Malignant tumors were considered as the leading causes of mortality globally. More and more studies found that dysregulated genes played an important role in the carcinogenesis. The aim of this study was to explore the significance of KPNA2 in human five major cancers including non-small cell lung cancer (NSCLC), gastric cancer, colorectal cancer, breast cancer, hepatocellular carcinoma and bladder cancer based on bioinformatics analysis.
The data were collected and comprehensive analyzed based on multiple databases. KPNA2 mRNA expression in 6 major cancers were investigated in Oncomine, the human protein atlas and GEPIA databases. The mutation status of KPNA2 in the 6 major cancers were evaluated by online data analysis tool Catalog of Somatic Mutations in Cancer (COSMIC) and cBioPortal. Co-expressed genes with KPNA2 were identified by using LinkedOmics and made pairwise correlation by Cancer Regulome tools. Protein-protein interaction (PPI) network relevant to KPNA2 was constructed by STRING database and KEGG pathway of the included proteins of the PPI network was explored and demonstrated by circus plot. Survival analysis relevant KPNA2 of the 6 cancers were performed by GEPIA online data analysis tool based on TCGA database.
Compared with paired normal tissue, KPNA2 mRNA was up-regulated in all of the 6 type cancers. KPNA2 mutations especially missense substitution were widely identified in 6 major cancers and interact with different genes in different cancer types. Genes involved in PPI network were mainly enriched in p53 signaling pathway, cell cycle, viral carcinogenesis, Foxo signaling pathway and et c. KPNA2 protein was mainly localized to the nucleoplasm and cytosol in cancer cells. Immunohistochemistry assay indicated that KPNA2 protein was also positive expressed in nucleoplasm with brownish yellow staining. Overall survival (OS) and progression free survival (PFS) were generally different between KPNA2 high and low expression groups.
KPNA2 was widely dysregulated and mutated in carcinomas and correlated with the patients prognosis which may be potential target for cancer treatment and biomarker for prognosis.