Identity-by-descent approaches identify regions of importance for genetic susceptibility to hereditary esophageal squamous cell carcinoma.

Abstract

Worldwide, the highest prevalence of esophageal cancer (EC) occurs in Northern China. High-density SNP arrays allow identification of identity-by-descent (IBD) segments in genomic DNAs representative of shared common ancestral regions. We utilized IBD approaches to map susceptibility loci associated with low-penetrance SNPs in high-risk Henan hereditary esophageal squamous cell carcinoma (ESCC) patients. Affymetrix GeneChip Human mapping SNP array IBD analysis was performed in 32 Henan family history-positive (FH+) ESCC patients, 18 Henan healthy unrelated individuals, and 45 Chinese individuals from a CHB HapMap dataset using PLink (scoring IBD segments individually) and Beagle (scoring of shared IBD segments among case/case vs. control/control pairs) software. Both analyses identified longer IBD segment lengths associated with FH+ ESCC compared to controls. However, there was no strong evidence for a genetic founder effect. Pairing IBD analysis with BEAGLE identified 8 critical IBD segments residing at 2q32.1-q32.2, 3p22.3-p22.2, 4q21.1-q21.21, 7p22.2, 8q23.2-q23.3, 10q23.33-q24.1, 14q24.3 and 16q11.2-q12.1, which were more significantly shared among case/case compared to control/control. The shared IBD segments in FH+ ESCC samples with no overlap with control/CHB Hapmap may encompass potential cancer susceptibility loci. Selected targeted genes, PLCE1, GPT2, SIAH1 and CYP2C-18, residing within the IBD segments at 10q23.33-q24.1 and 16q11.2-q12.1, had statistically significant differential expression in primary ESCC tissues and are likely involved in ESCC carcinogenesis. The importance of these IBD segments to the etiology and development of ESCC in high-risk areas requires further study with expanded sample sizes. This is the first report employing the pairing IBD approach for elucidation of the genetic basis of hereditary ESCC in Henan by applying high throughput SNP array analysis.