Abstract | BACKGROUND: METHODS: In this study, all metabolism-related mRNAs and lncRNAs in osteosarcoma were extracted and identified based on transcriptomic data from the TCGA database. Usingsurvival analysis, univariate and multivariate independent prognostic analysis, gene set enrichment analysis, and nomogram, a prognostic signature with metabolic lncRNAs as prognostic factors was constructed. RESULTS: Nine prognostic factors included lncRNA AC009779.2, lncRNA AL591895.1, lncRNA AC026271.3, lncRNA LPP-AS2, lncRNA LINC01857, lncRNA AP005264.1, lncRNA LINC02454, lncRNA AL133338.1, and lncRNA AC135178.5, respectively. Survival analysis indicated that alterations of specific lncRNA expression were strongly correlated with poor prognosis in osteosarcoma. Univariate and multivariate independent prognostic analysis showed that the prognostic signature had a good independent predictive ability for patient survival. The results of GSEA suggested that these predictors may be involved in the metabolism of certain substances or energy in cancer. The nomogram was further drawn for clinical guidance and assistance in clinical decision-making. CONCLUSIONS: This study identified multiple metabolism-related lncRNAs, which may be novel therapeutic targets for osteosarcoma, and contributed to better explore the specific metabolic regulatory mechanisms of lncRNA in osteosarcoma.
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Authors | Xingyin Chen, Zhengyun Ye, Pan Lou, Wei Liu, Ying Liu |
Journal | Journal of orthopaedic surgery and research
(J Orthop Surg Res)
Vol. 16
Issue 1
Pg. 523
(Aug 23 2021)
ISSN: 1749-799X [Electronic] England |
PMID | 34425868
(Publication Type: Journal Article)
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Copyright | © 2021. The Author(s). |
Chemical References |
- Biomarkers, Tumor
- RNA, Long Noncoding
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Topics |
- Adolescent
- Biomarkers, Tumor
(genetics)
- Child
- Gene Expression Regulation, Neoplastic
- Humans
- Osteosarcoma
(genetics)
- Prognosis
- RNA, Long Noncoding
(genetics)
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