EPISODE · Jun 16, 2026 · 22 MIN
1137-CTDPathSim2.0：基于多组学数据表征肿瘤与细胞系相似性
from 聊聊Sci
这项研究介绍了 CTDPathSim2.0，这是一种通过整合多组学数据（包括基因表达、DNA甲基化和拷贝数变异）来评估癌症细胞系与患者肿瘤样本相似性的计算流程。研究人员通过去卷积算法处理肿瘤的异质性，并结合生物通路活性，为22种癌症类型建立了精细的相似性评分体系。结果表明，该工具在预测临床药物反应以及识别组织特异性细胞系方面优于现有的单组学方法。该成果已开发为 R 软件程序包，旨在帮助科研人员筛选最能代表人类肿瘤的实验模型，从而提高癌症精准医疗和药物研发的转化效率。References:Bose, B., Bozdag, S. Identifying cell lines across pan-cancer to be used in preclinical research as a proxy for patient tumor samples. Commun Biol 7, 1101 (2024). https://doi.org/10.1038/s42003-024-06812-3前往小宇宙评论区与主播互动
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1137-CTDPathSim2.0：基于多组学数据表征肿瘤与细胞系相似性
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