Prediction of prognosis, immune infiltration and immunotherapy response with N6-methyladenosine-related lncRNA clustering patterns in cervical cancer.

LncRNAs and tumor microenvironment (TME) exert an important effect in antitumor immunity. Nonetheless, the role of m6A-related lncRNA clustering patterns in prognosis, TME and immunotherapy of cervical cancer (CC) remains unknown. Here, based on 7 m6A-related prognostic lncRNAs obtained from TCGA-CC dataset, two m6AlncRNA clustering patterns were determined. m6AlncRNA clusterA was characterized by immune cell infiltrates and immune activation. m6AlncRNA clusterB was characterized by enrichment of immune evasion and tumorigenic activation pathways as well as survival and clinical stage disadvantage. Then, principal component analysis algorithms were used to construct m6AlncRNAscore based on prognostic differentially expressed genes between two m6AlncRNA clusters to quantify m6AlncRNA clustering patterns. m6AlncRNAscore was an independent prognostic protective factor. Higher Th2 and Treg cells and enrichment of immunosuppressive pathways were observed in the low-m6AlncRNAscore group, with poorer survival. High-m6AlncRNAscore was characterized by increased infiltration of activated CD8 T cell, enrichment of immune activation pathways, lower IL-10 and TGF-beta1 levels, and higher immunophenscore values, indicating inflamed TME and better anti-tumor immunotherapy efficacy. Quantitative Real-Time Polymerase Chain Reaction was used for detection of m6A-related prognostic lncRNAs. Collectively, we identified two m6AlncRNA clustering patterns which play a nonnegligible role in the prognosis, TME heterogeneity and immunotherapy of CC patients.

m6A-Related lncRNAs Are Potential Prognostic Biomarkers of Cervical Cancer and Affect Immune Infiltration.

The correlation of m6A-related lncRNAs with the prognosis and immune microenvironment of cervical cancer is not yet clear. In this study, we identified 7 m6A-related prognostic lncRNAs by Pearson correlation and univariate Cox regression analyses based on TCGA-cervical cancer dataset. Then, patients were divided into two clusters by consensus clustering based on the 7 m6A-related prognostic lncRNA expression. Cluster 1 was characterized by survival and stage disadvantage, enrichment of immunosuppressive and carcinogenic activation pathways. Besides, cluster 1 had higher immunosuppressive factor TGFbeta and lower immune cell infiltration compared with cluster 2. According to the expression of 7 m6A-related lncRNA, a 6-m6A-related lncRNA risk score model was established in the training set by LASSO regression analysis. The high-risk group had worse overall survival than the low-risk group. No matter in the training or validation sets, the m6A-related lncRNA risk score was an independent prognostic factor for overall survival. Meanwhile, we validated the independent prognostic value of risk score in the disease-specific survival and progression-free survival by multivariate Cox analysis. The high-risk group was characterized by higher TGFbeta and regulatory T cell and was rich in malignant pathways. Additionally, we also detected and compared the expression levels of four m6A-related prognostic lncRNA in 9 tumor samples and 9 normal tissues using quantitative real-time polymerase chain reaction assay. In conclusion, the novel m6A-related lncRNA risk score is a potential prognostic predictor of cervical cancer patients. These 6 m6A-related lncRNAs might serve as key mediators of the immune microenvironment and represent promising therapeutic targets for improving cervical cancer prognosis.