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Updated: Feb 6, 2026

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells
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Optimizing drug combinations against multiple myeloma using a quadratic phenotypic optimization platform (QPOP)

Masturah Bte Mohd Abdul Rashid1,2, Tan Boon Toh1, Lissa Hooi1

  • 1Cancer Science Institute of Singapore, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599, Singapore.

Science Translational Medicine
|August 10, 2018
PubMed

Insights

A new platform, quadratic phenotypic optimization platform (QPOP), identifies effective drug combinations for bortezomib-resistant multiple myeloma. QPOP optimizes treatments by reversing epigenetic changes and works in cell lines, mouse models, and patient samples.

Area of Science:

  • Hematology
  • Oncology
  • Pharmacology
  • Computational Biology

Background:

  • Multiple myeloma is an incurable blood cancer requiring combination drug therapies.
  • Proteasome inhibitors like bortezomib have improved survival but resistance is common.
  • There is a critical need for novel, effective drug combinations for resistant multiple myeloma.

Purpose of the Study:

  • To develop and apply a novel computational platform, QPOP, for optimizing drug combinations against bortezomib-resistant multiple myeloma.
  • To identify effective drug combinations that overcome resistance mechanisms.
  • To validate QPOP's efficacy in preclinical models and patient-derived samples.

Main Methods:

  • Developed the quadratic phenotypic optimization platform (QPOP) to model drug combination effects using quadratic surfaces.
  • Applied QPOP to bortezomib-resistant multiple myeloma cell lines to identify optimal drug combinations.
  • Validated QPOP-identified combinations in a xenograft mouse model and ex vivo patient samples.

Main Results:

  • QPOP identified drug combinations that effectively treated bortezomib-resistant multiple myeloma.
  • These combinations were found to reverse DNA methylation and tumor suppressor silencing associated with resistance.
  • QPOP successfully optimized drug dosages and minimized toxicity in vivo and personalized treatments for patients.

Conclusions:

  • QPOP is a powerful platform for discovering and optimizing drug combinations for complex diseases like multiple myeloma.
  • The identified combinations offer a promising strategy to overcome bortezomib resistance.
  • QPOP demonstrates potential for personalized medicine by optimizing treatments based on patient-specific contexts.

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