biostudies-literatureAdebayo OOMSM/TU/UABNCRR NIH HHSMSMNHLBI NIH HHSNIMHD NIH HHSNational Cancer InstituteNCI NIH HHSRuth L. Kirschstein National Research Service AwardWinship Cancer Institute2228https://www.ebi.ac.uk/biostudies/studies/S-EPMC9104534biostudies-literatureUnknown14(9)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 <i>t</i>-tests (dead and alive MM patients). The clinical performance of biomarker candidates was evaluated using overall CancersMultivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed Multiple Myeloma Patients.PMC9104534C06 RR018386G12MD0076021G12RR026250-03T32 HL103104U54 CA118638T32HL1031041C06 RR18386U54CA118638U54MD007602Oseni SOJain SBarwick BGDill CDAdebayo AOOhandjo AQLillard JWGriffen TLAdebayo OODammer EBSingh RYan FBoise LHfalseMultivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed Multiple Myeloma Patients.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 <i>t</i>-tests (dead and alive MM patients). The clinical performance of biomarker candidates was evaluated using overall 2022-01-01T00:00:00Z2022 Apr2026-04-08T09:37:39.379Z2024-11-07T13:40:26.83ZS-EPMC91045343556535610.3390/cancers14092228