Multi-Scale Agent-Based Multiple Myeloma Cancer Modeling and the Related Study of the Balance between Osteoclasts and Osteoblasts

Abstract

Research BackgroundCurrently, multiple myeloma is the second most common hematological malignancy in the U.S., constituting 1% of all cancers. With conventional treatment, the median survival time is typically 3–4 years, although it can be extended to 5–7 years or longer with advanced treatments. Recent research indicated that an increase in osteoclast (OC) activity is often associated withmultiple myeloma (MM) and that a decrease inosteoblast (OB) activity contributesto the osteolytic lesions in MM. Normally, the populations of OCs and OBs are inequilibrium, and an imbalance in this statecontributes to the development of lesions.Research proceduresA multi-scale agent-based multiple myeloma model was developed to simulate the proliferation, migration and death of OBs and OCs. Subsequently, this model was employed to investigate the efficacy of thethree most commonly used drugs for MM treatment under the following two premises: the reduction in the progression of MM and the re-establishment of the equilibrium between OCs and OBs.Research purposesThe simulated results not only demonstrated the capacity of the model to choose optimal combinations of the drugs but also showed that the optimal use of the three drugs can restore the balance between OCs and OBs as well as kill MMs. Furthermore, the drug synergism analysis function of the model revealed that restoring the balance between OBs and OCs can significantly increase the efficacy of drugs against tumor cells.

A new conceptual framework for the therapy by optimized multidimensional pulses of therapeutic activity. The case of multiple myeloma model

“…Such formulation of the objective function is in line with the concept of adaptive therapy [13]. The alternative formulation exists [29] based on the OBs and OCs abundances that aims to restore their balance disrupted by MM. Productive and broadly accepted paradigm in the area of the multi-objective optimization is the Wald's "minimax" optimality [52,53,54].…”

“…Physiological numbers of OCs and OBs are guaranteed by their mutual influence via autocrine and paracrine signaling. Due to serious health implications of the MM cancer, several mathematical models were developed to understand nonlinear dynamics of the OCs and OBs production, homeostasis and decay [26,27,28,29,30], proposing alternative equations to describe the system. The assembly composed of many coupled submodels [31] has been considered to adequately describe calcium homeostasis and intracellular signaling as occurring in the process of bone remodeling.…”

“…On the other hand, formation of JCs belonging to the wide class of pathological cell fusion processes in cancer [37,38], already captured at some basic level in [9], can be considered as an alternative mechanism contributing to the phenotypic heterogeneity thereby increasing the chemical resistance and metastatic potential. Promising approach to the MM analysis represents the agent based model introduced in [29] which incorporates DKK1-Wnt-OPG/RANKL pathway and cytokine stimulation. The main strength of the model consists in the study of therapeutic effects of Lidamycin, glucocorticoids and Anti-DKK1 mAb (BHQ880).…”

Investigation of mechanism of bone regeneration in a porous biodegradable calcium phosphate (CaP) scaffold by a combination of a multi-scale agent-based model and experimental optimization/validation

“…Sensitive analysis [17] is employed to evaluate the impact of the parameter on the behavior of the model. Each parameter value in the …”

“…15 is to compute the average relative error (ARE)[17,29,30] for testing model's predictive precision. Eq.…”