Prognostic value of Kinesin‐4 family genes mRNA expression in early‐stage pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy

Background The aim of this study was to investigate the potential prognostic value of Kinesin‐4 family genes mRNA expression in early‐stage pancreatic ductal adenocarcinoma (PDAC) patients after pancreaticoduodenectomy. Methods Kaplan‐Meier survival analysis method with log‐rank test and Cox proportional hazards regression analysis were performed to figure out the association between Kinesin‐4 family genes expression and PDAC patients overall survival time. Joint‐effect survival analysis and stratified survival analysis were carried out to assess the prognosis prediction value of prognosis‐related gene. Nomogram was constructed for the individualized prognosis prediction. In addition, we had used the gene set enrichment analysis and genome‐wide co‐expression analysis to further explore the potential mechanism. Results KIF21A expression level was significantly associated with PDAC patient clinical prognosis outcome and patient with a high expression of KIF21A would have a shorter overall survival time. The prognosis prediction significance of KIF21A was well validated by the joint‐effect survival analysis, stratified survival analysis, and nomogram. Meanwhile, the gene set enrichment analysis and genome‐wide co‐expression analysis revealed that KIF21A might involve in DNA damage and repair, transcription and translation process, post‐translation protein modification, cell cycle, carcinogensis genes and pathways. Conclusions Our current research demonstrated that KIF21A could serve as a potential prognostic biomarker for patient with early‐stage PDAC after pancreaticoduodenectomy. In this study, we investigated the potential prognostic value of Kinesin‐4 family genes mRNA expression in early‐stage pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy. We established the prognostic significance of KIF21A and inferred the possible mechanism by gene set enrichment analysis and genome‐wide co‐expression analysis.