scholarly journals Adaptive dynamics of unstable cancer populations: the canonical equation

2017 ◽  
Author(s):  
Guim Aguadé-Gorgorió ◽  
Ricard Solé
Keyword(s):  
Immune Responses ◽  
Tumor Progression ◽  
Cancer Cell ◽  
Genetic Instability ◽  
Adaptive Dynamics ◽  
Canonical Equation ◽  
Cell Populations ◽  
Simple Version ◽  
Physical Constraints ◽  
Environment Modelling

In most instances of tumour development, genetic instability plays a role in allowing cancer cell populations to respond to selection barriers, such as physical constraints or immune responses, and rapidly adapt to an always changing environment. Modelling instability is a nontrivial task, since by definition evolving changing instability leads to changes in the underlying landscape. In this paper we explore mathematically a simple version of unstable tumor progression using the formalism of Adaptive Dynamics (AD) where selection and mutation are explicitly coupled. Using a set of basic fitness landscapes, the so called canonical equation for the evolution of genetic instability on a minimal scenario associated to a population of unstable cells is derived. The implications and potential extensions of this model are discussed.

scholarly journals Discrete and continuum phenotype-structured models for the evolution of cancer cell populations under chemotherapy

2020 ◽  
Vol 15 ◽  
pp. 14 ◽  
Author(s):  
Rebecca E.A. Stace ◽  
Thomas Stiehl ◽  
Mark A.J. Chaplain ◽  
Anna Marciniak-Czochra ◽  
Tommaso Lorenzi
Keyword(s):  
Cancer Cell ◽  
Cell Population ◽  
Evolutionary Dynamics ◽  
Analytical Description ◽  
Chemotherapeutic Agents ◽  
Cell Populations ◽  
Theoretical Ground ◽  
Individual Based Model ◽  
Nonlocal Parabolic Equation ◽  
Epigenetic Drug

We present a stochastic individual-based model for the phenotypic evolution of cancer cell populations under chemotherapy. In particular, we consider the case of combination cancer therapy whereby a chemotherapeutic agent is administered as the primary treatment and an epigenetic drug is used as an adjuvant treatment. The cell population is structured by the expression level of a gene that controls cell proliferation and chemoresistance. In order to obtain an analytical description of evolutionary dynamics, we formally derive a deterministic continuum counterpart of this discrete model, which is given by a nonlocal parabolic equation for the cell population density function. Integrating computational simulations of the individual-based model with analysis of the corresponding continuum model, we perform a complete exploration of the model parameter space. We show that harsher environmental conditions and higher probabilities of spontaneous epimutation can lead to more effective chemotherapy, and we demonstrate the existence of an inverse relationship between the efficacy of the epigenetic drug and the probability of spontaneous epimutation. Taken together, the outcomes of the model provide theoretical ground for the development of anticancer protocols that use lower concentrations of chemotherapeutic agents in combination with epigenetic drugs capable of promoting the re-expression of epigenetically regulated genes.

scholarly journals Cancer stem cells and cisplatin‐resistant cells isolated from non‐small‐lung cancer cell lines constitute related cell populations

2014 ◽  
Vol 3 (5) ◽  
pp. 1099-1111 ◽  
Author(s):  
Blanca D. Lopez‐Ayllon ◽  
Veronica Moncho‐Amor ◽  
Ander Abarrategi ◽  
Inmaculada Ibañez Cáceres ◽  
Javier Castro‐Carpeño ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Cell Populations ◽  
Lung Cancer Cell ◽  
Related Cell ◽  
Resistant Cells

scholarly journals Interstitial flow promotes macrophage polarization toward an M2 phenotype

2018 ◽  
Vol 29 (16) ◽  
pp. 1927-1940 ◽  
Author(s):  
Ran Li ◽  
Jean Carlos Serrano ◽  
Hao Xing ◽  
Tara A. Lee ◽  
Hesham Azizgolshani ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Tumor Microenvironment ◽  
Tumor Progression ◽  
Cancer Cell ◽  
Interstitial Fluid ◽  
Macrophage Polarization ◽  
Interstitial Flow ◽  
Interstitial Fluid Flow ◽  
M2 Polarization ◽  
Tumor Tissues

Tumor tissues are characterized by an elevated interstitial fluid flow from the tumor to the surrounding stroma. Macrophages in the tumor microenvironment are key contributors to tumor progression. While it is well established that chemical stimuli within the tumor tissues can alter macrophage behaviors, the effects of mechanical stimuli, especially the flow of interstitial fluid in the tumor microenvironment, on macrophage phenotypes have not been explored. Here, we used three-dimensional biomimetic models to reveal that macrophages can sense and respond to pathophysiological levels of interstitial fluid flow reported in tumors (∼3 µm/s). Specifically, interstitial flow (IF) polarizes macrophages toward an M2-like phenotype via integrin/Src-mediated mechanotransduction pathways involving STAT3/6. Consistent with this flow-induced M2 polarization, macrophages treated with IF migrate faster and have an enhanced ability to promote cancer cell migration. Moreover, IF directs macrophages to migrate against the flow. Since IF emanates from the tumor to the surrounding stromal tissues, our results suggest that IF could not only induce M2 polarization of macrophages but also recruit these M2 macrophages toward the tumor masses, contributing to cancer cell invasion and tumor progression. Collectively, our study reveals that IF could be a critical regulator of tumor immune environment.

Capturing quantitative features of protein expression from in situ fluorescence microscopic images of cancer cell populations

2017 ◽  
pp. 279-297
Author(s):  
Joana Figueiredo ◽  
Ana Sofia Ribeiro ◽  
Tânia Mestre ◽  
Sofia Esménio ◽  
Martina Fonseca ◽  
...  
Keyword(s):  
Protein Expression ◽  
Cancer Cell ◽  
Cell Populations ◽  
Microscopic Images

scholarly journals Tumor Growth Progression in Ectopic and Orthotopic Xenografts from Inflammatory Breast Cancer Cell Lines

2021 ◽  
Vol 8 (9) ◽  
pp. 194
Author(s):  
Sara Caceres ◽  
Angela Alonso-Diez ◽  
Belén Crespo ◽  
Laura Peña ◽  
Maria J. Illera ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Progression ◽  
Cell Line ◽  
Cancer Cell ◽  
Inflammatory Breast Cancer ◽  
Steroid Hormone ◽  
Cancer Cell Line ◽  
Histological Features ◽  
Inflammatory Breast Cancer Cell ◽  
Orthotopic Xenografts

Xenografts can grow in immunosuppressed hosts, such as SCID mice, and tumor material can be injected into hosts either ectopically or orthotopically. Choosing the correct model to use is a crucial step in animal research. The aim of this study was to report the differences between ectopic and orthotopic xenografts in tumor progression, metastasis capacity, histological features, and steroid hormone profiles in xenografts from the cIMC (canine inflammatory mammary cancer) cell line IPC-366 and hIBC (human inflammatory breast cancer) cell line SUM149. To achieve this purpose, 40 female mice 6–8 weeks old were inoculated with IPC-366 and SUM149 cells subcutaneously (ectopic models) or into mammary fat pad (orthotopic models). Mice were monitored for tumor progression and appearance of metastases, and generated tumors were analyzed in terms of histological examination and steroid hormone production. The results revealed differences in tumor appearance and percentage of metastasis between ectopic and orthotopic models, which were higher in the ectopic xenografts from both cell lines. However, both models had similar characteristics of tumor progression, histological features, and steroid hormone secretion profiles. We show that the ectopic model can be validated as a good and useful model of tumor development in addition to, not contrary to, the orthotopic model in breast cancer research.

scholarly journals Increased Expression of the Pro-Protein Convertase Furin Predicts Decreased Survival in Ovarian Cancer

2007 ◽  
Vol 29 (4) ◽  
pp. 289-299
Author(s):  
Robert E. Page ◽  
Andrés J. P. Klein-Szanto ◽  
Samuel Litwin ◽  
Emmanuelle Nicolas ◽  
Raid Al-Jumaily ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Tumor Progression ◽  
Real Time ◽  
Cell Lines ◽  
Cancer Cell ◽  
Real Time Pcr ◽  
Ovarian Tumor ◽  
Cancer Cell Lines ◽  
Rt Pcr ◽  
Primary Tumors

Background: Proprotein convertases (PCs) are serine proteases that after restricted proteolysis activate many proteins that play a crucial role in cancer such as metalloproteinases, growth factors and growth factor receptors, adhesion molecules, and angiogenic factors. Although the expression of several PCs is increased in many tumors, their expression in primary ovarian tumors has not been studied in detail. We sought to determine if there was an association between the expression of the ubiquitously expressed PCs, furin, PACE-4, PC-5 and PC-7, and ovarian tumor progression. Methods: We assessed their expression by RT-PCR, Real-time PCR, Western blot, and immunohistochemistry using cells derived from normal human ovarian surface epithelium (HOSE) and cancer cell lines as well as ovarian epithelial cancer specimens (45 RT-PCR/Real-time PCR, and 120 archival specimens for Immunohistochemistry). Results: We found that furin expression was restricted to the cancer cell lines. In contrast, PACE-4 and PC-7 showed expression only in normal HOSE cells lines. Furthermore, furin was predominantly expressed in primary tumors from patients who survived for less than five years. The other PCs are either expressed in the group of survivors (PC-7 and PACE4) or expressed in low amounts (PC-5). Conclusions: Our studies point to a clear relationship between furin and ovarian cancer. In addition, these results show that furin exhibits the closest association with ovarian cancer among the ubiquitously expressed PCs, arguing against the redundancy of these proteases. In summary, furin may constitute a marker for ovarian tumor progression and could contribute to predict the outcome of this disease.

Introduction to Clinical Immunology: Overview of the Immune Response, Autoimmune Conditions, and Immunosuppressive Therapeutics for Rheumatic Diseases

2016 ◽  
Author(s):  
Steven K. Lundy ◽  
Alison Gizinski ◽  
David A. Fox
Keyword(s):  
Immune Response ◽  
Immune System ◽  
T Cell ◽  
Immune Responses ◽  
Autoimmune Diseases ◽  
Adaptive Immunity ◽  
Cell Populations ◽  
Hematopoietic Stem ◽  
Innate And Adaptive Immunity ◽  
Adaptive Immune

The immune system is a complex network of cells and mediators that must balance the task of protecting the host from invasive threats. From a clinical perspective, many diseases and conditions have an obvious link to improper functioning of the immune system, and insufficient immune responses can lead to uncontrolled acute and chronic infections. The immune system may also be important in tumor surveillance and control, cardiovascular disease, health complications related to obesity, neuromuscular diseases, depression, and dementia. Thus, a working knowledge of the role of immunity in disease processes is becoming increasingly important in almost all aspects of clinical practice. This review provides an overview of the immune response and discusses immune cell populations and major branches of immunity, compartmentalization and specialized immune niches, antigen recognition in innate and adaptive immunity, immune tolerance toward self antigens, inflammation and innate immune responses, adaptive immune responses and helper T (Th) cell subsets, components of the immune response that are important targets of treatment in autoimmune diseases, mechanisms of action of biologics used to treat autoimmune diseases and their approved uses, and mechanisms of other drugs commonly used in the treatment of autoimmune diseases. Figures show the development of erythrocytes, platelets, lymphocytes, and other immune system cells originating from hematopoietic stem cells that first reside in the fetal liver and later migrate to the bone marrow, antigen–major histocompatibility complex recognition by T cell receptor control of T cell survival and activation, and Th cells as central determinants of the adaptive immune response toward different stimuli. Tables list cell populations involved in innate and adaptive immunity, pattern recognition receptors with known ligands, autoantibody-mediated human diseases: examples of pathogenic mechanisms, selected Food and Drug Administration–approved autoimmune disease indications for biologics, and mechanism of action of biologics used to treat autoimmune diseases.   This review contains 3 highly rendered figures, 5 tables, and 64 references.

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