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.

Cancers
|May 14, 2022
PubMed

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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