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RNA-Sequencing-Based Transcriptomic Score with Prognostic and Theranostic Values in Multiple Myeloma
Elina Alaterre1, Veronika Vikova1, Alboukadel Kassambara1,2
1Institute of Human Genetics, UMR 9002 CNRS-UM, 34395 Montpellier, France.
Journal of Personalized Medicine
|October 23, 2021
Summary
A new gene risk score from RNA-seq data helps predict outcomes for multiple myeloma (MM) patients undergoing stem cell transplantation. High-risk patients show distinct gene expression patterns, guiding precision medicine strategies.
Area of Science:
- Hematological Oncology
- Genomics
- Biomedical Research
Background:
- Multiple myeloma (MM) is a prevalent hematological cancer driven by malignant plasma cell proliferation.
- Genome-wide expression profiling (GEP) using DNA microarrays has significantly advanced MM research and clinical applications.
- GEP in MM aids in patient stratification, risk assessment, target identification, and understanding treatment resistance.
Purpose of the Study:
- To develop and validate a prognostic gene risk score for newly diagnosed multiple myeloma patients.
- To identify key biological pathways and gene expression patterns associated with high-risk MM.
- To explore the correlation of the gene risk score with somatic mutations and targeted therapy responses.
Main Methods:
- Construction of a 267-gene risk score using RNA-sequencing (RNA-seq) data.
- Validation of the risk score in two independent cohorts of newly diagnosed MM patients (n=674 and n=76) treated with high-dose Melphalan and autologous stem cell transplantation.
- Analysis of gene expression pathways, somatic mutation profiles, and targeted treatment responses.
Main Results:
- The RNA-seq-based gene risk score demonstrated significant prognostic value in both independent cohorts.
- High-risk patients exhibited expression of genes in pathways including interferon response, cell proliferation, hypoxia, IL-6 signaling, stem cell genes, MYC, and epigenetic deregulation.
- The risk score correlated with specific MM somatic mutations and responses to targeted agents like EZH2, MELK, and Aurora kinase inhibitors.
Conclusions:
- The developed gene risk score is a valuable prognostic tool for newly diagnosed MM patients.
- Gene expression profiles in high-risk MM provide insights into disease pathophysiology and potential therapeutic vulnerabilities.
- This RNA-seq-based approach supports the development of precision medicine strategies for multiple myeloma treatment.

