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  • 1
    Keywords: CANCER ; EXPRESSION ; tumor ; Germany ; human ; THERAPY ; INFORMATION ; TOOL ; DISEASE ; RISK ; DISTINCT ; GENE ; GENE-EXPRESSION ; GENES ; GENOME ; microarray ; SAMPLE ; SAMPLES ; PATIENT ; DNA ; MECHANISM ; prognosis ; mechanisms ; BIOLOGY ; BREAST ; breast cancer ; BREAST-CANCER ; DELETION ; IDENTIFICATION ; AMPLIFICATION ; COMPARATIVE GENOMIC HYBRIDIZATION ; PATTERNS ; gene expression ; CHROMOSOMAL-ABERRATIONS ; TUMOR PROGRESSION ; statistics ; ABERRATIONS ; DELETIONS ; DNA methylation ; REGION ; REGIONS ; bioinformatics ; PARAMETERS ; ONCOGENE ; CLASS-I ; DNA AMPLIFICATION ; IMBALANCES ; METHYLATION ; CHROMOSOMAL IMBALANCES ; P53 STATUS ; SINGLE ; RE ; PATTERN ; THERAPIES ; PATIENT SURVIVAL ; LEVEL ; analysis ; methods ; computational biology ; RISK STRATIFICATION ; genomic ; microbiology ; transcriptome ; CONTACT ; ARRAY-CGH ; MYC ; aberration ; HUMAN-BREAST ; DNA-METHYLATION ; biotechnology ; chromosomal aberration
    Abstract: Motivation: In cancer, chromosomal imbalances like amplifications and deletions, or changes in epigenetic mechanisms like DNA methylation influence the transcriptional activity. These alterations are often not limited to a single gene but affect several genes of the genomic region and may be relevant for the disease status. For example, the ERBB2 amplicon (17q21) in breast cancer is associated with poor patient prognosis. We present a general, unsupervised method for genome-wide gene expression data to systematically detect tumor patients with chromosomal regions of distinct transcriptional activity. The method aims to find expression patterns of adjacent genes with a consistently decreased or increased level of gene expression in tumor samples. Such patterns have been found to be associated with chromosomal aberrations and clinical parameters like tumor grading and thus can be useful for risk stratification or therapy. Results: Our approach was applied to 12 independent human breast cancer microarray studies comprising 1422 tumor samples. We prioritized chromosomal regions and genes predominantly found across all studies. The result highlighted not only regions which are well known to be amplified like 17q21 and 11q13, but also others like 8q24 (distal to MYC) and 17q24-q25 which may harbor novel putative oncogenes. Since our approach can be applied to any microarray study it may become a valuable tool for the exploration of transcriptional changes in diverse disease types. Availability: The R source codes which implement the method and an exemplary analysis are available at http://www.dkfz.de/mga2/people/buness/CTP/. Contact: a.buness@gmx.de Supplementary information: Supplementary data are available at Bioinformatics online
    Type of Publication: Journal article published
    PubMed ID: 17599933
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  • 2
    Keywords: CANCER ; EXPRESSION ; INHIBITOR ; proliferation ; SURVIVAL ; CELL ; Germany ; RISK ; GENE ; GENES ; HYBRIDIZATION ; microarray ; PROTEIN ; transcription ; TISSUE ; COMPLEX ; TRANSCRIPTION FACTOR ; IMPACT ; primary ; cell cycle ; CELL-CYCLE ; DOWN-REGULATION ; PHOSPHORYLATION ; COMPARATIVE GENOMIC HYBRIDIZATION ; PROMOTER ; UP-REGULATION ; ARRAYS ; PROMOTERS ; RATES ; MUTATIONS ; protein expression ; PROTEOMICS ; C-KIT ; RETINOBLASTOMA PROTEIN ; molecular ; ONCOLOGY ; ARRAY ; p16(INK4A) ; quantitative RT-PCR ; mRNA ; LEVEL ; TARGET GENES ; PHASE ; NUCLEAR ; LOSSES ; ENGLAND ; quantitative ; PLATFORM ; Rb ; GIST ; gastrointestinal ; DEPENDENT KINASES ; E2F1 ; E2FS ; PROGNOSTIC IMPLICATIONS ; RPPA
    Abstract: Loss of chromosome 9p is a reliable predictor of malignant behaviour in gastrointestinal stromal tumours (GISTS). p16(INK4A) located at 9p21 inhibits the CDK4/6/cyclin D complex from phosphorylating RB. Phosphorylation of RB through CDK4/6/cyclin D in early G(1) phase frees the transcription factor E2F1 from RB and enables mRNA transcription of genes essential for G(1)/S phase transition. This study aims to determine the impact of 9p loss on mRNA and protein expression of p16(INK4A) and further key cell cycle regulators in the different phases of the cell cycle. Sixty primary GISTS previously characterized for 9p loss by comparative genomic hybridization were analysed for mRNA expression of p16(INK4A), p15(INK4B), CDK4, CDK6, cyclin D, p 21(CIP1)p27(KIP1), CDK2, cyclin E, cyclin B, RB and E2F1, using quantitative RT-PCR. The protein expression of CDK6, CDK2, p2(CIP1), p27(KIP1) and phosphorylated RB (S807/S811) was evaluated using protein arrays as a novel and highly sensitive platform for profiling of protein abundance and protein phosphorylation. In parallel, the nuclear percentages of immunohistochemical staining for p16(INK4A), cyclin D, E2F1 and RB were quantified on a tissue microarray. GISTS with 9p loss had significantly higher proliferation rates, higher metastatic behaviour and shorter disease-free survival. On the molecular level, GISTS with 9p loss had a significantly reduced mRNA as well as nuclear protein expression of p16(INK4A). RB was significantly more phosphorylated in these tumours, together with increased mRNA expression and nuclear staining for E2F1 Furthermore, GISTS with 9p loss had up-regulation of the late G(1)/S phase promoters CDK2 and cyclin E. We conclude that loss of 9p accompanied by early G(1) phase inhibitor p16(INK4A) down-regulation in GISTS facilitates phosphorylation of RB, enabling F2F1-dependent transcription of genes essential for late G(1)/S phase transition. This study provides a possible basis for the accelerated proliferation and particularly malignant behaviour in GISTS with 9p loss. Copyright (C) 2008 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd
    Type of Publication: Journal article published
    PubMed ID: 18438954
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  • 3
    Keywords: ACTIVATION, ANTIGEN, ASSOCIATION, BIOPSY, CANCER, cancer risk, CANCER-RISK, CELLS, DIFFERENTIAL EXPR
    Abstract: Background: Insufficient sensitivity and specificity of prostate biopsies for cancer detection. Objectives: Based on evidence from our microarray analyses, we hypothesized that considerable molecular changes precede morphologically detectable malignant transformation of prostate epithelial tissues. The identification of such changes could lead to novel strategies in the clinical management of prostate cancer. Design, Setting, and Participants: Histologically normal, fresh prostate tissue from prostate cancer patients, healthy donors, and cancer suspect patients with continuous negative biopsies were analyzed. Measurements: To identify molecular changes between 29 tumor-free prostate tissues from healthy donors and 27 patients with proven prostate cancer, we performed a global microarray screening. 'Based on this screening as well as literature data, we selected a subset of 29 genes for validation by arrayed real-time reverse transcription-polymerase chain reaction (RT-PCR) using histologically tumor-free biopsy samples from 114 patients representing three prostate cancer risk groups. Results and Limitations: We identified five genes (FOS, EGR1, MYC, TFRC, and FOLH1), which displayed significant differential expression between morphologically normal prostate tissues from men of each of the three risk groups. These results were independent from age, prostate-specific antigen (PSA), frequency and timing of previous prostate biopsies, tissue composition, tumor stage, and tumor grade. in univariate logistic regression analyses, the transcript levels of these genes were found to be highly indicative for the presence or absence of cancer in the entire prostate. The study was designed as a proof of principle. The clinical relevance of our results has to be evaluated in a larger clinical setting. Conclusions: Our results suggest a measurable molecular cancer phenotype in histologically normal prostate tissue indicating the presence of prostate cancer elsewhere in the organ. (C) 2008 European Association of Urology. Published by Elsevier B.V. All rights reserved
    Type of Publication: Journal article published
    PubMed ID: 18501497
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  • 4
    Keywords: RECEPTOR ; CANCER ; EXPRESSION ; SURVIVAL ; tumor ; Germany ; CLASSIFICATION ; DIAGNOSIS ; GENE ; GENE-EXPRESSION ; microarray ; ACCURACY ; BREAST ; breast cancer ; BREAST-CANCER ; IDENTIFICATION ; gene expression ; VECTOR ; STRATEGIES ; ROBUSTNESS ; CONSTRUCTION ; ESTROGEN-RECEPTOR ; INTEGRATION ; ESTROGEN ; PROFILES ; estrogen receptor ; SIGNATURE ; PRIMARY BREAST-CANCER ; STRATEGY ; BENEFIT
    Abstract: Background: The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive) and histological grade (low/high) of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM), predictive analysis of microarrays (PAM), random forest (RF) and k-top scoring pairs (kTSP). Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV) aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results: For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In particular, the better predictive results of DV in across platform classification indicate higher robustness of the classifier when trained on single channel data and applied to gene expression ratios. Conclusions: We present a systematic evaluation of strategies for the integration of independent microarray studies in a classification task. Our findings in across studies classification may guide further research aiming on the construction of more robust and reliable methods for stratification and diagnosis in clinical practice
    Type of Publication: Journal article published
    PubMed ID: 20042109
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  • 5
    Keywords: CANCER ; GROWTH ; INHIBITOR ; proliferation ; SURVIVAL ; tumor ; CELL-PROLIFERATION ; Germany ; KINASE ; INFORMATION ; TOOL ; DISEASE ; GENE ; GENES ; GENOME ; microarray ; PROTEIN ; PROTEINS ; transcription ; TUMORS ; RESOLUTION ; ACTIVATION ; DNA ; BIOLOGY ; cell cycle ; CELL-CYCLE ; CYCLE ; ASSOCIATION ; MOUSE ; IDENTIFICATION ; PROGRESSION ; ASSAY ; microarrays ; PROSTATE-CANCER ; STRATEGIES ; DNA-REPLICATION ; REPLICATION ; signaling ; RE ; TUMORIGENICITY ; genomics ; TRANSITION ; DNA replication ; C-ELEGANS ; cell proliferation ; PROTEIN-ANALYSIS ; development ; ASSAYS ; DIFFERENTIALLY EXPRESSED GENES ; high throughput ; HIGH-THROUGHPUT ; LONG ; PRIME ; PRINCIPLES ; REPRESSOR ; ROLES
    Abstract: 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 (G(1)-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
    Type of Publication: Journal article published
    PubMed ID: 16140941
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  • 6
    Keywords: EXPRESSION ; SURVIVAL ; Germany ; DENSITY ; TOOL ; DISEASE ; GENE ; GENE-EXPRESSION ; GENES ; microarray ; TISSUE ; ACCURACY ; HEART ; TIME ; PATIENT ; COMPLEX ; COMPLEXES ; BIOMARKERS ; DOWN-REGULATION ; IDENTIFICATION ; PATTERNS ; gene expression ; microarrays ; ARRAYS ; COUNTRIES ; PATHOGENESIS ; INVOLVEMENT ; IMMUNE-RESPONSE ; FAILURE ; RECEPTORS ; DILATED CARDIOMYOPATHY ; MANAGEMENT ; IMPLEMENTATION ; ANGIOTENSIN-II ; TECHNICAL ASPECTS ; PROFILES ; TECHNOLOGY ; EVENTS ; ONTOLOGY ; SIGNATURE ; downregulation ; prospective ; prospective study ; cardiomyopathies ; CARDIOMYOPATHY ; HUMAN ATRIAL ; HUMAN MYOCARDIUM ; MICROARRAY PLATFORMS ; OLIGONUCLEOTIDE MICROARRAYS ; STAGE HEART-FAILURE
    Abstract: 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
    Type of Publication: Journal article published
    PubMed ID: 17045896
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  • 7
    Keywords: ACTIVATION, ANTIGEN, assembly, CANCER, CANCER CELLS, CANCER-CELLS, CELL, CELLS, COLON-CANCER, colore
    Abstract: Most malignant features of cancer cells are triggered by activated oncogenes and the loss of tumor suppressors due to mutation or epigenetic inactivation. It is still unclear, to what extend the escape of emerging cancer cells from recognition and elimination by the immune system is determined by similar mechanisms. We compared the transcriptomes of HCT116 colorectal cancer cells deficient in DNA methyltransferases (DNMTs) and of cells, in which the RAS pathway as the major growth-promoting signaling system is blocked by inhibition of MAPK. We identified the MHC Class I genes HLA-A1/A2 and the ULBP2 gene encoding 1 of the 8 known ligands of the activating NK receptor NKG2D among a cluster of immune genes up-regulated under the conditions of both DNMT-deficiency and MEK-inhibition. Bisulphite sequencing analyses of HCT116 with DNMT deficiency or after MEK-inhibition showed that de-methylation of the ULPB2 promoter correlated with its enhanced surface expression. The HLA-A promoters were not methylated indicating that components of the HLA assembly machinery were also suppressed in DNMT-deficient and MEK-inhibited cells. Increased HLA-A2 surface expression was correlated with enhanced recognition and lysis by A2-specific CTL. On the contrary, elevated ULBP2 expression was not reflected by enhanced recognition and lysis by NK cells. Cosuppression of HLA Class I and NKG2D ligands and genes encoding peptide transporters or proteasomal genes mediates a strong functional link between RAS activation, DNMT activity and disruption of the antigen presenting system controlling immune recognition in colorectal cancer cells. (C) 2009 UICC
    Type of Publication: Journal article published
    PubMed ID: 19569244
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  • 8
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  • 9
    Keywords: CLASSIFICATION ; BIOLOGY ; MOLECULAR-BIOLOGY ; genetics ; REPRODUCIBILITY ; molecular biology ; TASK
    Type of Publication: Journal article published
    PubMed ID: 16646817
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  • 10
    Keywords: RECEPTOR ; CANCER ; EXPRESSION ; GROWTH ; GROWTH-FACTOR ; CELL ; Germany ; INHIBITION ; KINASE ; PATHWAY ; QUANTIFICATION ; SYSTEM ; SYSTEMS ; DISTINCT ; GENOME ; microarray ; PROTEIN ; PROTEINS ; SAMPLE ; SAMPLES ; ACTIVATION ; BIOLOGY ; MOLECULAR-BIOLOGY ; BREAST ; breast cancer ; BREAST-CANCER ; STIMULATION ; microarrays ; ARRAYS ; systems biology ; PROTEOMICS ; EPIDERMAL-GROWTH-FACTOR ; signaling ; molecular biology ; molecular ; RE ; ARRAY ; EGFR ; analysis ; methods ; HIGH-THROUGHPUT ; HER2 ; GEFITINIB ; comparison ; BREAST-CANCER-CELLS ; EGF ; ERK1/2 ; reverse phase protein array ; HER2/neu ; herceptin
    Abstract: Protein microarrays allow highly accurate comparison and quantification of numerous biological samples in parallel while requiring only little material. This qualifies protein arrays for systems biology and clinical research where only limited sample material is available, but a precise read-out is required. With the introduction of signal normalization steps to monitor the drop size of manually contact-spotted RP protein arrays, the usefulness of normalizer proteins to ensure a high-throughput but inexpensive protein analysis was demonstrated. This approach was applied for the analysis of signaling through ERBB receptor activated kinases in the breast cancer cell line MCF-7. Activation of ERK1/2 and AKT by ERBB1 (EGFR), ERRB2 (HER2/neu), and ERBB3-4 was monitored in a time-resolved manner. Analysis of pathway activation by stimulation with epidermal growth factor and heregulin, or inhibition by blocking with gefitinib or herceptin allowed a characterization of the distinct signaling properties of the different ERBB receptor subtypes
    Type of Publication: Journal article published
    PubMed ID: 18351692
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