Automated array-CGH optimized for archival formalin-fixed, paraffin-embedded tumor material

BACKGROUND: Array Comparative Genomic Hybridization (aCGH) is a rapidly evolving technology that still lacks complete standardization. Yet, it is of great importance to obtain robust and reproducible data to enable meaningful multiple hybridization comparisons. Special difficulties arise when aCGH is performed on archival formalin-fixed, paraffin-embedded (FFPE) tissue due to its variable DNA quality. Recently, we have developed an effective DNA quality test that predicts suitability of archival samples for BAC aCGH. METHODS: In this report, we first used DNA from a cancer cell-line (SKBR3) to optimize the aCGH protocol for automated hybridization, and subsequently optimized and validated the procedure for FFPE breast cancer samples. We aimed for highest throughput, accuracy, and reproducibility applicable to FFPE samples, which can also be important in future diagnostic use. RESULTS: Our protocol of automated array-CGH on archival FFPE ULS-labeled DNA showed very similar results compared with published data and our previous manual hybridization method. CONCLUSION: This report combines automated aCGH on unamplified archival FFPE DNA using non-enzymatic ULS labeling, and describes an optimized protocol for this combination resulting in improved quality and reproducibility

Breast cancer cell lines carry cell line-specific genomic alterations that are distinct from aberrations in breast cancer tissues: Comparison of the CGH profiles between cancer cell lines and primary cancer tissues

<p>Abstract</p> <p>Background</p> <p>Cell lines are commonly used in various kinds of biomedical research in the world. However, it remains uncertain whether genomic alterations existing in primary tumor tissues are represented in cell lines and whether cell lines carry cell line-specific genomic alterations. This study was performed to answer these questions.</p> <p>Methods</p> <p>Array-based comparative genomic hybridization (CGH) was employed with 4030 bacterial artificial chromosomes (BACs) that cover the genome at 1.0 megabase resolution to analyze DNA copy number aberrations (DCNAs) in 35 primary breast tumors and 24 breast cancer cell lines. DCNAs were compared between these two groups. A tissue microdissection technique was applied to primary tumor tissues to reduce the contamination of samples by normal tissue components.</p> <p>Results</p> <p>The average number of BAC clones with DCNAs was 1832 (45.3% of spotted clones) and 971 (24.9%) for cell lines and primary tumor tissues, respectively. Gains of 1q and 8q and losses of 8p, 11q, 16q and 17p were detected in >50% of primary cancer tissues. These aberrations were also frequently detected in cell lines. In addition to these alterations, the cell lines showed recurrent genomic alterations including gains of 5p14-15, 20q11 and 20q13 and losses of 4p13-p16, 18q12, 18q21, Xq21.1 and Xq26-q28 that were barely detected in tumor tissue specimens. These are considered to be cell line-specific DCNAs. The frequency of the HER2 amplification was high in both cell lines and tumor tissues, but it was statistically different between cell lines and primary tumors (P = 0.012); 41.3 ± 29.9% for the cell lines and 15.9 ± 18.6% for the tissue specimens.</p> <p>Conclusions</p> <p>Established cell lines carry cell lines-specific DCNAs together with recurrent aberrations detected in primary tumor tissues. It must therefore be emphasized that cell lines do not always represent the genotypes of parental tumor tissues.</p

Activation of Estrogen-Responsive Genes Does Not Require Their Nuclear Co-Localization

The spatial organization of the genome in the nucleus plays a role in the regulation of gene expression. Whether co-regulated genes are subject to coordinated repositioning to a shared nuclear space is a matter of considerable interest and debate. We investigated the nuclear organization of estrogen receptor alpha (ERα) target genes in human breast epithelial and cancer cell lines, before and after transcriptional activation induced with estradiol. We find that, contrary to another report, the ERα target genes TFF1 and GREB1 are distributed in the nucleoplasm with no particular relationship to each other. The nuclear separation between these genes, as well as between the ERα target genes PGR and CTSD, was unchanged by hormone addition and transcriptional activation with no evidence for co-localization between alleles. Similarly, while the volume occupied by the chromosomes increased, the relative nuclear position of the respective chromosome territories was unaffected by hormone addition. Our results demonstrate that estradiol-induced ERα target genes are not required to co-localize in the nucleus

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

<p>Abstract</p> <p>Background</p> <p>Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer.</p> <p>Results</p> <p>Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD) analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations.</p> <p>Conclusions</p> <p>Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.</p

Array-CGH and breast cancer

The introduction of comparative genomic hybridization (CGH) in 1992 opened new avenues in genomic investigation; in particular, it advanced analysis of solid tumours, including breast cancer, because it obviated the need to culture cells before their chromosomes could be analyzed. The current generation of CGH analysis uses ordered arrays of genomic DNA sequences and is therefore referred to as array-CGH or matrix-CGH. It was introduced in 1998, and further increased the potential of CGH to provide insight into the fundamental processes of chromosomal instability and cancer. This review provides a critical evaluation of the data published on array-CGH and breast cancer, and discusses some of its expected future value and developments