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 glioblastomas, 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 f67% 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.

Biomarkers for primary or secondary risk prediction of cardiovascular disease (CVD) are urgently needed to improve individual treatment and clinical trial design. The vast majority of biomarker discovery studies has concentrated on plasma/serum as an easily accessible source. Although numerous markers have been identified, their added predictive value on top of traditional risk factors has been limited, as the biological specimen does not specifically reflect expression profiles related with CVD progression and because the signal is often diluted by marker release from other organs. In contrast to serum markers, circulating cells serve as indicators of the actual disease state due to their active role in the pathogenesis of CVD and are responsible for the majority of secreted biomarkers. Therefore, the CIRCULATING CELLS study was initiated, focusing on the cellular effectors of atherosclerosis in the circulation. In total, 714 patients with coronary artery disease (CAD) symptoms were included. Blood cell fractions (monocytes, T-lymphocytes, platelets, granulocytes, PBMC) of all individual patients were isolated and stored for analysis. Concomitantly, extensive flow cytometric characterization of these populations was performed. From each patient, a detailed clinical profile together with extensive questionnaires about medical history and life style was obtained. Various high-throughput -omics approaches (protein, mRNA, miRNA) are currently being undertaken. Data will be integrated with advanced bioinformatics for discovery and validation of secondary risk markers for adverse events. Overall, the CIRCULATING CELLS study grants the interesting possibility that it will both identify novel biomarkers and provide useful insights into the pathophysiology of CAD in patients.

BackgroundNext generation sequencing provides clinical research scientists with direct read out of innumerable variants, including personal, pathological and common benign variants. The aim of resequencing studies is to determine the candidate pathogenic variants from individual genomes, or from family-based or tumor/normal genome comparisons. Whilst the use of appropriate controls within the experimental design will minimize the number of false positive variations selected, this number can be reduced further with the use of high quality whole genome reference data to minimize false positives variants prior to candidate gene selection. In addition the use of platform related sequencing error models can help in the recovery of ambiguous genotypes from lower coverage data.DescriptionWe have developed a whole genome database of human genetic variations, Huvariome, determined by whole genome deep sequencing data with high coverage and low error rates. The database was designed to be sequencing technology independent but is currently populated with 165 individual whole genomes consisting of small pedigrees and matched tumor/normal samples sequenced with the Complete Genomics sequencing platform. Common variants have been determined for a Benelux population cohort and represented as genotypes alongside the results of two sets of control data (73 of the 165 genomes), Huvariome Core which comprises 31 healthy individuals from the Benelux region, and Diversity Panel consisting of 46 healthy individuals representing 10 different populations and 21 samples in three Pedigrees. Users can query the database by gene or position via a web interface and the results are displayed as the frequency of the variations as detected in the datasets. We demonstrate that Huvariome can provide accurate reference allele frequencies to disambiguate sequencing inconsistencies produced in resequencing experiments. Huvariome has been used to support the selection of candidate cardiomyopathy related genes which have a homozygous genotype in the reference cohorts. This database allows the users to see which selected variants are common variants (> 5% minor allele frequency) in the Huvariome core samples, thus aiding in the selection of potentially pathogenic variants by filtering out common variants that are not listed in one of the other public genomic variation databases. The no-call rate and the accuracy of allele calling in Huvariome provides the user with the possibility of identifying platform dependent errors associated with specific regions of the human genome.ConclusionHuvariome is a simple to use resource for validation of resequencing results obtained by NGS experiments. The high sequence coverage and low error rates provide scientists with the ability to remove false positive results from pedigree studies. Results are returned via a web interface that displays location-based genetic variation frequency, impact on protein function, association with known genetic variations and a quality score of the variation base derived from Huvariome...

BackgroundAccurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata.ResultsWe have developed a tool called the HeatMapper that provides such visualizations in a dynamic and flexible manner and is available from .ConclusionThe HeatMapper allows an accessible and comprehensive visualization of the results of gene expression profiling and cluster analysis.

Aims: Skin toxicity is a common adverse effect of breast radiotherapy. We investigated whether inverse-planned intensity-modulated radiotherapy (IMRT) would reduce the incidence of skin toxicity compared with forward field-in-field breast IMRT (FiF-IMRT) in early stage breast cancer. Materials and methods: This phase III randomised controlled trial compared whole-breast irradiation with either FiF-IMRT or helical tomotherapy IMRT (HT-IMRT), with skin toxicity as the primary end point. Patients received 50 Gy in 25 fractions and were assessed to compare skin toxicity between treatment arms. Results: In total, 177 patients were available for assessment and the median follow-up was 73.1 months. Inverse IMRT achieved more homogeneous coverage than FiF-IMRT; erythema and moist desquamation were higher with FiF-IMRT compared with HT-IMRT (61% versus 34%; P < 0.001; 33% versus 11%; P < 0.001, respectively). Multivariate analysis showed large breast volume, FiF-IMRT and chemotherapy were independent factors associated with worse acute toxicity. There was no difference between treatment arms in the incidence of late toxicities. The 5-year recurrence-free survival was 96.3% for both FiF-IMRT and HT-IMRT and the 5-year overall survival was 96.3% for FiF-IMRT and 97.4% for HT-IMRT. Conclusions: Our study showed significant reduction in acute skin toxicity using HT-IMRT compared with FiF-IMRT, without significant reduction in late skin toxicities. On the basis of these findings, inverse-planned IMRT could be used in routine practice for whole-breast irradiation with careful plan optimisation to achieve the required dose constraints for organs at risk.