Discrimination of pancreato-biliary cancer and pancreatitis patients by non-invasive liquid biopsy.

BACKGROUND: Current diagnostics for the detection of pancreato-biliary cancers (PBCs) need to be optimized. We therefore propose that methylated cell-free DNA (cfDNA) derived from non-invasive liquid biopsies serves as a novel biomarker with the ability to discriminate pancreato-biliary cancers from non-cancer pancreatitis patients. METHODS: Differentially methylated regions (DMRs) from plasma cfDNA between PBCs, pancreatitis and clinical control samples conditions were identified by next-generation sequencing after enrichment using methyl-binding domains and database searches to generate a discriminatory panel for a hybridization and capture assay with subsequent targeted high throughput sequencing. RESULTS: The hybridization and capture panel, covering around 74 kb in total, was applied to sequence a cohort of 25 PBCs, 25 pancreatitis patients, 25 clinical controls, and seven cases of Intraductal Papillary Mucinous Neoplasia (IPMN). An unbiased machine learning approach identified the 50 most discriminatory methylation markers for the discrimination of PBC from pancreatitis and controls resulting in an AUROC of 0.85 and 0.88 for a training (n = 45) and a validation (n = 37) data set, respectively. The panel was also able to distinguish high grade from low grade IPMN samples. CONCLUSIONS: We present a proof of concept for a methylation biomarker panel with better performance and improved discriminatory power than the current clinical marker CA19-9 for the discrimination of pancreato-biliary cancers from non-cancerous pancreatitis patients and clinical controls. This workflow might be used in future diagnostics for the detection of precancerous lesions, e.g. the identification of high grade IPMNs vs. low grade IPMNs.

A Model-Based Workflow to Benchmark the Clinical Cholestasis Risk of Drugs.

We present a generic workflow combining physiology-based computational modeling and in vitro data to assess the clinical cholestatic risk of different drugs systematically. Changes in expression levels of genes involved in the enterohepatic circulation of bile acids were obtained from an in vitro assay mimicking 14 days of repeated drug administration for 10 marketed drugs. These changes in gene expression over time were contextualized in a physiology-based bile acid model of glycochenodeoxycholic acid. The simulated drug-induced response in bile acid concentrations was then scaled with the applied drug doses to calculate the cholestatic potential for each compound. A ranking of the cholestatic potential correlated very well with the clinical cholestasis risk obtained from medical literature. The proposed workflow allows benchmarking the cholestatic risk of novel drug candidates. We expect the application of our workflow to significantly contribute to the stratification of the cholestatic potential of new drugs and to support animal-free testing in future drug development.

Network integration and modelling of dynamic drug responses at multi-omics levels.

Uncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin). Dynamic molecular analysis at in vivo drug exposure levels reveal a network of 175 disease-associated proteins and identify common modules of anthracycline cardiotoxicity in vitro, related to mitochondrial and sarcomere function as well as remodeling of extracellular matrix. These in vitro-identified modules are transferable and are evaluated with biopsies of cardiomyopathy patients. This to our knowledge most comprehensive study on anthracycline cardiotoxicity demonstrates a reproducible workflow for molecular medicine and serves as a template for detecting adverse drug responses from complex omics data.

Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets.

Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks ("modules"). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene-protein interactions directly affected by genetic variance in CAD risk loci.

Methylation patterns in serum DNA for early identification of disseminated breast cancer.

BACKGROUND: Monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant circulating DNA methylation (DNAme) patterns are likely to provide a highly specific cancer signal. We hypothesized that cell-free DNAme markers could indicate disseminated breast cancer, even in the presence of substantial quantities of background DNA. METHODS: We used reduced representation bisulfite sequencing (RRBS) of 31 tissues and established serum assays based on ultra-high coverage bisulfite sequencing in two independent prospective serum sets (n = 110). The clinical use of one specific region, EFC#93, was validated in 419 patients (in both pre- and post-adjuvant chemotherapy samples) from SUCCESS (Simultaneous Study of Gemcitabine-Docetaxel Combination adjuvant treatment, as well as Extended Bisphosphonate and Surveillance-Trial) and 925 women (pre-diagnosis) from the UKCTOCS (UK Collaborative Trial of Ovarian Cancer Screening) population cohort, with overall survival and occurrence of incident breast cancer (which will or will not lead to death), respectively, as primary endpoints. RESULTS: A total of 18 BC specific DNAme patterns were discovered in tissue, of which the top six were further tested in serum. The best candidate, EFC#93, was validated for clinical use. EFC#93 was an independent poor prognostic marker in pre-chemotherapy samples (hazard ratio [HR] for death = 7.689) and superior to circulating tumor cells (CTCs) (HR for death = 5.681). More than 70% of patients with both CTCs and EFC#93 serum DNAme positivity in their pre-chemotherapy samples relapsed within five years. EFC#93-positive disseminated disease in post-chemotherapy samples seems to respond to anti-hormonal treatment. The presence of EFC#93 serum DNAme identified 42.9% and 25% of women who were diagnosed with a fatal BC within 3-6 and 6-12 months of sample donation, respectively, with a specificity of 88%. The sensitivity with respect to detecting fatal BC was ~ 4-fold higher compared to non-fatal BC. CONCLUSIONS: Detection of EFC#93 serum DNAme patterns offers a new tool for early diagnosis and management of disseminated breast cancers. Clinical trials are required to assess whether EFC#93-positive women in the absence of radiological detectable breast cancers will benefit from anti-hormonal treatment before the breast lesions become clinically apparent.

The potential of circulating tumor DNA methylation analysis for the early detection and management of ovarian cancer.

BACKGROUND: Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence. METHODS: We analyzed 699 cancerous and non-cancerous tissues using a methylation array or reduced representation bisulfite sequencing to discover the most specific OC methylation patterns. A three-DNA-methylation-serum-marker panel was developed using targeted ultra-high coverage bisulfite sequencing in 151 women and validated in 250 women with various conditions, particularly in those associated with high CA125 levels (endometriosis and other benign pelvic masses), serial samples from 25 patients undergoing neoadjuvant chemotherapy, and a nested case control study of 172 UKCTOCS control arm participants which included serum samples up to two years before OC diagnosis. RESULTS: The cell-free DNA amount and average fragment size in the serum samples was up to ten times higher than average published values (based on samples that were immediately processed) due to leakage of DNA from white blood cells owing to delayed time to serum separation. Despite this, the marker panel discriminated high grade serous OC patients from healthy women or patients with a benign pelvic mass with specificity/sensitivity of 90.7% (95% confidence interval [CI] = 84.3-94.8%) and 41.4% (95% CI = 24.1-60.9%), respectively. Levels of all three markers plummeted after exposure to chemotherapy and correctly identified 78% and 86% responders and non-responders (Fisher's exact test, p = 0.04), respectively, which was superior to a CA125 cut-off of 35 IU/mL (20% and 75%). 57.9% (95% CI 34.0-78.9%) of women who developed OC within two years of sample collection were identified with a specificity of 88.1% (95% CI = 77.3-94.3%). Sensitivity and specificity improved further when specifically analyzing CA125 negative samples only (63.6% and 87.5%, respectively). CONCLUSIONS: Our data suggest that DNA methylation patterns in cell-free DNA have the potential to detect a proportion of OCs up to two years in advance of diagnosis and may potentially guide personalized treatment. The prospective use of novel collection vials, which stabilize blood cells and reduce background DNA contamination in serum/plasma samples, will facilitate clinical implementation of liquid biopsy analyses.

diXa: a data infrastructure for chemical safety assessment.

MOTIVATION: The field of toxicogenomics (the application of '-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. RESULTS: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. AVAILABILITY AND IMPLEMENTATION: http://www.dixa-fp7.eu CONTACT: d.hendrickx@maastrichtuniversity.nl; info@dixa-fp7.eu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Interference of peritoneal dialysis fluids with cell cycle mechanisms.

INTRODUCTION: Peritoneal dialysis fluids (PDF) differ with respect to osmotic and buffer compound, and pH and glucose degradation products (GDP) content. The impact on peritoneal membrane integrity is still insufficiently described. We assessed global genomic effects of PDF in primary human peritoneal mesothelial cells (PMC) by whole genome analyses, quantitative real-time polymerase chain reaction (RT-PCR) and functional measurements. METHODS: PMC isolated from omentum of non-uremic patients were incubated with conventional single chamber PDF (CPDF), lactate- (LPDF), bicarbonate- (BPDF) and bicarbonate/lactate-buffered double-chamber PDF (BLPDF), icodextrin (IPDF) and amino acid PDF (APDF), diluted 1:1 with medium. Affymetrix GeneChip U133Plus2.0 (Affymetrix, CA, USA) and quantitative RT-PCR were applied; cell viability was assessed by proliferation assays. RESULTS: The number of differentially expressed genes compared to medium was 464 with APDF, 208 with CPDF, 169 with IPDF, 71 with LPDF, 45 with BPDF and 42 with BLPDF. Out of these genes 74%, 73%, 79%, 72%, 47% and 57% were downregulated. Gene Ontology (GO) term annotations mainly revealed associations with cell cycle (p = 10(-35)), cell division, mitosis, and DNA replication. One hundred and eighteen out of 249 probe sets detecting genes involved in cell cycle/division were suppressed, with APDF-treated PMC being affected the most regarding absolute number and degree, followed by CPDF and IPDF. Bicarbonate-containing PDF and BLPDF-treated PMC were affected the least. Quantitative RT-PCR measurements confirmed microarray findings for key cell cycle genes (CDK1/CCNB1/CCNE2/AURKA/KIF11/KIF14). Suppression was lowest for BPDF and BLPDF, they upregulated CCNE2 and SMC4. All PDF upregulated 3 out of 4 assessed cell cycle repressors (p53/BAX/p21). Cell viability scores confirmed gene expression results, being 79% of medium for LPDF, 101% for BLPDF, 51% for CPDF and 23% for IPDF. Amino acid-containing PDF (84%) incubated cells were as viable as BPDF (86%). CONCLUSION: In conclusion, PD solutions substantially differ with regard to their gene regulating profile and impact on vital functions of PMC, i.e. on cells known to be essential for peritoneal membrane homeostasis.

DNA methylation markers for early detection of women's cancer: promise and challenges.

Breast, ovarian and endometrial cancers cause significant morbidity and mortality. Despite the presence of existing screening, diagnostic and treatment modalities, they continue to pose considerable unsolved challenges. Overdiagnosis is a growing problem in breast cancer screening and neither screening nor early diagnosis of ovarian or endometrial cancer is currently possible. Moreover, treatment of the diversity of these cancers presenting in the clinic is not sufficiently personalized at present. Recent technological advances, including reduced representation bisulfite sequencing, methylation arrays, digital PCR, next-generation sequencing and advanced statistical data analysis, enable the analysis of methylation patterns in cell-free tumor DNA in serum/plasma. Ongoing work is bringing these methods together for the analysis of samples from large clinical trials, which have been collected well in advance of cancer diagnosis. These efforts pave the way for the development of a noninvasive method that would enable us to overcome existing challenges to personalized medicine.

Genome-wide gene expression profiling of formalin-fixed paraffin-embedded breast cancer core biopsies using microarrays.

The routine workflow for invasive cancer diagnostics includes biopsy processing by formalin fixation and paraffin embedding. It has been shown only recently that this kind of sample can be used for gene expression analysis with microarrays. To support this view, the authors conducted a microarray study using formalin-fixed paraffin-embedded (FFPE) core needle biopsies from breast cancers. Typically, for the 3'-biased chip type that was used, the probe sets interrogate sequences near the poly-A-tail of the transcripts, and this kind of probe turned out to be suitable to measure RNA levels in FFPE biopsies. For ER and HER2, the authors observed strong correlations between RNA levels and protein expression (p = 0.000003 and p = 0.0022). ER and HER2 classification of the biopsies by the RNA levels was feasible with high sensitivity and specificity (AUROC = 0.93 and AUROC = 0.96). Furthermore, a signature of 346 genes was identified that correlated with ER and a signature of 528 genes that correlated with HER2 protein status. Many of these genes (ER: 63%) could be confirmed by analysis of gene expression data from frozen tissues. The findings support the notion that clinically relevant information can be gained from microarray analyses of FFPE cancer biopsies. This opens new opportunities for biomarker detection studies and the integration of microarrays into the workflow of cancer diagnostics.

Changes in gene expression induced by phosphorothioate oligodeoxynucleotides (including G3139) in PC3 prostate carcinoma cells are recapitulated at least in part by treatment with interferon-beta and -gamma.

PURPOSE: G3139 is an antisense bcl-2 phosphorothioate oligodeoxyribonucleotide that is currently being evaluated in Phase III clinical trials in several human cancers. The aim of the present work was to further identify the apparent non-bcl-2-dependent mechanism of this action of this compound in PC3 prostate cancer cells. EXPERIMENTAL DESIGN: We performed Affymetrix U95A oligonucleotide microarray studies on mRNA isolated from cells treated with G3139 and related oligonucleotides. RESULTS: Hierarchical clustering revealed the presence of a set of genes of which the expression was elevated on both 1 and 3 days after oligonucleotide treatment. Significantly, the persistence of expression of the up-regulation of these genes, many of which are members of the IFN cascade, was greater for G3139 than for any other oligomer evaluated. Furthermore, many of the genes with the greatest up-regulation of expression are also those of which the expression is up-regulated after treatment of cells with IFNs. Treatment of PC3 cells with either IFN-beta or -gamma recapitulated some of the aspects of the molecular and phenotypic changes observed after treatment with a G3139/Lipofectin complex. These include down-regulation of bcl-2 protein expression itself, down-regulation of protein kinase C alpha protein expression (but not that of other protein kinase C isoforms), alteration in p21/Waf1/Cip1 protein expression, up-regulation of MHC-I cell surface expression, and profound suppression of cell growth in the absence of a notable increase in cellular apoptosis. However, G3139 (when complexed with Lipofectin) did not induce the up-regulation of expression of either type I or type II IFNs, nor could IFNs be found in conditioned media from treated cells. CONCLUSIONS: Oligonucleotide microarray experiments demonstrated that G3139 could induce elements of the IFN cascade in PC3 cells in vitro. In addition, the cellular phenotype obtained after treatment with exogenous IFN could, at least in part, recapitulate that obtained after G3139 treatment. Nevertheless, the oligonucleotide microarray experiments we performed also demonstrated that there are extremely large qualitative and quantitative differences between the two treatments.

GPR99, a new G protein-coupled receptor with homology to a new subgroup of nucleotide receptors.

BACKGROUND: Based on sequence similarity, the superfamily of G protein-coupled receptors (GPRs) can be subdivided into several subfamilies, the members of which often share similar ligands. The sequence data provided by the human genome project allows us to identify new GPRs by in silico homology screening, and to predict their ligands. RESULTS: By searching the human genomic database with known nucleotide receptors we discovered the gene for GPR99, a new orphan GPR. The mRNA of GPR99 was found in kidney and placenta. Phylogenetic analysis groups GPR99 into the P2Y subfamily of GPRs. Based on the phylogenetic tree we propose a new classification of P2Y nucleotide receptors into two subgroups predicting a nucleotide ligand for GPR99. By assaying known nucleotide ligands on heterologously expressed GPR99, we could not identify specifically activating substances, indicating that either they are not agonists of GPR99 or that GPR99 was not expressed at the cell surface. Analysis of the chromosomal localization of all genes of the P2Y subfamily revealed that all members of subgroup "a" are encoded by less than 370 kb on chromosome 3q24, and that the genes of subgroup "b" are clustered on one hand to chromosome 11q13.5 and on the other on chromosome 3q24-25.1 close to the subgroup "a" position. Therefore, the P2Y subfamily is a striking example for local gene amplification. CONCLUSIONS: We identified a new orphan receptor, GPR99, with homology to the family of G protein-coupled nucleotide receptors. Phylogenetic analysis separates this family into different subgroups predicting a nucleotide ligand for GPR99.