Identification of hub genes affecting gestational diabetes mellitus based on GEO database.

This research aimed to obtain gestational diabetes mellitus (GDM) related hub genes, providing new targets for clinical diagnosis and treatment of GDM. The microarray data of GSE9984 and GSE103552 were obtained from the Gene Expression Omnibus (GEO). The dataset GSE9984 contained placental gene expression profiles of 8 GDM patients and four healthy specimens. The dataset GSE103552 contained 20 specimens from GDM patients and 17 normal specimens. The differentially expressed genes (DEGs) were identified by GEO2R online analysis. DAVID database was applied to conduct functional enrichment analysis of the DEGs. The Search Tool for the Retrieval of Interacting Genes (STRING) database was adopted to acquire protein-protein interaction (PPI) networks. A total of 195 up-regulated and 371 down-regulated DEGs were selected in the GSE9984, and total of 191 up-regulated and 229 down-regulated DEGs were selected in the GSE103552. In the two datasets, 24 common differential genes were obtained and named co-DEGs. The Gene Ontology (GO) annotation analysis indicated the DEGs participated in multi-multicellular organism process, endocrine hormone secretion, long-chain fatty acid biosynthetic process, cell division, unsaturated fatty acid biosynthetic process, cell adhesion and cell recognition. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that GSE9984 and GSE103552 were related to vitamin digestion and absorption, tryptophan metabolism, steroid hormone biosynthesis, Ras signaling pathway, protein digestion and absorption, PPAR signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway. PPI was constructed in string database, and six hub genes were selected, including CCNB1, APOA2, AHSG and IGFBP1. Four critical genes were identified to be considered as therapeutic potential biomarkers of GDM, including CCNB1, APOA2, AHSG and IGFBP1.

Circ_0078607 inhibits the progression of ovarian cancer via regulating the miR-32-5p/SIK1 network.

BACKGROUND: Circular RNA (circRNA) has been shown to be involved in the regulation of human disease progression, including ovarian cancer (OC). Circ_0078607 was found to participate in OC progression. But its function and mechanism in OC deserve further exploration. METHODS: The expression levels of circ_0078607, salt-inducible kinase 1 (SIK1) and microRNA (miR)-32-5p were examined by qRT-PCR. And the protein expression levels of SIK1, metastasis marker and apoptosis marker were determined using western blot analysis. EDU staining, colony formation assay, transwell assay and flow cytometry were used to detect the proliferation, migration, invasion and apoptosis of cells. Moreover, dual-luciferase reporter assay was employed to verify the interaction between miR-32-5p and circ_0078607 or SIK1. Xenograft models were constructed to perform in vivo experiments. RESULTS: Circ_0078607 and SIK1 were downregulated in OC tissues and cells. Overexpressed circ_0078607 and SIK1 could inhibit OC cell proliferation, migration, invasion, and promote apoptosis. MiR-32-5p could be sponged by circ_0078607, and its overexpression could reverse the suppressive effect of circ_0078607 on OC progression. Furthermore, SIK1 was a target of miR-32-5p, and circ_0078607 could regulate SIK1 by sponging miR-32-5p. The inhibitory effect of circ_0078607 on OC progression also could be reversed by SIK1 silencing. In vivo experiments showed that circ_0078607 reduced OC tumorigenesis by regulating the miR-32-5p/SIK1 axis. CONCLUSION: Circ_0078607 could serve as a sponge of miR-32-5p to regulate SIK1 expression, thereby inhibiting OC progression.

Regulatory B cells contribute to the impaired antitumor immunity in ovarian cancer patients.

Multiple factors in the tumor microenvironment were found to inhibit antitumor adaptive immune responses, allowing tumor persistence and growth. In this study, ascites from ovarian cancer patients were collected. We observed that a population of interleukin-10(+) B (IL-10(+) B) cells was preferentially enriched in the ascites. This population was associated with naive B cell phenotype or IgM or class-switched memory B cell phenotypes. The frequencies of IL-10(+) B cells were negatively correlated with the frequencies of interferon gamma-producing (IFN-g(+)) CD8(+) T cells and were positively correlated with the frequencies of Foxp3(+) CD4(+) T cells. To examine whether increased IL-10(+) B cells in ascites could directly result in increased suppression of IFN-g production by CD8(+) T cells, we cocultured CD8(+) T cells with autologous blood B cells or ascitic B cells and found that CD8(+) T cells cocultured with ascitic B cells demonstrated significantly suppressed IFN-g production. This suppression was in part mediated by IL-10 as well as low CD80/CD86 expression, since depletion of IL-10 and stimulation of CD28 partially reverted IL-10(+) B cell-mediated suppression. Together, these data demonstrated an additional regulatory mechanism in the tumor microenvironment, which utilizes IL-10(+) B cells.