Dysregulated LncRNAs Act as Competitive Endogenous RNAs and Are Associated With Cervical Cancer Development in UYGHUR Women

The role of microRNA-9 in ovarian and cervical cancers: An updated overview

Ovarian and cervical cancers are the two most frequent kind of gynaecological cancers (GCs). In spite of advances in prevention, screening and treatment, cervical cancer still leads to an increased morbidity and mortality worldwide. Ovarian cancer is often detected at a late stage, which significantly reduces the effectiveness of available treatments. Therefore, novel methods are desperately needed to improve the clinical care of GC patients. MicroRNAs, also known as short noncoding RNAs (miRNAs/miRs), are a diverse group of RNAs with a length of 22 nucleotides. These typically cause translational repression and mRNA degradation by interacting with target mRNAs' 3' untranslated region (3'-UTR), together with other regions and gene promoters. Under certain conditions, they are also able to activate translation or regulate transcription. It has been demonstrated that miRNAs are crucial to several biological processes leading to tumorigenesis, including GCs. Recent research has shown that miR-9 affects carcinogenesis. In this review, we will provide an overview of current research on the potential utility of miR-9 in the diagnosis, prognosis, and therapy of ovarian and cervical malignancies.

Integrated analysis of long non-coding RNAs and mRNAs associated with condyloma acuminatum

Condyloma acuminatum (CA) is a prevalent sexually transmitted disease caused by low-risk human papillomavirus infection, characterized by high transmission and recurrence rates. Long non-coding RNAs (lncRNAs) play a crucial role in regulating gene transcription and are involved in various biological processes. Although recent studies have demonstrated the involvement of lncRNAs in cervical cancer, their expression profile and function in CA remain poorly understood. In this study, we aimed to identify messenger RNA (mRNA) and lncRNA expression patterns in CA using high-throughput lncRNA sequencing. We found that 3033 differentially expressed genes (DEGs) and 1090 differentially expressed lncRNAs (DELs) were significantly altered in CA compared to healthy controls. The results from quantitative reverse transcription polymerase chain reaction and immunohistochemical staining are in accordance with the observed trends in the sequencing data. Functional enrichment analysis revealed that upregulated DEGs in CA were involved in biological processes such as virus response, immune response, cell cycle regulation, the tumor necrosis factor signaling pathway, and the P53 signaling pathway. Co-expression network analysis identified potential target genes of DELs, with enrichment in biological processes such as cell differentiation, the intrinsic apoptotic signaling pathway, and pathways such as virus infection, pathways in cancer, T helper 17 cell differentiation, the mitogen-activated protein kinase signaling pathway, and the Wnt signaling pathway. Collectively, our findings indicate significant changes in the transcriptome profile, including mRNAs and lncRNAs, in CA compared to healthy controls. Our study provides new insights into the potential functions of lncRNAs in the pathogenesis of CA and identifies potential therapeutic targets for this disease.

Construction of ceRNA network and key gene screening in cervical squamous intraepithelial lesions

BACKGROUND

This study aimed to construct an endogenous competition network for cervical squamous intraepithelial lesions using differential gene screening.

METHODS

GSE149763 was used to screen differentially expressed long non-coding RNAs (lncRNAs) and mRNAs to predict correlated microRNAs (miRNAs). The correlated miRNAs and GSE105409 were used to screen differentially expressed miRNAs for differential co-expression analysis, and the co-expressed differentially expressed miRNAs were used to predict correlated mRNAs. Differentially expressed mRNAs, miRNAs, and lncRNAs were visualized, and differential gene screening, enrichment, and pathway analysis were performed.

RESULTS

The ceRNA network of cervical squamous intraepithelial was successfully established and a potential differentially expressed network was identified. The key genes were VEGFA and FOS, and the key pathway was the MAPK signaling pathway.

CONCLUSIONS

The differential expression and potential effects of the lncRNA BACH1-IT1/miR-140-5p/VEGFA axis, key genes, VEGFA and FOS, and MAPK signaling in CIN were clarified, and the occurrence and potential effects of CIN were further clarified. The underlying molecular mechanism provides a certain degree of reference for subsequent treatments and experimental research.

A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer

Cervical cancer (CESC) is the fourth most common and death-causing gynecological cancer, mostly induced by infection of human papillomavirus (HPV). Multiple components of the tumor microenvironment (TME), such as tumor infiltrating immune cells, could be targets of immunotherapy for HPV-related CESC. However, little is known about the TME of CESC until now. Here, we aimed to uncover the pathogenesis as well as to identify novel biomarkers to predict prognosis and immunotherapy efficacy for CESC. Combining the transcriptomic data and clinical characteristics, we identified differentially expressed genes in CESC samples from TCGA database by comparing the two groups with different ImmuneScore and StromalScore. Next, we detected ten key genes based on the PPI network and survival analyses with the univariate Cox regression model. Thereafter, we focused on CD3G, the only gene exhibiting increased RNA and protein expression in tumors by multiple analyses. Higher CD3G expression was associated with better survival; and it was also significantly associated with immune-related pathways through GSEA analysis. Furthermore, we found that CD3G expression was correlated with 16 types of TICs. Single cell RNA-sequencing data of CD3G in lymphocytes subgroup indicated its possible role in HPV defense. Hence, CD3G might be a novel biomarker in prognosis and immunotherapy for CESC patients.

Exploration of the Immune-Related Long Noncoding RNA Prognostic Signature and Inflammatory Microenvironment for Cervical Cancer

Purpose: Our research developed immune-related long noncoding RNAs (lncRNAs) for risk stratification in cervical cancer (CC) and explored factors of prognosis, inflammatory microenvironment infiltrates, and chemotherapeutic therapies. Methods: The RNA-seq data and clinical information of CC were collected from the TCGA TARGET GTEx database and the TCGA database. lncRNAs and immune-related signatures were obtained from the GENCODE database and the ImPort database, respectively. We screened out immune-related lncRNA signatures through univariate Cox, LASSO, and multivariate Cox regression methods. We established an immune-related risk model of hub immune-related lncRNAs to evaluate whether the risk score was an independent prognostic predictor. The xCell and CIBERSORTx algorithms were employed to appraise the value of risk scores which are in competition with tumor-infiltrating immune cell abundances. The estimation of tumor immunotherapy response through the TIDE algorithm and prediction of innovative recommended medications on the target to immune-related risk model were also performed on the basis of the IC50 predictor. Results: We successfully established six immune-related lncRNAs (AC006126.4, EGFR-AS1, RP4-647J21.1, LINC00925, EMX2OS, and BZRAP1-AS1) to carry out prognostic prediction of CC. The immune-related risk model was constructed in which we observed that high-risk groups were strongly linked with poor survival outcomes. Risk scores varied with clinicopathological parameters and the tumor stage and were an independent hazard factor that affect prognosis of CC. The xCell algorithm revealed that hub immune-related signatures were relevant to immune cells, especially mast cells, DCs, megakaryocytes, memory B cells, NK cells, and Th1 cells. The CIBERSORTx algorithm revealed an inflammatory microenvironment where naive B cells (p < 0.01), activated dendritic cells (p < 0.05), activated mast cells (p < 0.0001), CD8⁺ T cells (p < 0.001), and regulatory T cells (p < 0.01) were significantly lower in the high-risk group, while macrophages M0 (p < 0.001), macrophages M2 (p < 0.05), resting mast cells (p < 0.0001), and neutrophils (p < 0.01) were highly conferred. The result of TIDE indicated that the number of immunotherapy responders in the low-risk group (124/137) increased significantly (p = 0.00000022) compared to the high-risk group (94/137), suggesting that the immunotherapy response of CC patients was completely negatively correlated with the risk scores. Last, we compared differential IC50 predictive values in high- and low-risk groups, and 12 compounds were identified as future treatments for CC patients. Conclusion: In this study, six immune-related lncRNAs were suggested to predict the outcome of CC, which is beneficial to the formulation of immunotherapy.