Comprehensive Analysis Reveals the Potential Roles of CDKN3 in Pancancer and Verification in Endometrial Cancer.

Background: Cyclin-dependent kinase inhibitor 3 (CDKN3) has been studied in many cancers. However, the comprehensive and systematic pancancer analysis of CDKN3 genes is still lacking. Methods: Data were downloaded from online databases. R was used for analysis of the differential expression and gene alteration of CDKN3 and of the associations between CDKN3 expression and survival, signaling pathways, and drug sensitivity. Clinical samples and in vitro experiments were selected for verification. Results: CDKN3 expression was higher in most types of cancers, and this phenotype was significantly correlated with poor survival. CDKN3 showed gene alterations and copy number alterations in many cancers and associated with some immune-related pathways and factors. Drug sensitivity analysis elucidated that CDKN3 could be a useful marker for therapy selection. Clinical samples elucidated CDKN3 expressed high in endometrial cancer tissue. In vitro studies showed that CDKN3 induced pro-tumor effect in immune environment and facilitated endometrial cancer cell proliferation and G1/S phase transition. Conclusion: CDKN3 has been shown to be highly expressed in most types of cancers and promoted cancer cell progression. CDKN3 may serve as a novel marker in clinical diagnosis, treatment, and prognosis prediction in future.

Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.

Microbiota-relevant signatures have been investigated for human papillomavirus-related cervical cancer (CC), but lack consistency because of study- and methodology-derived heterogeneities. Here, four publicly available 16S rRNA datasets including 171 vaginal samples (51 CC versus 120 healthy controls) were analyzed to characterize reproducible CC-associated microbial signatures. We employed a recently published clustering approach called VAginaL community state typE Nearest CentroId clAssifier to assign the metadata to 13 community state types (CSTs) in our study. Nine subCSTs were identified. A random forest model (RFM) classifier was constructed to identify 33 optimal genus-based and 94 species-based signatures. Confounder analysis revealed confounding effects on both study- and hypervariable region-associated aspects. After adjusting for confounders, multivariate analysis identified 14 significantly changed taxa in CC versus the controls (P < 0.05). Furthermore, predicted functional analysis revealed significantly upregulated pathways relevant to the altered vaginal microbiota in CC. Cofactor, carrier, and vitamin biosynthesis were significantly enriched in CC, followed by fatty acid and lipid biosynthesis, and fermentation of short-chain fatty acids. Genus-based contributors to the differential functional abundances were also displayed. Overall, this integrative study identified reproducible and generalizable signatures in CC, suggesting the causal role of specific taxa in CC pathogenesis.

Glucose metabolic reprogramming and its therapeutic potential in obesity-associated endometrial cancer.

Endometrial cancer (EC) is a common gynecological cancer that endangers women health. Although substantial progresses of EC management have been achieved in recent years, the incidence of EC still remains high. Obesity has been a common phenomenon worldwide that increases the risk of EC. However, the mechanism associating obesity and EC has not been fully understood. Metabolic reprogramming as a remarkable characteristic of EC is currently emerging. As the primary factor of metabolic syndrome, obesity promotes insulin resistance, hyperinsulinemia and hyperglycaemia. This metabolic disorder remodels systemic status, which increases EC risk and is related with poor prognosis. Glucose metabolism in EC cells is complex and mediated by glycolysis and mitochondria to ensure energy requirement. Factors that affect glucose metabolism may have an impact on EC initiation and progression. In this study, we review the glucose metabolic reprogramming of EC not only systemic metabolism but also inherent tumor cell metabolism. In particular, the role of glucose metabolic regulation in malignant properties of EC will be focused. Understanding of metabolic profile and glucose metabolism-associated regulation mechanism in EC may provide novel perspective for treatment.

Which is the best management for women with normal cervical cytologic findings despite positivity for non-16/18 high risk human papillomaviruses?

Women who test positive for the human papillomavirus (HPV) but have normal cytology constitute the predominant subgroup of patients in the screening population in the post-vaccination era. The distribution of HPV genotypes changed dramatically, which was attributable to an increase in HPV vaccination coverage. These changes have created uncertainty about how to properly manage women with normal cytology, non-HPV16/18 infections, or persistent infections. Current recommendations include retesting and continued surveillance in the absence of HPV16/18 infection. However, these are not always applicable. The ability to implement genotyping or incorporate HPV16/18 with some additional high-risk HPV (HR-HPV) types for triage and management with the aim of identifying type-specific risks in this population could be acceptable. When the next set of guidelines is updated, generating potential triage strategies for detecting high-grade cervical lesions, such as the p16/Ki67 cytology assay and other alternatives that incorporate genotyping with newer tests, should be considered. Current clinical management is shifting to risk-based strategies; however, no specific risk threshold has been established in this population. Importantly, innovative triage testing should be evaluated in combination with primary screening and management. Furthermore, there is an untapped opportunity to coordinate HPV genotyping in combination with colposcopic characteristics to modify risk in this group. Hence, providing a more personalized schedule through the efficient application of risk stratification and improving the detection of pre-cancer and cancer is an option worth exploring.