Multicolour-banding fluorescence in situ hybridisation (mbanding-FISH) to identify recurrent chromosomal alterations in breast tumour cell lines

Recurrent chromosome breakpoints in tumour cells may point to cancer genes, but not many have been molecularly characterised. We have used multicolour-banding fluorescence in situ hybridisation (mbanding-FISH) on breast tumour cell lines to identify regions of chromosome break created by inversions, duplications, insertions and translocations on chromosomes 1, 5, 8, 12 and 17. We delineate a total of 136 regions of break, some of them occurring with high frequency. We further describe two examples of dual-colour FISH characterisation of breakpoints, which target the 1p36 and 5p11–12 regions. Both breaks involve genes whose function is unknown to date. The mbanding-FISH strategy constitutes an efficient first step in the search for potential cancer genes

Detection of copy number variation from array intensity and sequencing read depth using a stepwise Bayesian model

Abstract Background Copy number variants (CNVs) have been demonstrated to occur at a high frequency and are now widely believed to make a significant contribution to the phenotypic variation in human populations. Array-based comparative genomic hybridization (array-CGH) and newly developed read-depth approach through ultrahigh throughput genomic sequencing both provide rapid, robust, and comprehensive methods to identify CNVs on a whole-genome scale. Results We developed a Bayesian statistical analysis algorithm for the detection of CNVs from both types of genomic data. The algorithm can analyze such data obtained from PCR-based bacterial artificial chromosome arrays, high-density oligonucleotide arrays, and more recently developed high-throughput DNA sequencing. Treating parameters--e.g., the number of CNVs, the position of each CNV, and the data noise level--that define the underlying data generating process as random variables, our approach derives the posterior distribution of the genomic CNV structure given the observed data. Sampling from the posterior distribution using a Markov chain Monte Carlo method, we get not only best estimates for these unknown parameters but also Bayesian credible intervals for the estimates. We illustrate the characteristics of our algorithm by applying it to both synthetic and experimental data sets in comparison to other segmentation algorithms. Conclusions In particular, the synthetic data comparison shows that our method is more sensitive than other approaches at low false positive rates. Furthermore, given its Bayesian origin, our method can also be seen as a technique to refine CNVs identified by fast point-estimate methods and also as a framework to integrate array-CGH and sequencing data with other CNV-related biological knowledge, all through informative priors.</p

Assessment of a six gene panel for the molecular detection of circulating tumor cells in the blood of female cancer patients

<p>Abstract</p> <p>Background</p> <p>The presence of circulating tumor cells (CTC) in the peripheral blood of cancer patients has been described for various solid tumors and their clinical relevance has been shown. CTC detection based on the analysis of epithelial antigens might be hampered by the genetic heterogeneity of the primary tumor and loss of epithelial antigens. Therefore, we aimed to identify new gene markers for the PCR-based detection of CTC in female cancer patients.</p> <p>Methods</p> <p>Gene expression of 38 cancer cell lines (breast, ovarian, cervical and endometrial) and of 10 peripheral blood mononuclear cell (PBMC) samples from healthy female donors was measured using microarray technology (Applied Biosystems). Differentially expressed genes were identified using the maxT test and the 50% one-sided trimmed maxT-test. Confirmatory RT-qPCR was performed for 380 gene targets using the AB TaqMan^®Low Density Arrays. Then, 93 gene targets were analyzed using the same RT-qPCR platform in tumor tissues of 126 patients with primary breast, ovarian or endometrial cancer. Finally, blood samples from 26 healthy women and from 125 patients (primary breast, ovarian, cervical, or endometrial cancer, and advanced breast cancer) were analyzed following OncoQuick enrichment and RNA pre-amplification. Likewise, <it>hMAM </it>and <it>EpCAM </it>gene expression was analyzed in the blood of breast and ovarian cancer patients. For each gene, a cut-off threshold value was set at three standard deviations from the mean expression level of the healthy controls to identify potential markers for CTC detection.</p> <p>Results</p> <p>Six genes were over-expressed in blood samples from 81% of patients with advanced and 29% of patients with primary breast cancer. <it>EpCAM </it>gene expression was detected in 19% and 5% of patients, respectively, whereas <it>hMAM </it>gene expression was observed in the advanced group (39%) only. Multimarker analysis using the new six gene panel positively identified 44% of the cervical, 64% of the endometrial and 19% of the ovarian cancer patients.</p> <p>Conclusions</p> <p>The panel of six genes was found superior to <it>EpCAM </it>and <it>hMAM </it>for the detection of circulating tumor cells in the blood of breast cancer, and they may serve as potential markers for CTC derived from endometrial, cervical, and ovarian cancers.</p

A Case Matched Gender Comparison Transcriptomic Screen Identifies eIF4E and eIF5 as Potential Prognostic and Tractable Biomarkers in Male Breast Cancer

Purpose: Breast cancer (BC) affects both genders, but is understudied in men. Although still rare, male BC is being diagnosed more frequently. Treatments are wholly informed by clinical studies conducted in women, based on assumptions that underlying biology is similar. Experimental design: A transcriptomic investigation of male and female BC was performed, confirming transcriptomic data in silico. Biomarkers were immunohistochemically assessed in 697 MBCs (n=477, training; n=220, validation set) and quantified in pre- and post-treatment samples from a male BC patient receiving Everolimus and PI3K/mTOR inhibitor. Results: Gender-specific gene expression patterns were identified. eIF transcripts were up-regulated in MBC. eIF4E and eIF5 were negatively prognostic for overall survival alone (Log rank; p=0.013; HR=1.77, 1.12-2.8 and p=0.035; HR=1.68, 1.03-2.74, respectively), or when co-expressed (p=0.01; HR=2.66, 1.26-5.63), confirmed in the validation set. This remained upon multivariate Cox regression analysis (eIF4E p=0.016; HR 2.38 (1.18-4.8), eIF5 p=0.022; HR 2.55 (1.14-5.7); co-expression p=0.001; HR=7.04 (2.22-22.26)). Marked reduction in eIF4E and eIF5 expression was seen post BEZ235/Everolimus, with extended survival. Conclusions: Translational initiation pathway inhibition could be of clinical utility in male BC patients overexpressing eIF4E and eIF5. With mTOR inhibitors which target this pathway now in the clinic, these biomarkers may represent new targets for therapeutic intervention, although further independent validation is required

Update on inflammatory breast cancer

Inflammatory breast cancer (IBC) is both the least frequent and the most severe form of epithelial breast cancer. The diagnosis is based on clinical inflammatory signs and is reinforced by pathological findings. Significant progress has been made in the management of IBC in the past 20 years. Yet survival among IBC patients is still only one-half that among patients with non-IBC. Identification of the molecular determinants of IBC would probably lead to more specific treatments and to improved survival. In the present article we review recent advances in the molecular pathogenesis of IBC. A more comprehensive view will probably be obtained by pan-genomic analysis of human IBC samples, and by functional in vitro and in vivo assays. These approaches may offer better patient outcome in the near future

DNA copy number changes in young gastric cancer patients with special reference to chromosome 19

Only a few cytogenetic and genetic studies have been performed in gastric cancer patients in young age groups. In the present study we used the comparative genomic hybridisation (CGH) method to characterise frequent DNA copy number changes in 22 gastric cancer patients of 45 years or younger and three gastric cancer cell lines established from patients younger than 45 years. Analysis of DNA copy number changes revealed frequent DNA copy number increases at chromosomes 17q (52%), 19q (68%) and 20q (64%). To confirm the CGH results and to characterise the amplicon region on the most frequently amplified chromosome, chromosome 19, we carried out fluorescence in situ hybridisation (FISH) analysis and Southern blot analysis. Fluorescence in situ hybridisation with the bacterial artificial chromosome (BAC) clone mapped to 19q12 indicated a copy number increase in all eight tumour specimens studied. Southern blot analysis of six tumour specimens and three tumour cell lines, with five probes mapped to the 19q12-13.2 region, suggested cyclin E to be one of the candidate target genes in the 19q region for gastric cancer tumorigenesis. Cyclin E protein overexpression was verified in tumours with amplification on chromosome 19. Further studies are required to investigate the biological and clinical significance of 19q amplicon and cyclin E upregulation in gastric cancer of young patient

Molecular biology of breast cancer metastasis: Inflammatory breast cancer: clinical syndrome and molecular determinants

Inflammatory breast cancer (IBC) is an aggressive form of locally advanced breast cancer (LABC) that effects approximately 5% of women with breast cancer annually in the USA. It is a clinically and pathologically distinct form of LABC that is particularly fast growing, invasive, and angiogenic. Nearly all women have lymph node involvement at the time of diagnosis, and approximately 36% have gross distant metastases. Despite recent advances in multimodality treatments, the prognosis of patients with IBC is poor, with a median disease-free survival of less than 2.5 years. Recent work on the genetic determinants that underlie the IBC phenotype has led to the identification of genes that are involved in the development and progression of this disease. This work has been aided by the establishment of primary human cell lines and animal models. These advances suggest novel targets for future interventions in the diagnosis and treatment of IBC

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

BACKGROUND: The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. RESULTS: In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. CONCLUSION: The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation