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Multivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed
Olayinka O Adebayo1, Eric B Dammer2, Courtney D Dill1
1Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA.
Abstract:
The molecular mechanisms underlying chemoresistance in some newly diagnosed multiple myeloma (MM) patients receiving standard therapies (lenalidomide, bortezomib, and dexamethasone) are poorly understood. Identifying clinically relevant gene networks associated with death due to MM may uncover novel mechanisms, drug targets, and prognostic biomarkers to improve the treatment of the disease. This study used data from the MMRF CoMMpass RNA-seq dataset (N = 270) for weighted gene co-expression network analysis (WGCNA), which identified 21 modules of co-expressed genes. Genes differentially expressed in patients with poor outcomes were assessed using two independent sample t-tests (dead and alive MM patients). The clinical performance of biomarker candidates was evaluated using overall survival via a log-rank Kaplan-Meier and ROC test. Four distinct modules (M10, M13, M15, and M20) were significantly correlated with MM vital status and differentially expressed between the dead (poor outcomes) and the alive MM patients within two years. The biological functions of modules positively correlated with death (M10, M13, and M20) were G-protein coupled receptor protein, cell-cell adhesion, cell cycle regulation genes, and cellular membrane fusion genes. In contrast, a negatively correlated module to MM mortality (M15) was the regulation of B-cell activation and lymphocyte differentiation. MM biomarkers CTAG2, MAGEA6, CCND2, NEK2, and E2F2 were co-expressed in positively correlated modules to MM vital status, which was associated with MM's lower overall survival.
Insights
This study identified gene networks linked to mortality in multiple myeloma (MM) patients. Key biomarkers like CTAG2 and MAGEA6 were associated with poorer survival, offering potential new therapeutic targets.
Area of Science:
- Genomics
- Molecular Biology
- Oncology
Background:
- Chemoresistance mechanisms in newly diagnosed multiple myeloma (MM) patients receiving standard therapies are not fully understood.
- Identifying gene networks associated with MM mortality can reveal novel drug targets and prognostic biomarkers.
Purpose of the Study:
- To identify gene co-expression modules and biomarkers associated with survival outcomes in multiple myeloma.
- To uncover molecular mechanisms contributing to chemoresistance and MM progression.
Main Methods:
- Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-seq data from 270 MM patients.
- Differential gene expression analysis and survival analysis (Kaplan-Meier, ROC) were used to evaluate biomarker candidates.
Main Results:
- Four gene modules (M10, M13, M15, M20) significantly correlated with MM patient vital status.
- Modules M10, M13, and M20 (positively correlated with death) involve G-protein coupled receptors, cell-cell adhesion, cell cycle regulation, and membrane fusion.
- Module M15 (negatively correlated with death) is linked to B-cell activation and lymphocyte differentiation.
- Biomarkers CTAG2, MAGEA6, CCND2, NEK2, and E2F2 were co-expressed in modules associated with poorer overall survival.
Conclusions:
- Specific gene networks and biomarkers are significantly associated with survival in multiple myeloma patients.
- These findings highlight potential therapeutic targets and prognostic markers for improving MM treatment strategies.
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