Suppr超能文献

使用交互式神经母细胞瘤细胞系浏览器CLEAN对DNA损伤反应途径进行临床前探索。

Preclinical exploration of the DNA damage response pathway using the interactive neuroblastoma cell line explorer CLEAN.

作者信息

Gabre Jonatan L, Merseburger Peter, Claeys Arne, Siaw Joachim, Bekaert Sarah-Lee, Speleman Frank, Hallberg Bengt, Palmer Ruth H, Van den Eynden Jimmy

机构信息

Department of Human Structure and Repair, Anatomy and Embryology Unit, Ghent University, Ghent, Belgium.

Cancer Research Institute Ghent, Ghent, Belgium.

出版信息

NAR Cancer. 2024 Jan 11;6(1):zcad062. doi: 10.1093/narcan/zcad062. eCollection 2024 Mar.

Abstract

Neuroblastoma (NB) is the most common cancer in infancy with an urgent need for more efficient targeted therapies. The development of novel (combinatorial) treatment strategies relies on extensive explorations of signaling perturbations in neuroblastoma cell lines, using RNA-Seq or other high throughput technologies (e.g. phosphoproteomics). This typically requires dedicated bioinformatics support, which is not always available. Additionally, while data from published studies are highly valuable and raw data (e.g. fastq files) are nowadays released in public repositories, data processing is time-consuming and again difficult without bioinformatics support. To facilitate NB research, more user-friendly and immediately accessible platforms are needed to explore newly generated as well as existing high throughput data. To make this possible, we developed an interactive data centralization and visualization web application, called CLEAN (the Cell Line Explorer web Application of Neuroblastoma data; https://ccgg.ugent.be/shiny/clean/). By focusing on the regulation of the DNA damage response, a therapeutic target of major interest in neuroblastoma, we demonstrate how CLEAN can be used to gain novel mechanistic insights and identify putative drug targets in neuroblastoma.

摘要

神经母细胞瘤(NB)是婴儿期最常见的癌症,迫切需要更有效的靶向治疗。新型(联合)治疗策略的开发依赖于使用RNA测序或其他高通量技术(如磷酸化蛋白质组学)对神经母细胞瘤细胞系中的信号扰动进行广泛探索。这通常需要专门的生物信息学支持,但这种支持并非总是可得。此外,虽然已发表研究的数据非常有价值,且原始数据(如fastq文件)如今已在公共数据库中发布,但若无生物信息学支持,数据处理既耗时又困难。为促进NB研究,需要更用户友好且能立即访问的平台来探索新生成的以及现有的高通量数据。为实现这一点,我们开发了一个交互式数据集中化和可视化网络应用程序,称为CLEAN(神经母细胞瘤数据的细胞系探索者网络应用程序;https://ccgg.ugent.be/shiny/clean/)。通过聚焦于DNA损伤反应的调节,这是神经母细胞瘤中一个主要关注的治疗靶点,我们展示了CLEAN如何用于获得新的机制见解并识别神经母细胞瘤中潜在的药物靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69e3/10782898/e4847c4b2b83/zcad062figgra1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验