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Related Experiment Video

Updated: Nov 10, 2025

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells
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Multiple Myeloma: Heterogeneous in Every Way.

Anaïs Schavgoulidze1, Titouan Cazaubiel2, Aurore Perrot1,3

  • 1Centre de Recherche en Cancérologie de Toulouse, Institut National de la Santé et de la Recherche, Médicale U1037, 31059 Toulouse, France.

Cancers
|April 3, 2021
PubMed
Summary

Multiple myeloma (MM) prognosis is complex and heterogeneous. New prognostic factors beyond genetics and minimal residual disease are needed to improve patient outcome predictions.

Keywords:
cytogeneticsepigeneticsmicroenvironmentmultiple myelomaprognosis

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Area of Science:

  • Hematology
  • Oncology
  • Molecular Biology

Background:

  • Multiple myeloma (MM) is a bone marrow malignancy with heterogeneous patient prognoses despite treatment advances.
  • Current prognostic markers like cytogenetics and minimal residual disease do not fully explain outcome variability.
  • Limitations include undetected subclones and unexplored spatial heterogeneity within focal lesions.

Purpose of the Study:

  • To explore additional determinants of prognosis in multiple myeloma.
  • To investigate the role of gene expression, epigenetic regulation, and the tumor microenvironment.
  • To identify independent prognostic factors for improved patient stratification.

Main Methods:

  • Analysis of gene expression patterns in relation to cytogenetic events and epigenetic modifications.
  • Assessment of the impact of the bone marrow microenvironment on disease progression.
  • Evaluation of novel molecular and spatial factors as prognostic indicators.

Main Results:

  • Gene expression is intricately linked to cytogenetic events and epigenetic regulation.
  • The tumor microenvironment significantly influences multiple myeloma development and progression.
  • Several novel determinants have emerged as independent prognostic factors.

Conclusions:

  • Prognosis in multiple myeloma is multifactorial, involving more than just cytogenetics and minimal residual disease.
  • Integrating gene expression, epigenetic, and microenvironmental data can enhance prognostic accuracy.
  • These findings may lead to more precise predictions of patient prognosis and treatment response.