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RNA-Sequencing-Based Transcriptomic Score with Prognostic and Theranostic Values in Multiple Myeloma

Abstract : Multiple myeloma (MM) is the second most frequent hematological cancer and is characterized by the clonal proliferation of malignant plasma cells. Genome-wide expression profiling (GEP) analysis with DNA microarrays has emerged as a powerful tool for biomedical research, generating a huge amount of data. Microarray analyses have improved our understanding of MM disease and have led to important clinical applications. In MM, GEP has been used to stratify patients, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance. In this study, we built a gene risk score for 267 genes using RNA-seq data that demonstrated a prognostic value in two independent cohorts (n = 674 and n = 76) of newly diagnosed MM patients treated with high-dose Melphalan and autologous stem cell transplantation. High-risk patients were associated with the expression of genes involved in several major pathways implicated in MM pathophysiology, including interferon response, cell proliferation, hypoxia, IL-6 signaling pathway, stem cell genes, MYC, and epigenetic deregulation. The RNA-seq-based risk score was correlated with specific MM somatic mutation profiles and responses to targeted treatment including EZH2, MELK, TOPK/PBK, and Aurora kinase inhibitors, outlining potential utility for precision medicine strategies in MM.
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https://hal.umontpellier.fr/hal-03639307
Contributeur : Nathalie Salvy-Córdoba Connectez-vous pour contacter le contributeur
Soumis le : mardi 12 avril 2022 - 17:38:24
Dernière modification le : vendredi 9 septembre 2022 - 10:20:08
Archivage à long terme le : : mercredi 13 juillet 2022 - 19:31:24

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Distributed under a Creative Commons Paternité 4.0 International License

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Elina Alaterre, Veronika Vikova, Alboukadel Kassambara, Angélique Bruyer, Nicolas Robert, et al.. RNA-Sequencing-Based Transcriptomic Score with Prognostic and Theranostic Values in Multiple Myeloma. Journal of Personalized Medicine, MDPI, 2021, 11 (10), pp.988. ⟨10.3390/jpm11100988⟩. ⟨hal-03639307⟩

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