BACKGROUND: The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. METHODS: UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types. RESULTS: A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23â¼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm. CONCLUSION: CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.
Cyclin A2 , Endometrial Neoplasms , Humans , Female , Cyclin A2/genetics , Cyclin A2/metabolism , Endometrial Neoplasms/genetics , Endometrial Neoplasms/pathology , Endometrial Neoplasms/metabolism , Prognosis , Middle Aged , Tissue Array Analysis/methods , RNA-Seq , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Single-Cell Gene Expression Analysis
<p><b>OBJECTIVE</b>To analyze and further improvement the application of the China Infectious Diseases Automated-alert and Response System (CIDARS) in Guangxi Zhuang Autonomous Region.</p><p><b>METHODS</b>Results related to the amount of signal, proportion of signal responded, time to signal response, manner of signal verification and on each signal of Guangxi in CIDARS from 2009 to 2011 were described. Performance was compared between the periods of pre/ post the adjustment of parameters in CIDARS on December 10, 2010.</p><p><b>RESULTS</b>A total of 29 788 signals were generated on 16 infectious diseases in the system in Guangxi. 100% signals had been responded with the median time to response as 1.5 hours. The average amount of signal per county per week was 1.7;with 624 signals(2.09%)verified as suspected outbreaks preliminarily and 191 outbreaks of 9 diseases were finally confirmed by further field investigation. The sensitivity of CIDARS was 89.25% , and the timeliness of detection was 2.8 d. After adjusting the parameter of CIDARS, the number of signals reduced, and the sensitivity and timeliness of detection improved for most of the diseases.</p><p><b>CONCLUSION</b>The signals of CIDARS were responded timely, and the performance of CIDARS might be improved by adjusting the parameters of early-warning model, which helped enhance the ability of outbreaks-detection for local public health departments. However the current proportion of false positive signals still seemed to be high, suggesting that both the methods and parameters should be improved, according to the characteristics of different diseases.</p>
Humans , China , Epidemiology , Communicable Disease Control , Methods , Communicable Diseases , Epidemiology , Disease Notification , Methods , Disease Outbreaks , Models, Theoretical , Population Surveillance , Methods
