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  • American Association for Cancer Research (AACR)  (3)
  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 74, No. 19_Supplement ( 2014-10-01), p. 3387-3387
    Abstract: Lower grade gliomas can be histologically classified into astrocytomas, oligoastrocytomas, or oligodendrogliomas. The latter have come into focus because of their interesting characteristics: they have a more favorable outcome and better response to chemo/radiotherapy. This is correlated with a unique unbalanced translocation der(1;19)(q10;p10) causing a codeletion of the short arm of chromosome 1 and the long arm of chromosome 19. Like the other lower grade gliomas, a large percentage of oligodendrogliomas carry the IDH1 R132 mutation and this is associated with the presence of the codeletion. We identified a high number of mutations in the remaining alleles of the Capicua homolog gene (CIC) and in the far upstream element binding protein (FUBP1) in 1p/19q codeleted oligodendrogliomas (Eisenreich et al. 2013, doi:10.1371/journal.pone.0076623). Both genes are suspected to act as tumor suppressor genes. We then analyzed the expression profiles of 13 oligodendrogliomas and oligoastrocytomas both with the 1p/19q codeletion (nine samples) and without (four samples) using a combination of expression microarrays and transcriptome sequencing (RNA-Seq). Our results showed that all nine samples with the 1p/19q codeletion carried the heterozygous IDH1 R132H mutation while only one tumor without the codeletion carried said mutation. There was a high concordance between the results of RNA-Seq and the microarray experiments and both showed a distinctive expression signature between samples with the 1p/19q codeletion and those without. Using MSigDB, we found that the genes whose expression was altered in in tumors with the 1p/19q codeletion showed significant overlap with those involved in stemness and differentiation and genes that had CpG-rich promoters. Furthermore, there was an overlap with genes with altered expression in chronic myelogenous leukemia (CML). When we compared the expression of genes located on 1p and 19q between the tumors with the 1p/19q codeletion and those without, we found that only 82% of genes on 1p and 19q were downregulated significantly. When we ran the upregulated genes in PathScan, we found enrichment in GA binding protein alpha (GABPA)binding sites. GABPA expression levels were increased in our glioma samples with and without the 1p/19q codeletion. Investigating the expression levels of GABPA in the Cancer Genome Atlas (TCGA) GBM dataset also revealed an upregulation of this transcription factor. An increase in GABPA-mediated transcription was recently reported in CML but has not been yet reported in gliomas. We therefore propose that GABPA is an important transcription factor in gliomas. We are currently evaluating the function of GABPA in glioma what will also be presented. Acknowledgements: This project was partially supported by a MeDDrive grant of the Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden. Citation Format: Barbara Klink, Karol Szafranski, Jaime Campos-Valenzuela, Sophie Eisenreich, Dietmar Krex, Eva-Maria Gerlach, Karl Hackmann, Andreas Rump, Gabriele Schackert, Matthias Platzer, Lars Kaderali, Evelin Schröck, Khalil Abou-El-Ardat. Upregulation of gene expression in oligodendrogliomas is linked to an increase in GA binding protein alpha transcription. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3387. doi:10.1158/1538-7445.AM2014-3387
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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    detail.hit.zdb_id: 410466-3
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  • 2
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2007
    In:  Clinical Cancer Research Vol. 13, No. 5 ( 2007-03-01), p. 1459-1465
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 13, No. 5 ( 2007-03-01), p. 1459-1465
    Abstract: Purpose: To assess the feasibility of predicting neuroblastoma outcome using highly parallel quantitative real-time PCR data. Experimental Design: We generated expression profiles of 63 neuroblastoma patients, 47 of which were analyzed by both Affymetrix U95A microarrays and highly parallel real-time PCR on microfluidic cards (MFC; Applied Biosystems). Top-ranked genes discriminating patients with event-free survival or relapse according to high-level analysis of Affymetrix chip data, as well as known neuroblastoma marker genes (MYCN and NTRK1/TrkA), were quantified simultaneously by real-time PCR. Analysis of PCR data was accomplished using high-level bioinformatics methods including prediction analysis of microarray, significance analysis of microarray, and Computerized Affected Sibling Pair Analyzer and Reporter. Results: Internal validation of the MFC method proved it highly reproducible. Correlation of MFC and chip expression data varied markedly for some genes. Outcome prediction using prediction analysis of microarray on real-time PCR data resulted in 80% accuracy, which is comparable to results obtained using the Affymetrix platform. Real-time PCR data were useful for risk assessment of relapsing neuroblastoma (P = 0.0006, log-rank test) when Computerized Affected Sibling Pair Analyzer and Reporter analysis was applied. Conclusions: These data suggest that multiplex real-time PCR might be a promising approach to reduce the complexity of information obtained from whole-genome array experiments. It could provide a more convenient and less expensive tool for routine application in a clinical setting.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2007
    detail.hit.zdb_id: 1225457-5
    detail.hit.zdb_id: 2036787-9
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  • 3
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 14, No. 20 ( 2008-10-15), p. 6590-6601
    Abstract: Purpose: To predict individual survival times for neuroblastoma patients from gene expression data using the cancer survival prediction using automatic relevance determination (CASPAR) algorithm. Experimental Design: A first set of oligonucleotide microarray gene expression profiles comprising 256 neuroblastoma patients was generated. Then, CASPAR was combined with a leave-one-out cross-validation to predict individual times for both the whole cohort and subgroups of patients with unfavorable markers, including stage 4 disease (n = 67), unfavorable genetic alterations, intermediate-risk or high-risk stratification by the German neuroblastoma trial, and patients predicted as unfavorable by a recently described gene expression classifier (n = 83). Prediction accuracy of individual survival times was assessed by Kaplan-Meier analyses and time-dependent receiver operator characteristics curve analyses. Subsequently, classification results were validated in an independent cohort (n = 120). Results: CASPAR separated patients with divergent outcome in both the initial and the validation cohort [initial set, 5y-OS 0.94 ± 0.04 (predicted long survival) versus 0.38 ± 0.17 (predicted short survival), P & lt; 0.0001; validation cohort, 5y-OS 0.94 ± 0.07 (long) versus 0.40 ± 0.13 (short), P & lt; 0.0001]. Time-dependent receiver operator characteristics analyses showed that CASPAR-predicted individual survival times were highly accurate (initial set, mean area under the curve for first 10 years of overall survival prediction 0.92 ± 0.04; validation set, 0.81 ± 0.05). Furthermore, CASPAR significantly discriminated short ( & lt;5 years) from long survivors ( & gt;5 years) in subgroups of patients with unfavorable markers with the exception of MYCN-amplified patients (initial set). Confirmatory results with high significance were observed in the validation cohort [stage 4 disease (P = 0.0049), NB2004 intermediate-risk or high-risk stratification (P = 0.0017), and unfavorable gene expression prediction (P = 0.0017)]. Conclusions: CASPAR accurately forecasts individual survival times for neuroblastoma patients from gene expression data.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2008
    detail.hit.zdb_id: 1225457-5
    detail.hit.zdb_id: 2036787-9
    Location Call Number Limitation Availability
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