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Identification and validation of potential prognostic lncRNA biomarkers for predicting survival in patients with multiple myeloma

机译:鉴定和验证潜在的预后性lncRNA生物标志物,以预测多发性骨髓瘤患者的生存

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Background Dysregulated long non-coding RNAs (lncRNAs) have been found to have oncogenic and/or tumor suppressive roles in the development and progression of cancer, implying their potentials as novel independent biomarkers for cancer diagnosis and prognosis. However, the prognostic significance of expression profile-based lncRNA signature for outcome prediction in patients with multiple myeloma (MM) has not yet been investigated. Methods LncRNA expression profiles of a large cohort of patients with MM were obtained and analyzed by repurposing the publically available microarray data. An lncRNA-focus risk score model was developed from the training dataset, and then validated in the testing and another two independent external datasets. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance for survival prediction. The biological function of prognostic lncRNAs was predicted using bioinformatics analysis. Results Four lncRNAs were identified to be significantly associated with overall survival (OS) of patients with MM in the training dataset, and were combined to develop a four-lncRNA prognostic signature to stratify patients into high-risk and low-risk groups. Patients of training dataset in the high-risk group exhibited shorter OS than those in the low-risk group (HR?=?2.718, 95?% CI?=?1.937-3.815, p Conclusions Our results demonstrated potential application of lncRNAs as novel independent biomarkers for diagnosis and prognosis in MM. These lncRNA biomarkers may contribute to the understanding of underlying molecular basis of MM.
机译:背景技术已发现失调的长非编码RNA(lncRNA)在癌症的发展和进程中具有致癌和/或肿瘤抑制作用,这暗示了它们作为癌症诊断和预后的新型独立生物标记物的潜力。但是,尚未研究基于表达谱的lncRNA签名对多发性骨髓瘤(MM)患者预后的预测意义。方法通过重新利用公开的微阵列数据,获得并分析了大批MM患者的LncRNA表达谱。从训练数据集中开发了一个lncRNA聚焦风险评分模型,然后在测试和另外两个独立的外部数据集中进行了验证。随时间变化的接收器工作特征(ROC)曲线用于评估生存预测的预后表现。使用生物信息学分析预测了预后的lncRNA的生物学功能。结果在训练数据集中鉴定出4个与MM患者的总生存期(OS)显着相关的lncRNA,并结合以形成4-lncRNA的预后标志,将患者分为高风险和低风险组。高风险组的训练数据集患者的OS较低风险组的患者短(HR?=?2.718,95 %% CI?=?1.937-3.815,p结论)我们的结果证明了lncRNAs作为新型的潜在应用用于MM诊断和预后的独立生物标志物这些lncRNA生物标志物可能有助于理解MM的潜在分子基础。

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