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 m 6 A-related lncRNA clustering patterns in prognosis, TME and immunotherapy of cervical cancer (CC) remains unknown. Here, based on 7 m 6 A-related prognostic lncRNAs obtained from TCGA-CC dataset, two m 6 AlncRNA clustering patterns were determined. m 6 AlncRNA clusterA was characterized by immune cell infiltrates and immune activation. m 6 AlncRNA 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 m 6 AlncRNAscore based on prognostic differentially expressed genes between two m 6 AlncRNA clusters to quantify m 6 AlncRNA clustering patterns. m 6 AlncRNAscore was an independent prognostic protective factor. Higher Th2 and Treg cells and enrichment of immunosuppressive pathways were observed in the low-m 6 AlncRNAscore group, with poorer survival. High-m 6 AlncRNAscore 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 m 6 A-related prognostic lncRNAs. Collectively, we identified two m 6 AlncRNA clustering patterns which play a nonnegligible role in the prognosis, TME heterogeneity and immunotherapy of CC patients.