A new look towards BAC-based array CGH through a comprehensive comparison with oligo-based array CGH

BACKGROUND: Currently, two main technologies are used for screening of DNA copy number; the BAC (Bacterial Artificial Chromosome) and the recently developed oligonucleotide-based CGH (Chromosomal Comparative Genomic Hybridization) arrays which are capable of detecting small genomic regions with amplification or deletion. The correlation as well as the discriminative power of these platforms has never been compared statistically on a significant set of human patient samples.

RESULTS: In this paper, we present an exhaustive comparison between the two CGH platforms, undertaken at two independent sites using the same batch of DNA from 19 advanced prostate cancers. The comparison was performed directly on the raw data and a significant correlation was found between the two platforms. The correlation was greatly improved when the data were averaged over large chromosomic regions using a segmentation algorithm. In addition, this analysis has enabled the development of a statistical model to discriminate BAC outliers that might indicate microevents. These microevents were validated by the oligo platform results.

CONCLUSION: This article presents a genome-wide statistical validation of the oligo array platform on a large set of patient samples and demonstrates statistically its superiority over the BAC platform for the Identification of chromosomic events. Taking advantage of a large set of human samples treated by the two technologies, a statistical model has been developed to show that the BAC platform could also detect microevents.

DNA microarray profiling of genes differentially regulated by the histone deacetylase inhibitors vorinostat and LBH589 in colon cancer cell lines

BACKGROUND: Despite the significant progress made in colon cancer chemotherapy, advanced disease remains largely incurable and novel efficacious chemotherapies are urgently needed. Histone deacetylase inhibitors (HDACi) represent a novel class of agents which have demonstrated promising preclinical activity and are undergoing clinical evaluation in colon cancer. The goal of this study was to identify genes in colon cancer cells that are differentially regulated by two clinically advanced hydroxamic acid HDACi, vorinostat and LBH589 to provide rationale for novel drug combination partners and identify a core set of HDACi-regulated genes.

METHODS: HCT116 and HT29 colon cancer cells were treated with LBH589 or vorinostat and growth inhibition, acetylation status and apoptosis were analyzed in response to treatment using MTS, Western blotting and flow cytometric analyses. In addition, gene expression was analyzed using the Illumina Human-6 V2 BeadChip array and Ingenuity Pathway Analysis.

RESULTS: Treatment with either vorinostat or LBH589 rapidly induced histone acetylation, cell cycle arrest and inhibited the growth of both HCT116 and HT29 cells. Bioinformatic analysis of the microarray profiling revealed significant similarity in the genes altered in expression following treatment with the two HDACi tested within each cell line. However, analysis of genes that were altered in expression in the HCT116 and HT29 cells revealed cell-line-specific responses to HDACi treatment. In addition a core cassette of 11 genes modulated by both vorinostat and LBH589 were identified in both colon cancer cell lines analyzed.

CONCLUSION: This study identified HDACi-induced alterations in critical genes involved in nucleotide metabolism, angiogenesis, mitosis and cell survival which may represent potential intervention points for novel therapeutic combinations in colon cancer. This information will assist in the identification of novel pathways and targets that are modulated by HDACi, providing much-needed information on HDACi mechanism of action and providing rationale for novel drug combination partners. We identified a core signature of 11 genes which were modulated by both vorinostat and LBH589 in a similar manner in both cell lines. These core genes will assist in the development and validation of a common gene set which may represent a molecular signature of HDAC inhibition in colon cancer.

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Application of SNPs for population genetics of nonmodel organisms:new opportunities and challenges

Recent improvements in the speed, cost and accuracy of next generation sequencing are revolutionizing the discovery of single nucleotide polymorphisms (SNPs). SNPs are increasingly being used as an addition to the molecular ecology toolkit in nonmodel organisms, but their efficient use remains challenging. Here, we discuss common issues when employing SNP markers, including the high numbers of markers typically employed, the effects of ascertainment bias and the inclusion of nonneutral loci in a marker panel. We provide a critique of considerations specifically associated with the application and population genetic analysis of SNPs in nonmodel taxa, focusing specifically on some of the most commonly applied methods.

Gene-associated markers can assign origin in a weakly structured fish, Atlantic herring

Regulations on the exploitation of populations of commercially important fish species and the ensuing consumer interest in sustainable products have increased the need to accurately identify the population of origin of fish and fish products. Although genomics-based tools have proven highly useful, there are relatively few examples in marine fish displaying accurate origin assignment. We synthesize data for 156 single-nucleotide polymorphisms typed in 1039 herring, Clupea harengus L., spanning the Northeast Atlantic to develop a tool that allows assignment of individual herring to their regional origin. We show the method's suitability to address specific biological questions, as well as management applications. We analyse temporally replicated collections from two areas, the Skagerrak (n = 81, 84, 66) and the western Baltic (n = 52, 52). Both areas harbour heavily fished mixed-origin stocks, complicating management issues. We report novel genetic evidence that herring from the Baltic Sea contribute to catches in the North Sea, and find support that western Baltic feeding aggregations mainly constitute herring from the western Baltic with contributions from the Eastern Baltic. Our study describes a general approach and outlines a database allowing individual assignment and traceability of herring across a large part of its East Atlantic distribution.

Natural Killer Cell-like signature observed in locally advanced rectal cancer after neoadjuvant chemoradiotherapy in a tumour regression grade dependent manner

Background: Around 10-15% of patients with locally advanced rectal cancer (LARC) undergo a pathologically complete response (TRG4) to neoadjuvant chemoradiotherapy; the rest of patients exhibit a spectrum of tumour regression (TRG1-3). Understanding therapy-related genomic alterations may help us to identify underlying biology or novel targets associated with response that could increase the efficacy of therapy in patients that do not benefit from the current standard of care.
Methods: 48 FFPE rectal cancer biopsies and matched resections were analysed using the WG-DASL HumanHT-12_v4 Beadchip array on the illumina iScan. Bioinformatic analysis was conducted in Partek genomics suite and R studio. Limma and glmnet packages were used to identify genes differentially expressed between tumour regression grades. Validation of microarray results will be carried out using IHC, RNAscope and RT-PCR.
Results: Immune response genes were observed from supervised analysis of the biopsies which may have predictive value. Differential gene expression from the resections as well as pre and post therapy analysis revealed induction of genes in a tumour regression dependent manner. Pathway mapping and Gene Ontology analysis of these genes suggested antigen processing and natural killer mediated cytotoxicity respectively. The natural killer-like gene signature was switched off in non-responders and on in the responders. IHC has confirmed the presence of Natural killer cells through CD56+ staining.
Conclusion: Identification of NK cell genes and CD56+ cells in patients responding to neoadjuvant chemoradiotherapy warrants further investigation into their association with tumour regression grade in LARC. NK cells are known to lyse malignant cells and determining whether their presence is a cause or consequence of response is crucial. Interrogation of the cytokines upregulated in our NK-like signature will help guide future in vitro models.

Establishing the Evidence Bar for Molecular Diagnostics in Personalised Cancer Care

While personalised cancer medicine holds great promise, targeting therapies to the biological characteristics of patients is limited by the number of validated biomarkers currently available. The implementation of biomarkers has undergone many challenges with few biomarkers reaching cancer patients in the clinic. There have been many biomarkers that have been published and claimed to be therapeutically useful, but few become part of the clinical decision-making process due to technical, validation and market access issues. To reduce this attrition rate, there is a significant need for policy makers and reimbursement agencies to define specific evidence requirements for the introduction of biomarkers into clinical practice. Once these requirements are more clearly defined, in an analogous manner to pharmaceuticals, researchers and diagnostic companies can better focus their biomarker research and development on meeting these specific requirements, which should lead to the more rapid introduction of new molecular oncology tests for patient benefit.

Personalised and Precision Medicine in Cancer Clinical Trials: Panacea for Progress or Pandora's Box?

Cancer clinical trials have been one of the key foundations for significant advances in oncology. However, there is a clear recognition within the academic, care delivery and pharmaceutical/biotech communities that our current model of clinical trial discovery and development is no longer fit for purpose. Delivering transformative cancer care should increasingly be our mantra, rather than maintaining the status quo of, at best, the often miniscule incremental benefits that are observed with many current clinical trials. As we enter the era of precision medicine for personalised cancer care (precision and personalised medicine), it is important that we capture and utilise our greater understanding of the biology of disease to drive innovative approaches in clinical trial design and implementation that can lead to a step change in cancer care delivery. A number of advances have been practice changing (e.g. imatinib mesylate in chronic myeloid leukaemia, Herceptin in erb-B2-positive breast cancer), and increasingly we are seeing the promise of a number of newer approaches, particularly in diseases like lung cancer and melanoma. Targeting immune checkpoints has recently yielded some highly promising results. New algorithms that maximise the effectiveness of clinical trials, through for example a multi-stage, multi-arm type design are increasingly gaining traction. However, our enthusiasm for the undoubted advances that have been achieved are being tempered by a realisation that these new approaches may have significant cost implications. This article will address these competing issues, mainly from a European perspective, highlight the problems and challenges to healthcare systems and suggest potential solutions that will ensure that the cost/value rubicon is addressed in a way that allows stakeholders to work together to deliver optimal cost-effective cancer care, the benefits of which can be transferred directly to our patients.

Calmodulin disruption impacts growth and motility in juvenile liver fluke

Background: Deficiencies in effective flukicide options and growing issues with drug resistance make current strategies for liver fluke control unsustainable, thereby promoting the need to identify and validate new control targets in Fasciola spp. parasites. Calmodulins (CaMs) are small calcium-sensing proteins with ubiquitous expression in all eukaryotic organisms and generally use fluctuations in intracellular calcium levels to modulate cell signalling events. CaMs are essential for fundamental processes including the phosphorylation of protein kinases, gene transcription, calcium transport and smooth muscle contraction. In the blood fluke Schistosoma mansoni, calmodulins have been implicated in egg hatching, miracidial transformation and larval development. Previously, CaMs have been identified amongst liver fluke excretory-secretory products and three CaM-like proteins have been characterised biochemically from adult Fasciola hepatica, although their functions remain unknown.

Methods: In this study, we set out to investigate the biological function and control target potential of F. hepatica CaMs (FhCaMs) using RNAi methodology alongside novel in vitro bioassays.

Results: Our results reveal that: (i) FhCaMs are widely expressed in parenchymal cells throughout the forebody region of juvenile fluke; (ii) significant transcriptional knockdown of FhCaM1-3 was inducible by exposure to either long (~200 nt) double stranded (ds) RNAs or 27 nt short interfering (si) RNAs, although siRNAs were less effective than long dsRNAs; (iii) transient long dsRNA exposure-induced RNA interference (RNAi) of FhCaMs triggered transcript knockdown that persisted for ≥ 21 days, and led to detectable suppression of FhCaM proteins; (iv) FhCaM RNAi significantly reduced the growth of juvenile flukes maintained in vitro; (v) FhCaM RNAi juveniles also displayed hyperactivity encompassing significantly increased migration; (vi) both the reduced growth and increased motility phenotypes were recapitulated in juvenile fluke using the CaM inhibitor trifluoperazine hydrochloride, supporting phenotype specificity.

Conclusions: These data indicate that the Ca(2+)-modulating functions of FhCaMs are important for juvenile fluke growth and movement and provide the first functional genomics-based example of a growth-defect resulting from gene silencing in liver fluke. Whilst the phenotypic impacts of FhCaM silencing on fluke behaviour do not strongly support their candidature as new flukicide targets, the growth impacts encourage further consideration, especially in light of the speed of juvenile fluke growth in vivo.

Promoting healthy dietary behaviour through personalised nutrition: technology push or technology pull?

The notion of educating the public through generic healthy eating messages has pervaded dietary health promotion efforts over the years and continues to do so through various media, despite little evidence for any enduring impact upon eating behaviour. There is growing evidence, however, that tailored interventions such as those that could be delivered online can be effective in bringing about healthy dietary behaviour change. The present paper brings together evidence from qualitative and quantitative studies that have considered the public perspective of genomics, nutrigenomics and personalised nutrition, including those conducted as part of the EU-funded Food4Me project. Such studies have consistently indicated that although the public hold positive views about nutrigenomics and personalised nutrition, they have reservations about the service providers' ability to ensure the secure handling of health data. Technological innovation has driven the concept of personalised nutrition forward and now a further technological leap is required to ensure the privacy of online service delivery systems and to protect data gathered in the process of designing personalised nutrition therapies.

Is it time for standards and a common data exchange format for digital image analysis?

Digital image analysis is at a crossroads. While the technology has made great strides over the past few decades, there is an urgent need for image analysis to inform the next wave of large scale tissue biomarker discovery studies in cancer. Drawing parallels from the growth of next generation sequencing, this presentation will consider the case for a common language or standard format for storing and communicating digital image analysis data. In this context, image analysis data comprises more than simply an image with markups and attached key-value pair metrics. The desire to objectively benchmark competing platforms or a push for data to be deposited to public repositories much like genomics data may drive the need for a standard that also encompasses granular, cell-by-cell data.

Schizophrenia risk from complex variation of complement component 4

Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia's strongest genetic association at a population level involves variation in the major histocompatibility complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to identify. Here we show that this association arises in part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C4A. Human C4 protein localized to neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals with schizophrenia.