Literature DB >> 29470992

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

Marissa Renardy1, Alexandra Jilkine2, Leili Shahriyari3, Ching-Shan Chou4.   

Abstract

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.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cancer; Homeostasis; Mathematical models; Negative feedback; Robustness; Self-renewal; Stem cell lineage; Tissue regeneration

Mesh:

Year:  2018        PMID: 29470992     DOI: 10.1016/j.jtbi.2018.02.017

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  6 in total

1.  Single-cell RNA-seq clustering: datasets, models, and algorithms.

Authors:  Lihong Peng; Xiongfei Tian; Geng Tian; Junlin Xu; Xin Huang; Yanbin Weng; Jialiang Yang; Liqian Zhou
Journal:  RNA Biol       Date:  2020-03-01       Impact factor: 4.652

2.  A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice.

Authors:  Navid Mohammad Mirzaei; Zuzana Tatarova; Wenrui Hao; Navid Changizi; Alireza Asadpoure; Ioannis K Zervantonakis; Yu Hu; Young Hwan Chang; Leili Shahriyari
Journal:  J Pers Med       Date:  2022-05-17

3.  Data Driven Mathematical Model of Colon Cancer Progression.

Authors:  Arkadz Kirshtein; Shaya Akbarinejad; Wenrui Hao; Trang Le; Sumeyye Su; Rachel A Aronow; Leili Shahriyari
Journal:  J Clin Med       Date:  2020-12-05       Impact factor: 4.241

4.  Epigenetic Inheritance From Normal Origin Cells Can Determine the Aggressive Biology of Tumor-Initiating Cells and Tumor Heterogeneity.

Authors:  Jiliang Feng; Dawei Zhao; Fudong Lv; Zhongyu Yuan
Journal:  Cancer Control       Date:  2022 Jan-Dec       Impact factor: 3.302

5.  Modelling stem cell ageing: a multi-compartment continuum approach.

Authors:  Yanli Wang; Wing-Cheong Lo; Ching-Shin Chou
Journal:  R Soc Open Sci       Date:  2020-03-18       Impact factor: 2.963

6.  A General Theoretical Framework to Study the Influence of Electrical Fields on Mesenchymal Stem Cells.

Authors:  Jonathan Dawson; Poh Soo Lee; Ursula van Rienen; Revathi Appali
Journal:  Front Bioeng Biotechnol       Date:  2020-10-20
  6 in total

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