Transcriptome Research of Key Modules and Hub Genes Associated with Primary Myelofibrosis by Weighted Co-expression Network Analysis.

Background: This study aimed to identify novel targets of diagnosis, therapy as well as prognosis for primary myelofibrosis (PMF). Methods: : The gene expression profiles of GSE26049 was obtained from GEO dataset, weighted gene co-expression network analysis (WGCNA) was then performed to identify the most related modules with PMF. Subsequently, GO (Gene Ontology), KEGG (Kyoto Encyclopedia Genes and Genomes), GSEA (Gene Set Enrichment Analysis) and PPI (Protein-Protein Interaction) network were conducted to fully understand the detailed information of the green module. Results: : Green module was strongly correlated with PMF disease after WGCNA analysis. 20 genes in green module were identified as hub genes responsible for the progression of PMF. Functional annotation and pathway analysis revealed that these hub genes were primarily enriched in erythrocyte differentiation, transcription factor binding, hemoglobin complex, transcription factor complex and cell cycle et al. Of which, EPB42, CALR, SLC4A1 and MPL had the most correlations with PMF. Conclusions: : This study elucidated that genes EPB42, CALR, SLC4A1 and MPL were significantly more highly expressed in PMF samples than in normal samples. These four genes may be considered candidate prognostic biomarkers and potential therapeutic targets for early stage of PMF. Meanwhile, EPB42 and SLC4A1 were firstly found to be highly correlated with the progression of PMF.