Construction of a four-mRNA prognostic signature with its ceRNA network in CESC

Revolutionizing prognosis: Introducing cell death index (CDI) as a powerful prognostic tool for CSCC patients

BACKGROUND

Cervical squamous cell carcinoma (CSCC) threatens the body health of women worldwide. This study aimed to foster a new concept of prognostic indicator named cell death index (CDI).

METHODS

RNA-seq and scRNA-seq datasets were downloaded from the GEO and TCGA database as the training and validation cohorts. Programmed cell death (PCD)-related gene signatures were obtained from published research. The construction of prognostic model was performed based on CDI value. Patients with CSCC were divided into high- and low-CDI groups. We explored the differences in overall survival time, immune infiltration, mutation status, and drug sensitivity between high and low CDI groups by R software.

RESULTS

We constructed prognostic model to calculate the CDI value with 23 genes. Patients with high CDI have shorter survival time than those with low CDI. CDI was considered a risk factor compared to other characteristics. The nomogram model estimated overall survival (OS) at 1, 3, and 6 years, with age, Stage, and CDI, indicating the accuracy of the model in predicting 1-, 3-, and 6-year survival rates. CDI values were negatively correlated with most immune checkpoint genes. We measured the significant drug sensitivity of Mitoxantrone, Sabutoclax, Sepantronium bromide, Topotecan, BI-2536, and BMS-754807 between high- and low-CDI groups with significant correlation.

CONCLUSION

This investigation constructed a novel effective prognostic indicator of CDI in patients with CSCC and identified potential genes associated with cell death that could be targeted for prognosis and treatment of CSCC.

CENPE is a diagnostic and prognostic biomarker for cervical cancer

Cervical squamous cell carcinoma (CESC) is a common cancer in women. Despite advancements in early diagnosis through high-risk human papillomavirus (HPV) screening, challenges remain in predicting and treating the disease. Hence, the identification of novel biomarkers for prognosis and therapeutic targets is crucial. CENPE, a microtubule-end directed motor protein that accumulates during the G2 phase, is recognized for its involvement in promoting cancer growth and progression. However, its specific role in CESC remains unclear. This research investigated the expression of CENPE in CESC utilizing data from The Cancer Genome Atlas (TCGA), which was further validated through gene expression profiles, the Human Protein Atlas (HPA), and clinical data. The study utilized Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and immune infiltration analysis to elucidate the role of CENPE in CESC. Additionally, Protein-protein interaction (PPI) networks and competing endogenous RNA (CeRNA) networks involving CENPE and its differentially expressed genes were established. Furthermore, Kaplan-Meier survival analysis was conducted to evaluate the impact of CENPE on patient prognosis. Our study revealed an upregulation of CENPE expression in cervical cancer tissues, which promotes the progression of CESC through IL-6-mediated PI3K-Akt and MAPK signaling pathways. The significant associations with ACNG3, LY6H, and SLC6A7 suggest that CENPE may play a role in tumor growth and metastasis, potentially involving the nervous system. Moreover, the correlations with ARIH1, KDM1A, KDM5B, and NSD3 indicate that CENPE could be a promising target for drug development. Our analysis of the ROC curve demonstrated a high diagnostic accuracy of CENPE in CESC (AUC: 0.997, CI: 0.990-1.000). Subgroup analysis highlighted substantial effects in patients under 50 years old, those with a height under 160 cm, individuals in peri- and post-menopausal stages, and patients in clinical stages 1 and 4. Additionally, COX regression analysis indicated that older age, lower BMI, and higher CENPE expression are associated with decreased 1-year, 3-year, and 5-year survival rates. In conclusion, CENPE emerges as a crucial factor in the initiation and advancement of cervical cancer, showing potential as a novel target for therapeutic interventions.

Exploring the role of disulfidptosis-related signatures in immune microenvironment, prognosis and therapeutic strategies of cervical cancer

BACKGROUND

Cervical cancer is characterized by a complex immunosuppressive tumor microenvironment (TME). Disulfidptosis is a recently identified form of programmed cell death that has emerged as a crucial factor in tumorigenesis. However, the research on the specific involvement of disulfidptosis within the TME is still in its early stages.

METHODS

Under glucose starvation, SiHa and HeLa cells underwent experiments employing diverse cell death inhibitors and SLC7A11 knockdown to observe their impact on cell survival. TCGA-CESC cohort was subjected to consensus clustering for disulfidptosis-related clusters. Prognosis, function, immune infiltration, and differentially expressed genes (DEGs) evaluations among clusters were compared. A prognostic model based on DEGs and disulfidptosis regulator genes (DRGs) was constructed and internally and externally validated. The correlation between YWHAG and clinicopathological characteristics in cervical cancer patients was investigated at both the mRNA and protein levels. Proliferation and migration assays were performed to uncover the roles of YWHAG in cervical cancer.

RESULTS

Experimental validation confirmed disulfidptosis in cervical cancer cell lines. Cervical cancer patients were classified into three clusters based on DRGs, showing notably improved prognosis and increased immune infiltration in cluster B. The developed disulfidptosis-related prognostic model effectively stratified patients into high- and low-risk groups. Low-risk patients exhibited more favorable responses to immunotherapy and improved overall prognosis. Additionally, YWHAG, recognized as a tumor-promoting gene, demonstrated active roles in enhancing the growth, migration, and invasion of cervical cancer cells.

CONCLUSION

Our research proposed a prognostic model for cervical cancer, probably contributing to tumor microenvironment traits and more potent immunotherapy strategy exploration.

Identification and Validation of eRNA as a Prognostic Indicator for Cervical Cancer

The survival of CESC patients is closely related to the expression of enhancer RNA (eRNA). In this work, we downloaded eRNA expression, clinical, and gene expression data from the TCeA and TCGA portals. A total of 7936 differentially expressed eRNAs were discovered by limma analysis, and the relationship between these eRNAs and survival was analyzed by univariate Cox hazard analysis, LASSO regression, and multivariate Cox hazard analysis to obtain an 8-eRNA model. Risk score heat maps, KM curves, ROC analysis, robustness analysis, and nomograms further indicate that this 8-eRNA model is a novel indicator with high prognostic performance independent of clinicopathological classification. The model divided patients into high-risk and low-risk groups, compared pathway diversity between the two groups through GSEA analysis, and provided potential therapeutic agents for high-risk patients.

Unraveling the role of the circadian clock genes in cervical squamous cell carcinoma and endocervical adenocarcinoma: A prognostic indicator for prognostic, immunotherapy response, and chemotherapy sensitivity

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) account for a significant proportion of gynecological malignancies and represent a major global health concern. Globally, CESC is ranked as the fourth most common cancer among women. Conventional treatment of this disease has a less favorable prognosis for most patients. However, the discovery of early molecular biomarkers is therefore important for the diagnosis of CESC, as well as for slowing down their progression process. Methods: To identify differentially expressed genes strongly associated with prognosis, univariate Cox proportional hazard analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used. Using multiple Cox proportional hazard regression, a multifactorial model for prognostic risk assessment was then created. Results: The expression of biological clock-related genes, which varied considerably among distinct subtypes and were associated with significantly diverse prognoses, was used to categorize CESC patients. These findings demonstrate how the nomogram developed based on the 7-CRGs signature may assist physicians in creating more precise, accurate, and successful treatment plans that can aid CESC patients at 1, 3, and 5 years. Conclusions: By using machine learning techniques, we thoroughly investigated the impact of CRGs on the prognosis of CESC patients in this study. By creating a unique nomogram, we were able to accurately predict patient prognosis. At the same time, we showed new perspectives on the development of CESC and its treatment by analyzing the associations of the prognostic model with immunity, enrichment pathways, chemotherapy sensitivity, and so on. This research provides a new direction for clinical treatment.

The miR-146b-3p/TNFAIP2 axis regulates cell differentiation in acute myeloid leukaemia

Our purpose is to verify that miR-146b-3p targets the downstream transcript TNFAIP2 in order to reveal the machinery underlying the miR-146b-3p/TNFAIP2 axis regulating acute myeloid leukaemia (AML) differentiation. Bioinformatics analyses were performed using multiple databases and R packages. The CD11b+ and CD14+ cell frequencies were detected using flow cytometry and immunofluorescence staining. The TNFAIP2 protein expression was evaluated using western blotting, immunocytochemistry and immunofluorescence staining. The qRT-PCR was conducted to detect the expression of TNFAIP2 and miR-146b-3p. TNFAIP2 and its correlated genes were enriched in multiple cell differentiation pathways. TNFAIP2 was upregulated upon leukaemic cell differentiation. miR-146b-3p directly targeted TNFAIP2, resulting in a decrease in TNFAIP2 expression. Forced expression of TNFAIP2 or knockdown of miR-146b-3p significantly induced the differentiation of MOLM-13 cells. In this study, we demonstrated that TNFAIP2 is a critical driver in inducing differentiation and that the miR-146b-3p/TNFAIP2 axis involves in regulating cell differentiation in AML.

Prediction of Prognosis and Chemotherapeutic Sensitivity Based on Cuproptosis-Associated lncRNAs in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is the fourth most common cancer. The 5-year survival rate for metastatic cervical cancer is less than 10%. The survival time of patients with recurrent cervical cancer is approximately 13-17 months. Cuproptosis is a novel type of cell death related to mitochondrial respiration. Accumulative studies showed that long non-coding RNAs (lncRNAs) regulated cervical cancer progression. Compressive bioinformatic analysis showed that nine cuproptosis-related lncRNAs (CRLs), including C002128.2, AC002563.1, AC009237.14, AC048337.1, AC145423.1, AL117336.1, AP001542.3, ATP2A1-AS1, and LINC00426, were independently correlated with the overall survival (OS) of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients. The time-dependent area under curve value reached 0.716 at 1 year, 0.718 at 3 years, and 0.719 at 5 years. Notably, CESC patients in the low-risk group had increased immune cell infiltration and expression of several immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade therapy. In addition, we also used the model for drug sensitivity analysis. Several drug sensitivities were more sensitive in high-risk patients and showed significant correlations with the risk models, such as Bortezomib_1191, Luminespib_1559, and Rapamycin_1084, suggesting that these drugs may be candidate clinical drugs for patients with a high risk of CESC. In summary, this study further explored the mechanism of CRLs in CESC and provided a more optimized prognostic model and some insights into chemotherapy of CESC.

Novel Prognostic Biomarkers for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Patients via Analysis of Competing Endogenous RNA (ceRNA) Network

Background

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is a common malignant gynecological cancer. The ceRNA networks play important roles in many tumors, while RILPL2-related ceRNA network has been seldom studied in CESC.

Methods

All CESC data was obtained from TCGA database. Differentially expressed RNAs and predicted target RNAs were cross analyzed to construct ceRNA network. RNA and clinicopathological characteristics' influence on overall survival (OS) were determined by univariate and multivariate Cox regression analyses. Lasso regression was used to construct the prediction model. Coexpression analysis was performed to explore the association of gene expression with CESC. This was followed by an experimental validation based on these results.

Results

Between high and low RILPL2 expression CESC patients, totally 1227 DEmRNAs, 39 DEmiRNAs, and 1544 DElncRNAs were identified. After multiple cross analyses, 1 miRNA hsa-miR-1293, 20 mRNAs, and 43 lncRNAs were maintained to construct ceRNA network. CADM3-AS1, LINC00092, and ZNF667-AS1 in ceRNA network were significantly associated with the OS of CESC patients, and patients with low expression of these lncRNAs had worse prognosis. Significant lower expressions of these lncRNAs were also observed in CESC cell line compared with normal cell line.

Conclusion

Low expressions of CADM3-AS1, LINC00092, and ZNF667-AS1 in ceRNA network were probably promising poor prognostic biomarkers for CESC patients. The genes show a prospective research area for CESC-targeted treatment in the future.