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1.
Oncogene ; 33(36): 4464-73, 2014 Sep 04.
Article in English | MEDLINE | ID: mdl-24096489

ABSTRACT

In an effort to identify novel biallelically inactivated tumor suppressor genes (TSGs) in sporadic invasive and preinvasive non-small-cell lung cancer (NSCLC) genomes, we applied a comprehensive integrated multiple 'omics' approach to investigate patient-matched, paired NSCLC tumor and non-malignant parenchymal tissues. By surveying lung tumor genomes for genes concomitantly inactivated within individual tumors by multiple mechanisms, and by the frequency of disruption in tumors across multiple cohorts, we have identified a putative lung cancer TSG, Eyes Absent 4 (EYA4). EYA4 is frequently and concomitantly deleted, hypermethylated and underexpressed in multiple independent lung tumor data sets, in both major NSCLC subtypes and in the earliest stages of lung cancer. We found that decreased EYA4 expression is not only associated with poor survival in sporadic lung cancers but also that EYA4 single-nucleotide polymorphisms are associated with increased familial cancer risk, consistent with EYA4s proximity to the previously reported lung cancer susceptibility locus on 6q. Functionally, we found that EYA4 displays TSG-like properties with a role in modulating apoptosis and DNA repair. Cross-examination of EYA4 expression across multiple tumor types suggests a cell-type-specific tumorigenic role for EYA4, consistent with a tumor suppressor function in cancers of epithelial origin. This work shows a clear role for EYA4 as a putative TSG in NSCLC.


Subject(s)
Carcinoma, Non-Small-Cell Lung/epidemiology , Gene Silencing , Lung Neoplasms/pathology , Trans-Activators/genetics , Carcinoma, Non-Small-Cell Lung/genetics , Chromosomes, Human, Pair 6 , DNA Methylation , Epigenesis, Genetic , Gene Deletion , Gene Expression Regulation, Neoplastic , Gene Frequency , Genes, Tumor Suppressor , Genetic Association Studies , Genetic Variation , Genome, Human , Humans , Lung Neoplasms/genetics , Polymorphism, Single Nucleotide , Trans-Activators/metabolism , Tumor Cells, Cultured
2.
Br J Cancer ; 103(8): 1277-83, 2010 Oct 12.
Article in English | MEDLINE | ID: mdl-20842114

ABSTRACT

BACKGROUND: Lung squamous cell carcinomas (SqCCs) occur at higher rates following arsenic exposure. Somatic DNA copy-number alterations (CNAs) are understood to be critical drivers in several tumour types. We have assembled a rare panel of lung tumours from a population with chronic arsenic exposure, including SqCC tumours from patients with no smoking history. METHODS: Fifty-two lung SqCCs were analysed by whole-genome tiling-set array comparative genomic hybridisation. Twenty-two were derived from arsenic-exposed patients from Northern Chile (10 never smokers and 12 smokers). Thirty additional cases were obtained for comparison from North American smokers without arsenic exposure. Twenty-two blood samples from healthy individuals from Northern Chile were examined to identify germline DNA copy-number variations (CNVs) that could be excluded from analysis. RESULTS: We identified multiple CNAs associated with arsenic exposure. These alterations were not attributable to either smoking status or CNVs. DNA losses at chromosomes 1q21.1, 7p22.3, 9q12, and 19q13.31 represented the most recurrent events. An arsenic-associated gain at 19q13.33 contains genes previously identified as oncogene candidates. CONCLUSIONS: Our results provide a comprehensive approach to molecular characteristics of the arsenic-exposed lung cancer genome and the non-smoking lung SqCC genome. The distinct and recurrent arsenic-related alterations suggest that this group of tumours may be considered as a separate disease subclass.


Subject(s)
Arsenic/toxicity , Carcinoma, Non-Small-Cell Lung/genetics , DNA Copy Number Variations/drug effects , Lung Neoplasms/genetics , Algorithms , Allelic Imbalance/genetics , Case-Control Studies , Chromosomes, Human , Comparative Genomic Hybridization , Environmental Exposure/adverse effects , Gene Expression Profiling , Gene Frequency , Humans , Oligonucleotide Array Sequence Analysis
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