A DNA Repair Pathway Score Predicts Survival in Human Multiple Myeloma

Scientific Contributions by Alboukadel Kassambara

A DNA repair score (DRscore) derived from prognostic gene signatures accurately predicts survival in multiple myeloma and may guide personalized treatment strategies targeting synthetic lethality.

Scientific Abstracts
Author
Affiliation
Published

May 15, 2014

Modified

May 21, 2025

Keywords

Alboukadel Kassambara, DNA repair, multiple myeloma, risk score, synthetic lethality, oncotarget, prognostic biomarkers

Kassambara A, Gourzones-Dmitriev C, Sahota S, Rème T, Moreaux J, Goldschmidt H, Constantinou A, Pasero P, Hose D, Klein B. A DNA Repair Pathway Score Predicts Survival in Human Multiple Myeloma: The Potential for Therapeutic Strategy. Oncotarget. 2014. Download the PDF

Summary of the Study

DNA repair is critical for maintaining genomic integrity and regulating transcription and replication. Multiple interlinked pathways exist to address different DNA damage types such as double strand breaks and nucleotide lesions. In cancer, deregulation of these repair mechanisms contributes to genomic instability and drug resistance.

In this study, we developed a DNA repair score (DRscore) using a consensus list of 84 DNA repair genes. Of these, 22 had significant prognostic value for both event-free survival (EFS) and overall survival (OS) in untreated multiple myeloma (MM) patients:

  • 17 genes correlated with poor prognosis
  • 5 genes correlated with good prognosis

The composite DRscore effectively stratified patients by survival risk and may help identify tumors dependent on specific DNA repair pathways. This opens the door for synthetic lethality-based strategies targeting those vulnerabilities in MM.

Important

In this study, Alboukadel Kassambara was the first author, performing the analysis and interpretation of the data. He developed the DNA repair score (DRscore), performed the gene expression and survival analysis, and contributed to wrote the manuscript, establishing a prognostic model with therapeutic implications for multiple myeloma.

Citation

Publication: In Oncotarget
Date: May 15, 2014
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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