SiCmiR地图:单细胞miRNA景观揭示了人类癌症中的Hub-miRNA和网络特征
Xiao-Xuan Cai1,2, Jing-Shan Liao2, Jia-Jun Ma2
1Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, P. R. China.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|February 15, 2026
概括
SiCmiR是一种新型的神经网络,可以从有限的基因数据中预测微RNA (miRNA) 表达,克服单细胞分析的挑战. 这使得我们能够对miRNA生物学和在各种癌症中发现生物标志物的新见解.
科学领域:
- 基因组学和生物信息学
- 分子生物学分子生物学
- 计算生物学 计算生物学
背景情况:
- 微RNAs (miRNAs) 是基因表达的关键调节者.
- 单细胞miRNA分析在技术上具有挑战性,限制了生物学见解.
- 现有的方法在单细胞RNA测序 (scRNA-seq) 中与数据稀疏性和脱落作斗争.
研究的目的:
- 开发一种用于预测单细胞水平上miRNA表达的计算方法.
- 为了克服小型RNA测序的技术限制.
- 为单细胞miRNA分析和生物标志物发现创建一个全面的资源.
主要方法:
- 开发了SiCmiR,一个双层神经网络,使用977个里程碑基因来预测miRNA表达.
- 在6462个TCGA配对miRNA-mRNA样本上训练SiCmiR.
- 构建了SiCmiR-Atlas,一个包含362个公共数据集 (936万个细胞,726种细胞类型) 的数据库.
主要成果:
- SiCmiR从有限的基因数据中准确地预测miRNA表达特征,降低scRNA-seq脱落的敏感性.
- 在各种癌症 (肝细胞癌,胰腺管道癌) 中确定了候选的枢纽miRNAs,并在质母细胞瘤中进行细胞外囊泡介导的交叉.
- SiCmiR在癌症类型和药物干扰中展示了最先进的准确性和概括性.
- SiCmiR-Atlas提供交互式可视化,生物标记物识别和miRNA目标网络.
结论:
- SiCmiR有效地将批量衍生的统计能力转化为对miRNA生物学单细胞视图.
- SiCmiR-Atlas 作为一个有价值的社区资源,用于单细胞miRNA研究和生物标志物发现.
- 开发的方法克服了以前的技术障碍,使我们能够更深入地了解miRNA在细胞过程和疾病中的功能.
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