Background: Genistein, a flavonoid in legumes and some herbal medicines, has various biological actions. Previous studies have shown that genistein decreased airway inflammation in allergic asthma. However, studies on how genistein affects immunoreactions in asthma are very limited. Objective: It was the aim of this study to investigate the effect of genistein on T helper 1 (Th1)/Th2 cytokines in a murine asthma model and to explore its underlying mechanisms. Methods: The asthma model was set up both in vivo and in vitro: the mice were divided into four groups in vivo, i.e. control group, ovalbumin-sensitized (OVA) group, Gen20 group (20 mg/kg genistein) and Gen40 group (40 mg/kg genistein), and into three groups in vitro, i.e. control group, OVA group, genistein group. Changes in lung histology were observed and concentrations of interleukin-4, interleukin-5 and interferon-γ in bronchoalveolar lavage fluid and serum were measured by enzyme-linked immunosorbent assay. The mRNA expression of GATA binding protein 3 (GATA-3), signal transducer and activator of transcription 6 (STAT-6) and T-box transcription factor (T-bet) in the lungs and CD4+ T cells of each group were detected by real-time PCR and the corresponding proteins were detected by Western blot. Results: The results showed that genistein attenuated OVA-induced airway inflammation, decreased Th2-type cytokines and increased Th1-type cytokines. Additionally, our data suggested that genistein may modulate the Th1/Th2 reaction by inhibiting GATA-3 and STAT-6 production while increasing T-bet production. Conclusion: Genistein may modulate the immunomodulatory actions caused by Th1/Th2 cytokines in asthma, at least partially, by the down-regulation of GATA-3 and STAT-6 and the up-regulation of T-bet.

Although an association between obesity and the occurrence of renal cell carcinoma (RCC) has been identified, the mechanism by which obesity functions to increase this risk of cancer remains unclear. Leptin, visfatin, apelin, resistin and adiponectin are peptide hormones secreted by adipocytes; it is considered that these may affect RCC development by exerting effects on proliferation, cell growth and inflammation. The aim of the present study was to investigate the association between the aforementioned adipokine genes and clear cell RCC (CC-RCC). The GSE6344 dataset was downloaded from the Gene Expression Omnibus database, and the relative expression levels of the adipokine genes were analyzed. To verify the results of the mRNA microarray, 77 paired samples of CC-RCC and corresponding adjacent normal tissue were allocated into two groups. The extraction of total RNA was conducted, and the mRNA expression of adipokine genes was analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The data from the GSE6344 dataset indicated that the expression of visfatin and apelin was upregulated (P<0.0001 and P<0.01, respectively), and adiponectin was downregulated (P<0.001) in the CC-RCC tissues compared with the adjacent normal tissues. The data from RT-qPCR demonstrated that visfatin and resistin gene expression was increased (P<0.01 and P<0.05, respectively) in the CC-RCC tissues. Furthermore, the mRNA expression level of leptin and adiponectin in the adjacent normal tissue was higher than those in the cancer tissue (P<0.01). The current study verifies that visfatin and adiponectin are associated with an increased risk of CC-RCC, which presents further insights into the molecular mechanisms of CC-RCC tumorigenesis.

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.