BACKGROUND: The transcriptomic signature has not been fully elucidated in PV, as well as mRNA markers for clinical variables (thrombosis, leukemic transformation, survival, etc.). We attempted to reveal and validate crucial co-expression modules and marker mRNAs correlating with polycythemia vera (PV) by weighted gene co-expression network analysis (WGCNA). MATERIAL AND METHODS: The GSE57793/26014/61629 datasets were downloaded from Gene Expression Omnibus (GEO) database and integrated into one fused dataset. By R software and 'WGCNA' package, the PV-specific co-expression module was identified, the pathway enrichment profile of which was obtained by over-representation analysis (ORA). Protein-protein interaction (PPI) network and hub gene analysis identified MAPK14 as our target gene. Then the distribution of MAPK14 expression in different disease/mutation types, were depicted based on external independent datasets. Genome-scale correlation analysis revealed the association of MAPK14 and JAK/STAT family genes. Then gene set enrichment analysis (GSEA) was performed to detect the activated and suppressed pathways associating with MAPK14 expression. Moreover, GSE47018 dataset was utilized to compare clinical variables (thrombosis, leukemic transformation, survival, etc.) between MAPK14-high and MAPK14-low groups. RESULTS: An integrated dataset including 177 samples (83 PV, 35 ET, 17 PMF and 42 normal donors) were inputted into WGCNA. The 'tan' module was identified as the PV-specific module (R = 0.56, p = 8e-16), the genes of which were dominantly enriched in pro-inflammatory pathways (Toll-like receptor (TLR)/TNF signaling, etc.). MAPK14 is identified as the top hub gene in PV-related PPI network with the highest betweenness. External datasets validated that the MAPK14 expression was significantly higher in PV than that of essential thrombocytosis (ET)/primary myelofibrosis (PMF) patients and normal donors. JAK2 homozygous mutation carriers have higher level of MAPK14 than that of other mutation types. The expression of JAK/STAT family genes significantly correlated with MAPK14, which also contributed to the activation of oxidated phosphorylation, interferon-alpha (IFNα) response and PI3K-Akt-mTOR signaling, etc. Moreover, MAPK14-high group have more adverse clinical outcomes (splenectomy, thrombosis, disease aggressiveness) and inferior survival than MAPK14-low group. CONCLUSION: MAPK14 over-expression was identified as a transcriptomic feature of PV, which was also related to inferior clinical outcomes. The results provided novel insights for biomarkers and therapeutic targets for PV.