Background: Cervical cancer, one of the leading causes of female deaths, remains a top cause of mortality in gynecologic oncology and tends to affect younger individuals. However, the pathogenesis of cervical cancer is still far from clear. Given the high incidence and mortality of cervical cancer, uncovering the causes and pathogenesis as well as identifying novel biomarkers are of great significance and are desperately needed. Materials and methods: First, raw data were downloaded from the Gene Expression Omnibus database. The Robuse Multi-Array Average algorithm and combat function of the sva package were subsequently applied to preprocess and remove batch effects. Differentially expressed genes (DEGs) analyzed with the limma package were followed by gene ontology and pathway analysis, and a protein–protein interaction (PPI) network based on the STRING website and the Cytoscape software was constructed. Weighted Correlation Network Analysis (WGCNA) was utilized to build the coexpression network. Subsequently, UALCAN websites were employed to conduct survival analysis. Finally, the oncomine database was used to validate the expression of ANLN in other datasets. Results: GSE29570 and GSE89657, including 49 cervical cancer tissues and 20 normal cervical tissues, were screened as the datasets. Three-hundred-twenty-four DEGs were identified and, among them, 123 were upregulated, while 201 were downregulated. The DEGs PPI network complex, contained 305 nodes and 4,962 edges, and 8 clusters were calculated according to k-core =2. Among them, cluster 1, which had 65 nodes and 1,780 edges, had the highest score in these clusters. In coexpression analysis, there were 86 hubgenes from the Brown modules that were chosen for further analysis. Sixty-one key genes were identified as the intersecting genes of the Brown module of WGCNA and DEGs. In survival analysis, only ANLN was a prognostic factor, and the survival was significantly better in the low-expression ANLN group. Conclusion: Our study suggested that ANLN may be a potential tumor oncogene and could serve as a biomarker for predicting the prognosis of cervical cancer patients.

Cardiovascular disease prevalence rises rapidly after menopause, which is believed to be derived from the loss of estrogen. It is reported that sympathetic tone is increased in postmenopause. The high level of oxidative stress in the rostral ventrolateral medulla (RVLM) contributes to increased sympathetic outflow. The focus of this study was to determine if estrogen replacement reduces oxidative stress in the RVLM and sympathetic outflow in the ovariectomized (OVX) rats. The data of this study showed that OVX rat increased oxidative stress in the RVLM and sympathetic tone; estrogen replacement improved cardiovascular functions but also reduced the level of oxidative stress in the RVLM. These findings suggest that estrogen replacement decreases blood pressure and sympathoexcitation in the OVX rats, which may be associated with suppression in oxidative stress in the RVLM through downregulation of protein expression of NADPHase (NOX4) and upregulation of protein expression of SOD1. The data from this study is beneficial for our understanding of the mechanism of estrogen exerting cardiovascular protective effects on postmenopause.

Background. Ovarian cancer is the most fatal gynecological malignancy. Owing to its insidious onset, rapid development, and poor prognosis, ovarian cancer is the fifth most common cause of death in women. Although immunotherapy-related drugs, such as Olaparib, can alleviate ovarian cancer progression, there are no remarkable breakthroughs for its effective treatment. It is considered that the transformation of normal cells to cancerous ones involves “recoding” of certain metabolic pathways. Diacylglycerol O-acyltransferase 1 (DGAT1) can synthesize triglycerides by transferring acyl-CoA to diacylglycerol, which plays a key role in lipid synthesis. However, the role of DGAT1 in ovarian cancer is not yet elucidated. Materials and Methods. We analyzed the correlation between DGAT1 and ovarian cancer staging, grading, vascular invasion, and prognosis by collating the information of ovarian cancer specimens from The Cancer Genome Atlas (TCGA) database. Furthermore, the effects of DGAT1 expression on proliferation, migration, invasion, and tumor growth were studied using ovarian cancer cell lines. GSEA was used to analyze the KEGG pathways and biological function enriched because of DGAT1 expression in ovarian cancer. Results. The expression of DGAT1 was elevated in advanced ( ), poorly differentiated ( ), and vascular invaded ( ) ovarian cancer specimens. Prognosis among patients with high expression of DGAT1 was poor. After DGAT1 expression was interfered, proliferation, migration, invasion, colony forming, and tumor growth of ovarian cancer cells were inhibited. In addition, GSEA showed that DGAT1 may be involved in the immune process. Conclusion. DGAT1 expression is associated with the clinical phenotype of ovarian cancer. We suggest that DGAT1 has potential implications in the treatment of ovarian cancer.

In endometrial carcinoma, the clinical outcome directly correlates with the TNM stage, but the lack of sufficient information prevents accurate prediction. The molecular mechanism underlying the competing endogenous RNA (ceRNA) hypothesis has not been investigated in endometrial cancer. Multi-bioinformatic analyses, including differentially expressed gene analysis, ceRNA network construction, Cox regression analysis, function enrichment analysis, and protein-protein network analysis, were performed on the sequence data acquired from The Cancer Genome Atlas (TCGA) data bank. A ceRNA network comprising 366 mRNAs, 27 microRNAs (miRNAs), and 66 long non-coding RNAs (lncRNAs) was established. Survival analysis performed with the univariate Cox regression analysis revealed nine lncRNAs with prognostic power in endometrial carcinoma. In multivariate Cox regression analysis, a signature comprising LINC00491, LINC00483, ADARB2-AS1, and C8orf49 showed remarkable prognostic power. Risk score and neoplasm status, but not TNM stage, were independent prognostic factors of endometrial carcinoma. A ceRNA network comprising differentially expressed mRNAs, miRNAs, and lncRNAs may reveal the molecular events involved in the progression of endometrial carcinoma. In addition, the signature with prognostic value may discriminate patients with increased risk for poor outcome, which may allow physicians to take accurate decisions.

Background/Aims: Ovarian cancer (OC) is the fifth leading cause of cancer-related death in women, and it is difficult to diagnose at an early stage. The purpose of this study was to explore the prognostic biological markers of OC. Methods: Univariate Cox regression analysis was used to identify genes related to OC prognosis from the Cancer Genome Atlas(TCGA) database. Immunohistochemistry was used to analyse the level of SPINK13 in OC and normal tissues. Cell proliferation, apoptosis and invasion were performed using MTT assay, flow cytometric analysis and Transwell assay, respectively. Results: We identified the Kazal-type serine protease inhibitor-13 (SPINK13) gene related to OC prognosis from the Cancer Genome Atlas (TCGA) database by univariate Cox regression analysis. Overexpression of SPINK13 was associated with higher overall survival rate in OC patients. Immunohistochemistry showed that the level of SPINK13 protein was significantly lower in OC tissues than in normal tissues (P < 0.05).In vitro experiments showed that the overexpression of SPINK13 inhibited cellular proliferation and promoted apoptosis. Moreover, SPINK13 inhibited cell migration and epithelial to mesenchymal transition (EMT). SPINK13 was found to inhibit the expression of urokinase-type plasminogen activator (uPA), while recombinant uPA protein could reverse the inhibitory effect of SPINK13 on OC metastasis. Conclusion: These results indicate that SPINK13 functions as a tumour suppressor. The role of SPINK13 in cellular proliferation, apoptosis and migration is uPA dependent, and SPINK13 may be used as a potential biomarker for diagnosis and targeted therapy in OC.

Detecting a new effective and hypotoxic anticancer drug is an emerging new strategy for cancer chemotherapy. Doxycycline (DC) is a kind of antibiotics but also inhibits tumorigenesis. MTT and cell invasion assay, flow cytometry, western-blot analysis and nude mice were used to investigate the effects and underlying mechanisms of doxycycline on epithelial ovarian cancer cells. Doxycycline inhibited the proliferation and invasion of SKOV3 and SKOV3/DDP; induced moderate apoptosis of SKOV3/DDP. CXCR4 expression at both mRNA and protein levels was downregulated in both cell lines when treated with doxycycline. Akt and ERK1/2 were involved in doxycycline effect on cell proliferation of SKOV3 but not of SKOV3/DDP. Akt and EKR1/2 phosphorylation were activated by SDF-1α, which was then inhibited by doxycycline in SKOV3. Pro-caspase-3 expression was significantly higher in SKOV3 than that in SKOV3/DDP which was upregulated when treated with doxycycline. In vivo, doxycycline inhibited peritoneal tumor xenograft and decreased malignant ascites. Doxycycline not only has an inhibitory effect on ovarian cancer, but also can increase sensitivity to cisplatin. SDF-1α/CXCR4-regulated Akt and ERK 1/2 activations are probably involved in the antitumor effect of doxycycline on SKOV3 cells, while upregulation of pro-caspase-3 may be the main mechanism involved in SKOV3/DDP cells.