Application of inter-simple sequence repeat PCR to XXXX models: assessment of genetic alterations in @entity105 .

@entity1 @entity38534 @entity5 @entity19 @entity957 @entity1042 @entity6732 @entity186 @entity7044 @entity105
Genomic instability is believed to play a significant role in @entity5 development by facilitating @entity5 progression and @entity5 heterogeneity. Inter-simple sequence repeat (inter-SSR) PCR has been proved to be a fast and reproducible technique for quantitation of genomic instability (amplifications, deletions, translocations, and insertions) in @entity1 @entity5 . However, the use of inter-SSR PCR in animal models of @entity5 has never been described. This new technique has been adapted in our laboratory for the analysis of spontaneous and induced @entity19 @entity5 . We established the best PCR conditions for each microsatellite-anchored primer and critically evaluated the reproducibility of the band patterns. We also studied the variation of the fingerprints between and within various inbred @entity19 strains, including wild-derived lines. Tumor-specific alterations were detected as gains, losses, or intensity changes in bands when compared with matched normal DNA. We quantitated the extent of alterations by dividing the number of altered bands in the @entity5 by the total number of bands in normal DNA (instability index). By means of inter-SSR PCR, we successfully analyzed genomic alterations in various @entity19 @entity5 , including spontaneous @entity6732 developed in @entity38534 knockout @entity19 as well as chemically induced @entity957 and @entity6732 . Instability index values ranged between 0 and 9%, the highest levels observed in @entity7044 -induced @entity6732 generated in @entity186 ( @entity186 ) nullizygote (-/-) @entity19 . We report here, for the first time, the use of inter-SSR PCR to detect somatic mutations in @entity19 tumoral DNA, including laser-capture microdissected, @entity1042 -fixed tissues. These PCR-based fingerprints provide a novel approach to assessing the number and onset of mutational events in @entity19 @entity5 and will help to understand better the mechanisms of @entity105 in @entity19 models.
