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

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.

Prognostic Value of an Immune Long Non-Coding RNA Signature in Liver Hepatocellular Carcinoma

In recent years, there has been a growing recognition of the important role that long non-coding RNAs (lncRNAs) play in the immunological process of hepatocellular carcinoma (LIHC). An increasing number of studies have shown that certain lncRNAs hold great potential as viable options for diagnosis and treatment in clinical practice. The primary objective of our investigation was to devise an immune lncRNA profile to explore the significance of immune-associated lncRNAs in the accurate diagnosis and prognosis of LIHC. Gene expression profiles of LIHC samples obtained from TCGA database were screened for immune-related genes. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate Cox analysis. Then, the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were performed to evaluate the capability of the immune lncRNA signature as a prognostic indicator. Six long non-coding RNAs were identified via correlation analysis and Cox regression analysis considering their interactions with immune genes. Subsequently, tumor samples were categorized into two distinct risk groups based on different clinical outcomes. Stratification analysis indicated that the prognostic ability of this signature acted as an independent factor. The Kaplan-Meier method was employed to conduct survival analysis, results showed a significant difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Additionally, data obtained from gene set enrichment analysis (GSEA) revealed several potential biological processes in which these biomarkers may be involved. To summarize, this study demonstrated that this six-lncRNA signature could be identified as a potential factor that can independently predict the prognosis of LIHC patients.

Exploring Immune-Related Gene Profiling and Infiltration of Immune Cells in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is a widespread malignancy among women, leading to a substantial global health impact. Despite extensive research, our understanding of the basic molecules and pathogenic processes of cervical squamous cell carcinoma is still insufficient. This investigation aims to uncover immune-related genes linked to CESC and delineate their functions. Leveraging data from the GEO and ImmPort databases, a total of 22 immune-related genes were identified. Multiple tools, including DAVID, the human protein atlas, STRING, GeneMANIA, and TCGA, were employed to delve into the expression and roles of these immune genes in CESC, alongside their connections to the disease's pathological features. Through RT-PCR, the study confirmed notable disparities in CXCL8 and CXCL10 mRNA expression between CESC and normal cervical tissue. The TCGA dataset's immune-related information reinforced the association of CXCL8 and CXCL10 with immune infiltration in CESC. This research sheds light on the potential of CXCL8 and CXCL10 as promising therapeutic targets and essential prognostic factors for individuals diagnosed with CESC.

Transcriptional Profiling of SARS-CoV-2-Infected Calu-3 Cells Reveals Immune-Related Signaling Pathways

The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in late 2019 and rapidly spread worldwide, becoming a pandemic that infected millions of people and caused significant deaths. COVID-19 continues to be a major threat, and there is a need to deepen our understanding of the virus and its mechanisms of infection. To study the cellular responses to SARS-CoV-2 infection, we performed an RNA sequencing of infected vs. uninfected Calu-3 cells. Total RNA was extracted from infected (0.5 MOI) and control Calu-3 cells and converted to cDNA. Sequencing was performed, and the obtained reads were quality-analyzed and pre-processed. Differential expression was assessed with the EdgeR package, and functional enrichment was performed in EnrichR for Gene Ontology, KEGG pathways, and WikiPathways. A total of 1040 differentially expressed genes were found in infected vs. uninfected Calu-3 cells, of which 695 were up-regulated and 345 were down-regulated. Functional enrichment analyses revealed the predominant up-regulation of genes related to innate immune response, response to virus, inflammation, cell proliferation, and apoptosis. These transcriptional changes following SARS-CoV-2 infection may reflect a cellular response to the infection and help to elucidate COVID-19 pathogenesis, in addition to revealing potential biomarkers and drug targets.