Transcriptional Impact of Rare and Private Copy Number Variants in Hypoplastic Left Heart Syndrome.

BACKGROUND: Hypoplastic left heart syndrome (HLHS) is a heterogeneous, lethal combination of congenital malformations characterized by severe underdevelopment of left heart structures, resulting in a univentricular circulation. The genetic determinants of this disorder are largely unknown. Evidence of copy number variants (CNVs) contributing to the genetic etiology of HLHS and other congenital heart defects has been mounting. However, the functional effects of such CNVs have not been examined, particularly in cases where the variant of interest is found in only a single patient. METHODS AND RESULTS: Whole-genome SNP microarrays were employed to detect CNVs in two patient cohorts (N = 70 total) predominantly diagnosed with some form of nonsyndromic HLHS. We discovered 16 rare or private variants adjacent to or overlapping 20 genes associated with cardiovascular or premature lethality phenotypes in mouse knockout models. We evaluated the impact of selected variants on the expression of nine of these genes through quantitative PCR on cDNA derived from patient heart tissue. Four genes displayed significantly altered expression in patients with an overlapping or proximal CNV verses patients without such CNVs. CONCLUSION: Rare and private genomic imbalances perturb transcription of genes that potentially affect cardiogenesis in a subset of nonsyndromic HLHS patients.

Application of SNP microarrays to the genome-wide analysis of chromosomal instability in premalignant airway lesions.

Chromosomal instability is central to the process of carcinogenesis. The genome-wide detection of somatic chromosomal alterations (SCA) in small premalignant lesions remains challenging because sample heterogeneity dilutes the aberrant cell information. To overcome this hurdle, we focused on the B allele frequency data from single-nucleotide polymorphism microarrays (SNP arrays). The difference of allelic fractions between paired tumor and normal samples from the same patient (delta-θ) provides a simple but sensitive detection of SCA in the affected tissue. We applied the delta-θ approach to small, heterogeneous clinical specimens, including endobronchial biopsies and brushings. Regions identified by delta-θ were validated by FISH and quantitative PCR in heterogeneous samples. Distinctive genomic variations were successfully detected across the whole genome in all invasive cancer cases (6 of 6), carcinoma in situ (3 of 3), and high-grade dysplasia (severe or moderate; 3 of 11). Not only well-described SCAs in lung squamous cell carcinoma, but also several novel chromosomal alterations were frequently found across the preinvasive dysplastic cases. Within these novel regions, losses of putative tumor suppressors (RNF20 and SSBP2) and an amplification of RASGRP3 gene with oncogenic activity were observed. Widespread sampling of the airway during bronchoscopy demonstrated that field cancerization reflected by SCAs at multiple sites was detectable. SNP arrays combined with delta-θ analysis can detect SCAs in heterogeneous clinical sample and expand our ability to assess genomic instability in the airway epithelium as a biomarker of lung cancer risk.