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

利用N6-甲基腺苷相关lncRNA聚类模式预测宫颈癌的预后、免疫浸润和免疫治疗反应

阅读:2
作者:Haixia Jia #,Meiting Cao #,Suhua Hao,Jiahao Wang,Jintao Wang

Abstract

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。