeting. In this work, we have examined the function of Krüppel-like factor 9 (KLF9), a transcription factor, in chemotherapy sensitization to histone deacetylase inhibitors (HDAC inhibitors).

Methods

Since GBM neurosphere cultures from patient-derived gliomas are enriched for GBM stem-like cells (GSCs) and form highly invasive and proliferative xenografts that recapitulate the features demonstrated in human patients diagnosed with GBM, we established inducible KLF9 expression systems in these GBM neurosphere cells and investigated cell death in the presence of epigenetic modulators such as histone deacetylase (HDAC) inhibitors.

Results

We demonstrated that KLF9 expression combined with HDAC inhibitor panobinostat (LBH589) dramatically induced glioma stem cell death via both apoptosis and necroptosis in a synergistic manner. The combination of KLF9 expression and LBH589 treatment affected cell cycle by substantially decreasing the percentage of cells at S-phase. This phenomenon is further corroborated by the upregulation of cell cycle inhibitors p21 and p27. Further, we determined that KLF9 and LBH589 regulated the expression of pro- and anti- apoptotic proteins, suggesting a mechanism that involves the caspase-dependent apoptotic pathway. In addition, we demonstrated that apoptosis and necrosis inhibitors conferred minimal protective effects against cell death, while inhibitors of the necroptosis pathway significantly blocked cell death.

Conclusions

Our findings suggest a detailed understanding of how KLF9 expression in cancer cells with epigenetic modulators like HDAC inhibitors may promote synergistic cell death through a mechanism involving both apoptosis and necroptosis that will benefit novel combinatory antitumor strategies to treat malignant brain tumors.

Effect of cellular de-differentiation on the dynamics and evolution of tissue and tumor cells in mathematical models with feedback regulation

Tissues are maintained by adult stem cells that self-renew and also differentiate into functioning tissue cells. Homeostasis is achieved by a set of complex mechanisms that involve regulatory feedback loops. Similarly, tumors are believed to be maintained by a minority population of cancer stem cells, while the bulk of the tumor is made up of more differentiated cells, and there is indication that some of the feedback loops that operate in tissues continue to be functional in tumors. Mathematical models of such tissue hierarchies, including feedback loops, have been analyzed in a variety of different contexts. Apart from stem cells giving rise to differentiated cells, it has also been observed that more differentiated cells can de-differentiate into stem cells, both in healthy tissue and tumors, aspects of which have also been investigated mathematically. This paper analyses the effect of de-differentiation on the basic and evolutionary dynamics of cells in the context of tissue hierarchy models that include negative feedback regulation of the cell populations. The models predict that in the presence of de-differentiation, the fixation probability of a neutral mutant is lower than in its absence. Therefore, if de-differentiation occurs, a mutant with identical parameters compared to the wild-type cell population behaves like a disadvantageous mutant. Similarly, the process of de-differentiation is found to lower the fixation probability of an advantageous mutant. These results indicate that the presence of de-differentiation can lower the rates of tumor initiation and progression in the context of the models considered here.

Emerging functional markers for cancer stem cell-based therapies: Understanding signaling networks for targeting metastasis

Metastasis is one of the most challenging issues in cancer patient management, and effective therapies to specifically target disease progression are missing, emphasizing the urgent need for developing novel anti-metastatic therapeutics. Cancer stem cells (CSCs) gained fast attention as a minor population of highly malignant cells within liquid and solid tumors that are responsible for tumor onset, self-renewal, resistance to radio- and chemotherapies, and evasion of immune surveillance accelerating recurrence and metastasis. Recent progress in the identification of their phenotypic and molecular characteristics and interactions with the tumor microenvironment provides great potential for the development of CSC-based targeted therapies and radical improvement in metastasis prevention and cancer patient prognosis. Here, we report on newly uncovered signaling mechanisms controlling CSC's aggressiveness and treatment resistance, and CSC-specific agents and molecular therapeutics, some of which are currently under investigation in clinical trials, gearing towards decisive functional CSC intrinsic or surface markers. One special research focus rests upon subverted regulatory pathways such as insulin-like growth factor 1 receptor signaling and its interactors in metastasis-initiating cell populations directly related to the gain of stem cell- and EMT-associated properties, as well as key components of the E2F transcription factor network regulating metastatic progression, microenvironmental changes, and chemoresistance. In addition, the study provides insight into systems biology tools to establish complex molecular relationships behind the emergence of aggressive phenotypes from high-throughput data that rely on network-based analysis and their use to investigate immune escape mechanisms or predict clinical outcome-relevant CSC receptor signaling signatures. We further propose that customized vector technologies could drastically enhance systemic drug delivery to target sites, and summarize recent progress and remaining challenges. This review integrates available knowledge on CSC biology, computational modeling approaches, molecular targeting strategies, and delivery techniques to envision future clinical therapies designed to conquer metastasis-initiating cells.

Role of the Interplay Between the Internal and External Conditions in Invasive Behavior of Tumors

Tumor growth, which plays a central role in cancer evolution, depends on both the internal features of the cells, such as their ability for unlimited duplication, and the external conditions, e.g., supply of nutrients, as well as the dynamic interactions between the two. A stem cell theory of cancer has recently been developed that suggests the existence of a subpopulation of self-renewing tumor cells to be responsible for tumorigenesis, and is able to initiate metastatic spreading. The question of abundance of the cancer stem cells (CSCs) and its relation to tumor malignancy has, however, remained an unsolved problem and has been a subject of recent debates. In this paper we propose a novel model beyond the standard stochastic models of tumor development, in order to explore the effect of the density of the CSCs and oxygen on the tumor's invasive behavior. The model identifies natural selection as the underlying process for complex morphology of tumors, which has been observed experimentally, and indicates that their invasive behavior depends on both the number of the CSCs and the oxygen density in the microenvironment. The interplay between the external and internal conditions may pave the way for a new cancer therapy.

The different pathogeneses of sporadic adenoma and adenocarcinoma in non-ampullary lesions of the proximal and distal duodenum

Non-ampullary duodenal adenoma with activation of Wnt/β-catenin signalling is common in familial adenomatous polyposis (FAP) patients, whereas sporadic non-ampullary adenoma is uncommon. The adenoma-carcinoma sequence similar to colon cancer is associated with duodenal tumors in FAP, but not always in sporadic tumors. We obtained 37 non-ampullary duodenal tumors, including 25 adenomas and 12 adenocarcinomas, were obtained from biopsies and endoscopic resections. We performed immunohistochemistry for β-catenin, the hallmark of Wnt activation, and aldehyde dehydrogenase 1 (ALDH1), a putative cancer stem cell marker. In non-ampullary lesions, abnormal nuclear localization of β-catenin was observed in 21 (84.0%) of 25 adenomas and 4 (33.3%) of 12 adenocarcinomas. In the proximal duodenum, nuclear β-catenin was less frequent in both adenomas and adenocarcinomas. Gastric duodenal metaplasia (GDM) was observed only in the proximal duodenum. All adenomas with GDM were the gastric foveolar and pyloric gland types, and showed only membranous β-catenin. The intestinal-type adenomas had nuclear β-catenin in the proximal and distal duodenum. ALDH1-positive cells were more frequent in adenocarcinomas than adenomas. Nuclear β-catenin accumulation frequently occurred in ALDH1-positive cells in adenoma, but not in adenocarcinoma. In the non-ampullary proximal duodenum, Wnt/β-catenin pathway activation was more closely associated with adenomas than adenocarcinomas, and while it might cooperate with ALDH1 in adenoma, it does not in adenocarcinoma. The pathogenesis thus may differ between sporadic adenoma and adenocarcinoma of non-ampullary duodenal lesions, especially in the proximal and distal duodenum.

Modeling the dynamics of oligodendrocyte precursor cells and the genesis of gliomas

Oligodendrocyte precursor cells (OPCs) have remarkable properties: they represent the most abundant cycling cell population in the adult normal brain and they manage to achieve a uniform and constant density throughout the adult brain. This equilibrium is obtained by the interplay of four processes: division, differentiation or death, migration and active self-repulsion. They are also strongly suspected to be at the origin of gliomas, when their equilibrium is disrupted. In this article, we present a model of the dynamics of OPCs, first in a normal tissue. This model is based on a cellular automaton and its rules are mimicking the ones that regulate the dynamics of real OPCs. The model is able to reproduce the homeostasis of the cell population, with the maintenance of a constant and uniform cell density and the healing of a lesion. We show that there exists a fair quantitative agreement between the simulated and experimental parameters, such as the cell velocity, the time taken to close a lesion, and the duration of the cell cycle. We present three possible scenarios of disruption of the equilibrium: the appearance of an over-proliferating cell, of a deadless/non-differentiating cell, or of a cell that lost any contact-inhibition. We show that the appearance of an over-proliferating cell is sufficient to trigger the growth of a tumor that has low-grade glioma features: an invasive behaviour, a linear radial growth of the tumor with a corresponding growth velocity of less than 2 mm per year, as well a cell density at the center which exceeds the one in normal tissue by a factor of less than two. The loss of contact inhibition leads to a more high-grade-like glioma. The results of our model contribute to the body of evidence that identify OPCs as possible cells of origin of gliomas.

Gliomas are the most common brain tumors and result in more years of life lost than any other tumor. Standard treatments only confer a limited improvement in overall survival, underscoring the need for new therapies. Finding the type of cells at the origin of these tumors could lead to the development of new drugs, specifically targeted towards these cells. The oligodendrocyte precursor cells are suspected to be these cells of origin, because they continue to proliferate through all the adult life. In this article, we present a model of the dynamics of these cells, first in the normal brain, and then we extrapolate our model to the pathological situation. We study several scenarios where, from the normal situation, a cell appears with one property different from those of the normal cells. We show that the alteration of only one of the properties of these cells in the model can lead to the formation of gliomas with different aggressiveness and very similar to real gliomas, reinforcing the suspicion that the precursor cells are at the origin of gliomas.

Biological noise and positional effects influence cell stemness

Biological (or cellular) noise is the random quantitative variability of proteins and other molecules in individual, genetically identical cells. As the result of biological noise in the levels of some transcription factors that determine a cell's differentiation status, differentiated cells may dedifferentiate to a stem cell state given a sufficiently long time period. Here, to provide direct evidence supporting this hypothesis, we used a live-cell monitoring system based on enhanced green fluorescent protein (eGFP) expression to continuously assess the "stemness" of individual human and murine malignant mesothelioma cells over a period of up to 3 months. Re-expression of the transcription factors, the top hierarchical stemness markers Sox2 (SRY-box 2) and Oct4 (octamer-binding transcription factor), monitored as cell eGFP expression was observed in a subpopulation of differentiated eGFP(-) malignant mesothelioma cells. However, we found that this transition was extremely rare. Of note, when it did occur, neighboring cells that were not direct descendants of a newly emerged eGFP(+) stem cell were more likely than non-neighboring cells to also become an eGFP(+) stem cell. This observation suggested a positional effect and led to a clustered "mosaic" reappearance of eGFP(+) stem cells. Moreover, stem cells reappeared even in cell cultures derived from one single differentiated eGFP(-) cell. On the basis of our experimental in vitro and in vivo findings, we developed a tumor growth model to predict the clustered localization of cancer stem cells within a tumor mass.

Synergy of Dendritic Cell Vaccines and Avasimibe in Treatment of Head and Neck Cancer in Mice

BACKGROUND The main purpose of this study was to explore the antitumor effect and mechanisms of ACAT1 inhibitor combined with CSCs-DC vaccine. MATERIAL AND METHODS We isolated HNSCC CSCs and gained CSCs antigens, then used CSCs antigens to load dendritic cells (DC) and generated a CSCs-DC vaccine. We treated mice after surgical excision of established SCC7 tumors with CSCs-DC vaccine and/or ACAT1 inhibitor, and recorded local tumor relapse and host survival. T cells and B cells were harvested from mice treated with CSCs-DC vaccine and/or ACAT1 inhibitor. We tested antibody production and the death rate of CSCs killed by T cells. RESULTS The tumors in the combined treatment group were smaller than in all other groups (P<0.01). The average survival time of the combined treatment group was 82 days and was the longest of all groups. Analysis of IgG levels secreted by B cell and CTL activity in spleens of mice found that results of the combined treatment group were the highest, and the results of the CSCs-DC group were lower than in the combined treatment group. The ACAT1 inhibitor group results were lower than in the CSCs-DC group and the combined treatment group results, but higher than in the PBS group, and the difference was statistically significant. CONCLUSIONS ACAT1 inhibitor enhanced the therapeutic effect of CSCs-DC vaccine in the treatment of the mouse HNSCC postoperative recurrence model. ACAT1 may play an important role in cancer immunotherapy.

Simulation framework for generating intratumor heterogeneity patterns in a cancer cell population

As cancer cell populations evolve, they accumulate a number of somatic mutations, resulting in heterogeneous subclones in the final tumor. Understanding the mechanisms that produce intratumor heterogeneity is important for selecting the best treatment. Although some studies have involved intratumor heterogeneity simulations, their model settings differed substantially. Thus, only limited conditions were explored in each. Herein, we developed a general framework for simulating intratumor heterogeneity patterns and a simulator (tumopp). Tumopp offers many setting options so that simulations can be carried out under various settings. Setting options include how the cell division rate is determined, how daughter cells are placed, and how driver mutations are treated. Furthermore, to account for the cell cycle, we introduced a gamma function for the waiting time involved in cell division. Tumopp also allows simulations in a hexagonal lattice, in addition to a regular lattice that has been used in previous simulation studies. A hexagonal lattice produces a more biologically reasonable space than a regular lattice. Using tumopp, we investigated how model settings affect the growth curve and intratumor heterogeneity pattern. It was found that, even under neutrality (with no driver mutations), tumopp produced dramatically variable patterns of intratumor heterogeneity and tumor morphology, from tumors in which cells with different genetic background are well intermixed to irregular shapes of tumors with a cluster of closely related cells. This result suggests a caveat in analyzing intratumor heterogeneity with simulations with limited settings, and tumopp will be useful to explore intratumor heterogeneity patterns in various conditions.

Immune modulation by a cellular network of mesenchymal stem cells and breast cancer cell subsets: Implication for cancer therapy

The immune modulatory properties of mesenchymal stem cells (MSCs) are mostly controlled by the particular microenvironment. Cancer stem cells (CSCs), which can initiate a clinical tumor, have been the subject of intense research. This review article discusses investigative studies of the roles of MSCs on cancer biology including on CSCs, and the potential as drug delivery to tumors. An understanding of how MSCs behave in the tumor microenvironment to facilitate the survival of tumor cells would be crucial to identify drug targets. More importantly, since CSCs survive for decades in dormancy for later resurgence, studies are presented to show how MSCs could be involved in maintaining dormancy. Although the mechanism by which CSCs survive is complex, this article focus on the cellular involvement of MSCs with regard to immune responses. We discuss the immunomodulatory mechanisms of MSC-CSC interaction in the context of therapeutic outcomes in oncology. We also discuss immunotherapy as a potential to circumventing this immune modulation.

Photobiomodulation of breast and cervical cancer stem cells using low-intensity laser irradiation

Breast and cervical cancers are dangerous threats with regard to the health of women. The two malignancies have reached the highest record in terms of cancer-related deaths among women worldwide. Despite the use of novel strategies with the aim to treat and cure advanced stages of cancer, post-therapeutic relapse believed to be caused by cancer stem cells is one of the challenges encountered during tumor therapy. Therefore, further attention should be paid to cancer stem cells when developing novel anti-tumor therapeutic approaches. Low-intensity laser irradiation is a form of phototherapy making use of visible light in the wavelength range of 630-905 nm. Low-intensity laser irradiation has shown remarkable results in a wide range of medical applications due to its biphasic dose and wavelength effect at a cellular level. Overall, this article focuses on the cellular responses of healthy and cancer cells after treatment with low-intensity laser irradiation alone or in combination with a photosensitizer as photodynamic therapy and the influence that various wavelengths and fluencies could have on the therapeutic outcome. Attention will be paid to the biomodulative effect of low-intensity laser irradiation on cancer stem cells.

The Impact of the Tumor Microenvironment on the Properties of Glioma Stem-Like Cells

Glioblastoma is the most common and highly malignant primary brain tumor, and patients affected with this disease exhibit a uniformly dismal prognosis. Glioma stem-like cells (GSCs) are a subset of cells within the bulk tumor that possess self-renewal and multi-lineage differentiation properties similar to somatic stem cells. These cells also are at the apex of the cellular hierarchy and cause tumor initiation and expansion after chemo-radiation. These traits make them an attractive target for therapeutic development. Because GSCs are dependent on the brain microenvironment for their growth, and because non-tumorigenic cell types in the microenvironment can influence GSC phenotypes and treatment response, a better understanding of these cell types is needed. In this review, we provide a focused overview of the contributions from the microenvironment to GSC homing, maintenance, phenotypic plasticity, and tumor initiation. The interaction of GSCs with the vascular compartment, mesenchymal stem cells, immune system, and normal brain cell types are discussed. Studies that provide mechanistic insight into each of these GSC–microenvironment interactions are warranted in the future.

Environmental factors in breast cancer invasion: a mathematical modelling review

This review presents a brief overview of breast cancer, focussing on its heterogeneity and the role of mathematical modelling and simulation in teasing apart the underlying biophysical processes. Following a brief overview of the main known pathophysiological features of ductal carcinoma, attention is paid to differential equation-based models (both deterministic and stochastic), agent-based modelling, multi-scale modelling, lattice-based models and image-driven modelling. A number of vignettes are presented where these modelling approaches have elucidated novel aspects of breast cancer dynamics, and we conclude by offering some perspectives on the role mathematical modelling can play in understanding breast cancer development, invasion and treatment therapies.

Stochasticity in the Genotype-Phenotype Map: Implications for the Robustness and Persistence of Bet-Hedging

Nongenetic variation in phenotypes, or bet-hedging, has been observed as a driver of drug resistance in both bacterial infections and cancers. Here, we study how bet-hedging emerges in genotype-phenotype (GP) mapping through a simple interaction model: a molecular switch. We use simple chemical reaction networks to implement stochastic switches that map gene products to phenotypes, and investigate the impact of structurally distinct mappings on the evolution of phenotypic heterogeneity. Bet-hedging naturally emerges within this model, and is robust to evolutionary loss through mutations to both the expression of individual genes, and to the network itself. This robustness explains an apparent paradox of bet-hedging-why does it persist in environments where natural selection necessarily acts to remove it? The structure of the underlying molecular mechanism, itself subject to selection, can slow the evolutionary loss of bet-hedging to ensure a survival mechanism against environmental catastrophes even when they are rare. Critically, these properties, taken together, have profound implications for the use of treatment-holidays to combat bet-hedging-driven resistant disease, as the efficacy of breaks from treatment will ultimately be determined by the structure of the GP mapping.

Cancer stem cells: understanding tumor hierarchy and heterogeneity

Heterogeneity within and between tumors is a well-known phenomenon that greatly complicates the diagnosis and treatment of cancer. A large body of research indicates that heterogeneity develops through time as tumor-initiating stem cells, also known as cancer stem cells (CSCs), evolve genetic or epigenetic alterations that allow them to differentiate into multiple tumor cell types. Similar to normal stem cells, CSCs can self-renew and possess long-term repopulation potential. However, unlike normal stem cells, CSCs are not subject to the usual controls that limit growth. Different models have been postulated to explain the heterogeneity of tumors, but it is widely agreed that interactions between tumor cells and their microenvironment create niches that promote CSC properties and enable their survival. Within the microenvironment, CSC self-renewal, replication, and differentiation are postulated to produce a hierarchy of cells constituting the tumor mass. Increased understanding of the factors that create and contribute to tumor heterogeneity may support the design of therapies that affect CSC function and their microenvironments.

Modeling head and neck cancer stem cell-mediated tumorigenesis

A large body of literature has emerged supporting the importance of cancer stem cells (CSCs) in the pathogenesis of head and neck cancers. CSCs are a subpopulation of cells within a tumor that share the properties of self-renewal and multipotency with stem cells from normal tissue. Their functional relevance to the pathobiology of cancer arises from the unique properties of tumorigenicity, chemotherapy resistance, and their ability to metastasize and invade distant tissues. Several molecular profiles have been used to discriminate a stem cell from a non-stem cell. CSCs can be grown for study and further enriched using a number of in vitro techniques. An evolving option for translational research is the use of mathematical and computational models to describe the role of CSCs in complex tumor environments. This review is focused discussing the evidence emerging from modeling approaches that have clarified the impact of CSCs to the biology of cancer.

The tumor as an organ: comprehensive spatial and temporal modeling of the tumor and its microenvironment

BACKGROUND

Research related to cancer is vast, and continues in earnest in many directions. Due to the complexity of cancer, a better understanding of tumor growth dynamics can be gleaned from a dynamic computational model. We present a comprehensive, fully executable, spatial and temporal 3D computational model of the development of a cancerous tumor together with its environment.

RESULTS

The model was created using Statecharts, which were then connected to an interactive animation front-end that we developed especially for this work, making it possible to visualize on the fly the on-going events of the system's execution, as well as the effect of various input parameters. We were thus able to gain a better understanding of, e.g., how different amounts or thresholds of oxygen and VEGF (vascular endothelial growth factor) affect the progression of the tumor. We found that the tumor has a critical turning point, where it either dies or recovers. If minimum conditions are met at that time, it eventually develops into a full, active, growing tumor, regardless of the actual amount; otherwise it dies.

CONCLUSIONS

This brings us to the conclusion that the tumor is in fact a very robust system: changing initial values of VEGF and oxygen can increase the time it takes to become fully developed, but will not necessarily completely eliminate it.

Therapeutic Efficacy of Cancer Stem Cell Vaccines in the Adjuvant Setting

Dendritic cell (DC)-based vaccine strategies aimed at targeting cancer stem-like cells (CSC) may be most efficacious if deployed in the adjuvant setting. In this study, we offer preclinical evidence that this is the case for a CSC-DC vaccine as tested in murine models of SCC7 squamous cell cancer and D5 melanoma. Vaccination of mice with an ALDH(high) SCC7 CSC-DC vaccine after surgical excision of established SCC7 tumors reduced local tumor relapse and prolonged host survival. This effect was augmented significantly by simultaneous administration of anti-PD-L1, an immune checkpoint inhibitor. In the minimal disease setting of D5 melanoma, treatment of mice with ALDH(high) CSC-DC vaccination inhibited primary tumor growth, reduced spontaneous lung metastases, and increased host survival. In this setting, CCR10 and its ligands were downregulated on ALDH(high) D5 CSCs and in lung tissues, respectively, after vaccination with ALDH(high) D5 CSC-DC. RNAi-mediated attenuation of CCR10 blocked tumor cell migration in vitro and metastasis in vivo T cells harvested from mice vaccinated with ALDH(high) D5 CSC-DC selectively killed ALDH(high) D5 CSCs, with additional evidence of humoral immunologic engagement and a reduction in ALDH(high) cells in residual tumors. Overall, our results offered a preclinical proof of concept for the use of ALDH(high) CSC-DC vaccines in the adjuvant setting to more effectively limit local tumor recurrence and spontaneous pulmonary metastasis, as compared with traditional DC vaccines, with increased host survival further accentuated by simultaneous PD-L1 blockade. Cancer Res; 76(16); 4661-72. ©2016 AACR.

Cancer Stem Cell Plasticity as Tumor Growth Promoter and Catalyst of Population Collapse

It is increasingly argued that cancer stem cells are not a cellular phenotype but rather a transient state that cells can acquire, either through intrinsic signaling cascades or in response to environmental cues. While cancer stem cell plasticity is generally associated with increased aggressiveness and treatment resistance, we set out to thoroughly investigate the impact of different rates of plasticity on early and late tumor growth dynamics and the response to therapy. We develop an agent-based model of cancer stem cell driven tumor growth, in which plasticity is defined as a spontaneous transition between stem and nonstem cancer cell states. Simulations of the model show that plasticity can substantially increase tumor growth rate and invasion. At high rates of plasticity, however, the cells get exhausted and the tumor will undergo spontaneous remission in the long term. In a series of in silico trials, we show that such remission can be facilitated through radiotherapy. The presented study suggests that stem cell plasticity has rather complex, nonintuitive implications on tumor growth and treatment response. Further theoretical, experimental, and integrated studies are needed to fully decipher cancer stem cell plasticity and how it can be harnessed for novel therapeutic approaches.

An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location

It is very important to understand the onset and growth pattern of breast primary tumours as well as their metastatic dissemination. In most cases, it is the metastatic disease that ultimately kills the patient. There is increasing evidence that cancer stem cells are closely linked to the progression of the metastatic tumour. Here, we investigate stem cell seeding to an avascular tumour site using an agent-based stochastic model of breast cancer metastatic seeding. The model includes several important cellular features such as stem cell symmetric and asymmetric division, migration, cellular quiescence, senescence, apoptosis and cell division cycles. It also includes external features such as stem cell seeding frequency and location. Using this model, we find that cell seeding rate and location are important features for tumour growth. We also define conditions in which the tumour growth exhibits decremented and exponential growth patterns. Overall, we find that seeding, senescence and division limit affect not only the number of stem cells, but also their spatial and temporal distribution.

Incorporating cancer stem cells in radiation therapy treatment response modeling and the implication in glioblastoma multiforme treatment resistance

PURPOSE

To perform a preliminary exploration with a simplistic mathematical cancer stem cell (CSC) interaction model to determine whether the tumor-intrinsic heterogeneity and dynamic equilibrium between CSCs and differentiated cancer cells (DCCs) can better explain radiation therapy treatment response with a dual-compartment linear-quadratic (DLQ) model.

METHODS AND MATERIALS

The radiosensitivity parameters of CSCs and DCCs for cancer cell lines including glioblastoma multiforme (GBM), non-small cell lung cancer, melanoma, osteosarcoma, and prostate, cervical, and breast cancer were determined by performing robust least-square fitting using the DLQ model on published clonogenic survival data. Fitting performance was compared with the single-compartment LQ (SLQ) and universal survival curve models. The fitting results were then used in an ordinary differential equation describing the kinetics of DCCs and CSCs in response to 2- to 14.3-Gy fractionated treatments. The total dose to achieve tumor control and the fraction size that achieved the least normal biological equivalent dose were calculated.

RESULTS

Smaller cell survival fitting errors were observed using DLQ, with the exception of melanoma, which had a low α/β = 0.16 in SLQ. Ordinary differential equation simulation indicated lower normal tissue biological equivalent dose to achieve the same tumor control with a hypofractionated approach for 4 cell lines for the DLQ model, in contrast to SLQ, which favored 2 Gy per fraction for all cells except melanoma. The DLQ model indicated greater tumor radioresistance than SLQ, but the radioresistance was overcome by hypofractionation, other than the GBM cells, which responded poorly to all fractionations.

CONCLUSION

The distinct radiosensitivity and dynamics between CSCs and DCCs in radiation therapy response could perhaps be one possible explanation for the heterogeneous intertumor response to hypofractionation and in some cases superior outcome from stereotactic ablative radiation therapy. The DLQ model also predicted the remarkable GBM radioresistance, a result that is highly consistent with clinical observations. The radioresistance putatively stemmed from accelerated DCC regrowth that rapidly restored compartmental equilibrium between CSCs and DCCs.

Evolution and phenotypic selection of cancer stem cells

Cells of different organs at different ages have an intrinsic set of kinetics that dictates their behavior. Transformation into cancer cells will inherit these kinetics that determine initial cell and tumor population progression dynamics. Subject to genetic mutation and epigenetic alterations, cancer cell kinetics can change, and favorable alterations that increase cellular fitness will manifest themselves and accelerate tumor progression. We set out to investigate the emerging intratumoral heterogeneity and to determine the evolutionary trajectories of the combination of cell-intrinsic kinetics that yield aggressive tumor growth. We develop a cellular automaton model that tracks the temporal evolution of the malignant subpopulation of so-called cancer stem cells(CSC), as these cells are exclusively able to initiate and sustain tumors. We explore orthogonal cell traits, including cell migration to facilitate invasion, spontaneous cell death due to genetic drift after accumulation of irreversible deleterious mutations, symmetric cancer stem cell division that increases the cancer stem cell pool, and telomere length and erosion as a mitotic counter for inherited non-stem cancer cell proliferation potential. Our study suggests that cell proliferation potential is the strongest modulator of tumor growth. Early increase in proliferation potential yields larger populations of non-stem cancer cells(CC) that compete with CSC and thus inhibit CSC division while a reduction in proliferation potential loosens such inhibition and facilitates frequent CSC division. The sub-population of cancer stem cells in itself becomes highly heterogeneous dictating population level dynamics that vary from long-term dormancy to aggressive progression. Our study suggests that the clonal diversity that is captured in single tumor biopsy samples represents only a small proportion of the total number of phenotypes.

We present an in silico computational model of tumor growth and evolution according to the cancer stem cell hypothesis. Inheritable traits of cells may be genetically or epigenetically altered, and traits that confer increased fitness to the cell will be selected for on the population level. Phenotypic evolution yields aggressive tumors with large heterogeneity, prompting the notion that the cancer stem cell population per se is highly heterogeneous. Within aggressive tumors cancer stem cells with low tumorigenic potential may be isolated. Simulations of our model suggest that the cells harvested in core needle biopsies represent less than 10% of the phenotypic heterogeneity of the total tumor population. Dependent on the cells captured in the sample, xenografted tumors may exhibit aggressive growth or long-term dormancy—dynamics that may suggest opposing treatment approaches for the same tumor when translated into clinical decision-making.

Numerical resolution of a model of tumour growth

We consider and solve numerically a mathematical model of tumour growth based on cancer stem cells (CSC) hypothesis with the aim of gaining some insight into the relation of different processes leading to exponential growth in solid tumours and into the evolution of different subpopulations of cells. The model consists of four hyperbolic equations of first order to describe the evolution of four subpopulations of cells. A fifth equation is introduced to model the evolution of the moving boundary. The coefficients of the model represent the rates at which reactions occur. In order to integrate numerically the four hyperbolic equations, a formulation in terms of the total derivatives is posed. A finite element discretization is applied to integrate the model equations in space. Our numerical results suggest the existence of a pseudo-equilibrium state reached at the early stage of the tumour, for which the fraction of CSC remains small. We include the study of the behaviour of the solutions for longer times and we obtain that the solutions to the system of partial differential equations stabilize to homogeneous steady states whose values depend only on the values of the parameters. We show that CSC may comprise different proportions of the tumour, becoming, in some cases, the predominant type of cells within the tumour. We also obtain that possible effective measure to detain tumour progression should combine the targeting of CSC with the targeting of progenitor cells.

Cancer stem cell vaccine inhibits metastases of primary tumors and induces humoral immune responses against cancer stem cells

The inability to target cancer stem cells (CSC) may be a significant factor contributing to treatment failure. We have developed a strategy to target the CSC populations in melanoma and squamous cell carcinoma using CSC lysate-pulsed dendritic cells (DCs). The CSC-DC vaccine was administered in the adjuvant setting after localized radiation therapy of established tumors. Using mouse models we demonstrated that DCs pulsed with CSCs enriched by virtue of their expression of the CSC marker ALDH (termed CSC-DC) significantly inhibited tumor growth, reduced development of pulmonary metastases and prolonged survival. The effect was associated with downregulation of chemokine (C-C motif) receptors CCR7 and CCR10 in tumor cells and decreased expression of the chemokine (C-C motif) ligands CCL21, CCL27 and CCL28 in lung tissue. The CSC-DC vaccine significantly reduced ALDH^high CSC frequency in primary tumors. Direct targeting of CSCs was demonstrated by the specific binding of IgG produced by ALDH^high CSC-DC vaccine-primed B cells to ALDH^high CSCs, resulting in lysis of these target CSCs in the presence of complement. These data suggest that the CSC-DC vaccine approach may be useful in the adjuvant setting where local and systemic relapse are high after conventional treatment of cancers.

Biological and clinical significance of cancer stem cell plasticity

In the past decade, the traditional view of cancers as a homogeneous collection of malignant cells is being replaced by a model of ever increasing complexity suggesting that cancers are complex tissues composed of multiple cell types. This complex model of tumorigenesis has been well supported by a growing body of evidence indicating that most cancers including those derived from blood and solid tissues display a hierarchical organization of tumor cells with phenotypic and functional heterogeneity and at the apex of this hierarchy are cells capable of self-renewal. These "tumor imitating cells" or "cancer stem cells" drive tumorigenesis and contribute to metastasis, treatment resistance and tumor relapse. Although tumor stem cells themselves may display both genetic and phenotypic heterogeneity, recent studies have demonstrated that cancer stem cells maintain plasticity to transition between mesenchymal-like (EMT) and epithelial-like (MET) states, which may be regulated by the tumor microenvironment. These stem cell state transitions may play a fundamental role in tumor progression and treatment resistance. In this review, we discuss the emerging knowledge regarding the plasticity of cancer stem cells with an emphasis on the signaling pathways and noncoding RNAs including microRNAs (miRNA) and long non-coding RNAs (lncRNAs) in regulation of this plasticity during tumor growth and metastasis. Lastly, we point out the importance of targeting both the EMT and MET states of CSCs in order to eliminate these lethal seeds of cancers.

A multicompartment mathematical model of cancer stem cell-driven tumor growth dynamics

Tumors are appreciated to be an intrinsically heterogeneous population of cells with varying proliferation capacities and tumorigenic potentials. As a central tenet of the so-called cancer stem cell hypothesis, most cancer cells have only a limited lifespan, and thus cannot initiate or reinitiate tumors. Longevity and clonogenicity are properties unique to the subpopulation of cancer stem cells. To understand the implications of the population structure suggested by this hypothesis--a hierarchy consisting of cancer stem cells and progeny non-stem cancer cells which experience a reduction in their remaining proliferation capacity per division--we set out to develop a mathematical model for the development of the aggregate population. We show that overall tumor progression rate during the exponential growth phase is identical to the growth rate of the cancer stem cell compartment. Tumors with identical stem cell proportions, however, can have different growth rates, dependent on the proliferation kinetics of all participating cell populations. Analysis of the model revealed that the proliferation potential of non-stem cancer cells is likely to be small to reproduce biologic observations. Furthermore, a single compartment of non-stem cancer cell population may adequately represent population growth dynamics only when the compartment proliferation rate is scaled with the generational hierarchy depth.

Conversion of differentiated cancer cells into cancer stem-like cells in a glioblastoma model after primary chemotherapy

Glioblastoma multiforme patients have a poor prognosis due to therapeutic resistance and tumor relapse. It has been suggested that gliomas are driven by a rare subset of tumor cells known as glioma stem cells (GSCs). This hypothesis states that only a few GSCs are able to divide, differentiate, and initiate a new tumor. It has also been shown that this subpopulation is more resistant to conventional therapies than its differentiated counterpart. In order to understand glioma recurrence post therapy, we investigated the behavior of GSCs after primary chemotherapy. We first show that exposure of patient-derived as well as established glioma cell lines to therapeutic doses of temozolomide (TMZ), the most commonly used antiglioma chemotherapy, consistently increases the GSC pool over time both in vitro and in vivo. Secondly, lineage-tracing analysis of the expanded GSC pool suggests that such amplification is a result of a phenotypic shift in the non-GSC population to a GSC-like state in the presence of TMZ. The newly converted GSC population expresses markers associated with pluripotency and stemness, such as CD133, SOX2, Oct4, and Nestin. Furthermore, we show that intracranial implantation of the newly converted GSCs in nude mice results in a more efficient grafting and invasive phenotype. Taken together, these findings provide the first evidence that glioma cells exposed to chemotherapeutic agents are able to interconvert between non-GSCs and GSCs, thereby replenishing the original tumor population, leading to a more infiltrative phenotype and enhanced chemoresistance. This may represent a potential mechanism for therapeutic relapse.

Estimating dose painting effects in radiotherapy: a mathematical model

Tumor heterogeneity is widely considered to be a determinant factor in tumor progression and in particular in its recurrence after therapy. Unfortunately, current medical techniques are unable to deduce clinically relevant information about tumor heterogeneity by means of non-invasive methods. As a consequence, when radiotherapy is used as a treatment of choice, radiation dosimetries are prescribed under the assumption that the malignancy targeted is of a homogeneous nature. In this work we discuss the effects of different radiation dose distributions on heterogeneous tumors by means of an individual cell-based model. To that end, a case is considered where two tumor cell phenotypes are present, which we assume to strongly differ in their respective cell cycle duration and radiosensitivity properties. We show herein that, as a result of such differences, the spatial distribution of the corresponding phenotypes, whence the resulting tumor heterogeneity can be predicted as growth proceeds. In particular, we show that if we start from a situation where a majority of ordinary cancer cells (CCs) and a minority of cancer stem cells (CSCs) are randomly distributed, and we assume that the length of CSC cycle is significantly longer than that of CCs, then CSCs become concentrated at an inner region as tumor grows. As a consequence we obtain that if CSCs are assumed to be more resistant to radiation than CCs, heterogeneous dosimetries can be selected to enhance tumor control by boosting radiation in the region occupied by the more radioresistant tumor cell phenotype. It is also shown that, when compared with homogeneous dose distributions as those being currently delivered in clinical practice, such heterogeneous radiation dosimetries fare always better than their homogeneous counterparts. Finally, limitations to our assumptions and their resulting clinical implications will be discussed.

Cancer Systems Biology: a peek into the future of patient care?

Traditionally, scientific research has focused on studying individual events, such as single mutations, gene function, or the effect that mutating one protein has on a biological phenotype. A range of technologies is beginning to provide information that will enable a holistic view of how genomic and epigenetic aberrations in cancer cells can alter the homeostasis of signalling networks within these cells, between cancer cells and the local microenvironment, and at the organ and organism level. This process, termed Systems Biology, needs to be integrated with an iterative approach wherein hypotheses and predictions that arise from modelling are refined and constrained by experimental evaluation. Systems biology approaches will be vital for developing and implementing effective strategies to deliver personalized cancer therapy. Specifically, these approaches will be important to select those patients who are most likely to benefit from targeted therapies and for the development and implementation of rational combinatorial therapies. Systems biology can help to increase therapy efficacy or bypass the emergence of resistance, thus converting the current-often short term-effects of targeted therapies into durable responses, ultimately to improve patient quality of life and provide a cure.

Dynamics between cancer cell subpopulations reveals a model coordinating with both hierarchical and stochastic concepts

Tumors are often heterogeneous in which tumor cells of different phenotypes have distinct properties. For scientific and clinical interests, it is of fundamental importance to understand their properties and the dynamic variations among different phenotypes, specifically under radio- and/or chemo-therapy. Currently there are two controversial models describing tumor heterogeneity, the cancer stem cell (CSC) model and the stochastic model. To clarify the controversy, we measured probabilities of different division types and transitions of cells via in situ immunofluorescence. Based on the experiment data, we constructed a model that combines the CSC with the stochastic concepts, showing the existence of both distinctive CSC subpopulations and the stochastic transitions from NSCCs to CSCs. The results showed that the dynamic variations between CSCs and non-stem cancer cells (NSCCs) can be simulated with the model. Further studies also showed that the model can be used to describe the dynamics of the two subpopulations after radiation treatment. More importantly, analysis demonstrated that the experimental detectable equilibrium CSC proportion can be achieved only when the stochastic transitions from NSCCs to CSCs occur, indicating that tumor heterogeneity may exist in a model coordinating with both the CSC and the stochastic concepts. The mathematic model based on experimental parameters may contribute to a better understanding of the tumor heterogeneity, and provide references on the dynamics of CSC subpopulation during radiotherapy.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner.

Knockdown of Bmi1 inhibits the stemness properties and tumorigenicity of human bladder cancer stem cell-like side population cells

B-cell-specific Moloney murine leukemia virus insertion site 1 (Bmi1) is directly involved in cell growth, proliferation and self-renewal of cancer stem cells (CSCs). The aim of the present study was to assess the role of Bmi1 in the maintenance of stemness properties and tumorigenicity of human bladder CSC-like side population (SP) cells. SP cells were sorted by flow cytometry using Hoechst 33342 staining. Bmi1 mRNA and protein expression in SP and non-SP (NSP) cells was analyzed by quantitative PCR, immunofluorescence and western blotting. The stemness properties of SP cells included cell proliferation, migration, self-renewal, chemotherapy resistance and cell cycle progression were assessed. Tumor formation was also assessed in human bladder cancer xenografts after Bmi1 silencing. The mRNA expression of Bmi1 was upregulated in SP cells when compared with that in the NSP cells. Knockdown of Bmi1 in SP cells resulted in inhibition of cell proliferation, migration and tumor sphere formation, enhanced sensitivity to cisplatin, and cell cycle arrest in the G0/G1 phase. Bmi1 knockdown inhibited cell cycle progression through derepression of the p16INK4a/p14ARF locus. Bmi1-siRNA SP cells failed to produce tumors in recipient mice, while typical urothelial carcinoma formed from subcutaneously injected scramble-siRNA SP cells. Bmi1 is crucial for the maintenance of stemness properties and tumorigenicity of human bladder CSC-like cells. Bmi1 may be a potential therapeutic target for the eradication of CSCs in bladder cancer.