PLoS ONE (Jan 2014)
Genome-wide analysis of loss of heterozygosity in breast infiltrating ductal carcinoma distant normal tissue highlights arm specific enrichment and expansion across tumor stages.
Abstract
Studies have shown concurrent loss of heterozygosity (LOH) in breast infiltrating ductal carcinoma (IDC) and adjacent or distant normal tissue. However, the overall extent of LOH in normal tissue and their significance to tumorigenesis remain unknown, as existing studies are largely based on selected microsatellite markers. Here we present the first autosome-wide study of LOH in IDC and distant normal tissue using informative loci deduced from SNP array-based and sequencing-based techniques. We show a consistently high LOH concurrence rate in IDC (mean = 24%) and distant normal tissue (m = 54%), suggesting for most patients (31/33) histologically normal tissue contains genomic instability that can be a potential marker of increased IDC risk. Concurrent LOH is more frequent in fragile site related genes like WWOX (9/31), NTRK2 (10/31), and FHIT (7/31) than traditional genetic markers like BRCA1 (0/23), BRCA2 (2/29) and TP53 (1/13). Analysis at arm level shows distant normal tissue has low level but non-random enrichment of LOH (topped by 8p and 16q) significantly correlated with matched IDC (Pearson r = 0.66, p = 3.5E-6) (topped by 8p, 11q, 13q, 16q, 17p, and 17q). The arm-specific LOH enrichment was independently observed in tumor samples from 548 IDC patients when stratified by tumor size based T stages. Fine LOH structure from sequencing data indicates LOH in low order tissues non-randomly overlap (∼67%) with LOH that usually has longer tract length (the length of genomic region affected by LOH) in high order tissues. The consistent observations from multiple datasets suggest progressive LOH in the development of IDC potentially through arm-specific pile up effect with discernible signature in normal tissue. Our finding also suggests that LOH detected in IDC by comparing to paired adjacent or distant normal tissue are more likely underestimated.