The aim of this study is to generate and validate biomarkers to stratify patients with Barretts esophagus in terms of risk for developing cancer. We studied gene expression profiling in 69 frozen specimens, consisting of esophageal squamous epithelium from 19 healthy subjects, 20 specimens from patients with Barretts esophagus and 21 cases of esophageal adenocarcinoma, 9 cased of esophageal squamous cell carcinoma by whole genome microarray analysis. Laser capture microdissection technique was applied to procure cells from defined regions of Barretts esophagus metaplasia and esophageal adenocarcinoma. Microarray results were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent cohort consisting of 42 cases. Furthermore, immunohistochemistry was performed using antibodies to two selected target molecules on a third independent cohort of 36 specimens, consisting of 36 cases. A total of 1176 genes were associated significantly with esophageal adenocarcinoma. The expression pattern of a 4 gene signature with the highest discriminant score based on linear discriminant analysis (GeneSpring GX10.2), was identified and validated by qRT-PCR in independent cohort.
Wdr66 is a novel marker for risk stratification and involved in epithelial-mesenchymal transition of esophageal squamous cell carcinoma.
Specimen part
View SamplesAcute myeloid leukemia (AML) is one of the most common and deadly forms of hematopoietic malignancies. We hypothesized that microarray studies could identify aberrantly expressed genes selectively expressed in AML blasts, believing that these genes may be potential therapeutic targets for adoptive T-cell strategies
No associated publication
Specimen part, Disease
View SamplesThe aim of the study was to get insights into transcriptional alterations in bone marrow mesenchymal stromal cells derived from acute myeloid leukemia patients
Molecular alterations in bone marrow mesenchymal stromal cells derived from acute myeloid leukemia patients.
Disease
View SamplesOvarian carcinoma has the highest mortality rate among gynecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300 gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p=0.0087). In a second validation step the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p=0.0063). In multivariate analysis, the OPI was independent of the postoperative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8 23.5, p=0.0049) and 1.9 (Duke cohort, CI 1.2 3.0, p=0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimised assessment of prognosis. As traditional treatment options are limited, this analysis may be able to optimise clinical management and to identify those patients that would be candidates for new therapeutic strategies.
A prognostic gene expression index in ovarian cancer - validation across different independent data sets.
Specimen part, Disease stage
View SamplesThe number of long-term survivors of high-risk neuroblastoma remains discouraging, with 10-year survival as low as 20%, despite decades of considerable international efforts to improve outcome. Major obstacles remain and include managing resistance to induction therapy, which causes tumor progression and early death in high-risk patients, and managing chemotherapy-resistant relapses, which can occur years after the initial diagnosis. Identifying and validating novel therapeutic targets is essential to improve treatment. Delineating and deciphering specific functions of single histone deacetylases in neuroblastoma may support development of targeted acetylome-modifying therapeutics for patients with molecularly defined high-risk neuroblastoma profiles. We show here that HDAC11 depletion in MYCN-driven neuroblastoma cell lines strongly induces cell death, mostly mediated by apoptotic programs. Genes necessary for mitotic cell cycle progression and cell division were most prominently enriched in at least two of three time points in whole-genome expression data combined from two cell systems, and all nine genes in these functional categories were strongly repressed, including CENPA, KIF14, KIF23 and RACGAP1. Enforced expression of one selected candidate, RACGAP1, partially rescued the induction of apoptosis caused by HDAC11 depletion. High-level expression of all nine genes in primary neuroblastomas signicantly correlated with unfavorable overall and event-free survival in patients, suggesting a role in mediating the more aggressive biological and clinical phenotype of these tumors. Our study identied a group of cell cycle-promoting genes regulated by HDAC11, being both predictors of unfavorable patient outcome and essential for tumor cell viability. The data indicates a signicant role of HDAC11 for mitotic cell cycle progression and survival of MYCN-amplified neuroblastoma cells, and suggests that HDAC11 could be a valuable drug target.
Neuroblastoma cells depend on HDAC11 for mitotic cell cycle progression and survival.
Cell line, Time
View SamplesAging animals undergo a variety of changes in molecular processes. Among these, the cellular circadian clock has been shown to change as animals age. Moreover, there is evidence that also core circadian clock proteins could influence the ageing behavior of vertebrates.
No associated publication
Specimen part
View SamplesThe routine workflow for invasive cancer diagnostics is based on biopsy processing by formalin fixation and subsequent paraffin embedding. Formalin-fixed paraffin-embedded (FFPE) tissue samples are easy to handle, stable and particularly suitable for morphologic evaluation, immunohistochemistry and in situ hybridization. However, it has become a paradigm that these samples cannot be used for genome-wide expression analysis with microarrays. To oppose this view, we present a pilot microarray study using FFPE core needle biopsies from breast cancers as RNA source. We found that microarray probes interrogating sequences near the poly-A-tail of the transcribed genes were well suitable to measure RNA levels in FFPE core needle biopsies. For the ER and the HER2 gene, we observed strong correlations between RNA levels measured in these probe sets and protein expression determined by immunohistochemistry (p = 0.000003 and p = 0.0022). Further, we have identified a signature of 364 genes that correlated with ER protein status and a signature of 528 genes that correlated with HER2 protein status. Many of these genes (ER: 60%) could be confirmed by analysis of an independent publicly available data set. Finally, a hierarchical clustering of the biopsies with respect to three recently reported gene expression grade signatures resulted in widely stable low and high expression grade clusters that correlated with the pathological tumor grade. These findings support the notion that clinically relevant information can be gained from microarray based gene expression profiling of FFPE cancer biopsies. This opens new opportunities for the integration of gene expression analysis into the workflow of invasive cancer diagnostics as well as translational research in the setting of clinical studies.
Genome-wide gene expression profiling of formalin-fixed paraffin-embedded breast cancer core biopsies using microarrays.
Disease stage
View SamplesActivity-dependent gene expression is central for sculpting neuronal connectivity in the brain. Despite the importance for synaptic plasticity, a comprehensive analysis of the temporal changes in the transcriptomic response to neuronal activity is lacking. In a genome wide survey we identified genes that were induced at 1, 4, 8, or 24 hours following neuronal activity in the hippocampus.
Genome-wide profiling of the activity-dependent hippocampal transcriptome.
Sex, Age, Specimen part, Time
View SamplesExpression data from 22 human myotubes (7 healthy controls, 4 Dysferlinopathy (DYSF), 4 Caveolinopathy 3 (CAV3), 4 Facioscapulohumeral muscular dystrophy(FSHD) and 3 Four and a half LIM 1 protein deficiency FHL1).cDNA microarray data showed that cyclin A1 levels are specifically elevated in FSHD vs. other muscular disorders such as CAV3, DYSF, FHL1 and healthy control. Data could be confirmed with RT-PCR and Western blot analysis showing up-regulated levels of cyclin A1 also on the protein level.
Altered expression of cyclin A 1 in muscle of patients with facioscapulohumeral muscle dystrophy (FSHD-1).
Age, Specimen part, Disease, Disease stage
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Cell line, Treatment
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