Identification of Long Non-Coding RNAs for Predicting Prognosis Among Patients with Thymoma
| Autor: | Yu Liu, Jian Gong, Lifang Ye, Qipeng Xie, Xujing Pan, Shengxin Jin, Guiye Wang, Hongqun Tao, Huaikai Wen |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Oncology Male medicine.medical_specialty Multivariate statistics Multivariate analysis Thymoma Kaplan-Meier Estimate General Biochemistry Genetics and Molecular Biology 03 medical and health sciences 0302 clinical medicine Text mining Internal medicine medicine Biomarkers Tumor Humans Aged Framingham Risk Score business.industry Proportional hazards model Gene Expression Profiling Univariate Thymus Neoplasms Middle Aged medicine.disease Prognosis Mediastinal Neoplasm Gene Expression Regulation Neoplastic 030104 developmental biology 030220 oncology & carcinogenesis Multivariate Analysis Female RNA Long Noncoding Neoplasm Recurrence Local business |
| Zdroj: | Clinical laboratory. 64(7) |
| ISSN: | 1433-6510 |
| Popis: | BACKGROUND Thymoma is the most common primary anterior mediastinal neoplasm with a high recurrence rate. Long noncoding RNAs (lncRNAs) have recently been indicated to be used as diagnostic and prognostic indicators for different cancers. The aim of this study was to identify new tumor-specific prognostic lncRNA markers that can improve the treatment and follow-up of patients with thymomas. METHODS One hundred seventeen thymoma patients with clinical information and level 3 RNAseqv2 data were downloaded from The Cancer Genome Atlas. Prognostic lncRNAs were identified using Kaplan-Meier survival analyses and univariate Cox proportional hazards regression analyses. A predictive risk scoring model was subsequently created using independently significant lncRNAs from a multivariate Cox regression analysis. RESULTS Masaoka stage and 13 lncRNAs were significantly associated with RFS among 117 thymoma patients, while 59 lncRNAs were significantly associated with OS (all p < 0.05). Multivariate analyses revealed that OS was only independently associated with one lncRNA (JPX) and that RFS was only independently associated with three lncRNAs (AFAP1-AS1, LINC00324, and VLDLR-AS1). A risk score model constructed by the three lncRNA expressions showed that the high-risk group was more likely to experience recurrence. CONCLUSIONS The expression profile for three lncRNAs (AFAP1-AS1, LINC00324, and VLDLR-AS1) could be used to independently predict RFS among thymoma patients, which may be as prognostic biomarkers for thymoma. |
| Databáze: | OpenAIRE |
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