scholarly journals Cellular cooperation shapes tumor growth: a statistical mechanics mathematical model

2018 ◽  
Author(s):  
Jeffrey West ◽  
Paul K. Newton
Keyword(s):  
Mathematical Model ◽  
Statistical Mechanics ◽  
Tumor Growth ◽  
Fitness Landscape ◽  
Cellular Level ◽  
Cellular Heterogeneity ◽  
Functional Coupling ◽  
Macroscopic Tumor ◽  
Growth Laws ◽  
Cellular Cooperation

AbstractA tumor is made up of a heterogeneous collection of cell types all competing on a fitness landscape mediated by micro-environmental conditions that dictate their interactions. Despite the fact that much is known about cell signaling and cellular cooperation, the specifics of how the cell-to-cell coupling and the range over which this coupling acts affect the macroscopic tumor growth laws that govern total volume, mass, and carrying capacity remain poorly understood. We develop a statistical mechanics approach that focuses on the total number of possible states each cell can occupy, and show how different assumptions on correlations of these states gives rise to the many different macroscopic tumor growth laws used in the literature. Although it is widely understood that molecular and cellular heterogeneity within a tumor is a driver of growth, here we emphasize that focusing on the functional coupling of these states at the cellular level is what determines macroscopic growth characteristics.Significance statementA mathematical model relating tumor heterogeneity at the cellular level to tumor growth at the macroscopic level is described based on a statistical mechanics framework. The model takes into account the number of accessible states available to each cell as well as their long-range coupling (population cooperation) to other cells. We show that the degree to which cell populations cooperate determine the number of independent cell states, which in turn dictates the macroscopic (volumetric) growth law. It follows that targeting cell-to-cell interactions could be a way of mitigating and controlling tumor growth.

scholarly journals Cellular interactions constrain tumor growth

2019 ◽  
Vol 116 (6) ◽  
pp. 1918-1923 ◽  
Author(s):  
Jeffrey West ◽  
Paul K. Newton
Keyword(s):  
Tumor Growth ◽  
Fitness Landscape ◽  
Cell Types ◽  
Cellular Level ◽  
Cellular Heterogeneity ◽  
Functional Coupling ◽  
Cellular Interactions ◽  
Macroscopic Tumor ◽  
Growth Laws ◽  
The Many

A tumor is made up of a heterogeneous collection of cell types, all competing on a fitness landscape mediated by microenvironmental conditions that dictate their interactions. Despite the fact that much is known about cell signaling, cellular cooperation, and the functional constraints that affect cellular behavior, the specifics of how these constraints (and the range over which they act) affect the macroscopic tumor growth laws that govern total volume, mass, and carrying capacity remain poorly understood. We develop a statistical mechanics approach that focuses on the total number of possible states each cell can occupy and show how different assumptions on correlations of these states give rise to the many different macroscopic tumor growth laws used in the literature. Although it is widely understood that molecular and cellular heterogeneity within a tumor is a driver of growth, here we emphasize that focusing on the functional coupling of states at the cellular level is what determines macroscopic growth characteristics.

scholarly journals Transcriptomic Changes of Murine Visceral Fat Exposed to Intermittent Hypoxia at Single Cell Resolution

2020 ◽  
Vol 22 (1) ◽  
pp. 261
Author(s):  
Abdelnaby Khalyfa ◽  
Wesley Warren ◽  
Jorge Andrade ◽  
Christopher A. Bottoms ◽  
Edward S. Rice ◽  
...  
Keyword(s):  
Intermittent Hypoxia ◽  
Cell Types ◽  
Cellular Level ◽  
Cellular Heterogeneity ◽  
Transcriptional Networks ◽  
Metabolic Dysfunction ◽  
Rna Seq ◽  
Obstructive Sleep ◽  
Differential Expressed Gene ◽  
Key Aspects

Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA) and induces metabolic dysfunction manifesting as inflammation, increased lipolysis and insulin resistance in visceral white adipose tissues (vWAT). However, the cell types and their corresponding transcriptional pathways underlying these functional perturbations are unknown. Here, we applied single nucleus RNA sequencing (snRNA-seq) coupled with aggregate RNA-seq methods to evaluate the cellular heterogeneity in vWAT following IH exposures mimicking OSA. C57BL/6 male mice were exposed to IH and room air (RA) for 6 weeks, and nuclei from vWAT were isolated and processed for snRNA-seq followed by differential expressed gene (DEGs) analyses by cell type, along with gene ontology and canonical pathways enrichment tests of significance. IH induced significant transcriptional changes compared to RA across 14 different cell types identified in vWAT. We identified cell-specific signature markers, transcriptional networks, metabolic signaling pathways, and cellular subpopulation enrichment in vWAT. Globally, we also identify 298 common regulated genes across multiple cellular types that are associated with metabolic pathways. Deconvolution of cell types in vWAT using global RNA-seq revealed that distinct adipocytes appear to be differentially implicated in key aspects of metabolic dysfunction. Thus, the heterogeneity of vWAT and its response to IH at the cellular level provides important insights into the metabolic morbidity of OSA and may possibly translate into therapeutic targets.

Unexplored functions of sex hormones in glioblastoma cancer stem cells

Endocrinology ◽  
2022 ◽  
Author(s):  
Juyeun Lee ◽  
Katie Troike ◽  
R’ay Fodor ◽  
Justin D Lathia
Keyword(s):  
Stem Cells ◽  
Immune Response ◽  
Sex Differences ◽  
Cancer Stem Cells ◽  
Tumor Growth ◽  
Sex Hormones ◽  
Cellular Heterogeneity ◽  
Cellular Functions ◽  
Biological Sex ◽  
Organismal Development

Abstract Biological sex impacts a wide array of molecular and cellular functions that impact organismal development and can influence disease trajectory in a variety of pathophysiological states. In non-reproductive cancers, epidemiological sex differences have been observed in a series of tumors, and recent work has identified previously unappreciated sex differences in molecular genetics and immune response. However, the extent of these sex differences in terms of drivers of tumor growth and therapeutic response is less clear. In glioblastoma, the most common primary malignant brain tumor, there is a male bias in incidence and outcome, and key genetic and epigenetic differences, as well as differences in immune response driven by immune-suppressive myeloid populations, have recently been revealed. Glioblastoma is a prototypic tumor in which cellular heterogeneity is driven by populations of therapeutically resistant cancer stem cells (CSCs) that underlie tumor growth and recurrence. There is emerging evidence that GBM CSCs may show a sex difference, with male tumor cells showing enhanced self-renewal, but how sex differences impact CSC function is not clear. In this mini-review, we focus on how sex hormones may impact CSCs in GBM and implications for other cancers with a pronounced CSC population. We also explore opportunities to leverage new models to better understand the contribution of sex hormones versus sex chromosomes to CSC function. With the rising interest in sex differences in cancer, there is an immediate need to understand the extent to which sex differences impact tumor growth, including effects on CSC function.

An Interdisciplinary Approach to Brain Tumor Growth Dynamics

2000 ◽  
Author(s):  
Salvatore Torquato ◽  
Thomas S. Deisboeck
Keyword(s):  
Brain Tumors ◽  
Tumor Growth ◽  
Computational Models ◽  
Growth Dynamics ◽  
Interdisciplinary Approach ◽  
Clinical Prognosis ◽  
Macroscopic Tumor ◽  
New Perspective ◽  
Clonal Composition

Abstract Intensive medical research over the last fifty years has left the prognosis for patients diagnosed with malignant brain tumors nearly unchanged. This suggests that a new perspective on the problem may offer important insight. We have undertaken an interdisciplinary research program, seeking to study brain tumors as complex systems. This research aims to develop computational models coupled with experimental assays to investigate the hypothesis of self-organizing behavior in tumor systems. Preliminary assays have revealed behavior consistent with this hypothesis. A cellular-automaton model to study the growth of the tumor core has been developed. This model has proven successful in reproducing macroscopic tumor growth from a limited parameter set. Further, it has been applied to investigate the importance of heterogeneity to determination of a clinical prognosis and has demonstrated the importance of understanding clonal composition in making an accurate prognosis.

scholarly journals Stemness-Attenuating miR-503-3p as a Paracrine Factor to Regulate Growth of Cancer Stem Cells

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Minkoo Seo ◽  
Seung Min Kim ◽  
Eun Young Woo ◽  
Ki-Cheol Han ◽  
Eun Joo Park ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Tumor Growth ◽  
Cellular Heterogeneity ◽  
Paracrine Factor ◽  
Adipose Stem Cell ◽  
Self Renewal ◽  
Human Adipose Stem Cell ◽  
Pluripotency Genes

Cancer stem cells (CSCs) with self-renewal abilities endorse cellular heterogeneity, resulting in metastasis and recurrence. However, there are no promising therapeutics directed against CSCs. Herein, we found that miR-503-3p inhibited tumor growth via the regulation of CSC proliferation and self-renewal. miR-503-3p, isolated from human adipose stem cell- (ASC-) derived exosomes, suppressed initiation and progression of CSCs as determined by anchorage-dependent (colony formation) and anchorage-independent (tumorsphere formation) assays. The expression of pluripotency genes was significantly decreased in miR-503-3p-treated CSCs. Furthermore, xenografts, which received miR-503-3p, exhibited remarkably reduced tumor growth in vivo. Thus, miR-503-3p may function as a stemness-attenuating factor via cell-to-cell communications.

Abstract LB-131: Mathematical model for tumor growth

2010 ◽  
Author(s):  
Jiang ji ◽  
Guangde tu ◽  
Mei zou
Keyword(s):  
Mathematical Model ◽  
Tumor Growth
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