Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model
Authored by Jing Su, Xiaobo Zhou, Zhiwei Ji, Dan Wu, Huiming Peng, Weiling Zhao, Brian Nlong Zhao
Date Published: 2017
DOI: 10.18632/oncotarget.13831
Sponsors:
Chinese National Natural Science Foundation
United States National Institutes of Health (NIH)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
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Model Code URLs:
Model code not found
Abstract
Multiple myeloma is a malignant still incurable plasma cell disorder.
This is due to refractory disease relapse, immune impairment, and
development of multidrug resistance. The growth of malignant plasma
cells is dependent on the bone marrow (BM) microenvironment and evasion
of the host's anti-tumor immune response. Hence, we hypothesized that
targeting tumor-stromal cell interaction and endogenous immune system in
BM will potentially improve the response of multiple myeloma (MM).
Therefore, we proposed a computational simulation of the myeloma
development in the complicated microenvironment which includes immune
cell components and bone marrow stromal cells and predicted the effects
of combined treatment with multi-drugs on myeloma cell growth. We
constructed a hybrid multiscale agent-based model (HABM) that combines
an ODE system and Agent-based model (ABM). The ODEs was used for
modeling the dynamic changes of intracellular signal transductions and
ABM for modeling the cell-cell interactions between stromal cells,
tumor, and immune components in the BM. This model simulated myeloma
growth in the bone marrow microenvironment and revealed the important
role of immune system in this process. The predicted outcomes were
consistent with the experimental observations from previous studies.
Moreover, we applied this model to predict the treatment effects of
three key therapeutic drugs used for MM, and found that the combination
of these three drugs potentially suppress the growth of myeloma cells
and reactivate the immune response. In summary, the proposed model may
serve as a novel computational platform for simulating the formation of
MM and evaluating the treatment response of MM to multiple drugs.
Tags
Agent-based model
modeling
Drug-resistance
Stem-cells
Mesenchymal stromal cells
Ode
Multiple myeloma
Immune
Refractory multiple-myeloma
Regulatory
t-cells
Immunomodulatory drugs
Thalidomide analogs
Signaling pathway
Accessory cells
Lenalidomide