| Popis: |
Abstract Glioblastoma (GBM) is one of the most lethal primary brain tumor with a poor median survival less than 15 months. Despite the development of the clinical strategies over the decades, the outcomes for GBM patients remain dismal due to the strong proliferation and invasion ability and the acquired resistance to radiotherapy and chemotherapy. Therefore, developing new biomarkers and therapeutic strategies targeting GBM is in urgent need. In this study, gene expression datasets and relevant clinical information were extracted from public cancers/glioma datasets, including TCGA, GRAVENDEEL, REMBRANDT, and GILL datasets. Differentially expressed genes were analyzed and NEK2 was picked as a candidate gene for subsequent validation. Human tissue samples and corresponding data were collected from our center and detected by immunohistochemistry analysis. Molecular biological assays and in vivo xenograft transplantation were performed to confirm the bioinformatic findings. High-throughput RNA sequencing, followed by KEGG analysis, GSEA analysis and GO analysis were conducted to identify potential signaling pathways related to NEK2 expression. Subsequent mechanism assays were used to verify the relationship between NEK2 and NF-κB signaling. Overall, we identified that NEK2 is significantly upregulated in GBM and the higher expression of NEK2 exhibited a poorer prognosis. Functionally, NEK2 knockdown attenuated cell proliferation, migration, invasion, and tumorigenesis of GBM while NEK2 overexpression promoted the GBM progression. Furthermore, High-throughput RNA sequencing and bioinformatics analysis indicated that NEK2 was positively related to the NF-κB signaling pathway in GBM. Mechanically, NEK2 activated the noncanonical NF-κB signaling pathway by phosphorylating NIK and increasing the activity and stability of NIK. In conclusion, NEK2 promoted the progression of GBM through activation of noncanonical NF-κB signaling, indicating that NEK2- NF-κB axis could be a potential drug target for GBM. |
Full text from SpringerLink