EZ Score Stratifies PRC2-Dependent Myeloma for Epigenetic Therapy

Scientific Contributions by Alboukadel Kassambara

This study defines a gene expression–based EZ score for identifying high-risk multiple myeloma patients who may benefit from PRC2 inhibition and shows synergistic effects with IMiD therapy.

Scientific Abstracts
Author
Affiliation
Published

October 3, 2018

Modified

May 21, 2025

Keywords

Alboukadel Kassambara, EZ score, PRC2, epigenetics, multiple myeloma, EZH2 inhibitor, EPZ-6438, Clinical Epigenetics

Herviou L, Kassambara A, Boireau S, Robert N, Requirand G, Müller-Tidow C, Vincent L, Seckinger A, Goldschmidt H, Cartron G, Hose D, Cavalli G, Moreaux J. PRC2 targeting is a therapeutic strategy for EZ score defined high-risk multiple myeloma patients and overcome resistance to IMiDs. Clinical Epigenetics. 2018. Download the PDF

Summary of the Study

Epigenetic modifications contribute to multiple myeloma (MM) pathogenesis and drug resistance. This study focuses on targeting the polycomb repressive complex 2 (PRC2) using an EZH2 inhibitor and proposes a risk stratification tool to identify responsive patients.

Key findings

  • PRC2 genes are upregulated in proliferative MM cells

  • Treatment with EPZ-6438 (EZH2 inhibitor) leads to:

    • Cell cycle arrest and apoptosis
    • Upregulation of tumor suppressors and B cell transcription factors
    • Repression of MYC
  • Resistance to EZH2i is linked to DNA methylation of PRC2 targets

  • Combination with lenalidomide (IMiD) yields synergistic effects

  • Developed and validated the EZ score, a gene expression–based prognostic tool identifying high-risk patients benefiting from PRC2 inhibition

Important

In this study, Alboukadel Kassambara contributed to the data analysis, specifically in the development and validation of the EZ score, a gene expression–based risk stratifier predicting benefit from EZH2-targeted therapy in high-risk myeloma patients.

Citation

Publication: In Clinical Epigenetics
Date: October 3, 2018
Type: Journal Article
PDF: Download the PDF

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Scientific Contributions

Note

Here are more scientific abstracts authored or co-authored by Alboukadel Kassambara. These contributions span computational biology, bioinformatics, biostatistics, machine learning, and multi-omics, with a focus on immuno-oncology and translational research.

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