ArticleJournal of theoretical biology2017
Determining the control networks regulating stem cell lineages in colonic crypts.
Article in Journal of theoretical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 28 citations in OpenAlex.
- Article
- Stochastic model for cell population dynamics quantifies homeostasis in colonic crypts and its disruption in early tumorigenesis.Proceedings. Biological sciences · 2023Article
- Spatial dynamics of feedback and feedforward regulation in cell lineages.PLoS computational biology · 2022Article
- Senescent cells and the incidence of age-related diseases.Aging cell · 2021Article
- Effect of feedback regulation on stem cell fractions in tissues and tumors: Understanding chemoresistance in cancer.Journal of theoretical biology · 2021Article
- Modelling stem cell ageing: a multi-compartment continuum approach.Royal Society open science · 2020Article
- A compartment size-dependent selective threshold limits mutation accumulation in hierarchical tissues.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Mathematical modeling reveals the factors involved in the phenomena of cancer stem cells stabilization.PloS one · 2019Article
- Optimization of Dose Schedules for Chemotherapy of Early Colon Cancer Determined by High-Performance Computer Simulations.Cancer informatics · 2019Article
- Mathematical modeling of the impact of cytokine response of acute myeloid leukemia cells on patient prognosis.Scientific reports · 2018Article
- Patterns of Tumor Progression Predict Small and Tissue-Specific Tumor-Originating Niches.Frontiers in oncology · 2018Article
- Clonal dominance and transplantation dynamics in hematopoietic stem cell compartments.PLoS computational biology · 2017Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
The question of stem cell control is at the center of our understanding of tissue functioning, both in healthy and cancerous conditions. It is well accepted that cellular fate decisions (such as divisions, differentiation, apoptosis) are orchestrated by a network of regulatory signals emitted by different cell populations in the lineage and the surrounding tissue. The exact regulatory network that governs stem cell lineages in a given tissue is usually unknown. Here we propose an algorithm to identify a set of candidate control networks that are compatible with (a) measured means and variances of cell populations in different compartments, (b) qualitative information on cell population dynamics, such as the existence of local controls and oscillatory reaction of the system to population size perturbations, and (c) statistics of correlations between cell numbers in different compartments. Using the example of human colon crypts, where lineages are comprised of stem cells, transit amplifying cells, and differentiated cells, we start with a theoretically known set of 32 smallest control networks compatible with tissue stability. Utilizing near-equilibrium stochastic calculus of stem cells developed earlier, we apply a series of tests, where we compare the networks' expected behavior with the observations. This allows us to exclude most of the networks, until only three, very similar, candidate networks remain, which are most compatible with the measurements. This work demonstrates how theoretical analysis of control networks combined with only static biological data can shed light onto the inner workings of stem cell lineages, in the absence of direct experimental assessment of regulatory signaling mechanisms. The resulting candidate networks are dominated by negative control loops and possess the following properties: (1) stem cell division decisions are negatively controlled by the stem cell population, (2) stem cell differentiation decisions are negatively controlled by the transit amplifying cell population.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.