发现与乳腺癌和前列腺癌中草药治疗相关的长非编码RNA的模式
Elham Dalalbashi Esfahani1, Esmaeil Ebrahimie2,3,4, Ali Niazi1
1Institute of Biotechnology Shiraz University Shiraz 7196484334 Iran.
Quantitative biology (Beijing, China)
|February 12, 2026
概括
这项研究确定了与乳腺癌和前列腺癌草药治疗相关的与癌症相关的长非编码RNA (lncRNAs). 一个深度学习模型准确地预测了这些lncRNA,突出了它们作为生物标志物的潜力.
科学领域:
- 基因组学和生物信息学
- 癌症研究 癌症研究
- 药理学 药理学是指药理学的学科.
背景情况:
- 长非编码RNAs (lncRNAs) 越来越多地被认为是癌症进展中的角色.
- lncRNAs与草药之间的关联在很大程度上仍未被探索.
- 了解这种联系可能会揭示乳腺癌和前列腺癌等癌症的新疗法策略.
研究的目的:
- 为了确定 lncRNAs 和草药干预在乳腺癌和前列腺癌之间潜在的关联.
- 使用机器学习开发和验证用于识别癌症相关 lncRNA 的预测模型.
- 探索 lncRNA 与传递 RNA (mRNA) 共同表达的网络,以应对草药治疗.
主要方法:
- 分析了来自乳腺和前列腺癌的RNA测序 (RNA-seq) 数据,以构建共表达网络.
- 对差异性共同表达的mRNA进行了基因本体学 (GO) 和通路分析,以了解lncRNA功能.
- 实现了包括深度学习在内的机器学习模型,以预测与癌症相关的lncRNAs,并使用属性加权来评估变量重要性.
主要成果:
- 发现 lncRNAs 与代谢过程基因广泛共同表达.
- 确定了两种关键的lncRNA-mRNA网络,它们与乳腺癌和前列腺癌有关.
- 深度学习模型在预测与癌症相关的lncRNA方面实现了高准确度 (91.11%),灵敏度 (88.33%) 和特异性 (93.33%),其中"癌症下调RNA" (DRAIC) 被确定为一个重要的特征.
结论:
- 这项研究在乳腺癌和前列腺癌的背景下,建立了lncRNAs和草药之间的联系.
- 已识别的lncRNAs,特别是DRAIC,显示出作为癌症诊断和预后的潜在生物标志物具有前途.
- 这项研究为进一步调查lncRNAs作为草药治疗癌症治疗中的治疗点提供了基础.
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