Biomedical subjects

Holger Sültmann

Publications and source records attributed to Holger Sültmann.

14 recordsLinked to original sources

PubMed2006

Identification and meta-analysis of a small gene expression signature for the diagnosis of estrogen receptor status in invasive ductal breast cancer.

In breast cancer, the determination of estrogen receptor (ER) expression is crucial for the decision on therapeutic strategies. Current ER expression analysis is based on immunohistochemical (IHC) staining of ER on formalin fixed tissue sections. However, low levels of ER expression frequently escape detection because of varying sensitivities of routine histopathological laboratories. Moreover, in estimating ER by IHC the receptor protein only is tested instead of the complex underlying ER pathway, which reflects its biological activity. To overcome this limitation, we have used the microarray technology to study 56 samples of invasive ductal carcinoma. We infer a robust and reliable signature of 10 genes, which is associated with ER expression and presumably therapeutically relevant biological processes. In a meta-analysis, the signature was tested on 3 further independent microarray gene expression data sets, covering different laboratories, array platforms, and clinics. The classification based on the signature showed a very low misclassification rate. In summary, the expression of few genes is sufficient to determine ER status. Future decisions on antiestrogen based therapy in breast cancer could be based on this signature rather than on immunostaining alone.

Adult↗

PubMed2006

Identification of a common gene expression signature in dilated cardiomyopathy across independent microarray studies.

OBJECTIVES: This study was designed to identify a common gene expression signature in dilated cardiomyopathy (DCM) across different microarray studies. BACKGROUND: Dilated cardiomyopathy is a common cause of heart failure in Western countries. Although gene expression arrays have emerged as a powerful tool for delineating complex disease patterns, differences in platform technology, tissue heterogeneity, and small sample sizes obscure the underlying pathophysiologic events and hamper a comprehensive interpretation of different microarray studies in heart failure. METHODS: We accounted for tissue heterogeneity and technical aspects by performing 2 genome-wide expression studies based on cDNA and short-oligonucleotide microarray platforms which comprised independent septal and left ventricular tissue samples from nonfailing (NF) (n = 20) and DCM (n = 20) hearts. RESULTS: Concordant results emerged for major gene ontology classes between cDNA and oligonucleotide microarrays. Notably, immune response processes displayed the most pronounced down-regulation on both microarray types, linking this functional gene class to the pathogenesis of end-stage DCM. Furthermore, a robust set of 27 genes was identified that classified DCM and NF samples with >90% accuracy in a total of 108 myocardial samples from our cDNA and oligonucleotide microarray studies as well as 2 publicly available datasets. CONCLUSIONS: For the first time, independent microarray datasets pointed to significant involvement of immune response processes in end-stage DCM. Moreover, based on 4 independent microarray datasets, we present a robust gene expression signature of DCM, encouraging future prospective studies for the implementation of disease biomarkers in the management of patients with heart failure.

Antibody Formation↗

PubMed2006

Analysis of pigmented villonodular synovitis with genome-wide complementary DNA microarray and tissue array technology reveals insight into potential novel therapeutic approaches.

OBJECTIVE: To characterize the gene expression profile and determine potential diagnostic markers and therapeutic targets in pigmented villonodular synovitis (PVNS). METHODS: Gene expression patterns in 11 patients with PVNS, 18 patients with rheumatoid arthritis (RA), and 19 patients with osteoarthritis (OA) were investigated using genome-wide complementary DNA microarrays. Validation of differentially expressed genes was performed by real-time quantitative polymerase chain reaction and immunohistochemical analysis on tissue arrays (80 patients with PVNS, 51 patients with RA, and 20 patients with OA). RESULTS: The gene expression profile in PVNS was clearly distinct from those in RA and OA. One hundred forty-one up-regulated genes and 47 down-regulated genes were found in PVNS compared with RA, and 153 up-regulated genes and 89 down-regulated genes were found in PVNS compared with OA (fold change > or = 1.5; Q < or = 0.001). Genes differentially expressed in PVNS were involved in apoptosis regulation, matrix degradation, and inflammation (ALOX5AP, ATP6V1B2, CD53, CHI3L1, CTSL, CXCR4, HSPA8, HSPCA, LAPTM5, MMP9, MOAP1, and SPP1). CONCLUSION: The gene expression signature in PVNS is similar to that of activated macrophages and is consistent with the local destructive course of the disease. The gene and protein expression patterns suggest that the ongoing proliferation in PVNS is sustained by apoptosis resistance. This result suggests the possibility of a potential novel therapeutic intervention against PVNS.

Arthritis, Rheumatoid↗

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

Functional profiling: from microarrays via cell-based assays to novel tumor relevant modulators of the cell cycle.

Cancer transcription microarray studies commonly deliver long lists of "candidate" genes that are putatively associated with the respective disease. For many of these genes, no functional information, even less their relevance in pathologic conditions, is established as they were identified in large-scale genomics approaches. Strategies and tools are thus needed to distinguish genes and proteins with mere tumor association from those causally related to cancer. Here, we describe a functional profiling approach, where we analyzed 103 previously uncharacterized genes in cancer relevant assays that probed their effects on DNA replication (cell proliferation). The genes had previously been identified as differentially expressed in genome-wide microarray studies of tumors. Using an automated high-throughput assay with single-cell resolution, we discovered seven activators and nine repressors of DNA replication. These were further characterized for effects on extracellular signal-regulated kinase 1/2 (ERK1/2) signaling (G1-S transition) and anchorage-independent growth (tumorigenicity). One activator and one inhibitor protein of ERK1/2 activation and three repressors of anchorage-independent growth were identified. Data from tumor and functional profiling make these proteins novel prime candidates for further in-depth study of their roles in cancer development and progression. We have established a novel functional profiling strategy that links genomics to cell biology and showed its potential for discerning cancer relevant modulators of the cell cycle in the candidate lists from microarray studies.

Animals↗

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↗

PubMed2005

Extraction and processing of high quality RNA from impalpable and macroscopically invisible prostate cancer for microarray gene expression analysis.

Molecular analyses of early-stage prostate cancers are necessary to assess their potential clinical significance based on established and/or novel biomarkers for tailored clinical management. A prerequisite for the application of RNA-based analyses of such, mostly macroscopically-undetectable, small prostate carcinomas is the recovery and preservation of sufficient RNA quantities and quality. Furthermore, in prostate cancer, heterogeneity is a common phenomenon that includes a juxtaposition of different tissue compositions and variable histological grades within the same tumor focus. To better understand the molecular mechanisms of prostate cancer, it is essential to correlate molecular data with a specific cell type. Here, we present a tissue collecting protocol which is aligned with the preoperative evaluation of tumor localization. In combination with the technique of laser microdissection and pressure catapulting, we are able to preserve RNA of high quality from homogeneous cell populations of macroscopically-undetectable small prostate carcinomas. To obtain the necessary RNA quantities for whole genome cDNA microarrays, the isolated total RNAs were amplified by T7-based RNA-polymerase in vitro transcription. The microarray analyses (Human Unigene Set RZPD3.1) resulted in 216 differentially expressed genes (191 down-regulated, 25 up-regulated). Among these were several known prostate cancer relevant genes, such as AMACR, TARP, LIM, GPR160 (all up-regulated), CAV1, NTN1, MT1X; CLU, TRIM29, SPARCL1 and HSPB8 (all down-regulated).

Down-Regulation↗

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

arrayMagic: two-colour cDNA microarray quality control and preprocessing.

UNLABELLED: arrayMagic is a software package for quality control and preprocessing of two-colour cDNA microarray data. The automated analysis pipeline comprises data import, normalization, replica merging, quality diagnostics and data export. The script-based processing combines reproducibility and flexibility at high-throughput and provides quality-assured and preprocessed microarray data to high-level follow-up analysis. AVAILABILITY: The R package arrayMagic is available with BSD license at http://www.bioconductor.org CONTACT: a.buness@dkfz.de SUPPLEMENTARY INFORMATION: The package contains documentation in the form of manual pages and a vignette with a guided tour of a typical workflow.

Algorithms↗

PubMed2004

Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments.

BACKGROUND: The requirement of a large amount of high-quality RNA is a major limiting factor for microarray experiments using biopsies. An average microarray experiment requires 10-100 microg of RNA. However, due to their small size, most biopsies do not yield this amount. Several different approaches for RNA amplification in vitro have been described and applied for microarray studies. In most of these, systematic analyses of the potential bias introduced by the enzymatic modifications are lacking. RESULTS: We examined the sources of error introduced by the T7 RNA polymerase based RNA amplification method through hybridisation studies on microarrays and performed statistical analysis of the parameters that need to be evaluated prior to routine laboratory use. The results demonstrate that amplification of the RNA has no systematic influence on the outcome of the microarray experiment. Although variations in differential expression between amplified and total RNA hybridisations can be observed, RNA amplification is reproducible, and there is no evidence that it introduces a large systematic bias. CONCLUSIONS: Our results underline the utility of the T7 based RNA amplification for use in microarray experiments provided that all samples under study are equally treated.

Adenocarcinoma↗

PubMed2004

From ORFeome to biology: a functional genomics pipeline.

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.

Animals↗

PubMed2004

Recent advances in transcription profiling of human cancer.

During the past 20 years, significant success in the therapy of certain cancer types has given rise to the hope that cancer will soon be curable. However, survival rates of most patients diagnosed with cancer have not substantially increased. Instead, it is becoming clear that many tumor types, which were previously regarded as homogeneous disease entities, are composed of different subtypes which lead to varying patient prognosis and survival rates. These findings complicate diagnosis and treatment of cancer patients and call for new anti-oncogenic therapies. DNA microarrays are powerful tools to investigate global gene expression in tumors and their corresponding normal tissues, to classify tumors based on their molecular properties, and to identify novel targets for future tumor therapy. Recent results of global gene expression analyses in various tumor types are reviewed, and their implications for diagnosis and therapy of human cancer are discussed.

Gene Expression Profiling↗

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↗

PubMed2000

Linkage Relationships and Haplotype Variation of the Major Histocompatibility Complex Class I A Genes in the Cichlid Fish Oreochromis niloticus.

The haplochromine cichlid species flocks of the East African Great Lakes are one of the best examples of adaptive radiation. Analysis of genetic variation among these species provides valuable information on species relationships and timing of speciation events. Although the haplochromine cichlids generally display little genetic variation, the major histocompatibility complex (Mhc) genes have been found to be highly variable. A study of the linkage relationships of the Mhc class I A genes in the cichlid fish Oreochromis niloticus was therefore undertaken. Class I loci were identified, and their segregation in seven mothers and their haploid embryos was determined. In total, 56 class I A sequences were found among the seven families. A strong concordance of segregation was observed in five haplotypes among the embryos, indicating a close linkage of all loci. The number of loci per haplotype varied from 11 to 17, while the total number of distinct loci found among all families was 22. These findings show that all class I A loci are linked in a single genetic cluster in O. niloticus.

Journal Article↗