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Mouse Models of Cancer Study

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Updated: Jun 23, 2026

Three-Dimensional Bone Extracellular Matrix Model for Osteosarcoma

Three-Dimensional Bone Extracellular Matrix Model for Osteosarcoma

Published on: April 12, 2019

Data-Driven Mathematical Model of Osteosarcoma.

Trang Le¹, Sumeyye Su¹, Arkadz Kirshtein²

¹Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA 01003, USA.

|June 2, 2021

Summary

This summary is machine-generated.

This study models osteosarcoma tumor growth, revealing that immune cell populations significantly impact progression. Macrophage and regulatory T cell dynamics were key factors influencing cancer cell proliferation.

Keywords:

data-driven mathematical model gene expression profiles immune interactions immune variations osteosarcoma sensitivity analysis tumor deconvolution tumor microenvironment

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Last Updated: Jun 23, 2026

Three-Dimensional Bone Extracellular Matrix Model for Osteosarcoma

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Published on: April 12, 2019

A Syngeneic Orthotopic Osteosarcoma Sprague Dawley Rat Model with Amputation to Control Metastasis Rate

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Intratibial Osteosarcoma Cell Injection to Generate Orthotopic Osteosarcoma and Lung Metastasis Mouse Models

Intratibial Osteosarcoma Cell Injection to Generate Orthotopic Osteosarcoma and Lung Metastasis Mouse Models

Published on: October 28, 2021

Area of Science:

Immunology
Computational Biology
Oncology

Background:

The immune system plays a critical role in tumor progression.
Understanding immune cell interactions within the osteosarcoma microenvironment is crucial for developing effective treatments.

Purpose of the Study:

To develop a data-driven mathematical model simulating immune cell and osteosarcoma microenvironment interactions.
To analyze tumor progression and immune system effects on cancer growth across different immune cell abundance profiles.

Main Methods:

Clustering osteosarcoma tumors into three groups based on immune cell gene expression profiles.
Developing a mathematical model to analyze tumor progression dynamics within each cluster.
Identifying key immune parameters influencing cancer and total cell populations.

Main Results:

Osteosarcoma tumors were classified into three immune cell abundance clusters.
Cluster 3 (balanced naive and M2 macrophages) showed slowest tumor growth; Cluster 2 (high naive macrophages) exhibited highest steady-state cancer populations.
Fastest cancer growth correlated with decreasing anti-tumor immunity (dendritic cells, T cells, IFN-γ) and increasing regulatory T cells.
Macrophage and regulatory T cell activation/decay rates were the most impactful immune parameters across all clusters.

Conclusions:

This study presents the first mathematical model for osteosarcoma progression, integrating immune dynamics.
The findings highlight specific immune cell populations and parameter dynamics associated with tumor growth rates.
The model provides a foundation for future investigations into osteosarcoma treatment strategies.