Uso de la Hibridación Genómica Comparativa-Array (HGC-a) en pacientes con retraso global del desarrollo y fenotipo particular. Revisión sistemática de la literatura

Introducción: la hibridación genómica comparativa en una técnica que permite la exploración de las anormalidades cromosómicas. Su utilidad en la aproximación de los pacientes con retraso global del desarrollo o fenotipo dismórfico, sin embargo, no ha sido explorada mediante una revisión sistemática de la literatura. Metodología: realizó una revisión sistemática de la literatura. Se incluyeron estudios controlados, cuasi-experimentales, de cohortes, de casos y controles, transversales y descriptivos publicados en idiomas inglés y español entre los años 2000 y 2013. Se realizó un análisis de la evidencia con un enfoque cualitativo y cuantitativo. Se realizó un análisis del riesgo de sesgo de los estudios incluidos. Resultados: se incluyeron 4 estudios que cumplieron con los criterios de inclusión. La prevalencia de alteraciones cromosómicas en los niños con retraso global del desarrollo fue de entre el 6 y 13%. El uso de la técnica permitió identificar alteraciones que no fueron detectadas mediante el cariotipo. Conclusiones: la hibridación genómica comparativa es una técnica útil en la aproximación diagnóstica de los niños con retraso global del desarrollo y del fenotipo dismórfico y permite una mayor detección de alteraciones comparada con el cariotipo.

Genetic diversity among Escherichia coli O157 : H7 isolates and identification of genes linked to human infections

An Escherichia coli oligonucleotide microarray based on three sequenced genomes was validated for comparative genomic microarray hybridization and used to study the diversity of E. coli O157 isolates from human infections and food and animal sources. Among 26 test strains, 24 (including both Shiga toxin [Stx]-positive and -negative strains) were found to be related to the two sequenced E. coli O157:117 strains, EDL933 and Sakai. However, these strains showed much greater genetic diversity than those reported previously, and most of them could not be categorized as either lineage I or H. Some genes were found more often in isolates from human than from nonhuman sources; e.g., ECs1202 and ECs2976, associated with stx2AB and stx1AB, were in all isolates from human sources but in only 40% of those from nonhuman sources. Some (but not all) lineage I-specific or -dominant genes were also more frequently associated with isolates from human. The results suggested that it might be more effective to concentrate our efforts on finding markers that are directly related to infection rather than those specific to certain lineages. In addition, two Stx-negative O157 cattle isolates (one confirmed to be 117) were significantly different from other Stx-positive and -negative E. coli O157:117 strains and were more similar to MG1655 in their gene content. This work demonstrates that not all E. coli O157:117 strains belong to the same clonal group, and those that were similar to E. coli K-12 might be less virulent.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

Genomic content and new insights on the origin of the B chromosome of the cichlid fish Astatotilapia latifasciata

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An Integrative Genomic and Transcriptomic Analysis Reveals Potential Targets Associated with Cell Proliferation in Uterine Leiomyomas

Background: Uterine Leiomyomas (ULs) are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs). Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs. Methodology: We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC) and gene expression microarrays (SAM). The CONEXIC algorithm was applied to integrate the data. Principal Findings: The integrated analysis identified the top 30 significant genes (P<0.01), which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively) and IGFBP5 (P = 0.0002 and P = 0.006, respectively) were up-regulated in the tumours when compared with the adjacent normal myometrium. Conclusions: The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs. © 2013 Cirilo et al.

Genomic Signatures Predict Poor Outcome in Undifferentiated Pleomorphic Sarcomas and Leiomyosarcomas

Undifferentiated high-grade pleomorphic sarcomas (UPSs) display aggressive clinical behavior and frequently develop local recurrence and distant metastasis. Because these sarcomas often share similar morphological patterns with other tumors, particularly leiomyosarcomas (LMSs), classification by exclusion is frequently used. In this study, array-based comparative genomic hybridization (array CGH) was used to analyze 20 UPS and 17 LMS samples from untreated patients. The LMS samples presented a lower frequency of genomic alterations compared with the UPS samples. The most frequently altered UPS regions involved gains at 20q13.33 and 7q22.1 and losses at 3p26.3. Gains at 8q24.3 and 19q13.12 and losses at 9p21.3 were frequently detected in the LMS samples. Of these regions, gains at 1q21.3, 11q12.2-q12.3, 16p11.2, and 19q13.12 were significantly associated with reduced overall survival times in LMS patients. A multivariate analysis revealed that gains at 1q21.3 were an independent prognostic marker of shorter survival times in LMS patients (HR = 13.76; P = 0.019). Although the copy number profiles of the UPS and LMS samples could not be distinguished using unsupervised hierarchical clustering analysis, one of the three clusters presented cases associated with poor prognostic outcome (P = 0.022). A relative copy number analysis for the ARNT, SLC27A3, and PBXIP1 genes was performed using quantitative real-time PCR in 11 LMS and 16 UPS samples. Gains at 1q21-q22 were observed in both tumor types, particularly in the UPS samples. These findings provide strong evidence for the existence of a genomic signature to predict poor outcome in a subset of UPS and LMS patients. © 2013 Silveira et al.

Identificação de perfis diferenciais de metilação do DNA na endometriose

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genomic screening of testicular germ cell tumors from monozygotic twins

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A tecnologia de microarray no estudo do câncer de cabeça e pescoço

(Microarray technology in study of head neck cancer). The microarray technology is a tool for global analysis of gene expression that allows investigating hundreds or thousands of genes in a sample using a hybridization reaction. This technology is based on hybridization between labeled targets derived from biological samples and an array of many DNA probes immobilized on a solid matrix, representing the genes of interest. The simultaneous study of hundreds of genes became the microarray technique a very important tool of global analysis, with applications in several areas, including the study of the development of cancer. Head and neck squamous cell carcinoma (HNSCC) is the fifth most common cancer worldwide, with a global annual incidence of 780,000 new cases. Large-scale studies involving microarrays have identified specific gene expression signatures associated with expression changes in HNSCC samples compared to normal tissue, as well as genes involved in clinical outcome and metastasis. However, the considerable heterogeneity among these studies occurs due to experimental design, number of samples, disease sites and stage, choice of microarray platform and results validation. Thus, there is much to be validated, before the technique has clinical utility. In relation to head and neck neoplasia, the large-scale gene analysis is very important, since the clinical and histopathological methods currently used appear to be insufficient to predict clinical progression and response to treatment. Thus, this approach could result in more effective diagnostic and prognostic and most appropriate therapy for this neoplasia.

Down-regulation of SLC8A1 as a putative apoptosis evasion mechanism by modulation of calcium levels in penile carcinoma

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Pseudolikelihood Approach for Simultaneous Analysis of Array Comparative Genomic Hybridizations (aCGH)

DNA sequence copy number has been shown to be associated with cancer development and progression. Array-based Comparative Genomic Hybridization (aCGH) is a recent development that seeks to identify the copy number ratio at large numbers of markers across the genome. Due to experimental and biological variations across chromosomes and across hybridizations, current methods are limited to analyses of single chromosomes. We propose a more powerful approach that borrows strength across chromosomes and across hybridizations. We assume a Gaussian mixture model, with a hidden Markov dependence structure, and with random effects to allow for intertumoral variation, as well as intratumoral clonal variation. For ease of computation, we base estimation on a pseudolikelihood function. The method produces quantitative assessments of the likelihood of genetic alterations at each clone, along with a graphical display for simple visual interpretation. We assess the characteristics of the method through simulation studies and through analysis of a brain tumor aCGH data set. We show that the pseudolikelihood approach is superior to existing methods both in detecting small regions of copy number alteration and in accurately classifying regions of change when intratumoral clonal variation is present.

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

A genomic approach to gene fusion technology

Gene expression profiling provides powerful analyses of transcriptional responses to cellular perturbation. In contrast to DNA array-based methods, reporter gene technology has been underused for this application. Here we describe a genomewide, genome-registered collection of Escherichia coli bioluminescent reporter gene fusions. DNA sequences from plasmid-borne, random fusions of E. coli chromosomal DNA to a Photorhabdus luminescens luxCDABE reporter allowed precise mapping of each fusion. The utility of this collection covering about 30% of the transcriptional units was tested by analyzing individual fusions representative of heat shock, SOS, OxyR, SoxRS, and cya/crp stress-responsive regulons. Each fusion strain responded as anticipated to environmental conditions known to activate the corresponding regulatory circuit. Thus, the collection mirrors E. coli's transcriptional wiring diagram. This genomewide collection of gene fusions provides an independent test of results from other gene expression analyses. Accordingly, a DNA microarray-based analysis of mitomycin C-treated E. coli indicated elevated expression of expected and unanticipated genes. Selected luxCDABE fusions corresponding to these up-regulated genes were used to confirm or contradict the DNA microarray results. The power of partnering gene fusion and DNA microarray technology to discover promoters and define operons was demonstrated when data from both suggested that a cluster of 20 genes encoding production of type I extracellular polysaccharide in E. coli form a single operon.

EGFR amplification and lack of activating mutations in metaplastic breast carcinomas

Metaplastic breast carcinomas are reported to harbour epidermal growth factor receptor (EGFR) overexpression in up to 80% of the cases, but EGFR gene amplification is the underlying genetic mechanism in around one-third of these. In this study, EGFR gene amplification as defined by chromogenic in situ hybridization and protein overexpression was examined in a cohort of 47 metaplastic breast carcinomas. Furthermore, the presence of activating EGFR mutations in exons 18, 19, 20, and 21 was investigated. Thirty-two cases showed EGFR overexpression and of these, 11 (34%) harboured EGFR gene amplification. In addition, EGFR amplification showed a statistically significant association with EGFR overexpression (p < 0.0094) and was restricted to carcinomas with homologous metaplasia. Ten cases, five with and five without EGFR amplification, were subjected to microarray-based CGH, which demonstrated that EGFR copy number gain may occur by amplification of a discrete genomic region or by gains of the short arm of chromosome 7 with a breakpoint near the EGFR gene locus, the minimal region of amplification mapping to EGFR, LANCL2, and SECOG. No activating EGFR mutations were identified, suggesting that this is unlikely to be a common alternative underlying genetic mechanism for EGFR expression in metaplastic breast carcinomas. Given that metaplastic breast carcinomas are resistant to conventional chemotherapy or hormone therapy regimens and that tumours with EGFR amplification are reported to be sensitive to EGFR tyrosine kinase inhibitors, these findings indicate that further studies are warranted to explore EGFR tyrosine kinase inhibitors as potential therapeutic agents for metaplastic breast carcinomas harbouring amplification of 7p11.2. Copyright (c) 2006 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd

FGFR1 emerges as a potential therapeutic target for lobular breast carcinomas

Purpose: Classic lobular carcinomas (CLC) account for 10% to 15% of all breast cancers. At the genetic level, CLCs show recurrent physical loss of chromosome16q coupled with the lack of E-cadherin (CDH1 gene) expression. However, little is known about the putative therapeutic targets for these tumors. The aim of this study was to characterize CLCs at the molecular genetic level and identify putative therapeutic targets. Experimental Design: We subjected 13 cases of CLC to a comprehensive molecular analysis including immunohistochemistry for E-cadherin, estrogen and progesterone receptors, HER2/ neu and p53; high-resolution comparative genomic hybridization (HR-CGH); microarray-based CGH (aCGH); and fluorescent and chromogenic in situ hybridization for CCND1 and FGFR1. Results: All cases lacked the expression of E-cadherin, p53, and HER2, and all but one case was positive for estrogen receptors. HR-CGH revealed recurrent gains on 1q and losses on 16q (both, 85%). aCGH showed a good agreement with but higher resolution and sensitivity than HR-CGH. Recurrent, high level gains at 11q13 (CCND1) and 8p12-p11.2 were identified in seven and six cases, respectively, and were validated with in situ hybridization. Examination of aCGH and the gene expression profile data of the cell lines, MDA-MB-134 and ZR-75-1, which harbor distinct gains of 8p12-p11.2, identified FGFR1 as a putative amplicon driver of 8p12-p11.2 amplification in MDA-MB-134. Inhibition of FGFR1 expression using small interfering RNA or a small-molecule chemical inhibitor showed that FGFR1 signaling contributes to the survival of MDA-MB-134 cells. Conclusions: Our findings suggest that receptor FGFR1 inhibitors may be useful as therapeutics in a subset of CLCs.