Background: Ovarian cancer (OC) is a major cause of most gynecological cancer deaths, and the rates of incidence and mortality are increasing worldwide. However, factors in the tumor microenvironment (TME) related to OC and certain prognostic markers of OC are still unknown. We aimed to identify biomarkers connected to prognostic immunity based on clinical patients' data from The Cancer Genome Atlas (TCGA). Methods: We used the ESTIMATE algorithm to compute the immune and matrix scores of OC patients from TCGA. Next, differentially expressed genes (DEGs) according to the immune and matrix scores were obtained. Subsequently, genes (GZMB, C2orf37, CXCL13, and UBD) connected with prognostic immunity were determined. Moreover, functional enrichment analysis and the protein-protein interaction network showed that these genes were enriched in many biological processes related to immune function. The Tumor Immune Estimation Resource (TIMER) algorithm was also used to analyze the immune prognostic genes according to six immuno-infiltrating cells. Results: According to high/low immune-scores and matrix-score groups, 682 common genes were identified, within 420 upregulated genes and 262 downregulated genes. Gene ontology (GO) analysis of biological process primarily enriched in T cell activation, regulation of lymphocyte activation and lymphocyte differentiation. OS analysis showed 45 genes (6.6%) were relevant in the final results. The Kaplan-Meier plotter database verified the top 10 genes related to prognosis, but only GZMB, C2orf37, CXCL13 and UBD were related to overall survival (OS). Conclusions: GZMB, CXCL13, and UBD may influence prognosis via their effects on the infiltration of immune cells and therefore represent potential targets for OC immunotherapy.

目的 寻找卵巢癌预后的关键基因,为卵巢癌治疗提供新的靶点.方法 从基因表达汇编(GEO)数据库GSE18520和GSE14407数据集、癌症基因组图谱(TCGA)数据库及基因型-组织表达(GTEx)数据库中下载卵巢癌相关数据,用R 3.6.2软件limma包进行差异表达基因分析,随后使用R 3.6.2软件clusterProfiler包对差异表达基因进行基因本体(GO)及京都基因与基因组百科全书(KEGG)富集分析.使用STRING数据库建立蛋白质-蛋白质相互作用网络,利用Cytoscape软件cytoHubba插件筛选核心基因,利用基因表达谱交互分析(GEPIA)数据库验证核心基因在卵巢癌组织中的表达情况,随后使用Kaplan-Meier Plotter数据库对核心基因进行生存分析.结果 通过GEO数据库GSE18520、GSE14407数据集及TCGA、GTEx数据库共同筛选获得69个差异表达基因,主要富集在ABC转运体、视黄醇代谢及Wnt信号通路.蛋白质-蛋白质相互作用网络分析提示共有9个核心基因,GEPIA数据库分析结果表明这9个基因在卵巢癌中高表达.Kaplan-Meier Plotter数据库分析结果表明,中心体相关蛋白55(CEP55)、序列相似性83家族蛋白成员D(FAM83D)、驱动蛋白家族成员20A(KIF20A)、细胞周期依赖性激酶亚基蛋白2(CKS2)和中心体相关激酶2(NEK2)基因高表达的卵巢癌患者总生存期比低表达的患者缩短,CEP55、FAM83D、KIF20A、叉头框蛋白M1(FOXM1)和TTK蛋白激酶(TTK)基因高表达的患者无进展生存期比低表达的患者缩短.结论 CEP55、FAM83D、KIF20A、CKS2、NEK2、FOXM1和TTK的表达与卵巢癌患者的预后密切相关.

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: 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.

Given the high morbidity and the trend of younger individuals being affected observed in cervical cancer, it is important to identify sensitive and effective biomarkers for predicting the survival outcome of patients. Based on data from 307 cervical cancer cases acquired from The Cancer Genome Atlas portal, 1920 differentially expressed mRNAs, 70 microRNAs(miRNAs), and 493 long non-coding(lncRNAs) were screened by comparing cervical cancer tissues with paracancerous tissues. A competing endogenous (ceRNA) network containing 50 lncRNAs, 16 miRNAs, and 81 mRNAs was constructed. Eighteen RNAs, comprising 13 mRNAs, 2 miRNAs, and 3 lncRNAs, were identified as significant prognostic factors by univariate Cox proportional hazards regression. ETS-related gene and fatty acid synthase signatures were discovered using a multivariate Cox regression model built to identify independent prognostic factors in cervical cancer patients. Receiver operating characteristic (ROC) analysis was used to determine the optimal cut-off value for distinguishing the risk level of cervical cancer patients. High-risk patients exhibited a poorer prognosis than low-risk patients did. This study focused on ceRNA networks to provide a novel perspective and insight into cervical cancer and suggested that the identified signature can serve as an independent prognostic biomarker in cervical cancer.

Objective To investigate the clinical value of total hysterectomy in the treatment of cervical intraepithelial neoplasia.Methods We retrospectively analyzed the clinical data of 283 patients undergoing total hysterectomy for cervical intraepithelial neoplasia in Changhai Hospital of Second Military Medical University from Jan.2009 to Dec.2016.Among the patients,206 cases received loop electrosurgical excision procedure (LEEP) before total hysterectomy (pre-operative LEEP group),28 only received total hysterectomy directly after colposcopy biopsy (hysterectomy group) and 49 received LEEP during total hysterectomy (intra-operative LEEP group).The changes of pathological grade and the lesion residual rates of the patients before and after operation were compared.The effect of clinicopathological features (age,pregnancy times,partus times,abortion times,menopausal years,pathology,human papilloma virus (HPV) infection,tumor family history and so on) on postoperative residual lesion were analyzed by univariate and multivariate analysis.Results The cure rate,lesion residual rate,pathological downgrade rate and pathological upgrade rate in the pre-operative LEEP group was 35.92％ (74/206),64.08％ (132/206),63.11％ (130/ 206) and 3.88％ (8/206),respectively,and two cases with canceration were found.In the hysterectomy group,the consistent rate of pathological diagnosis before and after operation,pathological downgrade rate and pathological upgrade rate were 57.14％(16/28),35.71％(10/28) and 7.14％(2/28),respectively,and one case with invasive carcinoma was found after operation.The lesion residual rate,pathological downgrading rate and pathological upgradirng rate in the intraoperative LEEP group were 40.82％ (20/49),65.31％ (32/49) and 8.16％ (4/49),respectively,and two cases with invasive carcinoma were found after operation.Univariate analysis showed that age and menopausal years were the factors influencing lesion remaining after LEEP (P＜0.05).Multivariate analysis showed that patients with longer menopausal years had lower risk of lesion remaining (P=0.02).The pregnancy times,partus times,abortion times,lesion involving glands,positive margins,HPV infection and family history of cancer had no significant effects on postoperative lesion remaining.Conclusion Total hysterectomy plays an important role in preventing the recurrence of cervical precancerous lesion and reducing the incidence of invasive carcinoma.It is suitable for people with few screening opportunities,poor follow-up conditions and no fertility requirements.Patients with high grade intraepithelial lesion who are not menopausal or have short menopausal years need to be followed up more closely and can receive total hysterectomy if necessary.

Cervical carcinoma is one of the main causes of women's cancer, and substantial side effects from standard treatment including platinum-based chemotherapy limit the options for escalation. In this paper, using cervical cancer cell lines and tumor-bearing mice as models, we report that CONPs could inhibit the proliferation of cancer cells in vitro and in vivo. Especially CONPs could inhibit tumor growth as cisplatin without weight loss. CONPs could also induce autophagy through AKT/mTOR pathway, which demonstrates that CONPs has the potential clinical applications.

Background: It has been demonstrated that preeclampsia, a pregnancy-specific hypertension disorder, is characterized by high blood pressure (BP) and sympathetic overactivity. Increased reactive oxygen species (ROS) in the rostral ventrolateral medulla (RVLM), a key region for controlling sympathetic tone, has been reported to contribute to high level of BP and sympathetic outflow. The aim of the present study was to determine the role of the RVLM ROS in mediating the preeclampsia-associated cardiovascular dysfunction. Methods: The animal model of preeclampsia was produced by administration of desoxycorticosterone acetate (DOCA) to pregnant rats. Results: Compared with normal pregnant rats without DOCA treatment (NP), the protein concentration and norepinephrine excretion in 24-h urine, as well as BP in pregnant rats with DOCA treatment (PDS) were significantly increased. The levels of superoxide anion and the protein expression of NADPH oxidase subtype (NOX4) in the RVLM were significantly increased in PDS than in NP groups. Furthermore, microinjection of the superoxide dismutase (SOD) mimic Tempol (5 nmol) into the RVLM significantly decreased BP, heart rate, and renal sympathetic never activity in PDS but not in NP group. Conclusion: The present data suggest that high BP and sympathetic overactivity in preeclampsia rats is associated with increased oxidative stress in the RVLM via upregulation of NOX4 expression.