High-resolution single-nucleotide polymorphism array and clustering analysis of loss of heterozygosity in human lung cancer cell lines

Pasi A. Jänne, Cheng Li, Xiaojun Zhao, Luc Girard, Tzu Hsiu Chen, John Minna, David C. Christiani, Bruce E. Johnson, Matthew Meyerson

Research output: Contribution to journalArticle

87 Scopus citations

Abstract

Chromosomal loss of heterozygosity (LOH) is a common mechanism for the inactivation of tumor suppressor genes in human epithelial cancers. Hybridization to single-nucleotide polymorphism (SNP) arrays is an efficient method to detect genome-wide cancer LOH. Here, we survey LOH patterns in a panel of 33 human lung cancer cell lines using SNP array hybridization containing 1500 SNPs. We compared the LOH patterns generated by SNP array hybridization to those previously obtained by 399 microsatellite markers and find a high degree of concordance between the two methods. A novel informatics platform, dChipSNP, was used to perform hierarchical tumor clustering based on genome-wide LOH patterns. We demonstrate that this method can separate non-small-cell and small-cell lung cancer samples based on their shared LOH. Furthermore, we analysed seven human lung cancer cell lines using a novel 10000 SNP array and demonstrate that this is an efficient and reliable method of high-density allelotyping. Using this array, we identified small regions of LOH that were not detected by lower density SNP arrays or by standard microsatellite marker panels.

Original languageEnglish (US)
Pages (from-to)2716-2726
Number of pages11
JournalOncogene
Volume23
Issue number15
DOIs
StatePublished - Apr 8 2004

Keywords

  • Loss of heterozygosity
  • Lung neoplasm
  • Non-small cell
  • Single-nucleotide polymorphism
  • Small-cell carcinoma

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Cancer Research

Fingerprint Dive into the research topics of 'High-resolution single-nucleotide polymorphism array and clustering analysis of loss of heterozygosity in human lung cancer cell lines'. Together they form a unique fingerprint.

  • Cite this