一种源自tRNA的小RNA预后评估指标的开发及其在骨肉瘤中的潜在功能
Development of a tRNA-Derived Small RNA Prognostic Panel and Their Potential Functions in Osteosarcoma.
作者信息
Tang Zhenming, Zhang Shuhui, Ling Zhougui
机构信息
Department of Pulmonary and Critical Care Medicine, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.
出版信息
Front Oncol. 2021 Aug 2;11:652040. doi: 10.3389/fonc.2021.652040. eCollection 2021.
BACKGROUND
Therapeutic outcomes of osteosarcoma treatment have not significantly improved in several decades. Therefore, strong prognostic biomarkers are urgently needed.
METHODS
We first extracted the tRNA-derived small RNA (tsRNA) expression profiles of osteosarcoma from the GEO database. Then, we performed a unique module analysis and use the LASSO-Cox model to select survival-associated tsRNAs. Model effectiveness was further verified using an independent validation dataset. Target genes with selected tsRNAs were predicted using RNAhybrid.
RESULTS
A LASSO-Cox model was established to select six prognostic tsRNA biomarkers: tRF-33-6SXMSL73VL4YDN, tRF-32-6SXMSL73VL4YK, tRF-32-M1M3WD8S746D2, tRF-35-RPM830MMUKLY5Z, tRF-33-K768WP9N1EWJDW, and tRF-32-MIF91SS2P46I3. We developed a prognostic panel for osteosarcoma patients concerning their overall survival by high-low risk. Patients with a low-risk profile had improved survival rates in training and validation dataset.
CONCLUSIONS
The suggested prognostic panel can be utilized as a reliable biomarker to predict osteosarcoma patient survival rates.
背景
几十年来骨肉瘤治疗的疗效并未显著改善。因此，迫切需要强大的预后生物标志物。
方法
我们首先从基因表达综合数据库（GEO数据库）中提取骨肉瘤的tRNA衍生小RNA（tsRNA）表达谱。然后，我们进行了独特模块分析，并使用套索-考克斯模型选择与生存相关的tsRNA。使用独立验证数据集进一步验证模型有效性。使用RNAhybrid预测所选tsRNA的靶基因。
结果
建立了套索-考克斯模型以选择六个预后tsRNA生物标志物：tRF-33-6SXMSL73VL4YDN、tRF-32-6SXMSL73VL4YK、tRF-32-M1M3WD8S746D2、tRF-35-RPM830MMUKLY5Z、tRF-33-K768WP9N1EWJDW和tRF-32-MIF91SS2P46I3。我们针对骨肉瘤患者的总生存期，根据高低风险制定了一个预后评估指标。低风险的患者在训练和验证数据集中生存率更高。
结论
所建议的预后评估指标可作为预测骨肉瘤患者生存率的可靠生物标志物。
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