five

Lenti-miR Library SW620, Pre vs Post Intrahepatic Selection. Homo sapiens

收藏
NIAID Data Ecosystem2026-03-08 收录
下载链接:
https://www.ncbi.nlm.nih.gov/bioproject/PRJNA242911
下载链接
链接失效反馈
官方服务:
资源简介:
Cells were transduced with a lentiviral Lenti-miR library composed of 661 miRNAs (System Biosciences) at a low multiplicity of infection (MOI) such that each cell over-expressed a single miRNA. The transduced population was then injected intra-hepatically into NOD-SCID mice for in vivo selection of miRNAs that when over-expressed, either promoted or suppressed metastatic liver colonization. Genomic DNA PCR amplication and recovery of lenti-viral miRNA inserts was performed on cells prior to injection, and from liver nodules, according to the manufacturer’s protocol. miRNA array profiling allowed for miRNA insert quantification prior to and subsequent to in vivo selection. Overall design: To use an unbiased approach to identify regulators of colon cancer metastasis, we transduced a population of colon cancer cells, SW620, with a lenti-miR library comprising of 661 human miRNAs, such that each individual cells over-express a single miRNA. The heterogenous population is then injected into the liver of immunodeficient mice. We theorized that cells over-expressing miRNAs that modulate colon cancer metastais will have differential representation in the whole population compared to a reference pool of cells. miRNAs that suppressed colon cancer metastasis will be lost in the resulting pool, while miRNAs that promote metastasis will be over-represented compared to the reference pool. Replicate pools of cells were transduced and injected into mice. After a period of 3-5 weeks, liver nodules were taken out and processed for lenti-viral derived miRNA profiling (Post samples) and compared to the reference pool of cells that were not injected into the mice (Pre Samples). The changes in miRNA representation between cells that underwent liver colonization were analyzed.
创建时间:
2014-03-28
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