Biomedical subjects

Anja von Heydebreck

Publications and source records attributed to Anja von Heydebreck.

11 recordsLinked to original sources

PubMed2005

Chromosomal clustering of a human transcriptome reveals regulatory background.

BACKGROUND: There has been much evidence recently for a link between transcriptional regulation and chromosomal gene order, but the relationship between genomic organization, regulation and gene function in higher eukaryotes remains to be precisely defined. RESULTS: Here, we present evidence for organization of a large proportion of a human transcriptome into gene clusters throughout the genome, which are partly regulated by the same transcription factors, share biological functions and are characterized by non-housekeeping genes. This analysis was based on the cardiac transcriptome identified by our genome-wide array analysis of 55 human heart samples. We found 37% of these genes to be arranged mainly in adjacent pairs or triplets. A significant number of pairs of adjacent genes are putatively regulated by common transcription factors (p = 0.02). Furthermore, these gene pairs share a significant number of GO functional classification terms. We show that the human cardiac transcriptome is organized into many small clusters across the whole genome, rather than being concentrated in a few larger clusters. CONCLUSION: Our findings suggest that genes expressed in concert are organized in a linear arrangement for coordinated regulation. Determining the relationship between gene arrangement, regulation and nuclear organization as well as gene function will have broad biological implications.

Binding Sites↗

PubMed2005

Prognostic role of E2F1 and members of the CDKN2A network in gastrointestinal stromal tumors.

PURPOSE: The aim of the current study was to examine the prognostic relevance of the CDKN2A tumor suppressor pathway in gastrointestinal stromal tumors (GIST). EXPERIMENTAL DESIGN: We determined the mRNA expression of p1(INK4A), p14(ARF), CDK4, RB1, MDM2, TP53, and E2F1 by quantitative reverse transcription-PCR in 38 cases of GISTs and correlated the findings with clinicopathologic factors, including mutation analysis of KIT and PDGFRA. RESULTS: The k-means cluster analysis yielded three prognostic subgroups of GISTs with distinct mRNA expression patterns of the CDKN2A pathway. GISTs with low mRNA expression of the CDKN2A transcripts p16(INK4A) and p14(ARF) but high mRNA expression of CDK4, RB1, MDM2, TP53, and E2F1 were associated with aggressive clinical behavior and unfavorable prognosis, whereas GISTs with a low mRNA expression of CDK4, RB1, MDM2, TP53, and E2F1 were not. GISTs with a moderate to high mRNA expression of all examined genes also seemed to be associated with unfavorable prognosis. Regarding mutation analysis, we found significant differences in the KIT/PDGFRA genotype among the three clusters. Univariate analysis revealed high expression of E2F1 to be associated with mitotic count, proliferation rate, KIT mutation, and aggressive clinical behavior. These findings on mRNA level could be confirmed by immunohistochemistry. CONCLUSION: Our findings implicate differential regulation schemes of the CDKN2A tumor suppressor pathway converging to up-regulation of E2F1 as the critical link to increased cell proliferation and adverse prognosis of GISTs.

Adult↗

PubMed2005

Oncogenetic tree models based on cytogenetic data: new insights into the development of epithelial tumors of the thymus.

Epithelial tumors of the thymus are rare neoplasms typically arising in the anterior mediastinum. There is an ongoing discussion whether thymomas of different histological subtypes form a biological continuum or represent distinct biological entities. To further investigate this question, we performed a statistical analysis of CGH data of 65 previously published cases. Losses of 3p, 6p, 6q, 13q, 16q, and 17p, as well as gains on 1q, were found in at least 10% of the cases. Comparing the data from B2, B3, and C thymomas, we noted an increasing complexity of karyotypes that may be well explained by a sequential order of these types. The frequencies of losses on 16q and 17p show a significant trend with respect to the sequence from B2 to B3 and C thymomas, indicating that these aberrations may be important events in the transition between these tumor types. To identify pathways of genetic development and progression of thymomas, we used oncogenetic tree models representing the dependencies between recurrent chromosomal aberrations. This analysis suggests that gains on the long arm of chromosome 1 occur early in tumor development and are correlated with losses on 6p and 6q. There is a weak correlation with losses on 16q and 17p, which appear to be late events. An independent pathway leads to losses on 3p and 13q, which are closely correlated. Our results indicate that the development of thymomas seems to be in some part a multistep mechanism. Oncogenetic tree models are a helpful means to determine developmental pathways of tumors arising from the same progenitor cell, as shown here for thymomas.

Chromosomes, Human, Pair 16↗

PubMed2005

Gene expression in kidney cancer is associated with cytogenetic abnormalities, metastasis formation, and patient survival.

Current diagnosis of renal cancer consists of histopathologic examination of tissue sections and classification into tumor stages and grades of malignancy. Until recently, molecular differences between tumor types were largely unknown. To examine such differences, we did gene expression measurements of 112 renal cell carcinoma and normal kidney samples on renal cell carcinoma-specific cDNA microarrays containing 4,207 genes and expressed sequence tags. The gene expression patterns showed deregulation of complete biological pathways in the tumors. Many of the molecular changes corresponded well to the histopathologic tumor types, and a set of 80 genes was sufficient to classify tumors with a very low error rate. Distinct gene expression signatures were associated with chromosomal abnormalities of tumor cells, metastasis formation, and patient survival. The data highlight the benefit of microarrays to detect novel tumor classes and to identify genes that are associated with patient variables and tumor properties.

Adult↗

PubMed2004

Equivalence test in quantitative reverse transcription polymerase chain reaction: confirmation of reference genes suitable for normalization.

In quantitative reverse transcription-polymerase chain reaction (qRT-PCR), normalization using reference genes is a common useful approach, but the validation of suitable reference genes remains a crucial problem. Use of unconfirmed reference genes may lead to misinterpretation of the expression of target genes. The aim of this study was to adapt an adequate statistical approach to identify and validate reference genes suitable for normalization in qRT-PCR assays. We introduce the equivalence test for the identification of stably expressed reference genes. To evaluate the advantages of this test, the expression of five genes widely used as reference genes (18S, B2M, HPRT1, LMNB1, and SDHA), and of two target genes (TP53 and MMP2), was determined with qRT-PCR in different tissues (clear cell renal cell carcinoma, colon carcinoma, and gastrointestinal stromal tumors). We demonstrate that a stable expression of a reference gene in one tumor type does not predict a stable expression in another tumor type. In addition, we found that even within one tumor type, the expression of a reference gene was not stable for different biological groupwise comparisons. These observations confirm that there is no universal reference gene and underline the importance of specific validation of potential reference genes for any experimental condition.

Adult↗

PubMed2004

Site-independent prognostic value of chromosome 9q loss in primary gastrointestinal stromal tumours.

Although the significance of tumour site for estimating malignant potential in gastrointestinal stromal tumours (GISTs) has recently been recognized, site-specific genetic patterns have not to date been defined. This study examined 52 c-kit-positive primary GISTs (with a mean follow-up of 42.3 months in 51 cases) from three different locations (35 gastric, 12 small intestinal, and five colorectal) using comparative genomic hybridization (CGH). In general, tumour site correlated with key prognostic factors, including tumour size, mitotic rate, proliferative activity, and probable malignant potential. Furthermore, several DNA copy number changes showed a site-dependent pattern. These included losses at 14q (gastric 83%, intestinal 35%; p = 0.001), losses at 22q (gastric 46%, intestinal 82%; p = 0.02), losses at 1p (gastric 23%, intestinal 88%; p = 1 x 10(-5)), losses at 15q (gastric 14%, intestinal 59%; p = 0.002), losses at 9q (gastric 14%, intestinal 53%; p = 0.006), and gains at 5p (gastric 11%, intestinal 53%; p = 0.002). These data demonstrate strong site-dependent genetic heterogeneity in GISTs that may form a basis for subclassification. Prognostic evaluation of DNA copy number changes identified losses at 9q as a site-independent prognostic marker associated with shorter disease-free survival (p = 0.03) and overall survival (p = 0.002). Furthermore, 9q loss also appeared to carry prognostic value in predicting overall survival for patients with advanced or progressive GISTs (p = 0.003).

Adult↗

PubMed2004

Maximum likelihood estimation of oncogenetic tree models.

We present a new approach for modelling the dependences between genetic changes in human tumours. In solid tumours, data on genetic alterations are usually only available at a single point in time, allowing no direct insight into the sequential order of genetic events. In our approach, genetic tumour development and progression is assumed to follow a probabilistic tree model. We show how maximum likelihood estimation can be used to reconstruct a tree model for the dependences between genetic alterations in a given tumour type. We illustrate the use of the proposed method by applying it to cytogenetic data from 173 cases of clear cell renal cell carcinoma, arriving at a model for the karyotypic evolution of this tumour.

Carcinoma, Renal Cell↗

PubMed2003

Cytogenetic and morphologic typing of 58 papillary renal cell carcinomas: evidence for a cytogenetic evolution of type 2 from type 1 tumors.

We evaluated clinical characteristics, patient outcome (mean follow-up, 47 months), and cytogenetic abnormalities in the largest as yet reported cytogenetic series of 47 primary and 11 secondary papillary renal cell carcinomas for differences between the recently proposed type 1 and type 2 subtypes. Secondary tumors were more often of type 2 morphology (P = 0.02), whereas primary type 2 tumors were associated with higher clinical stage (P = 0.001) and worse patient outcome (P = 0.02). Although both subtypes had at least one of the primary chromosomal gains at 17q, 7, and 16q, type 2 tumors had moderately lower frequencies of primary gains at 17p (61 versus 94%; P = 0.007) and 17q (72 versus 97%; P = 0.02). On the other hand, type 2 tumors overall had more chromosomal alterations than type 1 tumors (P = 0.01), particularly gains of 1q (28 versus 3%; P = 0.02) and losses of 8p (33 versus 0%; P = 0.001), 11 (28 versus 3%; P = 0.02), and 18 (44 versus 9%; P = 0.01). Hierarchical clustering suggested cytogenetic patterns common but not restricted to type 2 morphology, one characterized by multiple additional gains, and another predominantly showing additional losses. These findings provide genetic evidence that type 1 and type 2 tumors arise from common cytogenetic pathways and that type 2 tumors evolve from type 1 tumors. Independently of type, losses of 9p were statistically correlated with advanced disease (P = 0.0008) and may serve as a potential adverse prognostic marker in papillary renal cell carcinomas.

Adult↗

PubMed2003

Genome-wide array analysis of normal and malformed human hearts.

BACKGROUND: We present the first genome-wide cDNA array analysis of human congenitally malformed hearts and attempted to partially elucidate these complex phenotypes. Most congenital heart defects, which account for the largest number of birth defects in humans, represent complex genetic disorders. As a consequence of the malformation, abnormal hemodynamic features occur and cause an adaptation process of the heart. METHODS AND RESULTS: The statistical analysis of our data suggests distinct gene expression profiles associated with tetralogy of Fallot, ventricular septal defect, and right ventricular hypertrophy. Applying correspondence analysis, we could associate specific gene functions to specific phenotypes. Furthermore, our study design allows the suggestion that alterations associated with primary genetic abnormalities can be distinguished from those associated with the adaptive response of the heart to the malformation (right ventricular pressure overload hypertrophy). We provide evidence for the molecular transition of the hypertrophic right ventricle to normal left ventricular characteristics. Furthermore, we present data on chamber-specific gene expression. CONCLUSIONS: Our findings propose that array analysis of malformed human hearts opens a new window to understand the complex genetic network of cardiac development and adaptation. For detailed access, see the online-only Data Supplement.

Adaptation, Physiological↗

PubMed2003

Parameter estimation for the calibration and variance stabilization of microarray data.

We derive and validate an estimator for the parameters of a transformation for the joint calibration (normalization) and variance stabilization of microarray intensity data. With this, the variances of the transformed intensities become approximately independent of their expected values. The transformation is similar to the logarithm in the high intensity range, but has a smaller slope for intensities close to zero. Applications have shown better sensitivity and specificity for the detection of differentially expressed genes. In this paper, we describe the theoretical aspects of the method. We incorporate calibration and variance-mean dependence into a statistical model and use a robust variant of the maximum-likelihood method to estimate the transformation parameters. Using simulations, we investigate the size of the estimation error and its dependence on sample size and the presence of outliers. We find that the error decreases with the square root of the number of probes per array and that the estimation is robust against the presence of differentially expressed genes. Software is publicly available as an R package through the Bioconductor project (http://www.bioconductor.org).

Journal Article↗

PubMed2002

Variance stabilization applied to microarray data calibration and to the quantification of differential expression.

We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of differential expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements, and a difference statistic Deltah whose variance is approximately constant along the whole intensity range. This forms a basis for statistical inference from microarray data, and provides a rational data pre-processing strategy for multivariate analyses. For the transformation h, the parametric form h(x)=arsinh(a+bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. For large intensities, h coincides with the logarithmic transformation, and Deltah with the log-ratio. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation. We demonstrate our approach on data sets from different experimental platforms, including two-colour cDNA arrays and a series of Affymetrix oligonucleotide arrays.

Algorithms↗