| Autor: |
Adebayo OO; Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA., Dammer EB; Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA 30322, USA., Dill CD; Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA., Adebayo AO; Georgia Institute of Technology, Atlanta, GA 30332, USA., Oseni SO; Department of Immunology, Moffitt Cancer Center, Tampa, FL 33612, USA., Griffen TL; Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA., Ohandjo AQ; East-West Collaborative Research, Marietta, GA 30060, USA., Yan F; Department of Community Health and Preventive Medicine, Morehouse School of Medicine, Atlanta, GA 30310, USA., Jain S; Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA., Barwick BG; Winship Cancer Institute, 1365 Clifton Road NE, Atlanta, GA 30322, USA., Singh R; Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA., Boise LH; Winship Cancer Institute, 1365 Clifton Road NE, Atlanta, GA 30322, USA., Lillard JW Jr; Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA. |
| Abstrakt: |
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. |
