Identification and Validation of a Potential Prognostic 7-lncRNA Signature for Predicting Survival in Patients with Multiple Myeloma
| Autor: | Zhe Liu, Yun Zhong, Qinyuan Liao, Dangchi Li, Jingao Li |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Oncology medicine.medical_specialty Article Subject Kaplan-Meier Estimate Biology General Biochemistry Genetics and Molecular Biology 03 medical and health sciences 0302 clinical medicine Text mining Risk Factors Internal medicine Biomarkers Tumor medicine Humans KEGG Gene Multiple myeloma Proportional Hazards Models Framingham Risk Score General Immunology and Microbiology Receiver operating characteristic business.industry Proportional hazards model General Medicine Gene signature Prognosis medicine.disease Gene Expression Regulation Neoplastic Survival Rate 030104 developmental biology ROC Curve 030220 oncology & carcinogenesis Medicine RNA Long Noncoding Multiple Myeloma business Research Article |
| Zdroj: | BioMed Research International BioMed Research International, Vol 2020 (2020) |
| ISSN: | 2314-6141 2314-6133 |
| DOI: | 10.1155/2020/3813546 |
| Popis: | Background. An increasing number of studies have indicated that the abnormal expression of certain long noncoding RNAs (lncRNAs) is linked to the overall survival (OS) of patients with myeloma. Methods. Gene expression data of myeloma patients were downloaded from the Gene Expression Omnibus (GEO) database (GSE4581 and GSE57317). Cox regression analysis, Kaplan-Meier, and receiver operating characteristic (ROC) analysis were performed to construct and validate the prediction model. Single sample gene set enrichment (ssGSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to predict the function of a specified lncRNA. Results. In this study, a seven-lncRNA signature was identified and used to construct a risk score system for myeloma prognosis. This system was used to stratify patients with different survival rates in the training set into high-risk and low-risk groups. Test set, the entire test set, the external validation set, and the myeloma subtype achieved the authentication of the results. In addition, functional enrichment analysis indicated that 7 prognostic lncRNAs may be involved in the tumorigenesis of myeloma through cancer-related pathways and biological processes. The results of the immune score showed that IF_I was negatively correlated with the risk score. Compared with the published gene signature, the 7-lncRNA model has a higher C-index (above 0.8). Conclusion. In summary, our data provide evidence that seven lncRNAs could be used as independent biomarkers to predict the prognosis of myeloma, which also indicated that these 7 lncRNAs may be involved in the progression of myeloma. |
| Databáze: | OpenAIRE |
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