Background The specific long-term trend in ovarian cancer (OC) rates in China has been rarely investigated. We aimed to estimate the temporal trends in incidence and mortality rates from 1990 to 2019 in OC and predict the next 30-year levels. Data on the incidence, mortality rates, and the number of new cases and deaths cases due to OC in the China cohort from 1990 to 2019 were retrieved from the Global Burden of Disease Study 2019. Temporal trends in incidence and mortality rates were evaluated by joinpoint regression models. The incidence and mortality rates and the estimated number of cases from 2020 to 2049 were predicted using the Bayesian age–period–cohort model. Results Consecutive increasing trends in age-standardized incidence (average annual percent change [AAPC] = 2.03; 95% confidence interval [CI], 1.90–2.16; p < 0.001) and mortality (AAPC = 1.58; 95% CI, 1.38−1.78; p < 0.001) rates in OC were observed from 1990–2019 in China. Theoretically, both the estimated age-standardized (per 100,000 women) incidence (from 4.77 in 2019 to 8.95 in 2049) and mortality (from 2.88 in 2019 to 4.03 in 2049) rates will continue to increase substantially in the coming 30 years. And the estimated number of new cases of, and deaths from OC will increase by more than 3 times between 2019 and 2049. Conclusions The disease burden of OC in incidence and mortality has been increasing in China over the past 30 years and will be predicted to increase continuously in the coming three decades.
Objective: The role of the protein-coding gene arylacetamide deacetylase (AADAC) in the prognostication of ovarian cancer remains uncertain. We aimed to identify and validate its prognostic value using integrated bioinformatics analyses.Methods: Gene expression profiles of RNA-sequencing and microarray data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Univariate and multivariate Cox regression models were used to evaluate the prognostic value of gene expression. The predictive accuracy of the gene signature model was evaluated using a time-dependent receiver operating characteristic (ROC) curve. In addition, the correlation between immune infiltration and AADAC was identified. A nomogram of the gene signature with clinical parameters was constructed to estimate the clinical application of the signature for survival prediction in patients with ovarian cancer. Results: Univariate and multivariate Cox regression analyses in the training and validation cohorts indicatedthat a high AADAC expression signature was significantly and independently correlated with better survival outcomes in ovarian cancer. AADAC upregulation positively correlated with the infiltration of CD4+ memory T cells. Immunological signature gene sets were significantly enriched in CD4+ T cell regulation pathways.The area under the curve of the time-dependent ROC for overall survival indicated that the constructed nomogram had a moderate predictive ability for prognostic prediction in ovarian cancer. Conclusion:AADAC expression signature significantly and independently correlated with the survival outcome and CD4+ memory T cell infiltration in ovarian cancer, indicating its potential applicability in the prediction of prognosis and immunotherapy efficacy.
Rationale:Spontaneous complete uterine rupture during gestation is rare and has no specific symptoms; however, it is a life-threatening event for both the fetus and mother. The rupture typically happens in labor and is uncommon before labor. Herein, we present the case of a woman, encountering complete rupture at third trimester followed by laparoscopic cornuostomy.Patient concerns:A 26-year-old woman presented with acute right lower abdominal pain at 33 weeks and 5 days of gestation.Diagnoses:We made a diagnosis of threatened uterine rupture.Intervention:Urgent cesarean section performed. Exploration of the uterine dehiscence wound demonstrated that the myometrium was completely ruptured at the primary laparoscopic surgical scar with a defect of 40 mm, and live birth and preservation of the uterus was achieved.Outcome:On the third day of operation, she had a good recovery and was discharged. After a 6-week postpartum follow-up, she displayed a good level of rehabilitation.Lessons:Pregnancy after laparoscopic cornuostomy should be treated as high-risk gestation and the rupture during gestation of the uterine scar should be suspected once lower abdominal pain occurred. Swift diagnosis and prompt intervention play a crucial role in saving the lives of the fetus and the mother.
Therapeutic application of vaccines to endometrial carcinoma (EC) remains uncertain. In this study, we aimed to identify potential tumour antigens for use in the development of an anti-tumour mRNA vaccine and clarify immune subtypes and their characteristics for immunotherapeutic application in heterogeneous EC by integrating multi-omics data. Importantly, four potential tumour antigen candidates-PGR, RBPJ, PARVG and MSX1-were identified and significantly correlated with better overall survival, disease-free survival and distinct antigenpresenting cell infiltration in EC. In addition, two different immune subtypes by consensus clustering analysis of the immune-related genes were identified.Patients with C2 immunophenotypes exhibited superior survival outcomes and 'hot' immunoreactivity and harboured higher microsatellite instability scores and tumoral mutation burden but lower copy-number variation burden. Furthermore, the distinct expression of immunogenic cell death modulators and differential microenvironmental characteristics of immune-cell infiltration were also revealed between C1 and C2 immune-subtype tumours. Enrichment analysis of the co-expression of immune-related genes showed enrichment in immune response, immune cell-mediated immunity and antigen processing pathways. These results indicated that these identified tumour antigens can be used for developing antitumour mRNA vaccines, and tumours with C2 immunophenotypic characteristics demonstrated sensitivity and susceptibility to immunotherapy in EC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.