Modeling dynamics of mutants in heterogeneous stem cell niche

Shahriyari, Leili; Mahdipour-Shirayeh, Ali

doi:10.1088/1478-3975/aa5a61

Cited by 16 publications

(12 citation statements)

References 49 publications

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“…The impact of migration on the role of central and border stem cells has been also studied in [ 54 ] where only a bi-compartmental structure of the stem cell niche has been used. Furthermore, Mahdipour et al [ 55 ] have considered a general multi-compartmental structure for the colonic/intestinal crypt to analyze the fixation probability and time to fixation in the crypt.…”

Section: Discussionmentioning

confidence: 99%

“…The authors argue that stem cell symmetric division is preferred under natural selection for two-hit mutations. Furthermore, the role of migration in delaying cancer is investigated within a bi-compartmental stem cell niche [ 54 ]. A generalized multi-stage structure of the colonic/intestinal crypt has also been recruited to give an insight into the effect of subclonal heterogeneity, migration, immortality, and division polarity in carcinogenesis [ 55 ].…”

Section: Introductionmentioning

confidence: 99%

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Phenotypic heterogeneity in modeling cancer evolution

et al. 2017

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Phenotypic heterogeneity in modeling cancer evolution

et al. 2017

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“…Without oxygen however, the cytotoxicity of several chemotherapeutic drugs whose activity depends on generating free radicals is reduced. In addition, it has been shown that cancer stem cells (CSCs) tend to be located at the center of a solid tumor [ 152 , 153 , 154 , 155 , 156 , 157 ]. These CSCs are able to withstand lower oxygen levels than the general population of cancer cells [ 18 , 80 ].…”

Section: Tumor Microenvironmentmentioning

confidence: 99%

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

Senthebane

Rowe

Thomford

et al. 2017

IJMS

346

330

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Chemoresistance is a leading cause of morbidity and mortality in cancer and it continues to be a challenge in cancer treatment. Chemoresistance is influenced by genetic and epigenetic alterations which affect drug uptake, metabolism and export of drugs at the cellular levels. While most research has focused on tumor cell autonomous mechanisms of chemoresistance, the tumor microenvironment has emerged as a key player in the development of chemoresistance and in malignant progression, thereby influencing the development of novel therapies in clinical oncology. It is not surprising that the study of the tumor microenvironment is now considered to be as important as the study of tumor cells. Recent advances in technological and analytical methods, especially ‘omics’ technologies, has made it possible to identify specific targets in tumor cells and within the tumor microenvironment to eradicate cancer. Tumors need constant support from previously ‘unsupportive’ microenvironments. Novel therapeutic strategies that inhibit such microenvironmental support to tumor cells would reduce chemoresistance and tumor relapse. Such strategies can target stromal cells, proteins released by stromal cells and non-cellular components such as the extracellular matrix (ECM) within the tumor microenvironment. Novel in vitro tumor biology models that recapitulate the in vivo tumor microenvironment such as multicellular tumor spheroids, biomimetic scaffolds and tumor organoids are being developed and are increasing our understanding of cancer cell-microenvironment interactions. This review offers an analysis of recent developments on the role of the tumor microenvironment in the development of chemoresistance and the strategies to overcome microenvironment-mediated chemoresistance. We propose a systematic analysis of the relationship between tumor cells and their respective tumor microenvironments and our data show that, to survive, cancer cells interact closely with tumor microenvironment components such as mesenchymal stem cells and the extracellular matrix.

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“…There are many studies that use mathematical models to explain the dynamics of tumor growth, to develop clinical responses, to identify the right therapy combination, and to overcome drug resistance in various cancer types [ 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 ]. Although some studies include bone modeling, osteoblast cells, or osteosarcoma treatments [ 50 , 51 , 52 , 53 , 54 ], to the best of our knowledge, there is currently no mathematical model explaining the progression of osteosarcoma tumors.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Mathematical Model of Osteosarcoma

Kirshtein

et al. 2021

Cancers

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As the immune system has a significant role in tumor progression, in this paper, we develop a data-driven mathematical model to study the interactions between immune cells and the osteosarcoma microenvironment. Osteosarcoma tumors are divided into three clusters based on their relative abundance of immune cells as estimated from their gene expression profiles. We then analyze the tumor progression and effects of the immune system on cancer growth in each cluster. Cluster 3, which had approximately the same number of naive and M2 macrophages, had the slowest tumor growth, and cluster 2, with the highest population of naive macrophages, had the highest cancer population at the steady states. We also found that the fastest growth of cancer occurred when the anti-tumor immune cells and cytokines, including dendritic cells, helper T cells, cytotoxic cells, and IFN-γ, switched from increasing to decreasing, while the dynamics of regulatory T cells switched from decreasing to increasing. Importantly, the most impactful immune parameters on the number of cancer and total cells were the activation and decay rates of the macrophages and regulatory T cells for all clusters. This work presents the first osteosarcoma progression model, which can be later extended to investigate the effectiveness of various osteosarcoma treatments.

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Modeling dynamics of mutants in heterogeneous stem cell niche

Cited by 16 publications

References 49 publications

Phenotypic heterogeneity in modeling cancer evolution

Phenotypic heterogeneity in modeling cancer evolution

The Role of Tumor Microenvironment in Chemoresistance: To Survive, Keep Your Enemies Closer

Data-Driven Mathematical Model of Osteosarcoma

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