A combination of cuproptosis and lncRNAs predicts the prognosis and tumor immune microenvironment in cervical cancer.

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.

Copine 1 predicts poor clinical outcomes by promoting M2 macrophage activation in ovarian cancer.

OBJECTIVE: Copine 1 (CPNE1), a membrane-binding protein, influences the prognosis of various cancers. According to cBioPortal, CPNE1 amplification is a prevalent genetic mutation in ovarian cancer but with unknown oncogenic mechanism. METHODS: This study analysed the CPNE1 expression in ovarian cancer using online datasets, as validated by immunohistochemistry (IHC), quantitative polymerase chain reaction (qPCR) and western blotting. Concurrently, the prognostic value of CPNE1 was accessed. Cell Counting Kit-8, colony formation, transwells and xenograft experiments were performed to evaluate the functions of CPNE1 during ovarian cancer carcinogenesis. CPNE1 and its related genes were analysed by g:Profiler and Tumour Immune Estimation Resource. Furthermore, human monocytic THP-1 cells were co-cultured with ES2 cells to investigate the effect of CPNE1 on macrophage polarization. RESULTS: The results of bioinformatic analysis, IHC, qPCR and western blotting indicated a higher CPNE1 in ovarian cancer. CPNE1 overexpression demonstrated an association with a poor prognosis of ovarian cancer. Functionally, CPNE1 overexpression increased ES2 and SKOV3 cell proliferation, invasion and migration in vitro and promoted ovarian tumour xenograft growth in vivo, while CPNE1 knockdown led to opposite effects. Additionally, CPNE1 expression demonstrated an association with immune cell infiltration in ovarian cancer, especially macrophage. CPNE1 promoted protumour M2 macrophage polarization by upregulating cluster of differentiation 163 (CD163), CD206 and interleukin-10. CONCLUSIONS: Our study revealed that CPNE1 mediated M2 macrophage polarization and provided a therapeutic target for ovarian cancer.

Four Types of RNA Modification Writer-Related lncRNAs Are Effective Predictors of Prognosis and Immunotherapy Response in Serous Ovarian Carcinoma.

Serous ovarian carcinoma (SOC) is a gynecological malignancy with high mortality rates. Currently, there is a lack of reliable biomarkers for accurate SOC patient prognosis. Here, we analyzed SOC RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify prognostic biomarkers. Through the pearson correlation analysis, univariate Cox regression analysis, and LASSO-penalized Cox regression analysis, we identified nine lncRNAs significantly associated with four types of RNA modification writers (m6A, m1A, APA, and A-I) and with the prognosis of SOC patients (P <0.05). Six writer-related lncRNAs were ultimately selected following multivariate Cox analysis. We established a risk prediction model based on these six lncRNAs and evaluated its prognostic value in multiple groups (training set, testing set, and entire set). Our risk prediction model could effectively predict the prognosis of SOC patients with different clinical characteristics and their responses to immunotherapy. Lastly, we validated the predictive reliability and sensitivity of the lncRNA-based model via a nomogram. This study explored the association between RNA modification writer-related lncRNAs and SOC prognosis, providing a potential complement for the clinical management of SOC patients.