Effect of dedifferentiation on time to mutation acquisition in stem cell-driven cancers

Transcriptomics of mussel transmissible cancer MtrBTN2 suggests accumulation of multiple cancer traits and oncogenic pathways shared among bilaterians

Transmissible cancer cell lines are rare biological entities giving rise to diseases at the crossroads of cancer and parasitic diseases. These malignant cells have acquired the amazing capacity to spread from host to host. They have been described only in dogs, Tasmanian devils and marine bivalves. The Mytilus trossulus bivalve transmissible neoplasia 2 (MtrBTN2) lineage has even acquired the capacity to spread inter-specifically between marine mussels of the Mytilus edulis complex worldwide. To identify the oncogenic processes underpinning the biology of these atypical cancers we performed transcriptomics of MtrBTN2 cells. Differential expression, enrichment, protein-protein interaction network, and targeted analyses were used. Overall, our results suggest the accumulation of multiple cancerous traits that may be linked to the long-term evolution of MtrBTN2. We also highlight that vertebrate and lophotrochozoan cancers could share a large panel of common drivers, which supports the hypothesis of an ancient origin of oncogenic processes in bilaterians.

On tumoural growth and treatment under cellular dedifferentiation

Differentiated cancer cells may regain stem cell characteristics; however, the effects of such a cellular dedifferentiation on tumoural growth and treatment are currently understudied. Thus, we here extend a mathematical model of cancer stem cell (CSC) driven tumour growth to also include dedifferentiation. We show that dedifferentiation increases the likelihood of tumorigenesis and the speed of tumoural growth, both modulated by the proliferative potential of the non-stem cancer cells (NSCCs). We demonstrate that dedifferentiation also may lead to treatment evasion, especially when a treatment solely targets CSCs. Conversely, targeting both CSCs and NSCCs in parallel is shown to be more robust to dedifferentiation. Despite dedifferentiation, perturbing CSC-related parameters continues to exert the largest relative effect on tumoural growth; however, we show the existence of synergies between specific CSC- and NSCC-directed treatments which cause superadditive reductions of tumoural growth. Overall, our study demonstrates various effects of dedifferentiation on growth and treatment of tumoural lesions, and we anticipate our results to be helpful in guiding future molecular and clinical research on limiting tumoural growth in vivo.

Growth dynamics of breast cancer stem cells: effects of self-feedback and EMT mechanisms

Breast cancer stem cells (BCSCs) with the ability to self-renew and differentiate have been identified in primary breast cancer tissues and cell lines. The BCSCs are often resistant to traditional radiation and/or chemotherapies. Previous studies have also shown that successful therapy must eradicate cancer stem cells. The purpose of this paper is to develop a mathematical model with self-feedback mechanism to illustrate the issues regarding the difficulties of absolutely eliminating a breast cancer. In addition, we introduce the mechanism of the epithelial-mesenchymal transition (EMT) to investigate the influence of EMT on the effects of breast cancer growth and treatment. Results indicate that the EMT mechanism facilitates the growth of breast cancer and makes breast cancer more difficult to be cured. Therefore, targeting the signals involved in EMT can halt tumor progression in breast cancer. Finally, we apply the experimental data to carry out numerical simulations and validate our theoretical conclusions.

Effect of dedifferentiation on noise propagation in cellular hierarchy

Many fast renewing tissues have a hierarchical structure. Tissue-specific stem cells are at the root of this cellular hierarchy, which give rive to a whole range of specialized cells via cellular differentiation. However, increasing evidence shows that the hierarchical structure can be broken due to cellular dedifferentiation in which cells at differentiated stages can revert to the stem cell stage. Dedifferentiation has significant impacts on many aspects of hierarchical tissues. Here we investigate the effect of dedifferentiation on noise propagation by developing a stochastic model composed of different cell types. The moment equations are derived, via which we systematically investigate how the noise in the cell number is changed by dedifferentiation. Our results suggest that dedifferentiation have different effects on the noises in the numbers of stem cells and nonstem cells. Specifically, the noise in the number of stem cells is significantly reduced by increasing dedifferentiation probability. Due to the dual effect of dedifferentiation on nonstem cells, however, more complex changes could happen to the noise in the number of nonstem cells by increasing dedifferentiation probability. Furthermore, it is found that even though dedifferentiation could turn part of the noise propagation process into a noise-amplifying step, it is very unlikely to turn the entire process into a noise-amplifying cascade.

Upregulation of KIF11 in TP53 Mutant Glioma Promotes Tumor Stemness and Drug Resistance

Glioma is the most common type of primary brain malignancy with high morbidity and mortality, but little is known about its pathological mechanisms. Kinesin family member 11 (KIF11) is a key driver of malignancy in glioblastoma, a grade IV glioma, but its involvement in glioma chemoresistance remains to be determined. We accessed the TCGA open datasets, collected glioma tumor tissue samples, and analyzed the expression of KIF11 in glioma patients. Meanwhile, the correlation between KIF11 and survival outcomes was determined by the Kaplan-Meier analysis. The role of KIF11 in glioma tumor cell function was assessed in an in vitro knockdown and overexpressing system. Here, we found that KIF11 was upregulated in glioma tumors and negatively correlated with overall survival outcomes via analyzing the open datasets. KIF11 was negatively correlated with TP53 expression. Furthermore, KIF11 promoted the stemness in glioma cells, accompanied by increased cell proliferation and chemoresistance. Mechanistically, we found that KIF11 promoted cell cycle progression via upregulating cyclin expression.

Functional genomics of AP-2α and AP-2γ in cancers: in silico study

BACKGROUND

Among all causes of death, cancer is the most prevalent and is only outpaced by cardiovascular diseases. Molecular theory of carcinogenesis states that apoptosis and proliferation are regulated by groups of tumor suppressors or oncogenes. Transcription factors are example of proteins comprising representatives of both cancer-related groups. Exemplary family of transcription factors which exhibits dualism of function is Activating enhancer-binding Protein 2 (AP-2). Scientific reports concerning their function in carcinogenesis depend on particular family member and/or tumor type which proves the issue to be unsolved. Therefore, the present study examines role of the best-described AP-2 representatives, AP-2α and AP-2γ, through ontological analysis of their target genes and investigation what processes are differentially regulated in 21 cancers using samples deposited in Genomic Data Analysis Center (GDAC) Firehose.

METHODS

Expression data with clinical annotation was collected from TCGA-dedicated repository GDAC Firehose. Transcription factor targets were obtained from Gene Transcription Regulation Database (GTRD), TRANScription FACtor database (TRANSFAC) and Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST). Monocle3 R package was used for global samples profiling while Protein ANalysis THrough Evolutionary Relationships (PANTHER) tool was used to perform gene ontology analysis.

RESULTS

With RNA-seq data and Monocle3 or PANTHER tools we outlined differences in many processes and signaling pathways, separating tumor from normal tissues or tumors from each other. Unexpectedly, a number of alterations in basal-like breast cancer were identified that distinguished it from other subtypes, which could bring future clinical benefits.

CONCLUSIONS

Our findings indicate that while the AP-2α/γ role remains ambiguous, their activity is based on processes that underlie the cancer hallmarks and their expression could have potential in diagnosis of selected tumors.

RpS13 controls the homeostasis of germline stem cell niche through Rho1-mediated signals in the Drosophila testis

Objectives

Stem cell niche regulated the renewal and differentiation of germline stem cells (GSCs) in Drosophila. Previously, we and others identified a series of genes encoding ribosomal proteins that may contribute to the self‐renewal and differentiation of GSCs. However, the mechanisms that maintain and differentiate GSCs in their niches were not well understood.

Materials and Methods

Flies were used to generate tissue‐specific gene knockdown. Small interfering RNAs were used to knockdown genes in S2 cells. qRT‐PCR was used to examine the relative mRNA expression level. TUNEL staining or flow cytometry assays were used to detect cell survival. Immunofluorescence was used to determine protein localization and expression pattern.

Results

Herein, using a genetic manipulation approach, we investigated the role of ribosomal protein S13 (RpS13) in testes and S2 cells. We reported that RpS13 was required for the self‐renewal and differentiation of GSCs. We also demonstrated that RpS13 regulated cell proliferation and apoptosis. Mechanistically, we showed that RpS13 regulated the expression of ribosome subunits and could moderate the expression of the Rho1, DE‐cad and Arm proteins. Notably, Rho1 imitated the phenotype of RpS13 in both Drosophila testes and S2 cells, and recruited cell adhesions, which was mediated by the DE‐cad and Arm proteins.

Conclusion

These findings uncover a novel mechanism of RpS13 that mediates Rho1 signals in the stem cell niche of the Drosophila testis.

The evolution of metapopulation dynamics and the number of stem cells in intestinal crypts and other tissue structures in multicellular bodies

Carcinogenesis is a process of somatic evolution. Previous models of stem and transient amplifying cells in epithelial proliferating units like colonic crypts showed that intermediate numbers of stem cells in a crypt should optimally prevent progression to cancer. If a stem cell population is too small, it is easy for a mutator mutation to drift to fixation. If it is too large, it is easy for selection to drive cell fitness enhancing carcinogenic mutations to fixation. Here, we show that a multiscale microsimulation, that captures both within-crypt and between-crypt evolutionary dynamics, leads to a different conclusion. Epithelial tissues are metapopulations of crypts. We measured time to initiation of a neoplasm, implemented as inactivation of both alleles of a tumor suppressor gene. In our model, time to initiation is dependent on the spread of mutator clones in the crypts. The proportion of selectively beneficial and deleterious mutations in somatic cells is unknown and so was explored with a parameter. When the majority of non-neutral mutations are deleterious, the fitness of mutator clones tends to decline. When crypts are maintained by few stem cells, intercrypt competition tends to remove crypts with fixed mutators. When there are many stem cells within a crypt, there is virtually no crypt turnover, but mutator clones are suppressed by within-crypt competition. If the majority of non-neutral mutations are beneficial to the clone, then these results are reversed and intermediate-sized crypts provide the most protection against initiation. These results highlight the need to understand the dynamics of turnover and the mechanisms that control homeostasis, both at the level of stem cells within proliferative units and at the tissue level of competing proliferative units. Determining the distribution of fitness effects of somatic mutations will also be crucial to understanding the dynamics of tumor initiation and progression.

The effects of phenotypic plasticity on the fixation probability of mutant cancer stem cells

The cancer stem cell hypothesis claims that tumor growth and progression are driven by a (typically) small niche of the total cancer cell population called cancer stem cells (CSCs). These CSCs can go through symmetric or asymmetric divisions to differentiate into specialised, progenitor cells or reproduce new CSCs. While it was once held that this differentiation pathway was unidirectional, recent research has demonstrated that differentiated cells are more plastic than initially considered. In particular, differentiated cells can de-differentiate and recover their stem-like capacity. Two recent papers have considered how this rate of plasticity affects the evolutionary dynamic of an invasive, malignant population of stem cells and differentiated cells into existing tissue (Mahdipour-Shirayeh et al., 2017; Wodarz, 2018). These papers arrive at seemingly opposing conclusions, one claiming that increased plasticity results in increased invasive potential, and the other that increased plasticity decreases invasive potential. Here, we show that what is most important, when determining the effect on invasive potential, is how one distributes this increased plasticity between the compartments of resident and mutant-type cells. We also demonstrate how these results vary, producing non-monotone fixation probability curves, as inter-compartmental plasticity changes when differentiated cell compartments are allowed to continue proliferating, highlighting a fundamental difference between the two models. We conclude by demonstrating the stability of these qualitative results over various parameter ranges. Keywords: cancer stem cells, plasticity, de-differentiation, fixation probability.

A Mathematical Model of the Transition from Normal Hematopoiesis to the Chronic and Accelerated-Acute Stages in Myeloid Leukemia

A mathematical model given by a two-dimensional differential system is introduced in order to understand the transition process from the normal hematopoiesis to the chronic and accelerated-acute stages in chronic myeloid leukemia. A previous model of Dingli and Michor is refined by introducing a new parameter in order to differentiate the bone marrow microenvironment sensitivities of normal and mutant stem cells. In the light of the new parameter, the system now has three distinct equilibria corresponding to the normal hematopoietic state, to the chronic state, and to the accelerated-acute phase of the disease. A characterization of the three hematopoietic states is obtained based on the stability analysis. Numerical simulations are included to illustrate the theoretical results.

Effects of ordered mutations on dynamics in signaling networks

BACKGROUND

Many previous clinical studies have found that accumulated sequential mutations are statistically related to tumorigenesis. However, they are limited in fully elucidating the significance of the ordered-mutation because they did not focus on the network dynamics. Therefore, there is a pressing need to investigate the dynamics characteristics induced by ordered-mutations.

METHODS

To quantify the ordered-mutation-inducing dynamics, we defined the mutation-sensitivity and the order-specificity that represent if the network is sensitive against a double knockout mutation and if mutation-sensitivity is specific to the mutation order, respectively, using a Boolean network model.

RESULTS

Through intensive investigations, we found that a signaling network is more sensitive when a double-mutation occurs in the direction order inducing a longer path and a smaller number of paths than in the reverse order. In addition, feedback loops involving a gene pair decreased both the mutation-sensitivity and the order-specificity. Next, we investigated relationships of functionally important genes with ordered-mutation-inducing dynamics. The network is more sensitive to mutations subject to drug-targets, whereas it is less specific to the mutation order. Both the sensitivity and specificity are increased when different-drug-targeted genes are mutated. Further, we found that tumor suppressors can efficiently suppress the amplification of oncogenes when the former are mutated earlier than the latter.

CONCLUSION

Taken together, our results help to understand the importance of the order of mutations with respect to the dynamical effects in complex biological systems.

Modeling breast cancer progression to bone: how driver mutation order and metabolism matter

BACKGROUND

Not all the mutations are equally important for the development of metastasis. What about their order? The survival of cancer cells from the primary tumour site to the secondary seeding sites depends on the occurrence of very few driver mutations promoting oncogenic cell behaviours. Usually these driver mutations are among the most effective clinically actionable target markers. The quantitative evaluation of the effects of a mutation across primary and secondary sites is an important challenging problem that can lead to better predictability of cancer progression trajectory.

RESULTS

We introduce a quantitative model in the framework of Cellular Automata to investigate the effects of metabolic mutations and mutation order on cancer stemness and tumour cell migration from breast, blood to bone metastasised sites. Our approach models three types of mutations: driver, the order of which is relevant for the dynamics, metabolic which support cancer growth and are estimated from existing databases, and non-driver mutations. We integrate the model with bioinformatics analysis on a cancer mutation database that shows metabolism-modifying alterations constitute an important class of key cancer mutations.

CONCLUSIONS

Our work provides a quantitative basis of how the order of driver mutations and the number of mutations altering metabolic processis matter for different cancer clones through their progression in breast, blood and bone compartments. This work is innovative because of multi compartment analysis and could impact proliferation of therapy-resistant clonal populations and patient survival. Mathematical modelling of the order of mutations is presented in terms of operators in an accessible way to the broad community of researchers in cancer models so to inspire further developments of this useful (and underused in biomedical models) methodology. We believe our results and the theoretical framework could also suggest experiments to measure the overall personalised cancer mutational signature.

Role of mTORC1 in intestinal epithelial repair and tumorigenesis

mTORC1 signaling is the prototypical pathway regulating protein synthesis and cell proliferation. mTORC1 is active in stem cells located at the base of intestinal crypts but silenced as transit-amplifying cells differentiate into enterocytes or secretory cells along the epithelium. After an insult or injury, self-limiting and controlled activation of mTORC1 is critical for the renewal and repair of intestinal epithelium. mTORC1 promotes epithelial cell renewal by driving cryptic stem cell division, and epithelial cell repair by supporting the dedifferentiation and proliferation of enterocytes or secretory cells. Under repeated insult or injury, mTORC1 becomes constitutively active, triggering an irreversible return to stemness, cell division, proliferation, and inflammation among dedifferentiated epithelial cells. Epithelium-derived cytokines promulgate inflammation within the lamina propria, which in turn releases inflammatory factors that act back on the epithelium where undamaged intestinal epithelial cells participate in the pervading state of inflammation and become susceptible to tumorigenesis.

The invasion of de-differentiating cancer cells into hierarchical tissues

Many fast renewing tissues are characterized by a hierarchical cellular architecture, with tissue specific stem cells at the root of the cellular hierarchy, differentiating into a whole range of specialized cells. There is increasing evidence that tumors are structured in a very similar way, mirroring the hierarchical structure of the host tissue. In some tissues, differentiated cells can also revert to the stem cell phenotype, which increases the risk that mutant cells lead to long lasting clones in the tissue. However, it is unclear under which circumstances de-differentiating cells will invade a tissue. To address this, we developed mathematical models to investigate how de-differentiation is selected as an adaptive mechanism in the context of cellular hierarchies. We derive thresholds for which de-differentiation is expected to emerge, and it is shown that the selection of de-differentiation is a result of the combination of the properties of cellular hierarchy and de-differentiation patterns. Our results suggest that de-differentiation is most likely to be favored provided stem cells having the largest effective self-renewal rate. Moreover, jumpwise de-differentiation provides a wider range of favorable conditions than stepwise de-differentiation. Finally, the effect of de-differentiation on the redistribution of self-renewal and differentiation probabilities also greatly influences the selection for de-differentiation.

How can a tissue such as the blood system or the skin, which constantly produces a huge number of cells, avoids that errors accumulate in the cells over time? Such tissues are typically organized in cellular hierarchies, which induce a directional relation between different stages of cellular differentiation, minimizing the risk of retention of mutations. However, recent evidence also shows that some differentiated cells can de-differentiate into the stem cell phenotype. Why does de-differentiation arise in some tumors, but not in others? We developed a mathematical model to study the growth competition between de-differentiating mutant cell populations and non de-differentiating resident cell population. Our results suggest that the invasion of de-differentiation is jointly influenced by the cellular hierarchy (e.g. number of cell compartments, inherent cell division pattern) and the de-differentiation pattern, i.e. how exactly cells acquire their stem-cell like properties.

The biological characteristics of transcription factors AP-2α and AP-2γ and their importance in various types of cancers

The Activator Protein 2 (AP-2) transcription factor (TF) family is vital for the regulation of gene expression during early development as well as carcinogenesis process. The review focusses on the AP-2α and AP-2γ proteins and their dualistic regulation of gene expression in the process of carcinogenesis. Both AP-2α and AP-2γ influence a wide range of physiological or pathological processes by regulating different pathways and interacting with diverse molecules, i.e. other proteins, long non-coding RNAs (lncRNA) or miRNAs. This review summarizes the newest information about the biology of two, AP-2α and AP-2γ, TFs in the carcinogenesis process. We emphasize that these two proteins could have either oncogenic or suppressive characteristics depending on the type of cancer tissue or their interaction with specific molecules. They have also been found to contribute to resistance and sensitivity to chemotherapy in oncological patients. A better understanding of molecular network of AP-2 factors and other molecules may clarify the atypical molecular mechanisms occurring during carcinogenesis, and may assist in the recognition of new diagnostic biomarkers.

Nutlin-3-Induced Sensitization of Non-Small Cell Lung Cancer Stem Cells to Axitinib-Induced Apoptosis Through Repression of Akt1/Wnt Signaling

The aim of this study was to investigate the potential biological activities of nutlin-3 in the regulation of growth and proliferation of non-small cell lung cancer (NSCLC) stem cells (CSCs), which may help in sensitizing to axitinib-induced apoptosis. Nutlin-3 induction of p53 expression was used to test its role in controlling the cell division pattern and apoptosis of NSCLC cells. A549 cells and H460 cells were pretreated with nutlin-3 and then treated with either an Akt1 activator or shRNA-GSK3β, to investigate the potential role of p53 sensitization in the biological effects of axitinib. We also determined the expression levels of GSK3β and p-Akt1 in patients with NSCLC and determined their potential association with survival data using Kaplan-Meier plots and CBIOTAL. Increased p53 expression stimulated the induction of apoptosis by axitinib and promoted asymmetric cell division (ACD) of NSCLC CSCs. The repression of Akt phosphorylation induced by nutlin-3 promoted the ACD of lung CSCs, decreasing the proportion of the stem cell population. In addition to the induction of apoptosis by axitinib through inhibition of Wnt signaling, nutlin-3 treatment further enhanced axitinib-induced apoptosis by inhibiting Akt1/GSK3β/Wnt signaling. The low expression of GSK3β and increased expression of p-Akt in patients with NSCLC were closely associated with the development of NSCLC. TP53 stimulates the induction of apoptosis in NSCLC by axitinib and the ACD of lung CSCs through its regulatory effects on the p53/Akt/GSK3β pathways.

The Air Sac Primordium of Drosophila: A Model for Invasive Development

The acquisition of invasive properties preceding tumor metastasis is critical for cancer progression. This phenomenon may result from mutagenic disruption of typical cell function, but recent evidence suggests that cancer cells frequently co-opt normal developmental programs to facilitate invasion as well. The signaling cascades that have been implicated present an obstacle to identifying effective therapeutic targets because of their complex nature and modulatory capacity through crosstalk with other pathways. Substantial efforts have been made to study invasive behavior during organogenesis in several organisms, but another model found in Drosophilamelanogaster has not been thoroughly explored. The air sac primordium (ASP) appears to be a suitable candidate for investigating the genes and morphogens required for invasion due to the distinct overlap in the events that occur during its normal growth and the development of metastatic tumor cells. Among these events are the conversion of larval cells in the trachea into a population of mitotically active cells, reduced cell–cell contact along the leading edge of the ASP, and remodeling of the extracellular matrix (ECM) that surrounds the structure. Here, we summarize the development of ASPs and invasive behavior observed therein.

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.

Control of cell fraction and population recovery during tissue regeneration in stem cell lineages

Multicellular tissues are continually turning over, and homeostasis is maintained through regulated proliferation and differentiation of stem cells and progenitors. Following tissue injury, a dramatic increase in cell proliferation is commonly observed, resulting in rapid restoration of tissue size. This regulation is thought to occur via multiple feedback loops acting on cell self-renewal or differentiation. Models of ordinary differential equations have been widely used to study the cell lineage system. Prior modeling studies have suggested that loss of homeostasis and initiation of tumorigenesis can be contributed to the loss of control of these processes, and the rate of symmetric versus asymmetric division of the stem cells may also be altered. While most of the previous works focused on analysis of stability, existence and uniqueness of steady states of multistage cell lineage models, in this work we attempt to understand the cell lineage model from a different perspective. We compare three variants of hierarchical stem cell lineage tissue models with different combinations of negative feedbacks and use sensitivity analysis to examine the possible strategies for the cells to achieve certain performance objectives. Our results suggest that multiple negative feedback loops must be present in the stem cell lineage to keep the fractions of stem cells to differentiated cells in the total population as robust as possible to variations in cell division parameters, and to minimize the time for tissue recovery in a non-oscillatory manner.

Phenotypic heterogeneity in modeling cancer evolution

The unwelcome evolution of malignancy during cancer progression emerges through a selection process in a complex heterogeneous population structure. In the present work, we investigate evolutionary dynamics in a phenotypically heterogeneous population of stem cells (SCs) and their associated progenitors. The fate of a malignant mutation is determined not only by overall stem cell and non-stem cell growth rates but also differentiation and dedifferentiation rates. We investigate the effect of such a complex population structure on the evolution of malignant mutations. We derive exactly calculated results for the fixation probability of a mutant arising in each of the subpopulations. The exactly calculated results are in almost perfect agreement with the numerical simulations. Moreover, a condition for evolutionary advantage of a mutant cell versus the wild type population is given in the present study. We also show that microenvironment-induced plasticity in invading mutants leads to more aggressive mutants with higher fixation probability. Our model predicts that decreasing polarity between stem and non-stem cells’ turnover would raise the survivability of non-plastic mutants; while it would suppress the development of malignancy for plastic mutants. The derived results are novel and general with potential applications in nature; we discuss our model in the context of colorectal/intestinal cancer (at the epithelium). However, the model clearly needs to be validated through appropriate experimental data. This novel mathematical framework can be applied more generally to a variety of problems concerning selection in heterogeneous populations, in other contexts such as population genetics, and ecology.

Cell dynamics in tumour environment after treatments

Most cancer treatments cause necrotic cell deaths in the tumour microenvironment. Necrotic cells send signals to immune cells to start the wound healing process in the tissue. Therefore, we assume after stopping treatments there is a wound that needs to be healed. We develop a simple computational model to investigate cell dynamics during the wound healing process after treatments. The model predicts that the involvement of high-fitness cancer cells in the wound healing leads to fast relapse, and cancer cells outside of the wound can cause a slow recurrence of the tumour. Therefore, the absence of relapse after treatments may imply a slow-developing tumour that might not reach an observable size in the patients' lifetime. Additionally, the model indicates that the location of remaining cancer cells after treatments is an important factor in the recurrence time. The fastest recurrence happens when high-fitness cancer cells remain inside of the wound. However, the longest time to recurrence corresponds to cancer cells located outside of the wound. Note that this model is the first attempt to study cell dynamics in the wound healing process after cancer treatments, and it has some limitations that might influence the results. Experiments are needed to validate the results.

An improved pre-clinical patient-derived liquid xenograft mouse model for acute myeloid leukemia

Background

Xenotransplantation of patient-derived AML (acute myeloid leukemia) cells in NOD-scid Il2rγ^null (NSG) mice is the method of choice for evaluating this human hematologic malignancy. However, existing models constructed using intravenous injection in adult or newborn NSG mice have inferior engraftment efficiency, poor peripheral blood engraftment, or are difficult to construct.

Methods

Here, we describe an improved AML xenograft model where primary human AML cells were injected into NSG newborn pups intrahepatically.

Results

Introduction of primary cells from AML patients resulted in high levels of engraftment in peripheral blood, spleen, and bone marrow (BM) of recipient mice. The phenotype of engrafted AML cells remained unaltered during serial transplantation. The mice developed features that are consistent with human AML including spleen enlargement and infiltration of AML cells into multiple organs. Importantly, we demonstrated that although leukemic stem cell activity is enriched and mediated by CD34⁺CD117⁺ subpopulation, CD34⁺CD117⁻ subpopulation can acquire CD34⁺CD117⁺ phenotype through de-differentiation. Lastly, we evaluated the therapeutic potential of Sorafenib and Regorafenib in this AML model and found that periphery and spleen AML cells are sensitive to these treatments, whereas BM provides a protective environment to AML.

Conclusions

Collectively, our improved model is robust, easy-to-construct, and reliable for pre-clinical AML studies.

Electronic supplementary material

The online version of this article (10.1186/s13045-017-0532-x) contains supplementary material, which is available to authorized users.

Modeling dynamics of mutants in heterogeneous stem cell niche

Studying the stem cell (SC) niche architecture is a crucial step for investigating the process of oncogenesis and obtaining an effective stem cell therapy for various cancers. Recently, it has been observed that there are two groups of SCs in the SC niche collaborating with each other to maintain tissue homeostasis: border stem cells (BSCs), which are responsible in controlling the number of non-stem cells as well as stem cells, and central stem cells (CeSCs), which regulate the SC niche. Here, we develop a bi-compartmental stochastic model for the SC niche to study the spread of mutants within the niche. The analytic calculations and numeric simulations, which are in perfect agreement, reveal that in order to delay the spread of mutants in the SC niche, a small but non-zero number of SC proliferations must occur in the CeSC compartment. Moreover, the migration of BSCs to CeSCs delays the spread of mutants. Furthermore, the fixation probability of mutants in the SC niche is independent of types of SC division as long as all SCs do not divide fully asymmetrically. Additionally, the progeny of CeSCs have a much higher chance than the progeny of BSCs to take over the entire niche.

Emergence of heterogeneity in acute leukemias

BACKGROUND

Leukemias are malignant proliferative disorders of the blood forming system. Sequencing studies demonstrate that the leukemic cell population consists of multiple clones. The genetic relationship between the different clones, referred to as the clonal hierarchy, shows high interindividual variability. So far, the source of this heterogeneity and its clinical relevance remain unknown. We propose a mathematical model to study the emergence and evolution of clonal heterogeneity in acute leukemias. The model allows linking properties of leukemic clones in terms of self-renewal and proliferation rates to the structure of the clonal hierarchy.

RESULTS

Computer simulations imply that the self-renewal potential of the first emerging leukemic clone has a major impact on the total number of leukemic clones and on the structure of their hierarchy. With increasing depth of the clonal hierarchy the self-renewal of leukemic clones increases, whereas the proliferation rates do not change significantly. The emergence of deep clonal hierarchies is a complex process that is facilitated by a cooperativity of different mutations.

CONCLUSION

Comparison of patient data and simulation results suggests that the self-renewal of leukemic clones increases with the emergence of clonal heterogeneity. The structure of the clonal hierarchy may serve as a marker for patient prognosis.

REVIEWERS

This article was reviewed by Marek Kimmel, Tommaso Lorenzi and Tomasz Lipniacki.

A Computational Model of Cellular Engraftment on Lung Scaffolds

The possibility that stem cells might be used to regenerate tissue is now being investigated for a variety of organs, but these investigations are still essentially exploratory and have few predictive tools available to guide experimentation. We propose, in this study, that the field of lung tissue regeneration might be better served by predictive tools that treat stem cells as agents that obey certain rules of behavior governed by both their phenotype and their environment. Sufficient knowledge of these rules of behavior would then, in principle, allow lung tissue development to be simulated computationally. Toward this end, we developed a simple agent-based computational model to simulate geographic patterns of cells seeded onto a lung scaffold. Comparison of the simulated patterns to those observed experimentally supports the hypothesis that mesenchymal stem cells proliferate preferentially toward the scaffold boundary, whereas alveolar epithelial cells do not. This demonstrates that a computational model of this type has the potential to assist in the discovery of rules of cellular behavior.

The role of cell location and spatial gradients in the evolutionary dynamics of colon and intestinal crypts

BACKGROUND

Colon and intestinal crypts serve as an important model system for adult stem cell proliferation and differentiation. We develop a spatial stochastic model to study the rate of somatic evolution in a normal crypt, focusing on the production of two-hit mutants that inactivate a tumor suppressor gene. We investigate the effect of cell division pattern along the crypt on mutant production, assuming that the division rate of each cell depends on its location.

RESULTS

We find that higher probability of division at the bottom of the crypt, where the stem cells are located, leads to a higher rate of double-hit mutant production. The optimal case for delaying mutations occurs when most of the cell divisions happen at the top of the crypt. We further consider an optimization problem where the "evolutionary" penalty for double-hit mutant generation is complemented with a "functional" penalty that assures that fully differentiated cells at the top of the crypt cannot divide.

CONCLUSION

The trade-off between the two types of objectives leads to the selection of an intermediate division pattern, where the cells in the middle of the crypt divide with the highest rate. This matches the pattern of cell divisions obtained experimentally in murine crypts.

REVIEWERS

This article was reviewed by David Axelrod (nominated by an Editorial Board member, Marek Kimmel), Yang Kuang and Anna Marciniak-Czochra. For the full reviews, please go to the Reviewers' comments section.

The insights of Let-7 miRNAs in oncogenesis and stem cell potency

The ability of the classic tumour‐suppressive let‐7 family to inhibit carcinogenesis, tumour progression, recurrence and pluripotency of cancer stem cells has generated significant interest in the field of cancer research. Through suppressing and degrading downstream‐targeted mRNAs, let‐7 affected most aspects of cell biology. It is perplexing how let‐7 affects oncogenesis, as the large influx of new miRNAs and other kinds of non‐coding RNAs are continuously defined. In this review, we delineate the complex functions of let‐7 and discuss the future direction of let‐7 research.

In silico study of the impact of cancer stem cell dynamics and radiobiological hypoxia on tumour response to hyperfractionated radiotherapy

OBJECTIVES

Advanced head and neck carcinomas (HNCs) are aggressive tumours, mainly due to hypoxia and a cancer stem cell (CSC) subpopulation. The aim of this study was to simulate tumour growth and behaviour during radiotherapy of three HNC groups (governed by different growth kinetics, hypoxia levels and CSC division pattern) to determine correlation between resistance factors and responses to hyperfractionated radiotherapy.

METHODS

An in silico HNC model was developed based on biologically realistic input parameters. During radiotherapy simulation, three parameters were studied: growth kinetics, hypoxia and probability of CSC symmetrical division. Both independent and combined effects on tumour response to hyperfractionated radiotherapy were assessed.

RESULTS

Oxic and very mildly hypoxic HNCs were revealed to be controlled by hyperfractionated radiotherapy, irrespective of growth kinetics and CSC division pattern. Moderately hypoxic tumours had different responses to radiotherapy: while slowly proliferating HNCs were still controllable, tumours with higher cell turnover were more resistant. In rapidly proliferating tumours, the number of fractions needed for tumour control increased exponentially with the probability of CSC symmetrical division, whereas in moderately growing HNC, this behaviour was linear. Severely hypoxic tumours could not be controlled by radiotherapy alone. Tumours with CSCs in a severely hypoxic niche required adjuvant therapies to be eradicated.

CONCLUSIONS

Growth kinetics strongly influence tumour responses to treatment. Slowly growing tumours showed linear dependence between dose and hypoxia/CSC, whereas rapidly growing tumours followed exponential behaviour.

Replicator dynamics of cancer stem cell: Selection in the presence of differentiation and plasticity

The cancer stem cell hypothesis has evolved into one of the most important paradigms in cancer research. According to cancer stem cell hypothesis, somatic mutations in a subpopulation of cells can transform them into cancer stem cells with the unique potential of tumour initiation. Stem cells have the potential to produce lineages of non-stem cell populations (differentiated cells) via a ubiquitous hierarchal division scheme. Differentiation of a stem cell into (partially) differentiated cells can happen either symmetrically or asymmetrically. The selection dynamics of a mutant cancer stem cell should be investigated in the light of a stem cell proliferation hierarchy and presence of a non-stem cell population. By constructing a three-compartment Moran-type model composed of normal stem cells, mutant (cancer) stem cells and differentiated cells, we derive the replicator dynamics of stem cell frequencies where asymmetric differentiation and differentiated cell death rates are included in the model. We determine how these new factors change the conditions for a successful mutant invasion and discuss the variation on the steady state fraction of the population as different model parameters are changed. By including the phenotypic plasticity/dedifferentiation, in which a progenitor/differentiated cell can transform back into a cancer stem cell, we show that the effective fitness of mutant stem cells is not only determined by their proliferation and death rates but also according to their dedifferentiation potential. By numerically solving the model we derive the phase diagram of the advantageous and disadvantageous phases of cancer stem cells in the space of proliferation and dedifferentiation potentials. The result shows that at high enough dedifferentiation rates even a previously disadvantageous mutant can take over the population of normal stem cells. This observation has implications in different areas of cancer research including experimental observations that imply metastatic cancer stem cell types might have lower proliferation potential than other stem cell phenotypes while showing much more phenotypic plasticity and can undergo clonal expansion.

The overshoot and phenotypic equilibrium in characterizing cancer dynamics of reversible phenotypic plasticity

The paradigm of phenotypic plasticity indicates reversible relations of different cancer cell phenotypes, which extends the cellular hierarchy proposed by the classical cancer stem cell (CSC) theory. Since it is still questionable if the phenotypic plasticity is a crucial improvement to the hierarchical model or just a minor extension to it, it is worthwhile to explore the dynamic behavior characterizing the reversible phenotypic plasticity. In this study we compare the hierarchical model and the reversible model in predicting the cell-state dynamics observed in biological experiments. Our results show that the hierarchical model shows significant disadvantages over the reversible model in describing both long-term stability (phenotypic equilibrium) and short-term transient dynamics (overshoot) in cancer cell populations. In a very specific case in which the total growth of population due to each cell type is identical, the hierarchical model predicts neither phenotypic equilibrium nor overshoot, whereas the reversible model succeeds in predicting both of them. Even though the performance of the hierarchical model can be improved by relaxing the specific assumption, its prediction to the phenotypic equilibrium strongly depends on a precondition that may be unrealistic in biological experiments. Moreover, it still does not show as rich dynamics as the reversible model in capturing the overshoots of both CSCs and non-CSCs. By comparison, it is more likely for the reversible model to correctly predict the stability of the phenotypic mixture and various types of overshoot behavior.

The role of the bi-compartmental stem cell niche in delaying cancer

In recent years, by using modern imaging techniques, scientists have found evidence of collaboration between different types of stem cells (SCs), and proposed a bi-compartmental organization of the SC niche. Here we create a class of stochastic models to simulate the dynamics of such a heterogeneous SC niche. We consider two SC groups: the border compartment, S1, is in direct contact with transit-amplifying (TA) cells, and the central compartment, S2, is hierarchically upstream from S1. The S1 SCs differentiate or divide asymmetrically when the tissue needs TA cells. Both groups proliferate when the tissue requires SCs (thus maintaining homeostasis). There is an influx of S2 cells into the border compartment, either by migration, or by proliferation. We examine this model in the context of double-hit mutant generation, which is a rate-limiting step in the development of many cancers. We discover that this type of a cooperative pattern in the stem niche with two compartments leads to a significantly smaller rate of double-hit mutant production compared with a homogeneous, one-compartmental SC niche. Furthermore, the minimum probability of double-hit mutant generation corresponds to purely symmetric division of SCs, consistent with the literature. Finally, the optimal architecture (which minimizes the rate of double-hit mutant production) requires a large proliferation rate of S1 cells along with a small, but non-zero, proliferation rate of S2 cells. This result is remarkably similar to the niche structure described recently by several authors, where one of the two SC compartments was found more actively engaged in tissue homeostasis and turnover, while the other was characterized by higher levels of quiescence (but contributed strongly to injury recovery). Both numerical and analytical results are presented.