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Comparison of primary neuroblastoma tumors and derivative early-passage cell lines using genome-wide SNP array analysis

ABSTRACT: Stromal contamination is one of the major confounding factors in the analysis of primary solid tumor samples by single nucleotide polymorphism (SNP) arrays. As we propose to employ genome-wide SNP microarray analysis as a diagnostic platform for neuroblastoma, the sensitivity, specificity, and accuracy of these studies must be optimized. In order to investigate the effects of stroma, we derived early passage cell lines from nine primary tumors and compared their genomic signature with that of the primary tumors by 100K SNP array analysis. The average concordance between tumor and cell line for raw LOH (loss of heterozygosity) calls was 96% (range 91%-99%) and for raw copy number alterations (CNA), 71% (range 43%-87%). In general, there were a larger number of LOH events identified in the cell lines compared to the matched tumor samples (mean increase 3.2% ± 1.9%). We have developed an algorithm that shows that the presence of stroma contributes to under-reporting of LOH and copy number loss (CNL). Notable findings in this sample set were uniparental disomy (UPD) of chromosome arms 11p, 1q, 14q, and 15q and a novel area of amplification on chromosome band 11p15. Our analysis demonstrates that LOH was identified significantly more often in derived cell lines compared to the original tumor samples. While these may in part be due to clonal selection during adaptation to tissue culture, our study indicates contamination by normal stromal elements may be a major contributing factor in underestimation of LOH and CNL events. Keywords: genome wide SNP analysis

ORGANISM(S): Homo sapiens

PROVIDER: GSE14656 | GEO | 2009/01/31

SECONDARY ACCESSION(S): PRJNA112343

REPOSITORIES: GEO

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Project description:BACKGROUND: Cervical carcinoma develops as a result of multiple genetic alterations. Different studies investigated genomic alterations in cervical cancer mainly by means of metaphase comparative genomic hybridization (mCGH) and microsatellite marker analysis for the detection of loss of heterozygosity (LOH). Currently, high throughput methods such as array comparative genomic hybridization (array CGH), single nucleotide polymorphism array (SNP array) and gene expression arrays are available to study genome-wide alterations. Integration of these 3 platforms allows detection of genomic alterations at high resolution and investigation of an association between copy number changes and expression. RESULTS: Genome-wide copy number and genotype analysis of 10 cervical cancer cell lines by array CGH and SNP array showed highly complex large-scale alterations. A comparison between array CGH and SNP array revealed that the overall concordance in detection of the same areas with copy number alterations (CNA) was above 90%. The use of SNP arrays demonstrated that about 75% of LOH events would not have been found by methods which screen for copy number changes, such as array CGH, since these were LOH events without CNA. Regions frequently targeted by CNA, as determined by array CGH, such as amplification of 5p and 20q, and loss of 8p were confirmed by fluorescent in situ hybridization (FISH). Genome-wide, we did not find a correlation between copy-number and gene expression. At chromosome arm 5p however, 22% of the genes were significantly upregulated in cell lines with amplifications as compared to cell lines without amplifications, as measured by gene expression arrays. For 3 genes, SKP2, ANKH and TRIO, expression differences were confirmed by quantitative real-time PCR (qRT-PCR). CONCLUSION: This study showed that copy number data retrieved from either array CGH or SNP array are comparable and that the integration of genome-wide LOH, copy number and gene expression is useful for the identification of gene specific targets that could be relevant for the development and progression in cervical cancer. Keywords: DNA copynumber RNA expression correlation

Project description:We applied whole-genome single nucleotide polymorphism (SNP) arrays to define a comprehensive genetic profile of 23 esophageal adenocarcinoma (EAC) primary tumor biopsies based on loss of heterozygosity (LOH) and DNA copy number changes. Alterations were common, averaging 97 (range 23-208) per tumor. LOH and gains averaged 33 (range 3-83) and 31 (range 11-73) per tumor, respectively. Copy neutral LOH events averaged 27 (range 7-57) per EAC. We noted 126 homozygous deletions (HDs) across the EAC panel (range 0-11 in individual tumors). Frequent HDs within FHIT (17/23), WWOX (8/23) and DMD (6/23) suggest a role for common fragile sites or genomic instability in EAC etiology. HDs were also noted for known tumor suppressor genes (TSGs) including: CDKN2A, CDKN2B, SMAD4 and GALR1, and identified PDE4D and MGC48628 as potentially novel TSGs. All tumors showed LOH for most of chromosome 17p, suggesting that TSGs other than TP53 maybe targeted. Frequent gains were noted around MYC (13/23), BCL9 (12/23), CTAGE1 (14/23) and ZNF217 (12/23). Thus, we have confirmed previous reports indicating frequent changes to FHIT, CDKN2A, TP53 and MYC in EAC and identified additional genes of interest. Meta analysis of previous genome-wide EAC studies together with the data presented here, highlighted consistent regions of gain on 8q, 18q and 20q, and multiple LOH regions on 4q, 5q, 17p and 18q, suggesting that more than one gene may be targeted on each of these chromosome arms. The focal gains and deletions documented here are a step towards identifying the key genes involved in EAC development. Keywords: High Density SNP array Here we use Illumina 317K whole-genome single-nucleotide polymorphism arrays to define a comprehensive allelotype of melanoma based on loss of heterozygosity (LOH) and copy number changes in a panel of 23 esophageal adenocarcinoma (EAC) primary tumor biopsies. Each EAC was paired to normal squamous biopsy from 40328 (GSM266078) to generate the log_R_ratio.

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Comparison of primary neuroblastoma tumors and derivative early-passage cell lines using genome-wide SNP array analysis

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