scholarly journals Chromosomal Regions in Prostatic Carcinomas Studied by Comparative Genomic Hybridization, Hierarchical Cluster Analysis and Self-Organizing Feature Maps

2002 ◽  
Vol 24 (4-5) ◽  
pp. 167-179 ◽  
Author(s):  
Torsten Mattfeldt ◽  
Hubertus Wolter ◽  
Danilo Trijic ◽  
Hans‐Werner Gottfried ◽  
Hans A. Kestler
Keyword(s):  
Cluster Analysis ◽  
Comparative Genomic Hybridization ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Data Matrix ◽  
Comparative Genomic ◽  
Feature Maps ◽  
Genomic Hybridization ◽  
A Genome ◽  
Self Organizing

Comparative genomic hybridization (CGH) is an established genetic method which enables a genome‐wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that place. Therefore, large amounts of data quickly accumulate which must be put into a logical order. Cluster analysis can be used to assign individual cases (samples) to different clusters of cases, which are similar and where each cluster may be related to a different tumour biology. Another approach consists in a clustering of chromosomal regions by rewriting the original data matrix, where the cases are written as rows and the chromosomal regions as columns, in a transposed form. In this paper we applied hierarchical cluster analysis as well as two implementations of self‐organizing feature maps as classical and neuronal tools for cluster analysis of CGH data from prostatic carcinomas to such transposed data sets. Self‐organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule. We studied a group of 48 cases of incidental carcinomas, a tumour category which has not been evaluated by CGH before. In addition we studied a group of 50 cases of pT2N0‐tumours and a group of 20 pT3N0‐carcinomas. The results show in all case groups three clusters of chromosomal regions, which are (i) normal or minimally affected by losses and gains, (ii) regions with many losses and few gains and (iii) regions with many gains and few losses. Moreover, for the pT2N0‐ and pT3N0‐groups, it could be shown that the regions 6q, 8p and 13q lay all on the same cluster (associated with losses), and that the regions 9q and 20q belonged to the same cluster (associated with gains). For the incidental cancers such clear correlations could not be demonstrated.

scholarly journals Cluster Analysis of Comparative Genomic Hybridization (CGH) Data Using Self-Organizing Maps: Application to Prostate Carcinomas

2001 ◽  
Vol 23 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Torsten Mattfeldt ◽  
Hubertus Wolter ◽  
Ralf Kemmerling ◽  
Hans‐Werner Gottfried ◽  
Hans A. Kestler
Keyword(s):  
Cluster Analysis ◽  
Comparative Genomic Hybridization ◽  
Genetic Material ◽  
Comparative Genomic ◽  
Genomic Hybridization ◽  
Self Organizing Maps ◽  
Data Set ◽  
A Genome ◽  
Self Organizing

Comparative genomic hybridization (CGH) is a modern genetic method which enables a genome‐wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that region. Usually it is not possible to evaluate all 46 chromosomes of a metaphase, therefore several (up to 20 or more) metaphases are analyzed per individual, and expressed as average. Mostly one does not study one individual alone but groups of 20–30 individuals. Therefore, large amounts of data quickly accumulate which must be put into a logical order. In this paper we present the application of a self‐organizing map (Genecluster) as a tool for cluster analysis of data from pT2N0 prostate cancer cases studied by CGH. Self‐organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule, i.e., in our examples it gets the CGH data as only information (no clinical data). We studied a group of 40 recent cases without follow‐up, an older group of 20 cases with follow‐up, and the data set obtained by pooling both groups. In all groups good clusterings were found in the sense that clinically similar cases were placed into the same clusters on the basis of the genetic information only. The data indicate that losses on chromosome arms 6q, 8p and 13q are all frequent in pT2N0 prostatic cancer, but the loss on 8p has probably the largest prognostic importance.

Comparative Genomic Hybridization

2001 ◽  
Vol 125 (1) ◽  
pp. 81-84
Author(s):  
Irene J. Barrett ◽  
Brenda L. Lomax ◽  
Tatiana Loukianova ◽  
Steven S. Tang ◽  
Valia S. Lestou ◽  
...  
Keyword(s):  
Comparative Genomic Hybridization ◽  
Hybridization Analysis ◽  
Comparative Genomic ◽  
Amniotic Fluid Cell ◽  
Comparative Genomic Hybridization Analysis ◽  
Clinical Tool ◽  
Genomic Hybridization ◽  
Maternal Cell ◽  
Fetal Tissues ◽  
A Genome

Abstract Objective.—To demonstrate the effectiveness of comparative genomic hybridization (CGH) for analysis of reproductive pathology specimens in clinical cytogenetics laboratories. Design.—A total of 856 CGH analyses were performed on various placental and fetal tissues derived from 368 specimens of spontaneous abortions and on placentas from 219 pregnancies with live-born infants. The live-born infants were clinically evaluated as normally developed, with either a normal birth weight or with intrauterine growth restriction; some live-born infants had an abnormal prenatal triple screen with normal cytogenetic results on amniotic fluid cell cultures. Results.—Comparative genomic hybridization analysis was successfully performed on 856 samples from spontaneously aborted specimens and term placentas. Failure of analysis occurred in 1.6% of samples and was due to an insufficient amount of tissue for DNA extraction. Comparative genomic hybridization identified aneuploidy in 53% of spontaneous abortion samples and 3.1% of term placentas. Conclusions.—Comparative genomic hybridization analysis is a useful clinical tool for detection of aneuploidy in placental and fetal tissues. It provides a genome-wide screen while eliminating tissue culture failures, culture artifacts, and maternal cell contamination. We present practical guidelines for interpreting CGH profiles derived from human reproductive specimens.

scholarly journals Characterization of the Genome Composition of Bartonella koehlerae by Microarray Comparative Genomic Hybridization Profiling

2005 ◽  
Vol 187 (17) ◽  
pp. 6155-6165 ◽  
Author(s):  
Hillevi L. Lindroos ◽  
Alex Mira ◽  
Dirk Repsilber ◽  
Olga Vinnere ◽  
Kristina Näslund ◽  
...  
Keyword(s):  
Comparative Genomic Hybridization ◽  
Bartonella Henselae ◽  
Sequence Divergence ◽  
Genomic Islands ◽  
Vector System ◽  
Comparative Genomic ◽  
Genomic Hybridization ◽  
Bartonella Quintana ◽  
A Genome ◽  
Wide Range

ABSTRACT Bartonella henselae is present in a wide range of wild and domestic feline hosts and causes cat-scratch disease and bacillary angiomatosis in humans. We have estimated here the gene content of Bartonella koehlerae, a novel species isolated from cats that was recently identified as an agent of human endocarditis. The investigation was accomplished by comparative genomic hybridization (CGH) to a microarray constructed from the sequenced 1.93-Mb genome of B. henselae. Control hybridizations of labeled DNA from the human pathogen Bartonella quintana with a reduced genome of 1.58 Mb were performed to evaluate the accuracy of the array for genes with known levels of sequence divergence. Genome size estimates of B. koehlerae by pulsed-field gel electrophoresis matched that calculated by the CGH, indicating a genome of 1.7 to 1.8 Mb with few unique genes. As in B. quintana, sequences in the prophage and the genomic islands were reported absent in B. koehlerae. In addition, sequence variability was recorded in the chromosome II-like region, where B. koehlerae showed an intermediate retention pattern of both coding and noncoding sequences. Although most of the genes missing in B. koehlerae are also absent from B. quintana, its phylogenetic placement near B. henselae suggests independent deletion events, indicating that host specificity is not solely attributed to genes in the genomic islands. Rather, the results underscore the instability of the genomic islands even within bacterial populations adapted to the same host-vector system, as in the case of B. henselae and B. koehlerae.

scholarly journals Array-comparative genomic hybridization in sporadic benign pheochromocytomas

2009 ◽  
Vol 16 (2) ◽  
pp. 505-513 ◽  
Author(s):  
Francien H van Nederveen ◽  
Esther Korpershoek ◽  
Ronald J deLeeuw ◽  
Albert A Verhofstad ◽  
Jacques W Lenders ◽  
...  
Keyword(s):  
Comparative Genomic Hybridization ◽  
High Frequency ◽  
Chromosomal Abnormalities ◽  
Neurofibromatosis Type ◽  
The Other ◽  
Comparative Genomic ◽  
Genomic Hybridization ◽  
Von Hippel Lindau ◽  
A Genome ◽  
High Resolution Analysis

Pheochromocytomas (PCC) are catecholamine-producing tumors arising from the adrenal medulla that occur either sporadically or in the context of hereditary cancer syndromes, such as multiple endocrine neoplasia type 2 (MEN2), von Hippel-Lindau disease (VHL), neurofibromatosis type 1, and the PCC-paraganglioma syndrome. Conventional comparative genomic hybridization studies have shown loss of 1p and 3q in the majority of sporadic and MEN2-related PCC, and 3p and 11p loss in VHL-related PCC. The development of a submegabase tiling resolution array enabled us to perform a genome-wide high-resolution analysis of 36 sporadic benign PCC. The results show that there are two distinct patterns of abnormalities in these sporadic PCC, one consisting of loss of 1p with or without concomitant 3q loss in 20/36 cases (56%), the other characterized by loss of 3p with or without concomitant 11p loss in 11/36 (31%). In addition, we found loss of chromosome 22q at high frequency (35%), as well as the novel finding of high frequency chromosome 21q loss (21%). We conclude that there appear to be two subgroups of benign sporadic PCC, one of which has a pattern of chromosomal abnormalities that is comparable with PCC from patients with MEN2 and the other that is comparable with the PCC that arise in patients with VHL disease. In addition, genes on 21q and 22q might play a more important role in PCC pathogenesis than had been assumed thus far.

scholarly journals Leptospire Genomic Diversity Revealed by Microarray-Based Comparative Genomic Hybridization

2012 ◽  
Vol 78 (9) ◽  
pp. 3045-3050 ◽  
Author(s):  
Broderick Eribo ◽  
Sirima Mingmongkolchai ◽  
Tingfen Yan ◽  
Padunsri Dubbs ◽  
Karen E. Nelson
Keyword(s):  
Genetic Diversity ◽  
Cluster Analysis ◽  
Comparative Genomic Hybridization ◽  
Virulence Factors ◽  
Genomic Diversity ◽  
Comparative Genomic ◽  
Leptospira Interrogans ◽  
Genomic Hybridization ◽  
Content Type ◽  
Reference Genomes

ABSTRACTComparative genomic hybridization was used to compare genetic diversity of five strains ofLeptospira(Leptospira interrogansserovars Bratislava, Canicola, and Hebdomadis andLeptospira kirschneriserovars Cynopteri and Grippotyphosa). The array was designed based on two available sequencedLeptospirareference genomes, those ofL. interrogansserovar Copenhageni andL. interrogansserovar Lai. A comparison of genetic contents showed thatL. interrogansserovar Bratislava was closest to the reference genomes whileL. kirschneriserovar Grippotyphosa had the least similarity to the reference genomes. Cluster analysis indicated thatL. interrogansserovars Bratislava and Hebdomadis clustered together first, followed byL. interrogansserovar Canicola, before the twoL. kirschneristrains. Confirmed/potential virulence factors identified in previous research were also detected in the tested strains.

566: Comparative Genomic Hybridization of Chemotherapy Survived Wilms' Tumor Cells

2004 ◽  
Vol 171 (4S) ◽  
pp. 150-151
Author(s):  
Thorsten Schlomm ◽  
Bastian Gunawan ◽  
Hans J. Schulten ◽  
Norbert Graf ◽  
Ivo Leuschner ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Comparative Genomic Hybridization ◽  
Wilms Tumor ◽  
Comparative Genomic ◽  
Genomic Hybridization
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