This study aimed to evaluate the performance of Cobas HPV test in cervical cancer screening. A total of 3,442 women aged ≥20 years used Cobas HPV and hybrid capture 2 (HC2) tests were included in this study. Women with any positive result were examined by liquid-based cytology (LBC) test. Then subjects with abnormal LBC or positive Cobas HPV16/18 were further checked up by colposcopy to observe the visible lesions to perform the pathological examination. Of these 3,442 women, 328 cases were Cobas HPV positive, and the positive rate was 9.53% [95% confidence intervals (CI), 8.50%-10.53%]. The positive rate of HPV16, HPV18, and other 12 types of high-risk HPV were 1.54% (95%CI, 1.12%-1.95%), 0.55% (95%CI, 0.30%-0.80%), and 7.44% (95%CI, 6.56%-8.32%), respectively. The coincidence rate of Cobas HPV test and HC2 test was 90% (95%CI, 89.00%-91.00%; Kappa = 0.526) in the primary screening. Age had a non-linear relationship with Cobas HPV positive rate (χ 2 = 4.240, P = 0.040) and HPV16/18 typing positive rate (χ 2 = 6.610, P = 0.010).Compared with the LBC test, the Cobas HPV test had higher sensitivity when detecting patients with high cervical intraepithelial neoplasia (CIN2+ and CIN3+).

Purpose Pyroptosis has vital roles in tumorigenesis and cancer development; however, its relationship with cervical squamous cell cancer (CSCC) remains unexplored. In this study, we aimed to develop a CSCC prediction signature related to pyroptosis. Patients and Methods Consensus clustering analysis was conducted to detect pyroptosis-related subclusters for CSCC. Next, differentially expressed genes (DEGs) between subclusters were identified. Univariate, least absolute shrinkage and selection operator, and stepwise multivariate Cox regression analyses were applied to establish a prognostic model and a nomogram drawn. Additionally, functional enrichment analysis, tumor mutation burden, and immune characteristics associated with this signature were investigated. Results We constructed a seven-gene signature that functions as an independent predictor of prognosis in CSCC using data from The Cancer Genome Atlas. Patients with CSCC were divided into two groups based on median risk score, and patients in the low-risk group had significantly longer survival time than those in the high-risk group. Our findings were validated using Gene Expression Omnibus cohort data. We also established a nomogram, to expand the clinical applicability of our findings. The seven gene signature was associated with various molecular pathways, tumor mutation status, and immune microenvironment. Conclusion The pyroptosis-related risk signature consisting of seven genes developed here represents a potential robust biomarker for predicting prognosis and immunotherapy response in patients with CSCC.

No abstract