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

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer

A comparative study between mixed-type tumours from human salivary and canine mammary glands

<p>Abstract</p> <p>Background</p> <p>In comparative pathology, canine mammary tumours have special interest because of their similarities with human breast cancer. Mixed tumours are uncommon lesions in the human breast, but they are found most frequently in the mammary gland of the female dogs and in the human salivary glands. The aim of the study was to compare clinical, morphological and immunohistochemical features of human salivary and canine mammary gland mixed tumours, in order to evaluate the latter as an experimental model for salivary gland tumours.</p> <p>Methods</p> <p>Ten examples of each mixed tumour type (human pleomorphic adenoma and carcinomas ex-pleomorphic adenomas and canine mixed tumour and metaplastic carcinoma) were evaluated. First, clinical and morphologic aspects of benign and malignant variants were compared between the species. Then, streptavidin-biotin-peroxidase immunohistochemistry was performed to detect the expression of cytokeratins, vimentin, p63 protein, estrogen receptor, β-catenin, and E-cadherin.</p> <p>Results</p> <p>After standardization, similar age and site distributions were observed in human and canine tumours. Histological similarities were identified in the comparison of the benign lesions as well. Metaplastic carcinomas also resembled general aspects of carcinomas ex-pleomorphic adenomas in morphological evaluation. Additionally, immunohistochemical staining further presented similar antigenic expression between lesions.</p> <p>Conclusion</p> <p>There are many similar features between human salivary and canine mammary gland mixed tumours. This observation is of great relevance for those interested in the study and management of salivary gland tumours, since canine lesions may constitute useful comparative models for their investigations.</p

Next-generation sequencing

Next-generation sequencing (also known as massively parallel sequencing) technologies are revolutionising our ability to characterise cancers at the genomic, transcriptomic and epigenetic levels. Cataloguing all mutations, copy number aberrations and somatic rearrangements in an entire cancer genome at base pair resolution can now be performed in a matter of weeks. Furthermore, massively parallel sequencing can be used as a means for unbiased transcriptomic analysis of mRNAs, small RNAs and noncoding RNAs, genome-wide methylation assays and high-throughput chromatin immunoprecipitation assays. Here, I discuss the potential impact of this technology on breast cancer research and the challenges that come with this technological breakthrough

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

<p>Abstract</p> <p>Background</p> <p>Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.</p> <p>Methods</p> <p>This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.</p> <p>Results</p> <p>The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.</p> <p>Conclusions</p> <p>The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.</p

Levels of DNA methylation vary at CpG sites across the BRCA1 promoter, and differ according to triple negative and "BRCA-like" status, in both blood and tumour DNA

Triple negative breast cancer is typically an aggressive and difficult to treat subtype. It is often associated with loss of function of the BRCA1 gene, either through mutation, loss of heterozygosity or methylation. This study aimed to measure methylation of the BRCA1 gene promoter at individual CpG sites in blood, tumour and normal breast tissue, to assess whether levels were correlated between different tissues, and with triple negative receptor status, histopathological scoring for BRCA-like features and BRCA1 protein expression. Blood DNA methylation levels were significantly correlated with tumour methylation at 9 of 11 CpG sites examined (p<0.0007). The levels of tumour DNA methylation were significantly higher in triple negative tumours, and in tumours with high BRCA-like histopathological scores (10 of 11 CpG sites; p<0.01 and p<0.007 respectively). Similar results were observed in blood DNA (6 of 11 CpG sites; p<0.03 and 7 of 11 CpG sites; p<0.02 respectively). This study provides insight into the pattern of CpG methylation across the BRCA1 promoter, and supports previous studies suggesting that tumours with BRCA1 promoter methylation have similar features to those with BRCA1 mutations, and therefore may be suitable for the same targeted therapies