Astrocyte elevated gene-1 (AEG-1) is a recently discovered oncogene that has been reported to be highly expressed in various types of malignant tumors, including renal cell carcinoma. However, the precise role of AEG-1 in renal cancer cell proliferation and apoptosis has not been clarified. In this study, we transfected the renal cancer cell line Caki-1 with a plasmid expressing AEG-1 short hairpin RNA (shRNA) and obtained cell colonies with stable knockdown of AEG-1. We found that AEG-1 down-regulation inhibited cell proliferation and colony formation and arrested cell cycle progression at the sub-G1 and G0/G1 phase. Western blot analysis indicated that the expression of proliferating cell nuclear antigen (PCNA), cyclin D1 and cyclin E were significantly reduced following AEG-1 down-regulation. In addition, AEG-1 knockdown led to the appearance of apoptotic bodies in renal cancer cells, and the ratio of apoptotic cells significantly increased. Expression of the anti-apoptotic factor Bcl-2 was dramatically reduced, whereas the pro-apoptotic factors Bax, caspase-3 and poly (ADP-ribose) polymerase (PARP) were significantly activated. Finally, AEG-1 knockdown in Caki-1 cells remarkably suppressed cell proliferation and enhanced cell apoptosis in response to 5-fluorouracil (5-FU) treatment, suggesting that AEG-1 inhibition sensitizes Caki-1 cells to 5-FU. Taken together, our data suggest that AEG-1 plays an important role in renal cancer formation and development and may be a potential target for future gene therapy for renal cell carcinoma.

About a third of patients with kidney cancer experience recurrence or cancer-related progression. Clinically, kidney cancer prognoses may be quite different, even in patients with kidney cancer at the same clinical stage. Therefore, there is an urgent need to screen for kidney cancer prognosis biomarkers. Differentially expressed genes (DEGs) were identified using kidney cancer RNA sequencing data from the Gene Expression Omnibus (GEO) database. Biomarkers were screened using random forest (RF) and support vector machine (SVM) models, and a multigene signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. Univariate and multivariate Cox regression analyses were performed to explore the relationships between clinical features and prognosis. Finally, the reliability and clinical applicability of the model were validated, and relationships with biological pathways were identified. Western blots were also performed to evaluate gene expression. A total of 50 DEGs were obtained by intersecting the RF and SVM models. A seven-gene signature (RNASET2, EZH2, FXYD5, KIF18A, NAT8, CDCA7, and WNT7B) was constructed by LASSO regression. Univariate and multivariate Cox regression analyses showed that the seven-gene signature was an independent prognostic factor for kidney cancer. Finally, a predictive nomogram was established in The Cancer Genome Atlas (TCGA) cohort and validated internally. In tumor tissue, RNASET2 and FXYD5 were highly expressed and NAT8 was lowly expressed at the protein and transcription levels. This model could complement the clinicopathological characteristics of kidney cancer and promote the personalized management of patients with kidney cancer.

Built upon conservation of resource theory and self-determination theory, this study explores boundary conditions under which family-supportive supervisors (FSSs) influence employee-perceived leader–member exchange (LMX) and work–family enrichment (WFE). Findings from this research reveal that FSSs positively relate to employee perceptions of LMX and WFE. Employees’ collectivistic self-construals moderate the effect of FSSs on LMX but not on WFE. Implications and future research directions are discussed.

In FHF, a large number of DCs mature, express CD86, and activate MHC class II molecular pathways to induce a T cell response, and the AKT pathway is activated.

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