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E-GEOD-49200 GSE49200 transcription profiling by array Mus musculus

An oncogenic Kras expression signature identified by cross-species

·发布 2013年8月1日 ·更新 2015年7月20日
50
样本数
50
实验数
1
芯片平台
1
相关文献
实验描述

Mouse lung cancers were generated using the KrasLA model, in which a latent mutated Kras2 allele (resulting in the amino acid substitution G12D) is sporadically activated through spontaneous homologous recombination. These mice develop lung adenomas with full penetrance; over time, the tumors acquire morphologic characteristics reminiscent of those of human adenocarcinoma, such as nuclear atypia and a high mitotic index. KrasLA2 mice on a 129svJae background were crossed with wild type C57B/6J mice to obtain F1 progeny. The initial report of this mouse model described two alleles, KrasLA1 and KrasLA2. All expression profiles in this study were generated using the KrasLA2 mice. We call the model KrasLA throughout for simplicity. Mice bearing the KrasLA latent allele were allowed to develop to 5-6 month of age and sacrificed by cervical dislocation. Lungs were removed and placed in RNAlaterTM solution (Ambion). Individual tumors large enough to be easily dissected (3mm-8mm) were removed and cut into 2 pieces. One piece was placed in formalin to be used for histological analysis while the other piece was stored at -80 for RNA/DNA extraction. Gene expression profiling was perfomed on lung tumors derived from KrasLA mouse (n = 31) and normal mouse lung samples (n = 19).

参考文献
An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis.
Sweet-Cordero A, Mukherjee S, Subramanian A, You H, Roix JJ, Ladd-Acosta C, Mesirov J, Golub TR, Jacks T.
PMID: 15608639
芯片平台
A-AFFY-6
Affymetrix GeneChip Murine Genome U74Av2 [MG_U74Av2](50 例)
样本属性
age
5 to 6 month
genotype
KrasG12D, wild type
organism
Mus musculus
organism part
lung
实验信息
登记号
E-GEOD-49200
GEO 编号
GSE49200
实验类型
transcription profiling by array
物种
Mus musculus
发布日期
2013年8月1日
更新日期
2015年7月20日
提交者
J J Roix、 T R Golub、 J Mesirov、 H You、 C Ladd-Acosta、 A Subramanian、 A Sweet-Cordero、 S Mukherjee、 T Jacks、 Dedeepya Vaka
分析服务
分析服务

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