Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Affymetrix SNP array data for breast cancer formation in mouse

ABSTRACT: We investigated the CNAs in a four stage tumorigenesis model. This model included copy number analyses in non-transgenic NMRI mice (normal) and in transgenic SVT/t mice: non-malignant hyperplastic mammary glands and breast cancers, as well as breast cancer derived cell lines. We focused our research on copy number analyses to compare the genomic alterations that occur during tumorigenesis. We addressed the question, whether common predisposed chromosomal breakpoints could be seen to promote malignant transformation. We can report a characteristic increase of copy number alterations from normal to tumor stage in our model. Furthermore, we have identified chromosomal segments and found characteristic fragmentations. Affymetrix SNP array analysis was performed with Mouse Diversity Genotyping Arrays (Affymetrix). DNA was extracted from frozen biopsies of mammary tumor samples of six mice and two cell lines. Normalization and allele summarization were performed with the BRLMM-P algorithm provided and copy number analysis was performed for the each sample using the average signal intensity of both normal samples as the reference for copy number inference.

ORGANISM(S): Mus musculus

SUBMITTER: Christoph Standfuß

PROVIDER: E-GEOD-35873 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

SNP microarray analyses reveal copy number alterations and progressive genome reorganization during tumor development in SVT/t driven mice breast cancer.

Standfuss Christoph C Pospisil Heike H Klein Andreas A

BMC cancer 20120831

<h4>Background</h4>Tumor development is known to be a stepwise process involving dynamic changes that affect cellular integrity and cellular behavior. This complex interaction between genomic organization and gene, as well as protein expression is not yet fully understood. Tumor characterization by gene expression analyses is not sufficient, since expression levels are only available as a snapshot of the cell status. So far, research has mainly focused on gene expression profiling or alterations ...[more]

PMID: 22935085

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Project description:For sporadic Burkitt lymphoma (BL) few genetic lesions are known besides the pathognomonic IG-MYC translocations. Thirtynine molecularly-defined BL were analyzed with high-resolution single-nucleotide polymorphism chips for genomic imbalances and uniparental disomy (UPD). Imbalances were correlated to transcript profiling and selected miRNA analysis. Translocations affecting the MYC locus were studied by fluoresence in situ hybridization. We detected 528 copy number changes, defining 29 recurrently imbalanced regions. 518 regions of UPD were found, but these were rarely recurrent. Combined imbalance mapping and transcript profiling revealed a profound correlation between copy number and expression. Several recurrent imbalances affected the MYC pathway: The miRNA-supercluster 17-92 was frequently gained and the transcription factor E2F2 was recurrently deleted. Molecular BL lacking MYC translocations showed MYC gains. Amplifications of the polymerase iota gene were associated with increased genomic instability. The present findings suggests that UPDs play no major role in the pathogenesis of BL, whereas some genes may contribute to BL development through gene dosage effects. Amplifications of the polymerase iota gene may be functionally linked with increased genomic instability in BL. The pattern and rarity of chromosomal changes detectable even at the high resolution employed here, together with aberrations of genes regulating MYC activity, support that deregulation of the MYC pathway is the major force driving BL pathogenesis, but show that this deregulation is more complex than previously known. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from whole tissue. Copy number and LOH analysis of 500K SNP arrays was performed for 30 molecularly-defined Burkitt lymphomas. Genotyping was performed using the BRLMM-algorithm. Only a single 250k Chip was performed for nine additional Burkitts. 20 normal references (10 of those hybridized to nsp-chips) extracted from healthy blood donors, used as normals in the analysis in addition to the HapMap references provided by Affymetrix, are included in the set.

Project description:Generating sufficient DNA for high-throughput genetic analysis has always been a challenge for clinical settings where the amount of source DNA is limited. Multiple displacement amplification (MDA) has been proposed as a promising candidate for such situations. Previous work with lower-resolution arrays confirmed the utility of single-cell MDA products for large-size (~30 Mb) genome variation screening. We tested the performance of single-cell MDA products on the SNP 6.0 arrays to examine the performance of single-cell MDA in SNP genotyping, copy number polymorphism, de novo copy number variation (CNV) and loss of heterozygosity (LOH) analysis. Our data show that for SNP genotyping, single-cell MDA did not obtain complete genome coverage or high sequence fidelity. For CNV calling, single-cell MDA introduced stochastic amplification artifacts in log2 ratio profiles, reducing the robustness of CNV calling; however, by adjusting smooth window size, it is still possible to analyze large chromosomal aberrations, and homozygous deletions as small as 500 kb can still be identified from the noisy log2 ratio profiles. Our results also suggest that even with a modified protocol (reduction of reaction volume, addition of a molecular crowding reagent, minimization of reaction time), single-cell MDA presented little improvement over the unmodified protocol, but by increasing the number of cells as template to 5M-bM-^@M-^S10 cells, SNP 6.0 array results comparable to those of 10 ng genomic DNA MDA could be obtained. Algorithms like PICNIC improved the CNV calling, suggesting that better algorithms can better utilize single-cell MDA array results. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cell line samples, and multiple displacement samples. Genotyping, Copy number and LOH analysis of Affymetrix SNP 6.0 arrays was performed for 3 samples of unamplified cell line genomic DNA, 2 samples of DNA obtained by multiple displacement amplification from 10ng genomic DNA, 3 single-cell multiple displacement amplification (MDA) products, single cell modified MDA amplification product, 5-cell modified MDA amplification product, 10-cell modified MDA amplification product.

Dataset Information

Affymetrix SNP array data for breast cancer formation in mouse

Publications

SNP microarray analyses reveal copy number alterations and progressive genome reorganization during tumor development in SVT/t driven mice breast cancer.

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