Analysis of key genes and their functions in placental tissue of patients with gestational diabetes mellitus.

BACKGROUND: This study was aimed at screening out the potential key genes and pathways associated with gestational diabetes mellitus (GDM). METHODS: The GSE70493 dataset used for this study was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in the placental tissue of women with GDM in relation to the control tissue samples were identified and submitted to protein-protein interaction (PPI) network analysis and subnetwork module mining. Functional enrichment analyses of the PPI network and subnetworks were subsequently carried out. Finally, the integrated miRNA-transcription factor (TF)-DEG regulatory network was analyzed. RESULTS: In total, 238 DEGs were identified, of which 162 were upregulated and 76 were downregulated. Through PPI network construction, 108 nodes and 278 gene pairs were obtained, from which chemokine (C-X-C motif) ligand 9 (CXCL9), CXCL10, protein tyrosine phosphatase, receptor type C (PTPRC), and human leukocyte antigen (HLA) were screened out as hub genes. Moreover, genes associated with the immune-related pathway and immune responses were found to be significantly enriched in the process of GDM. Finally, miRNAs and TFs that target the DEGs were predicted. CONCLUSIONS: Four candidate genes (viz., CXCL9, CXCL10, PTPRC, and HLA) are closely related to GDM. miR-223-3p, miR-520, and thioredoxin-binding protein may play important roles in the pathogenesis of this disease.

Identification of potential crucial genes associated with early-onset pre-eclampsia via a microarray analysis.

AIM: This study aimed to identify potential key genes related to early-onset pre-eclampsia (EOPET), and to obtain a better understanding of the molecular mechanisms of this disease. METHODS: The microarray dataset GSE44711 was obtained from the Gene Expression Omnibus, including eight chorionic villi samples from EOPET placentas and eight normal controls. The differentially expressed genes (DEG) were identified using the LIMMA package, and their potential functions were predicted by Gene Ontology (GO) enrichment analysis. Furthermore, protein-protein interactions (PPI) were obtained from the STRING database, and the PPI network was visualized by Cytoscape software. Then, significant modules were screened out from the PPI network, and GO enrichment analysis for DEG in modules was performed. Also, the potential transcription factors (TF) regulating DEG in modules were predicted, and TF-DEG network was visualized by Cytoscape. RESULTS: A total of 270 upregulated and 200 downregulated DEG were identified. A set of DEG was related to functions such as female pregnancy and hormone metabolic process (e.g. NGF). In PPI network modules, some DEG (e.g. SERPINE1 and FN1) were significantly associated with anatomical structure morphogenesis, and some other DEG (e.g. GZMA) were relevant to the immune system process. Furthermore, SERPINE1, NGF, and FN1 interacted with each other and were regulated by RELA. CONCLUSION: The DEG related to hormone metabolic process (e.g. NGF), anatomical structure morphogenesis (e.g. SERPINE1 and FN1), and immune system process (e.g. GZMA) are predicted to play significant roles in the progress of EOPET, which will be confirmed by experiments in future.

Siva 1 inhibits proliferation, migration and invasion by phosphorylating Stathmin in ovarian cancer cells.

Ovarian cancer is one of the most common types of gynecologic malignant tumor, with high incidence and high mortality rates. It is difficult to diagnose ovarian cancer early due to the complex structure and function of the ovaries. Siva 1 is a well-known pro-apoptosis protein that functions in multiple types of cancer cells: There are several studies demonstrating that Siva 1 arrests apoptosis and facilitates cancer development in osteosarcoma and non-small cell lung cancer. Whether Siva 1 functions in ovarian cancer remains unknown. In the present study, it was established that Siva 1 was stably overexpressed in ovarian cancer cell lines, and demonstrated that the overexpression of Siva 1 inhibited proliferation, promoted apoptosis and suppressed migration and invasion by facilitating phosphorylation of Stathmin and polymerization of α-tubulin in ovarian cancer cells. These data provide specific novel insights into the molecular mechanism of ovarian cancer, and may be of significance for the clinical diagnosis and therapy of ovarian cancer.

Sphingosine kinase 1 enhances the invasion and migration of non-small cell lung cancer cells via the AKT pathway.

Sphingosine kinase 1 (SphK1) has been shown to play an important role in the progression of a number of human cancers. It has been reported that the expression of SphK1 is greatly elevated in non-small cell lung cancer (NSCLC) tissues. However, its role and underlying mechanisms in NSCLC have not been fully elucidated. In the present study, we found that SphK1 was highly expressed in NSCLC cells. Overexpression of SphK1 promoted the invasion and migration of NSCLC cells, while knockdown of SphK1 suppressed the invasion and migration. Furthermore, we demonstrated that SphK1 decreased the protein level of E-cadherin, yet increased the protein level of Snail. In addition, SphK1 was able to stimulate the activation of AKT. Inhibition of the AKT pathway attenuated the biological functions of NSCLC cells induced by overexpression of SphK1. Taken together, our findings suggest that SphK1 can enhance the invasion and migration of NSCLC cells via activation of the AKT pathway and regulation of E-cadherin and Snail expression. Thus, SphK1 could be a potential target for the detection and treatment of NSCLC.