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Genome-wide genetic characterization of bladder cancer: a comparison of high-density single-nucleotide polymorphism arrays and PCR-based microsatellite analysis.

Most human cancers are characterized by genomic instability, the accumulation of multiple genetic alterations, and allelic imbalance throughout the genome. Loss of heterozygosity (LOH) is a common form of allelic imbalance, and the detection of LOH has been used to identify genomic regions that harbor tumor suppressor genes and to characterize different tumor types, pathological stages and progression. Global patterns of LOH can be discerned by allelotyping of tumors with polymorphic genetic markers. Microsatellites are reliable genetic markers for studying LOH, but typically only a modest number of microsatellites are tested in LOH studies because the genotyping procedure can be laborious. Here we describe the use of a new alternative approach to comprehensive allelotyping in which samples are genotyped for nearly 1500 single-nucleotide polymorphism (SNP) loci distributed across all human autosomal arms. We examined the pattern of allelic imbalance in human transitional cell carcinomas of the urinary bladder including 36 primary tumors and 1 recurrent tumor with matched normal DNAs. The call rate for all SNPs was 78.5 +/- 1.87% overall samples. Overall, the median number of allelic imbalance was 47.5, ranging from 20 to 118. The mean number of allelic imbalances was 36.58, 51.30, and 67.78 for pT(a), pT(1), and > or =pT(2), respectively, and also increased by grade. The SNP microarray analysis result was validated by comparison with microsatellite allelotype analysis of 118 markers in the same tumors. Overall, the two methods produced consistent loss patterns at informative loci. The SNP assay discovered previously undiscovered allelic imbalances at chromosomal arms 12q, 16p, 1p, and 2q. The detection of LOH and other chromosomal changes using large numbers of SNP markers should enable rapid and accurate identification of allelic imbalance patterns that will facilitate the mapping and identification of important cancer genes. Moreover, SNP analysis raises the possibility of individual tumor genome-wide allelotyping with potential prognostic and diagnostic applications.