SET domains are conserved amino acid motifs present in chromosomal proteins that function in epigenetic control of gene expression. These proteins can be divided into four classes as typified by their Drosophila members E(Z), TRX, ASH1 and SU(VAR)3-9. Homologs of all four classes have been identified in yeast and mammals, but not in plants. A BLASTP screening of the Arabidopsis genome identified 37 genes: three E(z) homologs, five trx homologs, four ash1 homologs and 15 genes similar to Su(var)3-9. Seven genes were assigned as trx-related and three as ash1-related. Only four genes have been described previously. Our classification is based on the characteristics of the SET domains, cysteine-rich regions and additional conserved domains, including a novel YGD domain. RT-PCR analysis, cDNA cloning and matching ESTs show that at least 29 of the genes are active in diverse tissues. The high number of SET domain genes, possibly involved in epigenetic control of gene activity during plant development, can partly be explained by extensive genome duplication in Arabidopsis. Additionally, the lack of introns in the coding region of eight SU(VAR)3-9 class genes indicates evolution of new genes by retrotransposition. The identification of putative nuclear localization signals and AT-hooks in many of the proteins supports an anticipated nuclear localization, which was demonstrated for selected proteins.

BackgroundCancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number.ResultsA comprehensive Bioconductor package for copy number analysis is presented. The package offers a unified framework for single sample, multi-sample and multi-track segmentation and is based on statistically sound penalized least squares principles. Conditional on the number of breakpoints, the estimates are optimal in the least squares sense. A novel and computationally highly efficient algorithm is proposed that utilizes vector-based operations in R. Three case studies are presented.ConclusionsThe R package is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.

Distinct molecular subtypes of breast carcinomas have been identified, but translation into clinical use has been limited. We have developed two platform independent algorithms to explore genomic architectural distortion using array comparative genomic hybridization (aCGH) data to measure 1) whole arm gains and losses (WAAI) and 2) complex rearrangements (CAAI). By applying CAAI and WAAI to data from 595 breast cancer patients we were able to separate the cases into eight subgroups with different distributions of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the Luminal related groups while the complexity identified by CAAI had an overall independent prognostic power. This study emphasizes the relationship between structural genomic alterations, molecular subtype and clinical behavior, and show that objective score of genomic complexity (CAAI) is an independent prognostic marker in breast cancer.

CGH-Explorer is a program for visualization and statistical analysis of microarray-based comparative genomic hybridization (array-CGH) data. The program has preprocessing facilities, tools for graphical exploration of individual arrays or groups of arrays, and tools for statistical identification of regions of amplification and deletion.

Clinical DNA is often available in limited quantities requiring whole-genome amplification for subsequent genome-wide assessment of copy-number variation (CNV) by array-CGH. In pre-implantation diagnosis and analysis of micrometastases, even merely single cells are available for analysis. However, procedures allowing high-resolution analyses of CNVs from single cells well below resolution limits of conventional cytogenetics are lacking. Here, we applied amplification products of single cells and of cell pools (5 or 10 cells) from patients with developmental delay, cancer cell lines and polar bodies to various oligo tiling array platforms with a median probe spacing as high as 65 bp. Our high-resolution analyses reveal that the low amounts of template DNA do not result in a completely unbiased whole genome amplification but that stochastic amplification artifacts, which become more obvious on array platforms with tiling path resolution, cause significant noise. We implemented a new evaluation algorithm specifically for the identification of small gains and losses in such very noisy ratio profiles. Our data suggest that when assessed with sufficiently sensitive methods high-resolution oligo-arrays allow a reliable identification of CNVs as small as 500 kb in cell pools (5 or 10 cells), and of 2.6–3.0 Mb in single cells.

The presence of disseminated tumor cells (DTCs) in bone marrow (BM) identifies breast cancer patients with less favorable outcome. Furthermore, molecular characterization is required to investigate the malignant potential of these cells. This study presents a single‐cell array comparative genomic hybridization (SCaCGH) method providing molecular analysis of immunomorphologically detected DTCs. The resolution limit of the method was estimated using the cancer cell line SK‐BR‐3 on 44 and 244k arrays. The technique was further tested on 28 circulating tumor cells and four hematopoietic cells (HCs) from peripheral blood (n = 8 patients). The SCaCGH method was finally applied to 24 DTCs, three immunopositive cells morphologically classified as probable HCs from breast cancer patients and five HC controls from BM (n = 7 patients plus n = 1 healthy donor). The frequency of copy number changes of the DTCs revealed similarities with primary breast tumor samples. Three of the patients had available profiles for DTCs and the corresponding tumor tissue from primary surgery. More than two‐third of the analyzed DTCs disclosed equivalent changes, both to each other and to the corresponding primary disease, whereas the rest of the cells showed balanced profiles. The probable HCs revealed either balanced profiles (n = 2) or changes comparable to the tumor tissue and DTCs (n = 1), indicating morphological overlap between HCs and DTCs. Similar aberration patterns were visible in DTCs collected at diagnosis and at 3 years relapse‐free follow‐up. SCaCGH may be a powerful tool for the molecular characterization of DTCs.

IntroductionThe detection of circulating tumour cells (CTCs) in the peripheral blood and disseminated tumour cells (DTCs) in the bone marrow are promising prognostic tools for risk stratification in early breast cancer. There is, however, a need for further validation of these techniques in larger patient cohorts with adequate follow-up periods.MethodsWe assayed CTCs and DTCs at primary surgery in 733 stage I or II breast cancer patients with a median follow-up time of 7.6 years. CTCs were detected in samples of peripheral blood mononuclear cells previously stored in liquid-nitrogen using a previously-developed multi-marker quantitative PCR (QPCR)-based assay. DTCs were detected in bone marrow samples by immunocytochemical analysis using anti-cytokeratin antibodies.ResultsCTCs were detected in 7.9% of patients, while DTCs were found in 11.7%. Both CTC and DTC positivity predicted poor metastasis-free survival (MFS) and breast cancer-specific survival (BCSS); MFS hazard ratio (HR) = 2.4 (P < 0.001)/1.9 (P = 0.006), and BCSS HR = 2.5 (P < 0.001)/2.3 (P = 0.01), for CTC/DTC status, respectively). Multivariate analyses demonstrated that CTC status was an independent prognostic variable for both MFS and BCSS. CTC status also identified a subset of patients with significantly poorer outcome among low-risk node negative patients that did not receive adjuvant systemic therapy (MFS HR 2.3 (P = 0.039), BCSS HR 2.9 (P = 0.017)). Using both tests provided increased prognostic information and indicated different relevance within biologically dissimilar breast cancer subtypes.ConclusionsThese results support the use of CTC analysis in early breast cancer to generate clinically useful prognostic information.

Background: Microarray Comparative Genomic Hybridization (array CGH) provides a means to examine DNA copy number aberrations. Various platforms, brands and underlying technologies are available, facing the user with many choices regarding platform sensitivity and number, localization, and density distribution of probes.