The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous drug resistant disease

Ryan T Bishop1, Anna K Miller2, Matthew Froid2,3

  • 1Department of Tumor Microenvironment and Metastasis, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.

Nature Communications
|March 20, 2024
PubMed

Insights

This study introduces a novel model to understand how multiple myeloma (MM) evolves resistance. Targeting the bone microenvironment

Area of Science:

  • Oncology
  • Computational Biology
  • Cancer Research

Background:

  • Multiple myeloma (MM) is an incurable osteolytic cancer characterized by treatment-resistant relapse.
  • Understanding the complex interplay of myeloma cell-intrinsic and bone microenvironment extrinsic factors driving relapse is a significant challenge.
  • Current biological approaches are limited in defining the spatiotemporal mechanisms of resistance emergence.

Purpose of the Study:

  • To develop a biology-driven spatiotemporal hybrid agent-based model of the multiple myeloma-bone microenvironment.
  • To investigate the mechanisms by which myeloma cells acquire treatment resistance within the bone microenvironment.
  • To identify potential therapeutic strategies for optimizing treatment efficacy and delaying disease relapse.

Main Methods:

  • Development of a novel spatiotemporal hybrid agent-based model simulating the multiple myeloma-bone microenvironment.
  • Analysis of myeloma cell-intrinsic mechanisms contributing to treatment resistance.
  • Evaluation of the role of bone microenvironment-mediated drug resistance (EMDR) in enhancing resistant clone evolution.
  • In silico prediction and in vivo validation of therapeutic targeting of EMDR.

Main Results:

  • Multiple myeloma intrinsic mechanisms drive the evolution of treatment-resistant disease.
  • Bone microenvironment-mediated drug resistance (EMDR) significantly increases the probability and heterogeneity of resistant clones under treatment.
  • Targeting EMDR was predicted to deepen therapy response by eliminating sensitive clones near bone and stroma, a finding supported by in vivo studies.

Conclusions:

  • The developed model facilitates the study of multiple myeloma clonal evolution within the bone microenvironment over time.
  • Targeting bone microenvironment-mediated drug resistance is a promising strategy to enhance therapeutic response and delay relapse in multiple myeloma.
  • This computational approach can aid in optimizing treatment strategies for multiple myeloma patients.

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