five

NanoStrong miRNA from DU145 CF and HF cells

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE241078
下载链接
链接失效反馈
官方服务:
资源简介:
NanoString duplicate runs were created for CF- and HF-resistant cells, and for matched parental duplicate samples corresponding to each radioresistant cell type. Prostate cancer is the second most common cause of cancer death in men, and radiotherapy is a standard curative therapy for localized disease. Unfortunately, aggressive radioresistant relapses can arise, and the molecular underpinnings of radioresistance are unknown. Modern clinical radiotherapy is evolving to deliver higher doses of radiation in fewer fractions (hypofractionation). We therefore analyzed genomic, transcriptomic and proteomic data to characterize the determinants of prostate cancer radioresistance in cells treated with both conventionally fractionated and hypofractionated radiotherapy. Independent of fractionation schedule, resistance to radiotherapy involved massive genomic instability and abrogation of DNA mismatch repair. Specific prostate cancer driver genes were modulated at the RNA and protein levels, with distinct protein subcellular responses to radiotherapy. Conventional fractionation led to a far more aggressive biomolecular response than hypofractionation. Testing pre-clinical candidates identified in cell lines, we revealed POLQ as a radiosensitizer. POLQ-modulated radioresistance in model systems and was predictive of it in large patient cohorts. Pharmacologic and genetic inhibition of POLQ re-sensitized radioresistant cells, creating signatures seen in primary patient cohorts. The molecular response to radiation is highly multi-modal, and sheds light on prostate cancer lethality. We analyzed miRNA data to characterize the determinants of prostate cancer radioresistance in cells treated with both conventionally fractionated and hypofractionated radiotherapy.
创建时间:
2024-10-09
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