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  • 1
    Abstract: Chronic lymphocytic leukemia is a malignancy of mature B cells that strongly depend on microenvironmental factors and their deprivation has been identified as promising treatment approach for this incurable disease. Cytokine array screening of 247 chronic lymphocytic leukemia serum samples revealed elevated levels of TNF receptor-1 which were associated with poor clinical outcome. We detected a microenvironment-induced expression of TNF receptor-1 in chronic lymphocytic leukemia cells in vitro and aberrantly high expression of this receptor in proliferation centers of patients' lymph nodes. Stimulation of TNF receptor-1 with TNF-alpha enhanced NFkappaB activity and viability of chronic lymphocytic leukemia cells which was inhibited by wogonin. Therapeutic effects of wogonin were analyzed in mice after adoptive transfer of Em-TCL1 leukemic cells. Wogonin treatment prevented leukemia development when given early after transplantation. Treatment of full-blown leukemia resulted in loss of TNF receptor-1 on chronic lymphocytic leukemia cells and their mobilization to blood. Targeting TNF receptor-1 signaling is therefore proposed for treatment of chronic lymphocytic leukemia.
    Type of Publication: Journal article epub ahead of print
    PubMed ID: 29326123
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  • 2
    Keywords: B ; SIGNATURES ; ORGANIZATION ; gene expression ; CLASSIFICATION ; EXPRESSION ; GENE ; GENE-EXPRESSION
    Type of Publication: Book chapter
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  • 3
    Abstract: Analysis of high-dimensional biomarker data is in general of exploratory nature and aims to discover or dissect subgroups of patients sharing a specific pattern of biomarker measurements. One major challenge is to extract the relevant markers from the extremely large pool of measured markers. Specific techniques such as grouping and ordering and dimension reduction allow to aggregate huge amounts of data into single meaningful graphics. These graphics can guide the direction of exploration during the analysis. We present graphical tools for unsupervised and supervised objectives based on gene expression data of multiple myeloma patients which are part of the MAQC-II project.
    Type of Publication: Book chapter
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  • 4
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    German Medical Science GMS Publishing House; Düsseldorf
    In:  Mainz//2011; 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi); 20110926-20110929; Mainz; DOC11gmds086 /20110920/
    Publication Date: 2011-09-20
    Keywords: survival analysis ; time-dependent covariable ; Andersen-Gill model ; ddc: 610
    Language: English
    Type: conferenceObject
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  • 5
    Keywords: SURVIVAL ; Germany ; MODEL ; MODELS ; INFORMATION ; RISK ; GENE ; microarray ; prognosis ; BIOLOGY ; ASSOCIATION ; VARIANTS ; BREAST-CANCER ; MICROARRAY DATA ; NUMBER ; REQUIRES ; PREDICTION ; REGRESSION ; VARIANT ; model selection ; development ; survival analysis ; GENE-EXPRESSION SIGNATURE ; SURVIVAL PREDICTION ; ADAPTIVE LASSO ; High dimensions ; NONCONCAVE PENALIZED LIKELIHOOD ; ORACLE PROPERTIES ; Penalized proportional hazards ; Predictive accuracy ; PROBABILITIES ; PROPORTIONAL HAZARDS MODEL ; VARIABLE SELECTION
    Abstract: The Cox proportional hazards regression model is the most popular approach to model covariate information for survival times. In this context, the development of high-dimensional models where the number of covariates is much larger than the number of observations (p 〉〉 n) is an ongoing challenge. A practicable approach is to use ridge penalized Cox regression in such situations. Beside focussing on finding the best prediction rule, one is often interested in determining a subset of covariates that are the most important ones for prognosis. This could be a gene set in the biostatistical analysis of microarray data. Covariate selection can then, for example, be done by L-1-penalized Cox regression using the lasso (Tibshirani (1997). Statistics in Medicine 16, 385-395). Several approaches beyond the lasso, that incorporate covariate selection, have been developed in recent years. This includes modifications of the lasso as well as nonconvex variants such as smoothly clipped absolute deviation (SCAD) (Fan and Li (2001). Journal of the American Statistical Association 96, 1348-1360; Fan and Li (2002). The Annals of Statistics 30, 74-99). The purpose of this article is to implement them practically into the model building process when analyzing high-dimensional data with the Cox proportional hazards model. To evaluate penalized regression models beyond the lasso, we included SCAD variants and the adaptive lasso (Zou (2006). Journal of the American Statistical Association 101, 1418-1429). We compare them with "standard" applications such as ridge regression, the lasso, and the elastic net. Predictive accuracy, features of variable selection, and estimation bias will be studied to assess the practical use of these methods. We observed that the performance of SCAD and adaptive lasso is highly dependent on nontrivial preselection procedures. A practical solution to this problem does not yet exist. Since there is high risk of missing relevant covariates when using SCAD or adaptive lasso applied after an inappropriate initial selection step, we recommend to stay with lasso or the elastic net in actual data applications. But with respect to the promising results for truly sparse models, we see some advantage of SCAD and adaptive lasso, if better preselection procedures would be available. This requires further methodological research
    Type of Publication: Journal article published
    PubMed ID: 20166132
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  • 6
    Keywords: RECEPTOR ; APOPTOSIS ; CANCER ; CELLS ; EXPRESSION ; SURVIVAL ; carcinoma ; CELL ; IN-VIVO ; MODEL ; MODELS ; PROSTATE ; LUNG-CANCER ; POPULATION ; RISK ; GENE ; validation ; prognosis ; ASSOCIATION ; polymorphism ; POLYMORPHISMS ; single nucleotide polymorphism ; SUSCEPTIBILITY ; VARIANTS ; BREAST ; MOUSE ; PROGRESSION ; ovarian cancer ; OVARIAN-CANCER ; PROSTATE-CANCER ; CANCER-CELLS ; ADHESION ; CANCER-PATIENTS ; pathology ; RANDOMIZED-TRIAL ; tumour suppressor gene ; ONCOLOGY ; VARIANT ; GENETIC-VARIATION ; GENE POLYMORPHISM ; tumours ; Genetic ; single nucleotide ; DOMAIN-CONTAINING OXIDOREDUCTASE ; FRAGILE SITE GENES ; Tumour modifier gene ; WWOX
    Abstract: WWOX is a bona fide tumour suppressor, with hypomorphic and knockout mouse models exhibiting increased tumour susceptibility. In ovarian cancer cells WWOX transfection abolishes tumourigenicity, suppresses tumour cell adhesion to extracellular matrix and induces apoptosis in non-adherent cells. One-third of ovarian tumours show loss of WWOX expression, and this loss significantly associates with clear cell and mucinous histology, advanced stage, low progesterone receptor expression and poor survival, suggesting that WWOX status affects ovarian cancer progression and prognosis. Genetic variation in other tumour suppressors (e.g. p53 and XPD) is reported to modify cancer progression/outcome, and single nucleotide polymorphisms (SNPs) within the WWOX gene are reported to associate with prostate cancer risk. We previously identified polymorphic variants within WWOX, some of which have potential to affect its expression. We therefore examined a cancer modifier role for these WWOX variants. Eight SNPs, based upon location, frequency and potential to affect WWOX expression, were genotyped in 554 ovarian cancer patients (CGP samples), and associations with pathological and survival data were examined. The CGP samples demonstrated significant associations after Bonferroni correction between Isnp1 and both tumour grade (p(corr) = 0.033) and histology (p(corr) = 0.046), Isnp8 and tumour grade (p(corr) = 0.032) and T1497G and progression-free survival (p(corr) = 0.037). None of these positive associations were confirmed in an independent ovarian cancer population (Scotroc1 samples, n = 863). While these results may suggest that the associations are false positives, differences between the two populations cannot be excluded, and thus highlight the challenges in validation studies. (C) 2009 Elsevier Ltd. All rights reserved
    Type of Publication: Journal article published
    PubMed ID: 20074932
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  • 7
    Keywords: CANCER ; EXPRESSION ; CELL ; Germany ; GENOME ; microarray ; PROTEIN ; PROTEINS ; PATIENT ; COMPLEX ; COMPLEXES ; QUALITY ; BIOLOGY ; antibodies ; antibody ; ASSAY ; microarrays ; DESIGN ; ARRAYS ; REPRODUCIBILITY ; CANCER-PATIENTS ; CANCER PATIENTS ; pancreatic cancer ; PROTEOMICS ; PROTEOMIC ANALYSIS ; SERUM ; FEATURES ; PANCREATIC-CANCER ; antibody microarray ; HEALTHY-SUBJECTS ; methods ; HUMAN PLASMA ; DEPLETION ; QUANTITATIVE PROTEOMICS ; proteomic ; ABUNDANCE PROTEINS ; BIOMARKER DISCOVERY
    Abstract: Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.
    Type of Publication: Journal article published
    PubMed ID: 20164060
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  • 8
    Abstract: BACKGROUND: Chronic lymphocytic leukemia has a variable clinical course. Genomic aberrations identify prognostic subgroups, pointing towards distinct underlying biological mechanisms that are poorly understood. In particular it remains unclear whether the prognostic subgroups of chronic lymphocytic leukemia are characterized by different levels of leukemogenic proteins. DESIGN AND METHODS: Expression of 23 proteins involved in apoptosis, proliferation, DNA damage, and signaling or whose genes map to chromosomal regions known to be critical in chronic lymphocytic leukemia was quantified in 185 cytogenetically well characterized cases of chronic lymphocytic leukemia using immunoblotting. Cases were categorized hierarchically into deletion(17p), deletion(11q), trisomy 12, deletion(13q) as sole abnormality or normal karyotype. Statistical analysis was performed for expression differences between these subgroups. In addition, the expression levels of CDK4, P27 and P53 were quantified over the clinical course and compared to levels in immunopurified B cells from healthy individuals. RESULTS: In subgroups with a good prognosis, differential expression was mainly seen for proteins that regulate apoptosis. In contrast, in cytogenetic subgroups with a worse prognosis, differential expression was mostly detected for proteins that control DNA damage and proliferation. Expression levels of CDK4, P27 and P53 were higher compared to those in B cells from healthy individuals and significantly correlated with increasing hierarchical risk. In addition, no significant longitudinal changes of expression levels of CDK4, P27 and P53 could be detected in chronic lymphocytic leukemia patients. CONCLUSIONS: Differences in expression levels of apoptosis- and proliferation-controlling proteins define distinct prognostic subgroups of chronic lymphocytic leukemia and uncover a correlation of levels of CDK4, P27 and P53 proteins with higher hierarchical risk.
    Type of Publication: Journal article published
    PubMed ID: 20713460
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  • 9
    Keywords: APOPTOSIS ; GENES ; GENOME ; DOWN-REGULATION ; LYMPHOMA ; TARGETS ; METHYLATION ; HUMAN CANCER-CELLS ; epigenetic regulation ; SIGNATURES
    Abstract: Dysregulated microRNA (miRNA) expression contributes to the pathogenesis of hematopoietic malignancies, including chronic lymphocytic leukemia (CLL). However, an understanding of the mechanisms that cause aberrant miRNA transcriptional control is lacking. In this study, we comprehensively investigated the role and extent of miRNA epigenetic regulation in CLL. Genome-wide profiling conducted on 24 CLL and 10 healthy B cell samples revealed global DNA methylation patterns upstream of miRNA sequences that distinguished malignant from healthy cells and identified putative miRNA promoters. Integration of DNA methylation and miRNA promoter data led to the identification of 128 recurrent miRNA targets for aberrant promoter DNA methylation. DNA hypomethylation accounted for more than 60% of all aberrant promoter-associated DNA methylation in CLL, and promoter DNA hypomethylation was restricted to well-defined regions. Individual hyper- and hypomethylated promoters allowed discrimination of CLL samples from healthy controls. Promoter DNA methylation patterns were confirmed in an independent patient cohort, with 11 miRNAs consistently showing an inverse correlation between DNA methylation status and expression level. Together, our findings characterize the role of epigenetic changes in the regulation of miRNA transcription and create a repository of disease-specific promoter regions that may provide additional insights into the pathogenesis of CLL. Cancer Res; 72(15); 3775-85. (c)2012 AACR.
    Type of Publication: Journal article published
    PubMed ID: 22710432
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  • 10
    Keywords: DNA methylation ; FACTOR-KAPPA-B ; CHRONIC LYMPHOCYTIC-LEUKEMIA ; DISEASE PROGRESSION ; CHROMOSOME 13Q14 ; TUMOR-SUPPRESSOR LOCUS ; LONG NONCODING RNAS ; PROMOTER CPG METHYLATION ; PI3K/NF-KAPPA-B PATHWAY ; ANTISENSE TRANSCRIPTS
    Abstract: Non-coding RNAs are much more common than previously thought. However, for the vast majority of non-coding RNAs, the cellular function remains enigmatic. The two long non-coding RNA (lncRNA) genes DLEU1 and DLEU2 map to a critical region at chromosomal band 13q14.3 that is recurrently deleted in solid tumors and hematopoietic malignancies like chronic lymphocytic leukemia (CLL). While no point mutations have been found in the protein coding candidate genes at 13q14.3, they are deregulated in malignant cells, suggesting an epigenetic tumor suppressor mechanism. We therefore characterized the epigenetic makeup of 13q14.3 in CLL cells and found histone modifications by chromatin-immunoprecipitation (ChIP) that are associated with activated transcription and significant DNA-demethylation at the transcriptional start sites of DLEU1 and DLEU2 using 5 different semi-quantitative and quantitative methods (aPRIMES, BioCOBRA, MCIp, MassARRAY, and bisulfite sequencing). These epigenetic aberrations were correlated with transcriptional deregulation of the neighboring candidate tumor suppressor genes, suggesting a coregulation in cis of this gene cluster. We found that the 13q14.3 genes in addition to their previously known functions regulate NF-kB activity, which we could show after overexpression, siRNA-mediated knockdown, and dominant-negative mutant genes by using Western blots with previously undescribed antibodies, by a customized ELISA as well as by reporter assays. In addition, we performed an unbiased screen of 810 human miRNAs and identified the miR-15/16 family of genes at 13q14.3 as the strongest inducers of NF-kB activity. In summary, the tumor suppressor mechanism at 13q14.3 is a cluster of genes controlled by two lncRNA genes that are regulated by DNA-methylation and histone modifications and whose members all regulate NF-kB. Therefore, the tumor suppressor mechanism in 13q14.3 underlines the role both of epigenetic aberrations and of lncRNA genes in human tumorigenesis and is an example of colocalization of a functionally related gene cluster.
    Type of Publication: Journal article published
    PubMed ID: 23593011
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