Identification of a three-gene-based prognostic model in multiple myeloma using bioinformatics analysis.

ABSTRACT:

Background

Multiple myeloma (MM), the second most hematological malignancy, has high incidence and remains incurable till now. The pathogenesis of MM is poorly understood. This study aimed to identify novel prognostic model for MM on gene expression profiles.

Methods

Gene expression datas of MM (GSE6477, GSE136337) were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in GSE6477 between case samples and normal control samples were screened by the limma package. Meanwhile, enrichment analysis was conducted, and a protein-protein interaction (PPI) network of these DEGs was established by STRING and cytoscape software. Co-expression modules of genes were built by Weighted Correlation Network Analysis (WGCNA). Key genes were ident

SUBMITTER: Pan Y 

PROVIDER: S-EPMC8247704 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature