Human epididymis protein 4 promotes P­glycoprotein­mediated chemoresistance in ovarian cancer cells through interactions with Annexin II.

The aim of the present study was to investigate the effects of human epididymis protein 4 (HE4) on drug resistance and its underlying mechanisms. The associations among proteins were detected by immunoprecipitation and immunofluorescence assays. Then, stably transfected cell lines CAOV3­HE4­L and CAOV3­A2­L expressing HE4 short hairpin (sh)RNAs and ANXA2 shRNAs, respectively, were constructed. MTT assay, immunocytochemistry, western blotting, reverse transcription­quantitative polymerase chain reaction (RT­qPCR) and flow cytometry were employed to examine drug sensitivity, as well as the expression and activity of P­glycoprotein (P­gp). HE4 and P­gp in epithelial ovarian cancer tissues were assessed via immunohistochemistry. MicroRNAs that targeted the P­gp gene, ABCB1, were predicted using bioinformatics methods, and their expression was evaluated by RT­qPCR. The common signaling pathways shared by HE4, ANXA2 and P­gp were selected by Gene Set Enrichment Analysis (GSEA). The interaction of HE4, ANXA2 and P­gp were confirmed. P­gp expression was positively associated with HE4 and ANXA2 expression, respectively. Moreover, it was observed that there was no significant rescue of P­gp expression in CAOV3­A2­L cells following the administration of active HE4 protein. In addition, the expression of HE4 and P­gp in ovarian cancer tissues of drug­resistant patients were higher compared with that of the drug­sensitive group (P<0.05). Furthermore, the results revealed that hsa­miR­129­5p was significantly increased accompanied by decreased HE4 or ANXA2 expression and P­gp expression in CAOV3­HE4­L and CAOV3­A2­L cells. GSEA analyses disclosed that HE4, ANXA2 and P­gp genes were commonly enriched in the signaling pathway involved in regulating the actin cytoskeleton. These results indicated that HE4 promotes P­gp­mediated drug resistance in ovarian cancer cells through the interactions with ANXA2, and the underlying mechanism may be associated with decreased expression of hsa­miR­129­5p and dysregulation of the actin cytoskeleton signaling pathway.

Systematic profiling of alternative splicing signature reveals prognostic predictor for cervical cancer.

AIM: Cervical cancer is a common malignant carcinoma of the gynecological tract with high morbidity and mortality. Therefore, it is crucial to elucidate the pathogenesis, prevention, diagnosis and prognosis of cervical cancer by searching for the involved key genes. METHOD: In this study, the alternative splicing (AS) events of 253 patients with cervical cancer were analyzed, and 41,766 AS events were detected in 9961 genes. Univariate analysis was performed to screen prognostic AS events. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to identify the pathways in which these AS events were involved. RESULTS: We found that exon skip (ES) is the main AS event in patients with cervical cancer. There was pronounced consistency between the genes involved in overall survival and those involved in recurrence. At the same time, we found that a gene may exhibit several different types of AS events, and these different AS events may be related to prognosis. Four characteristic genes, HSPA14, SDHAF2, CAMKK2 and TM9SF1, that can be used as prognostic markers for cervical cancer were selected. CONCLUSION: The importance of AS events in the development of cervical cancer and prediction of prognosis was revealed by a large amount of data at the whole genome level, which may provide a potential target for cervical cancer treatment. We also provide a new method for exploring the pathogenesis of cervical cancer to determine clinical treatment and prognosis more accurately.

TMEFF1 overexpression and its mechanism for tumor promotion in ovarian cancer.

BACKGROUND: Transmembrane protein with epidermal growth factor-like and two follistatin-like domains 1 (TMEFF1) has an anticarcinogenic effect in brain tumors. However, little is known about the role of TMEFF1 in epithelial ovarian cancer (EOC). MATERIALS AND METHODS: TMEFF1 expression in EOC was detected by immunohistochemistry; its relationship with clinical pathological parameters and its influence on prognosis were analyzed. The MTT, scratch, Transwell assays, and flow cytometry were used to assess the malignant behavior of ovarian cancer cell. Changes in node proteins in MAPK and PI3K/AKT signaling pathways and the expression of epithelial-mesenchymal transformation markers were measured by Western blot. The regulatory effect of p53 on TMEFF1 was verified by chromatin immunoprecipitation (ChIP) assay and Western blot. RESULTS: TMEFF1 expression was higher in the EOC group than in the borderline and benign tumor groups and normal ovary group; its high expression was significantly related to International Federation of Gynecology and Obstetrics stage (P=0.024) and independently predicted shorter overall survival (P<0.01). TMEFF1 overexpression in ovarian cancer cells induced increased cellular proliferation, migration, and invasion but reduced apoptosis. In addition, the percentage of phosphorylated node proteins in MAPK and PI3K/AKT signaling pathways increased significantly. The expression of E-cadherin decreased but that of vimentin and N-cadherin increased. After the addition of MAPK (PD98059) and PI3K (GDC-0941) pathway inhibitors, ovarian cancer cells overexpressing TMEFF1 showed suppressed malignant behavior. TMEFF1 protein expression in an ovarian cancer cell lines (CAOV3 and ES-2) was downregulated after the inhibition of TP53. The transcription factor, p53, bound the promoter region of the TMEFF1 gene according to ChIP. CONCLUSION: TMEFF1 is a carcinogenic gene in ovarian cancer and can be regulated by p53 transcription. Through MAPK and PI3K/AKT signaling pathways, TMEFF1 promotes the malignant behavior in EOC. Therefore, TMEFF1 may be considered as a potential therapeutic target for ovarian cancer.

Identification of molecular marker associated with ovarian cancer prognosis using bioinformatics analysis and experiments.

BACKGROUND: Ovarian cancer is one of the three major malignant tumors of the female reproductive system, and the mortality associated with ovarian cancer ranks first among gynecologic malignant tumors. The pathogenesis of ovarian cancer is not yet clearly defined but elucidating this process would be of great significance for clinical diagnosis, prevention, and treatment. For this study, we used bioinformatics to identify the key pathogenic genes and reveal the potential molecular mechanisms of ovarian cancer; we used immunohistochemistry to validate them. METHODS: We analyzed and integrated four gene expression profiles (GSE14407, GSE18520, GSE26712, and GSE54388), which were downloaded from the Gene Expression Omnibus (GEO) database, with the aim of obtaining a common differentially expressed gene (DEG). Then, we performed Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). We then established a protein-protein interaction (PPI) network of the DEGs through the Search Tool for the Retrieval of Interacting Genes (STRING) database and selected hub genes. Finally, survival analysis of the hub genes was performed using a Kmplotter online tool. RESULTS: A total of 226 DEGs were detected after the analysis of the four gene expression profiles; of these, 87 were upregulated genes and 139 were downregulated. GO analysis results showed that DEGs were significantly enriched in biological processes including the G2/M transition of the mitotic cell cycle, the apoptotic process, cell proliferation, blood coagulation, and positive regulation of the canonical Wnt signaling pathway. KEGG analysis results showed that DEGs were particularly enriched in the cell cycle, the p53 signaling pathway, the Wnt signaling pathway, the Ras signaling pathway, the Rap1 signaling pathway, and tyrosine metabolism. We selected 50 hub genes from the PPI network, which had 147 nodes and 655 edges, and 30 of them were associated with the prognosis of ovarian cancer. We performed immunohistochemistry on phosphoserine aminotransferase 1 (PSAT1). PSAT1 was highly expressed in cancer tissues, and its expression level was related to clinical stage and tissue differentiation in ovarian cancer. A Cox proportional risk model suggested that high expression of PSAT1 and late clinical stage were independent risk factors for survival and prognosis of ovarian cancer patients. CONCLUSION: The detection of DEGs using bioinformatics analysis might be crucial to understanding the pathogenesis of ovarian cancer, especially the molecular mechanisms of its development. The association between PSAT1 expression and the occurrence, development, and prognosis of ovarian cancer was further verified by immunohistochemistry. The PSAT1 expression can be used as a prognostic marker to provide a potential target for the diagnosis and treatment of ovarian cancer.

Screening of prognostic biomarkers for endometrial carcinoma based on a ceRNA network.

OBJECTIVE: This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers. METHODS: RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival. RESULTS: We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs. CONCLUSION: Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma.

Decreased expression of peroxiredoxin1 inhibits proliferation, invasion, and metastasis of ovarian cancer cell.

AIM: The aim of this study was to explore the expression of peroxiredoxin1 (PRDX1) in epithelial ovarian cancer, analyze the relationship between PRDX1 and clinicopathologic parameters of patients with ovarian cancer, including their prognosis, and describe changes and the mechanisms involved in malignant biologic behavior of ovarian cancer cells when PRDX1 expression is inhibited. METHODS: The expression of PRDX1 was detected immunohistochemically in 15 samples of normal ovarian tissue, 21 benign, 11 borderline, and 101 malignant epithelial ovarian tumors. Changes in ovarian cancer cell proliferation, invasion, and metastasis before and after inhibiting PRDX1 expression were assessed by cell function assay. Additionally, gene set enrichment analysis (GSEA) of PRDX1 was performed by the Cancer Genome Atlas database. A protein- protein interaction network was then constructed and a pathway function analysis of the genes in the network was conducted. RESULTS: PRDX1 expression was mainly localized to the cytoplasm, as well as the nucleus of cells. The expression rate of PRDX1 in epithelial ovarian malignant tissues (96.04%) was significantly higher than that in borderline (72.72%) and benign (57.14%) epithelial ovarian tumors, and normal ovarian tissue (20%; all P<0.05). Cox multivariate regression analysis indicated that advanced clinical stage, low tissue differentiation, and high expression of PRDX1 were independent risk factors affecting the prognosis of epithelial ovarian cancer (all P<0.05). Cell function assay verified that the decreased expression of PRDX1 inhibited ovarian cancer cell proliferation, invasion, and metastasis. GSEA analysis indicated that PRDX1 was significantly related to the Wnt signaling pathway. Western blot analysis confirmed that PRDX1 could regulate the expression of ß-catenin in the Wnt pathway. CONCLUSION: Decreased expression of PRDX1 can attenuate cell proliferation, invasion, and metastasis of ovarian cancer cells. The expression of PRDX1 is related to the prognosis of patients with ovarian cancer and can therefore be used as a biomarker.