http://repub.eur.nl/res/aut/26148/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/26314/ 2011-05-26T00:00:00Z CHEK2 1100delC is a moderate-risk cancer susceptibility allele that confers a high breast cancer risk in a polygenic setting. Gene expression profiling of CHEK2 1100delC breast cancers may reveal clues to the nature of the polygenic CHEK2 model and its genes involved. Here, we report global gene expression profiles of a cohort of 155 familial breast cancers, including 26 CHEK2 1100delC mutant tumors. In line with previous work, all CHEK2 1100delC mutant tumors clustered among the hormone receptor-positive breast cancers. In the hormone receptor-positive subset, a 40-gene CHEK2 signature was subsequently defined that significantly associated with CHEK2 1100delC breast cancers. The identification of a CHEK2 gene signature implies an unexpected biological homogeneity among the CHEK2 1100delC breast cancers. In addition, all 26 CHEK2 1100delC tumors classified as luminal intrinsic subtype breast cancers, with 8 luminal A and 18 luminal B tumors. This biological make-up of CHEK2 1100delC breast cancers suggests that a relatively limited number of additional susceptibility alleles are involved in the polygenic CHEK2 model. Identification of these as-yet-unknown susceptibility alleles should be aided by clues from the 40-gene CHEK2 signature. http://repub.eur.nl/res/pub/33885/ 2011-03-01T00:00:00Z Background Dysfunctioning of CCAAT/enhancer binding protein α (C/EBP α) in acute myeloid leukemia can be caused, amongst others, by mutations in the encoding gene (CEBPA) and by promoter hypermethylation. CEBPA-mutated acute myeloid leukemia is associated with a favorable outcome, but this may be restricted to the case of double mutations in CEBPA in adult acute myeloid leukemia. In pediatric acute myeloid leukemia, data on the impact of these mutations are limited to one series, and data on promoter hypermethylation are lacking. Our objective was to investigate the characteristics, gene expression profiles and prognostic impact of the different CEBPA aberrations in pediatric acute myeloid leukemia. Design and Methods We screened a large pediatric cohort (n=252) for CEBPA single and double mutations by direct sequencing, and for promoter hypermethylation by methylation-specific polymerase chain reaction. Furthermore, we determined the gene-expression profiles (Affymetrix HGU133 plus 2.0 arrays) of this cohort (n=237). Results Thirty-four mutations were identified in 20 out of the 252 cases (7.9%), including 14 doublemutant and 6 single-mutant cases. CEBPA double mutations conferred a significantly better 5-year overall survival compared with single mutations (79% versus 25%, respectively; P=0.04), and compared with CEBPA wild-type acute myeloid leukemia excluding core-binding factor cases (47%; P=0.07). Multivariate analysis confirmed that the double mutations were an independent favorable prognostic factor for survival (hazard ratio 0.23, P=0.04). The combination of screening for promoter hypermethylation and gene expression profiling identified five patients with silenced CEBPA, of whom four cases relapsed. All cases characteristically expressed T-lymphoid markers. Moreover, unsupervised clustering of gene expression profiles showed a clustering of CEBPA double-mutant and silenced cases, pointing towards a common hallmark of abrogated C/EBPα-functioning in these acute myeloid leukemias. Conclusions We showed the independent favorable outcome of patients with CEBPA double-mutant acute myeloid leukemia in a large pediatric series. This molecular marker may, therefore, improve risk-group stratification in pediatric acute myeloid leukemia. For the first time, CEBPA-silenced cases are suggested to confer a poor outcome in pediatric acute myeloid leukemia, indicating that further investigation of this aberration is needed. Furthermore, clustering of gene expression profiles provided insight into the biological similarities and diversities of the different aberrations in CEBPA in pediatric acute myeloid leukemia. http://repub.eur.nl/res/pub/21266/ 2010-10-07T00:00:00Z To identify molecularly defined subgroups in multiple myeloma, gene expression profiling was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/GMMG-HD4 trial. Hierarchical clustering identified 10 subgroups; 6 corresponded to clusters described in the University of Arkansas for Medical Science (UAMS) classification, CD-1 (n = 13, 4.1%), CD-2 (n = 34, 1.6%), MF (n = 32, 1.0%), MS (n = 33, 1.3%), proliferation-associated genes (n = 15, 4.7%), and hyperdiploid (n = 77, 24.1%). Moreover, the UAMSlow percentage of bone disease cluster was identified as a subcluster of the MF cluster (n = 15, 4.7%). One subgroup (n = 39, 12.2%) showed a myeloid signature. Three novel subgroups were defined, including a subgroup of 37 patients (11.6%) characterized by high expression of genes involved in the nuclear factor kappa light-chain-enhancer of activated B cells pathway, which include TNFAIP3 and CD40. Another subgroup of 22 patients (6.9%) was characterized by distinct overexpression of cancer testis antigens without overexpression of proliferation genes. The third novel cluster of 9 patients (2.8%) showed upregulation of protein tyrosine phosphatases PRL-3 and PTPRZ1 as well as SOCS3. To conclude, in addition to 7 clusters described in the UAMS classification, we identified 3 novel subsets of multiple myeloma that may represent unique diagnostic entities. http://repub.eur.nl/res/pub/28514/ 2010-05-21T00:00:00Z Background: Tiling-arrays are applicable to multiple types of biological research questions. Due to its advantages (high sensitivity, resolution, unbiased), the technology is often employed in genome-wide investigations. A major challenge in the analysis of tiling-array data is to define regions-of-interest, i.e., contiguous probes with increased signal intensity (as a result of hybridization of labeled DNA) in a region. Currently, no standard criteria are available to define these regions-of-interest as there is no single probe intensity cut-off level, different regions-of-interest can contain various numbers of probes, and can vary in genomic width. Furthermore, the chromosomal distance between neighboring probes can vary across the genome among different arrays.Results: We have developed Hypergeometric Analysis of Tiling-arrays (HAT), and first evaluated its performance for tiling-array datasets from a Chromatin Immunoprecipitation study on chip (ChIP-on-chip) for the identification of genome-wide DNA binding profiles of transcription factor Cebpa (used for method comparison). Using this assay, we can refine the detection of regions-of-interest by illustrating that regions detected by HAT are more highly enriched for expected motifs in comparison with an alternative detection method (MAT). Subsequently, data from a retroviral insertional mutagenesis screen were used to examine the performance of HAT among different applications of tiling-array datasets. In both studies, detected regions-of-interest have been validated with (q)PCR.Conclusions: We demonstrate that HAT has increased specificity for analysis of tiling-array data in comparison with the alternative method, and that it accurately detects regions-of-interest in two different applications of tiling-arrays. HAT has several advantages over previous methods: i) as there is no single cut-off level for probe-intensity, HAT can detect regions-of-interest at various thresholds, ii) it can detect regions-of-interest of any size, iii) it is independent of probe-resolution across the genome, and across tiling-array platforms and iv) it employs a single user defined parameter: the significance level. Regions-of-interest are detected by computing the hypergeometric-probability, while controlling the Family Wise Error. Furthermore, the method does not require experimental replicates, common regions-of-interest are indicated, a sequence-of-interest can be examined for every detected region-of-interest, and flanking genes can be reported. http://repub.eur.nl/res/pub/27720/ 2010-05-01T00:00:00Z Breast cancer has for long been recognized as a highly diverse tumor group, but the underlying genetic basis has been elusive. Here, we report an extensive molecular characterization of a collection of 41 human breast cancer cell lines. Protein and gene expression analyses indicated that the collection of breast cancer cell lines has retained most, if not all, molecular characteristics that are typical for clinical breast cancers. Gene mutation analyses identified 146 oncogenic mutations among 27 well-known cancer genes, amounting to an average of 3.6 mutations per cell line. Mutations in genes from the p53, RB and PI3K tumor suppressor pathways were widespread among all breast cancer cell lines. Most important, we have identified two gene mutation profiles that are specifically associated with luminal-type and basal-type breast cancer cell lines. The luminal mutation profile involved E-cadherin and MAP2K4 gene mutations and amplifications of Cyclin D1, ERBB2 and HDM2, whereas the basal mutation profile involved BRCA1, RB1, RAS and BRAF gene mutations and deletions of p16 and p14ARF. These subtype-specific gene mutation profiles constitute a genetic basis for the heterogeneity observed among human breast cancers, providing clues for their underlying biology and providing guidance for targeted pharmacogenetic intervention in breast cancer patients. http://repub.eur.nl/res/pub/27795/ 2010-05-01T00:00:00Z We have used copy number variation (CNV) analysis with SNP mapping arrays for miRNA-15a and miRNA-16-1 expression analysis in patients with multiple myeloma (MM) with or without deletion of chromosome 13q14. MiRNA-15a and miRNA-16 display a range of expression patterns in MM patients, independent of the chromosome 13 status. These findings suggest that genes other than miR-15a and miR-16 may explain the prognostic significance of 13q14 deletions. http://repub.eur.nl/res/pub/35770/ 2007-07-01T00:00:00Z PURPOSE. To investigate the potential phenotypic and genetic differences among the Staphylococcus epidermidis isolates obtained from control subjects (lower conjunctival sac; n = 14) with those from patients with keratitis (corneal scrapings; n = 18) or endophthalmitis (vitreous; n = 24). METHODS. Biofilm-forming capacity was detected by PCR for the icaAB gene and phenotyping by microtiter plate assay and congo red agar plate. Genotyping was performed by using fluorescence-amplified fragment length polymorphism (FAFLP) and in silico analysis of the FAFLP profiles. RESULTS. Biofilm phenotyping (congo red agar/microtiter plate) differentiated disease-causing strains from control subjects. PCR assays (mecA, icaAB) were not useful in differentiating disease-causing strains from that of control subjects. The biofilm-forming capability appeared more critical in the pathogenesis of keratitis than in that of endophthalmitis. Cluster analysis of FAFLP data generated 11 clusters comprising 4 major clusters (I, II, III, and V) and 7 minor ones. FAFLP analysis clearly showed clustering of most of the commensal isolates in cluster I, separate from keratitis and endophthalmitis isolates. In silico analysis mapped signature bands to genes such as ebh, tagD, ptsI, and sepA, which might have a significant role in transforming less virulent populations of S. epidermidis to more virulent ones. CONCLUSIONS. The population dynamics of S. epidermidis revealed that there are significant genetic variations that can be detected through FAFLP between ocular disease causing isolates and the commensal population. Copyright http://repub.eur.nl/res/pub/35367/ 2007-06-15T00:00:00Z Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histologic subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was done on 26 glioblas tomas, 22 oligodendrogliomas, and 6 control brain samples. Our results show that Human Exon arrays can identify subgroups of gliomas based on their histologic appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas, a subset of which (47% and 33%) were confirmed by reverse transcription-PCR (RT-PCR). In addition, exon level expression profiling also identified >700 novel exons. Expression of ∼67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants, and can identify novel exons. The splice variants identified by exon level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets. http://repub.eur.nl/res/pub/35802/ 2007-05-01T00:00:00Z We compared multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and amplified fragment length polymorphism (AFLP) for typing of Staphylococcus aureus and show that the methods yield similar results, although with differences in resolving power and reproducibility. Epidemiological conditions should determine which is the optimal typing method to be used. http://repub.eur.nl/res/pub/36739/ 2007-01-01T00:00:00Z Comparative high-throughput amplified fragment length polymorphism (htAFLP) analysis was performed on a set of 25 complement-resistant and 23 complement-sensitive isolates of Moraxella catarrhalis in order to determine whether there were complement phenotype-specific markers within this species. The htAFLP analysis used 21 primer-pair combinations, generating 41364 individual fragments and 2273 fragment length polymorphisms, with an average of 862 polymorphisms per isolate. Analysis of polymorphism data clearly indicated the presence of two phylogenetic lineages and 40 (2%) lineage-specific polymorphisms. However, despite the presence of 361 (16%) statistically significant complement phenotype-associated polymorphisms, no single marker was 100% complement phenotype-specific. Furthermore, no complement phenotype-specific marker was found within different phylogenetic lineages. These findings agree with previous results indicating that the complement resistance phenotype within M. catarrhalis is probably defined by multiple genes, although not all of these genes may be present within all M. catarrhalis isolates.