Christian Ruckert

High-Resolution Genomic Copy Number Profiling of Glioblastoma Multiforme by Single Nucleotide Polymorphism DNA Microarray

Glioblastoma multiforme (GBM) is an extremely malignant brain tumor. To identify new genomic alterations in GBM, genomic DNA of tumor tissue/explants from 55 individuals and 6 GBM cell lines were examined using single nucleotide polymorphism DNA microarray (SNP-Chip). Further gene expression analysis relied on an additional 56 GBM samples. SNP-Chip results were validated using several techniques, including quantitative PCR (Q-PCR), nucleotide sequencing, and a combination of Q-PCR and detection of microsatellite markers for loss of heterozygosity with normal copy number [acquired uniparental disomy (AUPD)]. Whole genomic DNA copy number in each GBM sample was profiled by SNP-Chip. Several signaling pathways were frequently abnormal. Either the p16(INK4A)/p15(INK4B)-CDK4/6-pRb or p14(ARF)-MDM2/4-p53 pathways were abnormal in 89% (49 of 55) of cases. Simultaneous abnormalities of both pathways occurred in 84% (46 of 55) samples. The phosphoinositide 3-kinase pathway was altered in 71% (39 of 55) GBMs either by deletion of PTEN or amplification of epidermal growth factor receptor and/or vascular endothelial growth factor receptor/platelet-derived growth factor receptor α. Deletion of chromosome 6q26-27 often occurred (16 of 55 samples). The minimum common deleted region included PARK2, PACRG, QKI, and PDE10A genes. Further reverse transcription Q-PCR studies showed that PARK2 expression was decreased in another collection of GBMs at a frequency of 61% (34 of 56) of samples. The 1p36.23 region was deleted in 35% (19 of 55) of samples. Notably, three samples had homozygous deletion encompassing this site. Also, a novel internal deletion of a putative tumor suppressor gene, LRP1B, was discovered causing an aberrant protein. AUPDs occurred in 58% (32 of 55) of the GBM samples and five of six GBM cell lines. A common AUPD was found at chromosome 17p13.3-12 (included p53 gene) in 13 of 61 samples and cell lines. Single-strand conformational polymorphism and nucleotide sequencing showed that 9 of 13 of these samples had homozygous p53 mutations, suggesting that mitotic recombination duplicated the abnormal p53 gene, probably providing a growth advantage to these cells. A significantly shortened survival time was found in patients with 13q14 (RB) deletion or 17p13.1 (p53) deletion/AUPD. Taken together, these results suggest that this technique is a rapid, robust, and inexpensive method to profile genome-wide abnormalities in GBM.(Mol Cancer Res 2009;7(5):665–77)

AML with translocation t(8;16)(p11;p13) demonstrates unique cytomorphological, cytogenetic, molecular and prognostic features

Balanced chromosomal rearrangements define distinct entities in acute myeloid leukemia (AML). Here, we present 13 AML cases with t(8;16)(p11;p13) with observed low incidence (13/6124 patients), but more frequent presentation in therapy-related AML than in de novo AML (7/438 versus 6/5686, P=0.00001). Prognosis was poor with median overall survival of 4.7 months. Cytomorphology was characterized by parallel positive myeloperoxidase and non-specific esterase staining, therefore, French–American–British (FAB)-classification was impossible and origin of the AML with t(8;16) from an early stem cell with myeloid and monoblastic potential is hypothesized. Erythrophagocytosis was observed in 7/13 cases. Using gene expression profiling on 407 cases, patients with t(8;16) were compared to AML FAB subtypes with normal karyotype. Principal component analyses demonstrated that AML with t(8;16) were distinct from FAB subtypes M1, M4, M5a/b. When further compared to AML showing balanced rearrangements, that is, current WHO categories t(15;17), t(8;21), inv(16) and t(11q23)/MLL, AML with t(8;16) cases were clustered close to t(11q23)/MLL sharing commonly expressed genes. Subsequently, a pairwise comparison discriminated AML with t(8;16) from AML with t(11q23)/MLL, thus defining a highly unique signature for AML with t(8;16). In conclusion, AML with t(8;16) demonstrates unique cytomorphological, cytogenetic, molecular and prognostic features and is a specific subtype of AML.

Genomic profiling of adult acute lymphoblastic leukemia by single nucleotide polymorphism oligonucleotide microarray and comparison to pediatric acute lymphoblastic leukemia

Background Differences in survival have been reported between pediatric and adult acute lymphoblastic leukemia. The inferior prognosis in adult acute lymphoblastic leukemia is not fully understood but could be attributed, in part, to differences in genomic alterations found in adult as compared to in pediatric acute lymphoblastic leukemia. Design and Methods We compared two different sets of high-density single nucleotide polymorphism array genotyping data from 75 new diagnostic adult and 399 previously published diagnostic pediatric acute lymphoblastic leukemia samples. The patients’ samples were randomly acquired from among Caucasian and Asian populations and hybridized to either Affymetrix 50K or 250K single nucleotide polymorphism arrays. The array data were investigated with Copy Number Analysis for GeneChips (CNAG) software for allele-specific copy number analysis. Results The high density single nucleotide polymorphism array analysis of 75 samples of adult acute lymphoblastic leukemia led to the identification of numerous cryptic and submicroscopic genomic lesions with a mean of 7.6 genomic alterations per sample. The patterns and frequencies of lesions detected in the adult samples largely reproduced known genomic hallmarks detected in previous single nucleotide polymorphism-array studies of pediatric acute lymphoblastic leukemia, such as common deletions of 3p14.2 (FHIT), 5q33.3 (EBF), 6q, 9p21.3 (CDKN2A/B), 9p13.2 (PAX5), 13q14.2 (RB1) and 17q11.2 (NF1). Some differences between adult and pediatric acute lymphoblastic leukemia were identified when the pediatric data set was partitioned into hyperdiploid and non-hyperdiploid cases and then compared to the nearly exclusively non-hyperdiploid adult samples. In this analysis, adult samples had a higher rate of deletions of chromosome 17p (TP53) and duplication of 17q. Conclusions Our analysis of adult acute lymphoblastic leukemia cases led to the identification of new potential target lesions relevant for the pathogenesis of acute lymphoblastic leukemia. However, no unequivocal pattern of submicroscopic genomic alterations was found to separate adult acute lymphoblastic leukemia from pediatric acute lymphoblastic leukemia. Therefore, apart from different therapy regimen, differences of prognosis between adult and pediatric acute lymphoblastic leukemia are probably based on genetic subgroups according to cytogenetically detectable lesions but not focal genomic copy number microlesions.

Leukemia gene atlas--a public platform for integrative exploration of genome-wide molecular data.

Leukemias are exceptionally well studied at the molecular level and a wealth of high-throughput data has been published. But further utilization of these data by researchers is severely hampered by the lack of accessible integrative tools for viewing and analysis. We developed the Leukemia Gene Atlas (LGA) as a public platform designed to support research and analysis of diverse genomic data published in the field of leukemia. With respect to leukemia research, the LGA is a unique resource with comprehensive search and browse functions. It provides extensive analysis and visualization tools for various types of molecular data. Currently, its database contains data from more than 5,800 leukemia and hematopoiesis samples generated by microarray gene expression, DNA methylation, SNP and next generation sequencing analyses. The LGA allows easy retrieval of large published data sets and thus helps to avoid redundant investigations. It is accessible at www.leukemia-gene-atlas.org.

Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

BackgroundVisualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new hypotheses. Principal Component Analysis (PCA) is a widely used linear method to define the mapping between the high-dimensional data and its low-dimensional representation. During the last decade, many new nonlinear methods for dimension reduction have been proposed, but it is still unclear how well these methods capture the underlying structure of microarray gene expression data. In this study, we assessed the performance of the PCA approach and of six nonlinear dimension reduction methods, namely Kernel PCA, Locally Linear Embedding, Isomap, Diffusion Maps, Laplacian Eigenmaps and Maximum Variance Unfolding, in terms of visualization of microarray data.ResultsA systematic benchmark, consisting of Support Vector Machine classification, cluster validation and noise evaluations was applied to ten microarray and several simulated datasets. Significant differences between PCA and most of the nonlinear methods were observed in two and three dimensional target spaces. With an increasing number of dimensions and an increasing number of differentially expressed genes, all methods showed similar performance. PCA and Diffusion Maps responded less sensitive to noise than the other nonlinear methods.ConclusionsLocally Linear Embedding and Isomap showed a superior performance on all datasets. In very low-dimensional representations and with few differentially expressed genes, these two methods preserve more of the underlying structure of the data than PCA, and thus are favorable alternatives for the visualization of microarray data.

R453Plus1Toolbox: an R/Bioconductor package for analyzing Roche 454 Sequencing data

UNLABELLED The R453Plus1Toolbox is an R/Bioconductor package for the analysis of 454 Sequencing data. Projects generated with Roches data analysis software can be imported into R allowing advanced and customized analyses within the R/Bioconductor environment for sequencing data. Several methods were implemented extending the current functionality of Roches software. These extensions include methods for quality assurance and annotation of detected variants. Further, a pipeline for the detection of structural variants, e.g. balanced chromosomal translocations, is provided. AVAILABILITY The R453Plus1Toolbox is implemented in R and available at http://www.bioconductor.org/. A vignette outlining typical workflows is included in the package. CONTACT h.klein@uni-muenster.de SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures

BackgroundMultiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset.ResultsA database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application.ConclusionsThe presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

Influence of secreted frizzled receptor protein 1 (SFRP1) on neoadjuvant chemotherapy in triple negative breast cancer does not rely on WNT signaling

BackgroundTriple negative breast cancer (TNBC) is characterized by lack of expression of both estrogen and progesterone receptor as well as lack of overexpression or amplification of HER2. Despite an increased probability of response to chemotherapy, many patients resistant to current chemotherapy regimens suffer from a worse prognosis compared to other breast cancer subtypes. However, molecular determinants of response to chemotherapy specific to TNBC remain largely unknown. Thus, there is a high demand for biomarkers potentially stratifying triple negative breast cancer patients for neoadjuvant chemotherapies or alternative therapies.MethodsIn order to identify genes correlating with both the triple negative breast cancer subtype as well as response to neoadjuvant chemotherapy we employed publicly available gene expression profiles of patients, which had received neoadjuvant chemotherapy. Analysis of tissue microarrays as well as breast cancer cell lines revealed correlation to the triple negative breast cancer subtype. Subsequently, effects of siRNA-mediated knockdown on response to standard chemotherapeutic agents as well as radiation therapy were analyzed. Additionally, we evaluated the molecular mechanisms by which SFRP1 alters the carcinogenic properties of breast cancer cells.ResultsSFRP1 was identified as being significantly overexpressed in TNBC compared to other breast cancer subtypes. Additionally, SFRP1 expression is significantly correlated with an increased probability of positive response to neoadjuvant chemotherapy. Knockdown of SFRP1 in triple negative breast cancer cells renders the cells more resistant to standard chemotherapy. Moreover, tumorigenic properties of the cells are modified by knockdown, as shown by both migration or invasion capacity as well reduced apoptotic events. Surprisingly, we found that these effects do not rely on Wnt signaling. Furthermore, we show that pro-apoptotic as well as migratory pathways are differentially regulated after SFRP1 knockdown.ConclusionWe could firstly show that SFRP1 strongly correlates with the triple negative breast cancer subtype and secondly, that SFRP1 might be used as a marker stratifying patients to positively respond to neoadjuvant chemotherapy. The mechanisms by which tumor suppressor SFRP1 influences carcinogenic properties of cancer cells do not rely on Wnt signaling, thereby demonstrating the complexity of tumor associated signaling pathways.

The anti-androgen drug dutasteride renders triple negative breast cancer cells more sensitive to chemotherapy via inhibition of HIF-1α-/VEGF-signaling

Abstract Background: Triple negative breast cancer (TNBC) is characterized by lack of expression of both estrogen and progesterone receptor as well as lack of amplification of HER2. Patients with TNBC carry an unfavorable prognosis compared to other breast cancer subtypes given that endocrine or HER2 targeted therapies are not effective, rendering chemotherapy the sole effective treatment option to date. Therefore, there is a high demand for additional novel treatment options. Findings: We previously published a list of genes showing both higher gene expression rates in TNBC and, in addition, are known to encode targets of non-oncologic drugs. SRD5A1, which encodes the type-1 isoform of the steroid-5alpha-reductase, which is involved in androgen metabolism, was found to be one of these genes. Dutasteride is a dual blocker of both the type-1 and type-2 isoform of SRD5A1 and is indicated in the treatment of benign prostate hyperplasia. Treatment of TNBC cell lines with dutasteride was associated with a dose-dependent decrease in cell viability, altered protein expression of VEGF and HIF-1α and increased chemosensitivity. Conclusion: Our results demonstrate that the SRD5A1-corresponding anti-androgenic drug dutasteride might act as a combinatorial therapeutic option besides standard chemotherapy in highly aggressive TNBC.

Homeobox protein HB9 binds to the prostaglandin E receptor 2 promoter and inhibits intracellular cAMP mobilization in leukemic cells.

Background: HB9 is highly expressed in translocation t(7;12) positive infant AML. Results: HB9 binds to the PTGER2 promoter, down-regulates PTGER2 gene expression and subsequently represses cAMP synthesis in hematopoietic cells. Conclusion: Expression of HLXB9 represses PTGER2 mediated signaling. Significance: First molecular report of HB9-dependent target gene regulation in hematopoietic cells. The transcription factor HB9, encoded by the homeobox gene B9 (HLXB9), is involved in the development of pancreatic beta- and motor neuronal cells. In addition, HLXB9 is recurrently rearranged in young children with acute myeloid leukemia characterized by a chromosomal translocation t(7;12)-HLXB9/TEL and concomitant high expression of the unrearranged, wild-type HLXB9 allele. However, target genes of HB9 in hematopoietic cells are not known to date. In this study, we used ChIP-on-chip analysis together with expression profiling and identified PTGER2 (prostaglandin E receptor 2) as a target gene of HB9 in a hematopoietic cell line. The functional HB9 homeodomain as well as the HB9 binding domain within the PTGER2 promoter are essential for binding of HB9 to the PTGER2 promoter region and down-regulation of PTGER2 expression. Functionally, HB9 conducted down-regulation of PTGER2 results in a reduced content of intracellular cAMP mobilization and furthermore the decreased PTGER2 gene expression is valid in bone marrow cells from translocation t(7;12) positive patients. Among the primary and secondary target genes of HB9 in the myeloid cell line HL60, 78% of significantly regulated genes are down-regulated, indicating an overall repressive function of HB9. Differentially regulated genes were preferentially confined to pathways involved in cell-adhesion and cell-cell interactions, similar to the gene expression footprint of HLXB9-expressing cells from t(7;12) positive patients.