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肺癌中tsRNAs的诊断和预后值:一个元分析

Cheng Tang¹, Su-Xia Sun¹, Chao Gu²

¹Department of Respiratory Medicine, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China.

|January 28, 2025

概括

高水平的tRNA衍生小RNAs (tsRNAs) 显示出作为诊断肺癌 (LC) 和预测患者预后的生物标志物的潜力. 需要进一步的研究来证实这些发现.

科学领域:

生物标志物生物标志物
分子瘤学分子瘤学
诊断的准确性诊断的准确性

背景情况:

肺癌 (LC) 是全球癌症死亡的主要原因之一.
tRNA衍生小RNAs (tsRNAs) 正在成为LC发展中的关键参与者.
调查tsRNAs作为LC的新生物标志物是必不可少的.

研究的目的:

评估不同表达的tsRNAs在肺癌中的诊断和预后价值.
进行对LC中tsRNAs现有研究的元分析.

主要方法:

在PubMed和Web of Science的系统文献搜索到2024年1月10日.
使用诊断概率比率 (DOR) 和接收器运行特征曲线 (AUC) 下的区域用于诊断的元分析.
危险比率 (HRs) 和95%信心区间 (95%CI) 用于预后分析.

主要成果:

包括12项研究,表明tRNAs具有LC的诊断潜力 (联合DOR=7.32,AUC=0.81).
血清tRNA水平显示出强烈的诊断疗效 (DOR=16.56,AUC=0.88).
升高的tsRNA水平与较差的LC患者预后显著相关 (HR=1.59,95% CI:1.33-1.90).

结论:

高水平的tsRNA显示出对诊断肺癌和预测患者结果的希望.
需要进一步的高质量研究来验证这些发现和临床实用性.

关键词:

诊断诊断诊断的诊断肺癌是一种肺癌.进行元分析分析.预测预测预测预测的时间.我们的 tsRNAsRNAs.

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相关概念视频

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...