Biomedical subjects

Markus Ruschhaupt

Publications and source records attributed to Markus Ruschhaupt.

5 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

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↗

PubMed2004

A compendium to ensure computational reproducibility in high-dimensional classification tasks.

We demonstrate a concept and implementation of a compendium for the classification of high-dimensional data from microarray gene expression profiles. A compendium is an interactive document that bundles primary data, statistical processing methods, figures, and derived data together with the textual documentation and conclusions. Interactivity allows the reader to modify and extend these components. We address the following questions: how much does the discriminatory power of a classifier depend on the choice of the algorithm that was used to identify it; what alternative classifiers could be used just as well; how robust is the result. The answers to these questions are essential prerequisites for validation and biological interpretation of the classifiers. We show how to use this approach by looking at these questions for a specific breast cancer microarray data set that first has been studied by Huang et al. (2003).

Journal Article↗