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Gene expression profiling as a prognostic tool in multiple myeloma
Harmony Black1, Siobhan Glavey1,2
1Department of Haematology, Beaumont Hospital, Dublin D09 V2N0, Ireland.
Cancer Drug Resistance (Alhambra, Calif.)
|May 18, 2022
Summary
Gene expression profiling (GEP) offers new ways to predict outcomes for multiple myeloma (MM) patients. These molecular signatures can improve personalized medicine and combat drug resistance, outperforming current methods.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Multiple myeloma (MM) is a highly variable plasma cell cancer.
- Current treatments face challenges with therapy refractoriness and relapse.
- Improved prognostication and targeted therapies are crucial for enhancing overall survival (OS).
Purpose of the Study:
- To review the limitations of existing prognostic tools in MM.
- To highlight the emerging role of gene expression profiling (GEP) in MM diagnostics.
- To discuss GEP's potential in developing personalized medicine for drug resistance.
Main Methods:
- Review of recent gene expression profiling (GEP) studies in multiple myeloma.
- Analysis of identified gene signatures for predicting overall survival (OS).
- Comparison of GEP-based predictors with current clinical prognostic tools.
Main Results:
- GEP studies have revealed the molecular landscape of MM.
- Novel gene signatures have been identified that predict OS.
- These GEP-based signatures demonstrate superior performance compared to existing clinical predictors.
Conclusions:
- Gene expression profiling (GEP) shows significant promise for improving MM prognostication.
- GEP can aid in the development of personalized medicine strategies.
- Targeted therapies informed by GEP may help overcome drug resistance and improve patient outcomes.
