Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

Li Zhang; Xianzhe Tang; Jia Wan; Xianghong Zhang; Tao Zheng; Zhengjun Lin; Tang Liu

doi:10.3389/fmolb.2021.715764

Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

Front Mol Biosci. 2021 Oct 15:8:715764. doi: 10.3389/fmolb.2021.715764. eCollection 2021.

Authors

Li Zhang^{1

2}, Xianzhe Tang³, Jia Wan¹, Xianghong Zhang¹, Tao Zheng¹, Zhengjun Lin^{1

4}, Tang Liu¹

Affiliations

¹ Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, China.
² Department of Endocrinology, The Fifth Central Hospital of Tianjin, Tianjin, China.
³ Department of Orthopedics, Chenzhou No. 1 People's Hospital, Chenzhou, China.
⁴ Xiangya School of Medicine, Central South University, Changsha, China.

Abstract

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations. Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan-Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature. Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS. Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

Keywords: N6-methyladenosine methylation; immune microenvironment; long noncoding RNAs; prognostic signature; soft tissue sarcomas.