Computational modeling of interactions between multiple myeloma and the bone microenvironment
Yan Wang1, Peter Pivonka, Pascal R Buenzli
1Department of Infrastructure Engineering, School of Engineering, University of Melbourne, Melbourne, Victoria, Australia. wangyan00@tsinghua.org.cn
Plos One
|November 24, 2011
Summary
This study models multiple myeloma (MM) bone interactions, revealing two key feedback cycles driving disease progression. Identifying these
Area of Science:
- Biomedical modeling
- Computational biology
- Cancer research
Background:
- Multiple Myeloma (MM) causes osteolytic bone lesions.
- MM-bone interactions create 'vicious cycles' of bone resorption and tumor growth.
- The combined effect and relative importance of these interactions are not fully understood.
Purpose of the Study:
- To develop a computational model of MM-bone interactions.
- To determine if modeled intercellular signaling drives MM progression.
- To identify and quantify positive feedback cycles in MM bone microenvironment.
Main Methods:
- Developed a computational model based on existing bone remodeling models.
- Incorporated IL-6 and MM-BMSC adhesion pathways.
- Simulated MM disease progression numerically from normal to advanced states.
Main Results:
- Simulations align with known bone physiology and MM disease data.
- Two positive feedback cycles were identified as sufficient to drive MM progression.
- Quantitative analysis revealed the relative importance of these feedback cycles.
Conclusions:
- The developed model accurately simulates MM progression.
- Identified 'vicious cycles' and dominant processes governing MM bone interactions.
- Suggested potential drug targets by identifying key points to block feedback cycles.
