An De Bondt

Genome-wide copy number alterations detection in fresh frozen and matched FFPE samples using SNP 6.0 arrays

SNP arrays offer the opportunity to get a genome‐wide view on copy number alterations and are increasingly used in oncology. DNA from formalin‐fixed paraffin‐embedded material (FFPE) is partially degraded which limits the application of those technologies for retrospective studies. We present the use of Affymetrix GeneChip SNP6.0 for identification of copy number alterations in fresh frozen (FF) and matched FFPE samples. Fifteen pairs of adenocarcinomas with both frozen and FFPE embedded material were analyzed. We present an optimization of the sample preparation and show the importance of correcting the measured intensities for fragment length and GC‐content when using FFPE samples. The absence of GC content correction results in a chromosome specific “wave pattern” which may lead to the misclassification of genomic regions as being altered. The highest concordance between FFPE and matched FF were found in samples with the highest call rates. Nineteen of the 23 high level amplifications (83%) seen using FF samples were also detected in the corresponding FFPE material. For limiting the rate of “false positive” alterations, we have chosen a conservative False Discovery Rate (FDR). We observed better results using SNP probes than CNV probes for copy number analysis of FFPE material. This is the first report on the detection of copy number alterations in FFPE samples using Affymetrix GeneChip SNP6.0.

cn.FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate

Cost-effective oligonucleotide genotyping arrays like the Affymetrix SNP 6.0 are still the predominant technique to measure DNA copy number variations (CNVs). However, CNV detection methods for microarrays overestimate both the number and the size of CNV regions and, consequently, suffer from a high false discovery rate (FDR). A high FDR means that many CNVs are wrongly detected and therefore not associated with a disease in a clinical study, though correction for multiple testing takes them into account and thereby decreases the studys discovery power. For controlling the FDR, we propose a probabilistic latent variable model, ‘cn.FARMS’, which is optimized by a Bayesian maximum a posteriori approach. cn.FARMS controls the FDR through the information gain of the posterior over the prior. The prior represents the null hypothesis of copy number 2 for all samples from which the posterior can only deviate by strong and consistent signals in the data. On HapMap data, cn.FARMS clearly outperformed the two most prevalent methods with respect to sensitivity and FDR. The software cn.FARMS is publicly available as a R package at http://www.bioinf.jku.at/software/cnfarms/cnfarms.html.

MELK-T1, a small-molecule inhibitor of protein kinase MELK, decreases DNA-damage tolerance in proliferating cancer cells

Protein kinase MELK has oncogenic properties and is highly overexpressed in some tumors. In the present study, we show that a novel MELK inhibitor causes both the inhibition and degradation of MELK, culminating in replication stress and a senescence phenotype.

The high-level similarity of some disparate gene expression measures

Probe-level data from Affymetrix GeneChips can be summarized in many ways to produce probe-set level gene expression measures (GEMs). Disturbingly, the different approaches not only generate quite different measures but they could also yield very different analysis results. Here, we explore the question of how much the analysis results really do differ, first at the gene level, then at the biological process level. We demonstrate that, even though the gene level results may not necessarily match each other particularly well, as long as there is reasonably strong differentiation between the groups in the data, the various GEMs do in fact produce results that are similar to one another at the biological process level. Not only that the results are biologically relevant. As the extent of differentiation drops, the degree of concurrence weakens, although the biological relevance of findings at the biological process level may yet remain.

Functional and Transcriptional Characterization of Histone Deacetylase Inhibitor-Mediated Cardiac Adverse Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

Histone deacetylase (HDAC) inhibitors possess therapeutic potential to reverse aberrant epigenetic changes associated with cancers, neurological diseases, and immune disorders. Unfortunately, clinical studies with some HDAC inhibitors displayed delayed cardiac adverse effects, such as atrial fibrillation and ventricular tachycardia. However, the underlying molecular mechanism(s) of HDAC inhibitor‐mediated cardiotoxicity remains poorly understood and is difficult to detect in the early stages of preclinical drug development because of a delayed onset of effects. In the present study, we show for the first time in human induced pluripotent stem cell‐derived cardiomyocytes (hiPS‐CMs) that HDAC inhibitors (dacinostat, panobinostat, vorinostat, entinostat, and tubastatin‐a) induce delayed dose‐related cardiac dysfunction at therapeutic concentrations associated with cardiac adverse effects in humans. HDAC inhibitor‐mediated delayed effects on the beating properties of hiPS‐CMs developed after 12 hours by decreasing the beat rate, shortening the field potential duration, and inducing arrhythmic behavior under form of sustained contractions and fibrillation‐like patterns. Transcriptional changes that are common between the cardiotoxic HDAC inhibitors but different from noncardiotoxic treatments identified cardiac‐specific genes and pathways related to structural and functional changes in cardiomyocytes. Combining the functional data with epigenetic changes in hiPS‐CMs allowed us to identify molecular targets that might explain HDAC inhibitor‐mediated cardiac adverse effects in humans. Therefore, hiPS‐CMs represent a valuable translational model to assess HDAC inhibitor‐mediated cardiotoxicity and support identification of better HDAC inhibitors with an improved benefit‐risk profile.

Upregulation of MAPK Negative Feedback Regulators and RET in Mutant ALK Neuroblastoma: Implications for Targeted Treatment

Purpose: Activating ALK mutations are present in almost 10% of primary neuroblastomas and mark patients for treatment with small-molecule ALK inhibitors in clinical trials. However, recent studies have shown that multiple mechanisms drive resistance to these molecular therapies. We anticipated that detailed mapping of the oncogenic ALK-driven signaling in neuroblastoma can aid to identify potential fragile nodes as additional targets for combination therapies. Experimental Design: To achieve this goal, transcriptome profiling was performed in neuroblastoma cell lines with the ALKF1174L or ALKR1275Q hotspot mutations, ALK amplification, or wild-type ALK following pharmacologic inhibition of ALK using four different compounds. Next, we performed cross-species genomic analyses to identify commonly transcriptionally perturbed genes in MYCN/ALKF1174L double transgenic versus MYCN transgenic mouse tumors as compared with the mutant ALK-driven transcriptome in human neuroblastomas. Results: A 77-gene ALK signature was established and successfully validated in primary neuroblastoma samples, in a neuroblastoma cell line with ALKF1174L and ALKR1275Q regulable overexpression constructs and in other ALKomas. In addition to the previously established PI3K/AKT/mTOR, MAPK/ERK, and MYC/MYCN signaling branches, we identified that mutant ALK drives a strong upregulation of MAPK negative feedback regulators and upregulates RET and RET-driven sympathetic neuronal markers of the cholinergic lineage. Conclusions: We provide important novel insights into the transcriptional consequences and the complexity of mutant ALK signaling in this aggressive pediatric tumor. The negative feedback loop of MAPK pathway inhibitors may affect novel ALK inhibition therapies, whereas mutant ALK induced RET signaling can offer novel opportunities for testing ALK-RET oriented molecular combination therapies. Clin Cancer Res; 21(14); 3327–39. ©2015 AACR.

Mining the human genome using virtual reality

The analysis of genomic data and integration of diverse biological data sources has become increasingly difficult for researches in the life sciences. This problem is exacerbated by the speed with which new data is gathered through automated technology like DNA microarrays. We developed a virtual reality application for visualizing hierarchical relationships within a gene family and for visualizing networks of gene expression data. Integration of other information from multiple databases with these visualizations can aid pharmaceutical researchers in selecting target genes or proteins for new drugs. We found the application of virtual reality to the field of genomics to be successfull.

In Vitro Model for Hepatotoxicity Studies Based on Primary Human Hepatocyte Cultivation in a Perfused 3D Bioreactor System

Accurate prediction of the potential hepatotoxic nature of new pharmaceuticals remains highly challenging. Therefore, novel in vitro models with improved external validity are needed to investigate hepatic metabolism and timely identify any toxicity of drugs in humans. In this study, we examined the effects of diclofenac, as a model substance with a known risk of hepatotoxicity in vivo, in a dynamic multi-compartment bioreactor using primary human liver cells. Biotransformation pathways of the drug and possible effects on metabolic activities, morphology and cell transcriptome were evaluated. Formation rates of diclofenac metabolites were relatively stable over the application period of seven days in bioreactors exposed to 300 µM diclofenac (300 µM bioreactors (300 µM BR)), while in bioreactors exposed to 1000 µM diclofenac (1000 µM BR) metabolite concentrations declined drastically. The biochemical data showed a significant decrease in lactate production and for the higher dose a significant increase in ammonia secretion, indicating a dose-dependent effect of diclofenac application. The microarray analyses performed revealed a stable hepatic phenotype of the cells over time and the observed transcriptional changes were in line with functional readouts of the system. In conclusion, the data highlight the suitability of the bioreactor technology for studying the hepatotoxicity of drugs in vitro.

Microarray Profiling of DNA Extracted from FFPE Tissues Using SNP 6.0 Affymetrix Platform

High-density oligonucleotide microarrays are commonly used for GWAS studies as well as for tumor genome alteration identifications. The recent Affymetrix Genome-Wide SNP 6.0 microarray generation has two major advantages: (1) showing high genome coverage and (2) starting with very small amount of DNA material. The hybridization protocol needs to be standardized and highly reproducible, as DNA is first digested by restriction enzymes and then PCR-amplified to reduce genome complexity. Especially the restriction digestion step is highly sensitive to degradation of the initial material. The stronger the sample is degraded, the lower the number of restriction sites still present in the genome, and hence the less-efficient amplification step.Paraffin-embedded material generally only allows to extract partially degraded DNA, and therefore is difficult to analyze using SNP array technology. We and others (Jacobs et al., Cancer Res 67:2544-2551, 2007; Tuefferd et al., Genes Chromosomes Cancer 47:957-964, 2008) have shown that target preparation protocol can be adjusted to improve hybridization performances. The final in silico data analysis procedure should be modified accordingly to extract most of the biological information from the signal measured. By optimizing these crucial steps, it is possible to use Affymetrix SNP array 6.0 -technology in the context of genome variation, even for FFPE partially degraded material. This opens a lot of potential for large retrospective series of samples.

Chronic drug-induced effects on contractile motion properties and cardiac biomarkers in human induced pluripotent stem cell derived cardiomyocytes.

In the pharmaceutical industry risk assessments of chronic cardiac safety liabilities are mostly performed during late stages of preclinical drug development using in vivo animal models. Here, we explored the potential of human induced pluripotent stem cell‐derived cardiomyocytes (hiPS‐CMs) to detect chronic cardiac risks such as drug‐induced cardiomyocyte toxicity.