N6-Methyladenosine-Related lncRNAs Are Anticipated Biomarkers for Sarcoma Patients

Background. Soft tissue sarcomas (STSs) are rare tumors and occur at any site in the body. Our goal was to identify a putative molecular mechanism for N6-methyladenosine (m6A) lncRNA alteration and to develop predictive biomarkers for sarcoma. Methods. The lncRNA levels were obtained from TCGA datas...

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Published inJournal of oncology Vol. 2022; pp. 1093805 - 10
Main Authors Zhang, Xiaohe, Li, Hongbo, Zhou, Liuzhi, Wu, Di, Zhou, Shixiang, Yang, Yao, Hu, Yabin
Format Journal Article
LanguageEnglish
Published Egypt Hindawi 2022
Hindawi Limited
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Summary:Background. Soft tissue sarcomas (STSs) are rare tumors and occur at any site in the body. Our goal was to identify a putative molecular mechanism for N6-methyladenosine (m6A) lncRNA alteration and to develop predictive biomarkers for sarcoma. Methods. The lncRNA levels were obtained from TCGA datasets. Pearson correlation analysis was used to select all the lncRNAs that are connected to m6A. An m6A-related lncRNA model was built using LASSO Cox regression. To assess the prognostic efficiency of the model and potential lncRNAs, we performed univariate survival analysis and receiver operating characteristic (ROC) analysis. We also performed enrichment analysis to evaluate the roles of the potential genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to confirm m6A-related lncRNA expression in tissues. Results. Following Pearson correlation analysis on TCGA datasets, we identified 78 m6A-related lncRNAs. Next, we used LASSO Cox regression analysis and identified 13 m6A-related lncRNAs as prognostic lncRNAs. After calculating risk scores, sarcoma patients were divided into high- and low-risk groups depending on the median of risk scores. We also found that these lncRNAs were immune associated via enrichment analysis. Conclusions. Here, we found that SNHG1, FIRRE, and YEATS2-AS1 could serve as biomarkers to predict overall survival of sarcoma patients, which provides a new insight into treatment of STS.
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Academic Editor: Xiangya Ding
ISSN:1687-8450
1687-8450
DOI:10.1155/2022/1093805