Construction of a prognostic model for ovarian cancer based on a comprehensive bioinformatics analysis of cuproptosis-associated long non-coding RNA signatures.

Ovarian cancer (OCa) is a common malignancy in women, and the role of cuproptosis and its related genes in OCa is unclear. Using the GSE14407 dataset, we analyzed the expression and correlation of cuproptosis-related genes (CRGs) between tumor and normal groups. From the TCGA-OV dataset, we identified 20 cuproptosis-related long non-coding RNAs (CuLncs) associated with patient survival through univariate Cox analysis. OCa patients were divided into early-stage and late-stage groups to analyze CuLncs expression. Cluster analysis classified patients into two clusters, with Cluster1 having a poorer prognosis. Significant differences in "Lymphatic Invasion" and "Cancer status" were observed between clusters. Seven CRGs showed significant expression differences, validated using the human protein atlas (HPA) databases. Immune analysis revealed a higher ImmuneScore in Cluster1. GSEA identified associated signaling pathways. LASSO regression included 11 CuLncs to construct and validate a survival prediction model, classifying patients into high-risk and low-risk groups. Correlations between riskScore, Cluster phenotype, ImmuneScore, and immune cell infiltration were explored. Cell experiments showed that knocking down AC023644.1 decreases OCa cell viability. In conclusion, we constructed an accurate prognostic model for OCa based on 11 CuLncs, providing a basis for prognosis assessment and potential immunotherapy targets.

Elevated INHBA Promotes Tumor Progression of Cervical Cancer.

Objectives: This study aimed to explore the role of inhibin subunit beta A (INHBA) in the progression of cervical cancer (CCa) and investigate its potential as a therapeutic target. Specifically, the objectives were to assess the expression levels of INHBA in CCa, examine its correlation with patient survival, and elucidate its impact on CCa cell proliferation, cell cycle regulation, migration, invasion, and in vivo tumor growth and metastasis. Methods: To achieve the objectives, we conducted a comprehensive set of experimental methods. INHBA expression in CCa was analyzed, and its association with patient survival was assessed using clinical data. In vitro experiments involved the investigation of INHBA's effects on CCa cell proliferation, cell cycle dynamics, migration, and invasion through the epithelial-mesenchymal transition (EMT) process. Additionally, in vivo experiments were performed to evaluate the influence of INHBA on CCa growth and lung metastasis. Results: The results of this study revealed upregulated expression of INHBA in CCa, with a significant association between high INHBA expression and poor patient survival. Functionally, INHBA was found to promote the proliferation of CCa cells, regulate the cell cycle, and enhance migration and invasion through the EMT process in vitro. Moreover, in vivo experiments demonstrated that INHBA facilitated the growth and lung metastasis of CCa. Conclusion: In conclusion, our findings suggest that INHBA plays a crucial role in the progression of cervical cancer. The upregulation of INHBA is associated with poor patient survival, and its involvement in promoting key aspects of cancer progression makes it a potential therapeutic target for CCa treatment. These results provide valuable insights into the molecular mechanisms underlying CCa and offer a foundation for further exploration of targeted therapeutic interventions.

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma.

Background: N7-methylguanosine (m7G) has been implicated in the development of cancer. The role of m7G-related miRNAs in the survival prediction of UCEC patients has not been investigated. Current research was the first to construct an m7G-related miRNA model to accurately predict the survival of patients with uterine corpus endometrial carcinoma (UCEC) and to explore immune cell infiltration and immune activity in the tumor microenvironment. Methods: RNA-seq data and clinical information of UCEC patients were derived from The Cancer Genome Atlas (TCGA) database. Using the TargetScan online database, we predicted miRNAs linked to the m7G-related genes and identified miRNAs which were significantly associated with the survival in UCEC patients and constructed a risk scoring model. The TCGA-UCEC cases were scored according to the risk model, and the high- and low-risk groups were divided by the median risk value. Gene enrichment analysis and immune cell infiltration and immune function analysis were performed using "clusterProfiler" and "GSVA" packages in R. Results: The survival prediction model consisted of 9 miRNAs, namely, hsa-miR-1301, hsa-miR-940, hsa-miR-592, hsa-miR-3170, hsa-miR-876, hsa-miR-215, hsa-miR-934, hsa-miR-3920, and hsa-miR-216b. Survival of UCEC patients in the high-risk group was worse than that in the low-risk group (p < 0.001). The receiver operating characteristic (ROC) curve showed that the model had good predictive performance, and the area under the curve was 0.800, 0.690, and 0.705 for 1-, 3-, and 5-year survival predictions, respectively. There were differences in the degree of immune cell infiltration and immune activity between the low-risk and high-risk groups. The expression levels of the identified differentially expressed genes correlated with the susceptibility to multiple anticancer drugs. Conclusions: The survival prediction model constructed based on 9 m7G-related miRNAs had good predictive performance.

DFNA5 regulates immune cells infiltration and exhaustion.

BACKGROUND: DFNA5 (GSDME) belongs to Gasdermin familily that is involved in a variety of cancers and triggers cell pyroptosis after chemical treatment. However, the relationship in DFNA5 between prognosis and immune cells in diverse cancers has been receiving little attention. Tumor immune cells infiltration and exhaustion may associate with patients prognosis. The roles of DFNA5 in tumor immune cells infiltration and exhaustion have not been clarified. METHODS: The expression level of DFNA5 was determined by the Tumour Immune Estimation Resource and the Oncomine database. Then the impacts of DFNA5 in prognosis were assessed by Kaplan-Meier plotter and ULACAN. The correlations between DFNA5 and tumour-infiltrating lymphocytes were explored by TIMER. In addition, the relationships in the expression levels of DFNA5 and typical genes combination of tumour-infiltrating lymphocytes were analysed by GEPIA and TIMER. In this study, we screened the chemokine and immune related proteins interacted with DFNA5 using TurboID system to explore the instantaneous or weak interactions. RESULTS: DFNA5 significantly influences the prognosis in different cancers according to The Cancer Genome Atlas (TCGA). The expression levels of DFNA5 showed positive correlations to the infiltration of macrophages, CD8 + T cells, CD4 + T cells in liver hepatocellular carcinoma (LIHC), colon adenocarcinoma (COAD), and lung adenocarcinoma (LUAD). DFNA5 expression displayed obvious correlations with multiple lymphocytes gene makers in COAD, LIHC and LUAD. DFNA5 expression has effects on the prognosis of liver hepatocellular carcinoma and LUAD. DFNA5 upregulated the expression levels of PDCD1 and CD274 in a dose-dependent manner. Chemokine and immune related proteins interact with DFNA5. CONCLUSIONS: These results indicate that DFNA5 is related to patient prognosis and immune cells, consisting of macrophages, CD4 + T cells, and CD8 + T cells, in diverse cancers. In addition, DFNA5 expression might contribute to the regulation of T cell exhaustion, tumour-associated macrophages (TAMs), and Tregs in COAD, LIHC and LUAD. DFNA5 may regulate immune infiltration via EIF2AK2. IFNGR1 was related to the functions of PD-L1 expression and PD-1 checkpoint pathway. These results indicate that DFNA5 levels may be act as a prognostic factor and predict the degrees of immune cells infiltration in LIHC and LUAD.