RESUMO
BACKGROUND: Cuproptosis induces proteotoxic stress and eventually leads to cell death. However, the relationship between cuproptosis and lncRNAs in cervical cancer has not been fully elucidated. Therefore, we aim to explore the association among lncRNAs, cuproptosis and clinical features in cervical cancer. METHODS: RNA sequencing, genetic mutations, and clinical data of CESC patients were obtained from TCGA. Cuproptosis-associated genes were gathered. WGCNA was used to cluster important modules, and KEGG, GO, GSEA and GSVA were used to explore functional and pathway enrichment. The association between immune microenvironment and cuproptosis-related lncRNAs was performed by using cibersort algorithm and other platforms, including XCELL, TIMER, QUANTISEQ, MCPCOUNTER and EPIC. Fluorescence quantitative PCR was employed to detect the expression of LINC01833 and LINC02321, and CCK-8 and cell scratch assays were used to assess cell proliferation and migration capabilities after LINCRNA interference. RESULTS: 202 upregulated and 45 downregulated lncRNAs were selected. The survival analysis showed that there was a statistically significant difference in survival rates between the high-risk and low-risk groups. The prognosis of tumour mutation burden and the degree of immune infiltration were differed noticeably between the high-risk and low-risk groups. BHG712, TL-2-105, FR-180204, Masitinib, TAK-715, ODI-027, JW-7-24-2, and OSI-930 had substantially higher IC50 values in the high-risk group. Notably, we found AL360178.1 was associated with RNF44 E3 ubiquitin ligase expression. In cervical cancer cell lines, LINC01833 and LINC02321 displayed significant upregulation. Efficient siRNA transfection led to a decreased expression of LINC01833 and LINC02321. This knockdown significantly hindered both cell proliferation and migration capabilities in cervical cancer cells compared to the negative control. CONCLUSION: In conclusion, we constructed five cuprotosis-related lncRNA prognostic models, which may be new tumor therapeutic targets for the prevention and treatment of cervical cancer.
RESUMO
BACKGROUND: Cervical cancer (CC) remains a significant clinical challenge, even though its fatality rate has been declining in recent years. Particularly in developing countries, the prognosis for CC patients continues to be suboptimal despite numerous therapeutic advances. METHODS: Using The Cancer Genome Atlas database, we extracted CC-related data. From this, 52 methylation-related genes (MRGs) were identified, leading to the selection of a 10 long non-coding RNA (lncRNA) signature co-expressed with these MRGs. R programming was employed to filter out the methylation-associated lncRNAs. Through univariate, least absolute shrinkage and selection operator (i.e. LASSO) and multivariate Cox regression analysis, an MRG-associated lncRNA model was constructed. The established risk model was further assessed via the Kaplan-Meier method, principal component analysis, functional enrichment annotation and a nomogram. Furthermore, we explored the potential of this model with respect to guiding immune therapeutic interventions and predicting drug sensitivities. RESULTS: The derived 10-lncRNA signature, linked with MRGs, emerged as an independent prognostic factor. Segmenting patients based on their immunotherapy responses allowed for enhanced differentiation between patient subsets. Lastly, we highlighted potential compounds for distinguishing CC subtypes. CONCLUSIONS: The risk model, associated with MRG-linked lncRNA, holds promise in forecasting clinical outcomes and gauging the efficacy of immunotherapies for CC patients.
