Multivariant Transcriptome Analysis Identifies Modules and Hub Genes Associated with Poor Outcomes in Newly Diagnosed Multiple Myeloma Patients

• Type of Material: Article
• Authors: Olayinka O Adebayo, Morehouse School of Medicine; Eric Dammer, Emory University; Courtney D Dill, Morehouse School of Medicine; Adeyinka O Adebayo, Georgia Institute of Technology; Saheed O Oseni, Moffitt Cancer Center, Tampa; Ti’ara L Griffen, Morehouse School of Medicine; Adaugo Q Ohandjo, East-West Collaborative Research; Fengxia Yan, Morehouse School of Medicine; Sanjay Jain, Morehouse School of Medicine; Benjamin Barwick, Emory University; Rajesh Singh, Morehouse School of Medicine; Lawrence Boise, Emory University; James W Lillard, Morehouse School of Medicine
• Language: English
• Date: 2022-05-01
• Publisher: MDPI
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2022 by the authors.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.3390/cancers14092228
• Title of Journal or Parent Work: CANCERS
• Volume: 14
• Issue: 9
• Grant/Funding Information: Our study was funded in part by MSM/TU/UAB Partnership grant with the National Cancer Institute U54CA118638 and the Ruth L. Kirschstein National Research Service Award (NRSA) (T32HL103104), which provides grants to institutions to develop research training opportunities in cancer research for predoctoral and postdoctoral fellows. Additionally, facilities were supported by MSM (1G12RR026250-03; and 1C06 RR18386). BGB was supported by an ASH Scholar Award and Institutional Funds from Winship Cancer Institute.
• Keywords: chemoresistance; WGCNA; NETWORKS; ADHESION; Science & Technology; STEM-CELLS; PROLIFERATION; ANTIGENS; Life Sciences & Biomedicine; Oncology; EXPRESSION; BINDING; COEXPRESSION; Kaplan-Meier; CHEMOTHERAPY; multiple myeloma; log-rank; ROC; TRANSPLANTATION
• Research Categories: Chemistry, Biochemistry; Health Sciences, Medicine and Surgery; Biology, Microbiology

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.