five

Distinct Molecular Responses of Human Intestinal Organoids to Proton and Photon Radiation

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP584993
下载链接
链接失效反馈
官方服务:
资源简介:
Radiation exposure causes damage to tissues with high numbers of rapidly dividing cells such as the intestine. Mouse models have been widely used to understand the effects of radiation injury, repair following exposure, and to develop and test potential therapies for radiation-induced damage. However, although the mouse intestine shares physiological and molecular similarities with human intestine, translation and validation of findings in mouse radiation models to the human intestine have been limited by the lack of models. The development of ex vivo human intestinal organoids provides a new model in which the effects of radiation on the human intestinal epithelium can be examined and compared to in vivo animal models. Using human small intestinal jejunal organoids, multi-omic profiles were analyzed using bioinformatic pipelines to explore the response to a dose of proton and photon radiation exposure which may be encountered during a radiotherapy treatment or over time in high background radiation environments. Transcriptional signatures following radiation exposure were indicative of reprogramming of cells to a more primitive state that has been associated with regeneration and repair. Integrative analyses of transcriptomic and metabolomic datasets revealed enrichment of amino acid synthesis and metabolism pathways. Human intestinal organoids can complement and validate findings from traditional animal models and are emerging as a powerful tool to study responses to radiation exposure. Overall design: RNAseq analysis of crypt-like or villus-like human intestinal organoids (HIO) exposed to 1Gy gamma irradiation, 1Gy LET proton irradiation or left unirradiated. Three technical replicates for each donor crypt and villus HIO +/- radiation exposure were pooled prior to RNA extraction.
创建时间:
2026-01-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作