Estimation and assessment of raw copy numbers at the single locus level

ESCCdb: A Comprehensive Database and Key Regulator Exploring Platform Based on Cross Dataset Comparisons for Esophageal Squamous Cell Carcinoma

Esophageal cancer is the seventh most prevalent and the sixth most lethal cancer. Esophageal squamous cell carcinoma (ESCC) is one of the major esophageal cancer subtypes that accounts for 87 % of the total cases. However, its molecular mechanism remains unclear. Here, we present an integrated database for ESCC called ESCCdb, which includes a total of 56 datasets and published studies from the GEO, Xena or SRA databases and related publications. It helps users to explore a particular gene with multiple graphical and interactive views with one click. The results comprise expression changes across 20 datasets, copy number alterations in 11 datasets, somatic mutations from 12 papers, related drugs derived from DGIdb, related pathways, and gene correlations. ESCCdb enables directly cross-dataset comparison of a gene's mutations, expressions and copy number changes in multiple datasets. This allows users to easily assess the alterations in ESCC. Furthermore, survival analysis, drug-gene relationships, and results from whole-genome CRISPR/Cas9 screening can help users determine the clinical relevance, derive functional inferences, and identify potential drugs. Notably, ESCCdb also enables the exploration of the correlation structure and identification of potential key regulators for a process. Finally, we identified 789 consistently differential expressed genes; we summarized recurrently mutated genes and genes affected by significant copy number alterations. These genes may be stable biomarkers or important players during ESCC development. ESCCdb fills the gap between massive omics data and users' needs for integrated analysis and can promote basic and clinical ESCC research. The database is freely accessible at http://cailab.labshare.cn/ESCCdb.

A family study implicates GBE1 in the etiology of autism spectrum disorder

Autism spectrum disorders (ASD) are neurodevelopmental disorders with an estimated heritability of >60%. Family-based genetic studies of ASD have generally focused on multiple small kindreds, searching for de novo variants of major effect. We hypothesized that molecular genetic analysis of large multiplex families would enable the identification of variants of milder effects. We studied a large multigenerational family of European ancestry with multiple family members affected with ASD or the broader autism phenotype (BAP). We identified a rare heterozygous variant in the gene encoding 1,4-ɑ-glucan branching enzyme 1 (GBE1) that was present in seven of seven individuals with ASD, nine of ten individuals with the BAP, and none of four tested unaffected individuals. We genotyped a community-acquired cohort of 389 individuals with ASD and identified three additional probands. Cascade analysis demonstrated that the variant was present in 11 of 13 individuals with familial ASD/BAP and neither of the two tested unaffected individuals in these three families, also of European ancestry. The variant was not enriched in the combined UK10K ASD cohorts of European ancestry but heterozygous GBE1 deletion was overrepresented in large ASD cohorts, collectively suggesting an association between GBE1 and ASD.

Epithelial-to-Mesenchymal Transition Mediates Resistance to Maintenance Therapy with Vinflunine in Advanced Urothelial Cell Carcinoma

Simple Summary

Platinum-based chemotherapy is the first-line treatment for advanced urothelial cell carcinoma (aUCC). After first-line treatment, we previously showed that maintenance therapy with vinflunine improves progression-free survival. However, some patients are resistant to vinflunine and the specific mechanisms of resistance in aUCC are unclear. We analyzed the genomic landscape and the biological processes potentially related to vinflunine activity and found that epithelial-to-mesenchymal transition (EMT) plays a pivotal role as a resistance mechanism. In experiments with cell lines, curcumin reversed EMT and sensitized cells to vinflunine. We suggest that EMT mediates resistance to vinflunine and that the reversion of this process could enhance the effect of vinflunine in aUCC patients.

Abstract

In the phase II MAJA trial, maintenance therapy with vinflunine resulted in longer progression-free survival compared to best supportive care in advanced urothelial cell carcinoma (aUCC) patients who did not progress after first-line platinum-based chemotherapy. However, despite an initial benefit observed in some patients, unequivocal resistance appears which underlying mechanisms are presently unknown. We have performed gene expression and functional enrichment analyses to shed light on the discovery of these underlying resistance mechanisms. Differential gene expression profile of eight patients with poor outcome and nine with good outcome to vinflunine administered in the MAJA trial were analyzed. RNA was isolated from tumor tissue and gene expression was assessed by microarray. Differential expression was determined with linear models for microarray data. Gene Set Enrichment Analysis (GSEA) was used for the functional classification of the genes. In vitro functional studies were performed using UCC cell lines. Hierarchical clustering showed a differential gene expression pattern between patients with good and poor outcome to vinflunine treatment. GSEA identified epithelial-to-mesenchymal transition (EMT) as the top negatively enriched hallmark in patients with good outcome. In vitro analyses showed that the polyphenol curcumin downregulated EMT markers and sensitized UCC cells to vinflunine. We conclude that EMT mediates resistance to vinflunine and suggest that the reversion of this process could enhance the effect of vinflunine in aUCC patients.

Expanding control of the tumor cell cycle with a CDK2/4/6 inhibitor

The CDK4/6 inhibitor, palbociclib (PAL), significantly improves progression-free survival in HR⁺/HER2^- breast cancer when combined with anti-hormonals. We sought to discover PAL resistance mechanisms in preclinical models and through analysis of clinical transcriptome specimens, which coalesced on induction of MYC oncogene and Cyclin E/CDK2 activity. We propose that targeting the G₁ kinases CDK2, CDK4, and CDK6 with a small-molecule overcomes resistance to CDK4/6 inhibition. We describe the pharmacodynamics and efficacy of PF-06873600 (PF3600), a pyridopyrimidine with potent inhibition of CDK2/4/6 activity and efficacy in multiple in vivo tumor models. Together with the clinical analysis, MYC activity predicts (PF3600) efficacy across multiple cell lineages. Finally, we find that CDK2/4/6 inhibition does not compromise tumor-specific immune checkpoint blockade responses in syngeneic models. We anticipate that (PF3600), currently in phase 1 clinical trials, offers a therapeutic option to cancer patients in whom CDK4/6 inhibition is insufficient to alter disease progression.

Multi-platform profiling characterizes molecular subgroups and resistance networks in chronic lymphocytic leukemia

Knowledge of the genomic landscape of chronic lymphocytic leukemia (CLL) grows increasingly detailed, providing challenges in contextualizing the accumulated information. To define the underlying networks, we here perform a multi-platform molecular characterization. We identify major subgroups characterized by genomic instability (GI) or activation of epithelial-mesenchymal-transition (EMT)-like programs, which subdivide into non-inflammatory and inflammatory subtypes. GI CLL exhibit disruption of genome integrity, DNA-damage response and are associated with mutagenesis mediated through activation-induced cytidine deaminase or defective mismatch repair. TP53 wild-type and mutated/deleted cases constitute a transcriptionally uniform entity in GI CLL and show similarly poor progression-free survival at relapse. EMT-like CLL exhibit high genomic stability, reduced benefit from the addition of rituximab and EMT-like differentiation is inhibited by induction of DNA damage. This work extends the perspective on CLL biology and risk categories in TP53 wild-type CLL. Furthermore, molecular targets identified within each subgroup provide opportunities for new treatment approaches.

Chromosomal neighbourhoods allow identification of organ specific changes in gene expression

Although most genes share their chromosomal neighbourhood with other genes, distribution of genes has not been explored in the context of individual organ development; the common focus of developmental biology studies. Because developmental processes are often associated with initially subtle changes in gene expression, here we explored whether neighbouring genes are informative in the identification of differentially expressed genes. First, we quantified the chromosomal neighbourhood patterns of genes having related functional roles in the mammalian genome. Although the majority of protein coding genes have at least five neighbours within 1 Mb window around each gene, very few of these neighbours regulate development of the same organ. Analyses of transcriptomes of developing mouse molar teeth revealed that whereas expression of genes regulating tooth development changes, their neighbouring genes show no marked changes, irrespective of their level of expression. Finally, we test whether inclusion of gene neighbourhood in the analyses of differential expression could provide additional benefits. For the analyses, we developed an algorithm, called DELocal that identifies differentially expressed genes by comparing their expression changes to changes in adjacent genes in their chromosomal regions. Our results show that DELocal removes detection bias towards large changes in expression, thereby allowing identification of even subtle changes in development. Future studies, including the detection of differential expression, may benefit from, and further characterize the significance of gene-gene neighbour relationships.

Development of organs is typically associated with small and hard to detect changes in gene expression. Here we examined how often genes regulating specific organs are neighbours to each other in the genome, and whether this gene neighbourhood helps in the detection of changes in gene expression. We found that genes regulating individual organ development are very rarely close to each other in the mouse and human genomes. We built an algorithm, called DELocal, to detect changes in gene expression that incorporates information about neighbouring genes. Using transcriptomes of developing mouse molar teeth containing gene expression profiles of thousands of genes, we show how genes regulating tooth development are ranked high by DELocal even if their expression level changes are subtle. We propose that developmental biology studies can benefit from gene neighbourhood analyses in the detection of differential expression and identification of organ specific genes.

Transcriptome analysis of cadmium exposure in kidney fibroblast cells of the North Atlantic Right Whale (Eubalaena glacialis)

An 8X15k oligonucleotide microarray was developed consisting of 2334 Eubalaena glacialis probes and 2166 Tursiops truncatus probes and used to measure the effects, at transcriptomic level, of cadmium exposure in right whale kidney fibroblast cells. Cells were exposed to three concentrations (1 μM, 0.1 μM, and 0.01 μM) of cadmium chloride (CdCl₂) for three exposure times (1, 4, and 24 h). Cells exposed to 1 μM CdCl₂ for 4 h and 24 h showed upregulated genes involved in protection from metal toxicity and oxidative stress, protein renaturation, apoptosis inhibition, as well as several regulators of cellular processes. Downregulated genes represented a suite of functions including cell proliferation, transcription regulation, actin polymerization, and stress fiber synthesis. The collection of differentially expressed genes in this study support proposed mechanisms of cadmium-induced apoptosis such as ubiquitin proteasome system disruption, Ca²⁺ homeostasis interference, mitochondrial membrane potential collapse, reactive oxygen species (ROS) production, and cell cycle arrest. The results also have confirmed the right whale microarray as a reproducible tool in measuring differentiated gene expression that could be a valuable asset for transcriptome analysis of other baleen whales and potential health assessment protocols.

System-level analyses of keystone genes required for mammalian tooth development

When a null mutation of a gene causes a complete developmental arrest, the gene is typically considered essential for life. Yet, in most cases, null mutations have more subtle effects on the phenotype. Here we used the phenotypic severity of mutations as a tool to examine system‐level dynamics of gene expression. We classify genes required for the normal development of the mouse molar into different categories that range from essential to subtle modification of the phenotype. Collectively, we call these the developmental keystone genes. Transcriptome profiling using microarray and RNAseq analyses of patterning stage mouse molars show highly elevated expression levels for genes essential for the progression of tooth development, a result reminiscent of essential genes in single‐cell organisms. Elevated expression levels of progression genes were also detected in developing rat molars, suggesting evolutionary conservation of this system‐level dynamics. Single‐cell RNAseq analyses of developing mouse molars reveal that even though the size of the expression domain, measured in the number of cells, is the main driver of organ‐level expression, progression genes show high cell‐level transcript abundances. Progression genes are also upregulated within their pathways, which themselves are highly expressed. In contrast, a high proportion of the genes required for normal tooth patterning are secreted ligands that are expressed in fewer cells than their receptors and intracellular components. Overall, even though expression patterns of individual genes can be highly different, conserved system‐level principles of gene expression can be detected using phenotypically defined gene categories.

The phenotypic severity of mutations on mouse teeth is used to classify genes.

Genes essential for the progression of odontogenesis are highly expressed at the organ and cell level.

Many of the genes required for normal patterning are locally expressed ligands.

Genome-wide somatic copy number alteration analysis and database construction for cervical cancer

Cervical cancer is a common gynecological malignancy with high incidence and mortality. Somatic copy number alterations (CNAs) play an important role in identifying tumor suppressor genes and oncogenes and are a useful diagnostic indicator for many cancer types. However, the genomic landscape of CNAs in cervical cancer has not yet been comprehensively characterized. In the present study, we collected 974 cervical cancer samples from different data sources. All samples were analyzed by genomic arrays to obtain high-resolution CNAs. Focal genomic regions with CNA events and potential cancer driver genes were identified by GISTIC2.0. Meanwhile, we constructed a comprehensive cervical cancer database by PHP and self-written Perl and R scripts. In total, 54 recurrent regions of amplification and deletion were detected. Frequently altered tumor suppressor genes were found in these regions, including PIK3CA, ERBB2, EP300 and FBXW7. CNA hotspots and related enriched functional categories were also identified. The incidence of chromothripsis in cervical cancer was estimated to be 6.06%, and the chromosome pulverization hotspot regions were detected. Based on the curated data, we developed CNAdbCC (http://cailab.labshare.cn/CNAdbCC/), a comprehensive database for copy number alterations in cervical cancer. We provide a user-friendly Web interface for data mining and visualization. It is the most comprehensive public database devoted exclusively to genomic alterations in cervical cancer. These results extend our molecular understanding of cervical cancer. The database will enable researchers to explore specific CNA patterns in this lethal cancer and facilitate the discovery of therapeutic candidates.

A high-resolution 3D epigenomic map reveals insights into the creation of the prostate cancer transcriptome

To better understand the impact of chromatin structure on regulation of the prostate cancer transcriptome, we develop high-resolution chromatin interaction maps in normal and prostate cancer cells using in situ Hi-C. By combining the in situ Hi-C data with active and repressive histone marks, CTCF binding sites, nucleosome-depleted regions, and transcriptome profiling, we identify topologically associating domains (TADs) that change in size and epigenetic states between normal and prostate cancer cells. Moreover, we identify normal and prostate cancer-specific enhancer-promoter loops and involved transcription factors. For example, we show that FOXA1 is enriched in prostate cancer-specific enhancer-promoter loop anchors. We also find that the chromatin structure surrounding the androgen receptor (AR) locus is altered in the prostate cancer cells with many cancer-specific enhancer-promoter loops. This creation of 3D epigenomic maps enables a better understanding of prostate cancer biology and mechanisms of gene regulation.

In prostate cancer, chromatin structure can impact the transcriptome. Here, the authors develop high resolution chromatin interaction maps in prostate cancer cells using in situ Hi-C, revealing prostate cancer-specific TADs and enhancer-promoter loops surrounding the androgen receptor (AR) locus.

Differential Expression of DNA Repair Genes in Prognostically-Favorable versus Unfavorable Uveal Melanoma

Expression of DNA repair genes was studied in uveal melanoma (UM) in order to identify genes that may play a role in metastases formation. We searched for genes that are differentially expressed between tumors with a favorable and unfavorable prognosis. Gene-expression profiling was performed on 64 primary UM from the Leiden University Medical Center (LUMC), Leiden, The Netherlands. The expression of 121 genes encoding proteins involved in DNA repair pathways was analyzed: a total of 44 genes differed between disomy 3 and monosomy 3 tumors. Results were validated in a cohort from Genoa and Paris and the The Cancer Genome Atlas (TCGA) cohort. Expression of the PRKDC, WDR48, XPC, and BAP1 genes was significantly associated with clinical outcome after validation. PRKDC was highly expressed in metastasizing UM (p < 0.001), whereas WDR48, XPC, and BAP1 were lowly expressed (p < 0.001, p = 0.006, p = 0.003, respectively). Low expression of WDR48 and XPC was related to a large tumor diameter (p = 0.01 and p = 0.004, respectively), and a mixed/epithelioid cell type (p = 0.007 and p = 0.03, respectively). We conclude that the expression of WDR48, XPC, and BAP1 is significantly lower in UM with an unfavorable prognosis, while these tumors have a significantly higher expression of PRKDC. Pharmacological inhibition of DNA-PKcs resulted in decreased survival of UM cells. PRKDC may be involved in proliferation, invasion and metastasis of UM cells. Unraveling the role of DNA repair genes may enhance our understanding of UM biology and result in the identification of new therapeutic targets.

'Multi-omic' data analysis using O-miner

Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from '-omics' technologies. Created from a biologist's perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org.

Cytoskeletal transgelin 2 contributes to gender-dependent adipose tissue expandability and immune function

During adipogenesis, preadipocytes' cytoskeleton reorganizes in parallel with lipid accumulation. Failure to do so may impact the ability of adipose tissue (AT) to shift between lipid storage and mobilization. Here, we identify cytoskeletal transgelin 2 (TAGLN2) as a protein expressed in AT and associated with obesity and inflammation, being normalized upon weight loss. TAGLN2 was primarily found in the adipose stromovascular cell fraction, but inflammation, TGF-β, and estradiol also prompted increased expression in human adipocytes. Tagln2 knockdown revealed a key functional role, being required for proliferation and differentiation of fat cells, whereas transgenic mice overexpressing Tagln2 using the adipocyte protein 2 promoter disclosed remarkable sex-dependent variations, in which females displayed "healthy" obesity and hypertrophied adipocytes but preserved insulin sensitivity, and males exhibited physiologic changes suggestive of defective AT expandability, including increased number of small adipocytes, activation of immune cells, mitochondrial dysfunction, and impaired metabolism together with decreased insulin sensitivity. The metabolic relevance and sexual dimorphism of TAGLN2 was also outlined by genetic variants that may modulate its expression and are associated with obesity and the risk of ischemic heart disease in men. Collectively, current findings highlight the contribution of cytoskeletal TAGLN2 to the obese phenotype in a gender-dependent manner.-Ortega, F. J., Moreno-Navarrete, J. M., Mercader, J. M., Gómez-Serrano, M., García-Santos, E., Latorre, J., Lluch, A., Sabater, M., Caballano-Infantes, E., Guzmán, R., Macías-González, M., Buxo, M., Gironés, J., Vilallonga, R., Naon, D., Botas, P., Delgado, E., Corella, D., Burcelin, R., Frühbeck, G., Ricart, W., Simó, R., Castrillon-Rodríguez, I., Tinahones, F. J., Bosch, F., Vidal-Puig, A., Malagón, M. M., Peral, B., Zorzano, A., Fernández-Real, J. M. Cytoskeletal transgelin 2 contributes to gender-dependent adipose tissue expandability and immune function.

Contribution of epigenetic variation to adaptation in Arabidopsis

In plants, transgenerational inheritance of some epialleles has been demonstrated but it remains controversial whether epigenetic variation is subject to selection and contributes to adaptation. Simulating selection in a rapidly changing environment, we compare phenotypic traits and epigenetic variation between Arabidopsis thaliana populations grown for five generations under selection and their genetically nearly identical ancestors. Selected populations of two distinct genotypes show significant differences in flowering time and plant architecture, which are maintained for at least 2–3 generations in the absence of selection. While we cannot detect consistent genetic changes, we observe a reduction of epigenetic diversity and changes in the methylation state of about 50,000 cytosines, some of which are associated with phenotypic changes. Thus, we propose that epigenetic variation is subject to selection and can contribute to rapid adaptive responses, although the extent to which epigenetics plays a role in adaptation is still unclear.

Whether plant epigenetic variation is subject to selection and contributes to adaptation is under debate. Here, the authors compare DNA methylation and phenotypes of Arabidopsis lines subject to simulated selection and their nearly isogenic ancestors and provide evidence that epigenetic variation contributes to adaptive responses.

The Usage of Exon-Exon Splice Junctions for the Detection of Alternative Splicing using the REIDS model

Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes. Unfortunately, aberrant splicing events have been linked to genetic disorders. Therefore, understanding mechanisms of alternative splicing regulation and differences in splicing events between diseased and healthy tissues is crucial in advancing personalized medicine and drug developments. We propose a linear mixed model, Random Effects for the Identification of Differential Splicing (REIDS), for the identification of alternative splicing events using Human Transcriptome Arrays (HTA). For each exon, a splicing score is calculated based on two scores, an exon score and an array score. The junction information is used to rank the identified exons from strongly confident to less confident candidates for alternative splicing. The design of junctions was also discussed to highlight the complexity of exon-exon and exon-junction interactions. Based on a list of Rt-PCR validated probe sets, REIDS outperforms AltAnalyze and iGems in the % recall rate.

Copy Number Variation

Differences between genomes can be due to single nucleotide variants (SNPs), translocations, inversions and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 250 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease or phenotypic traits.While the link between SNPs and disease susceptibility has been well studied, to date there are still very few published CNV genome-wide association studies; probably owing to the fact that CNV analysis remains a slightly more complex task than SNP analysis (both in term of bioinformatics workflow and uncertainty in the CNV calling leading to high false positive rates and unknown false negative rates). This chapter aims at explaining computational methods for the analysis of CNVs, ranging from study design, data processing and quality control, up to genome-wide association study with clinical traits.

Triple Angiokinase Inhibitor Nintedanib Directly Inhibits Tumor Cell Growth and Induces Tumor Shrinkage via Blocking Oncogenic Receptor Tyrosine Kinases

The triple-angiokinase inhibitor nintedanib is an orally available, potent, and selective inhibitor of tumor angiogenesis by blocking the tyrosine kinase activities of vascular endothelial growth factor receptor (VEGFR) 1-3, platelet-derived growth factor receptor (PDGFR)-α and -β, and fibroblast growth factor receptor (FGFR) 1-3. Nintedanib has received regulatory approval as second-line treatment of adenocarcinoma non-small cell lung cancer (NSCLC), in combination with docetaxel. In addition, nintedanib has been approved for the treatment of idiopathic lung fibrosis. Here we report the results from a broad kinase screen that identified additional kinases as targets for nintedanib in the low nanomolar range. Several of these kinases are known to be mutated or overexpressed and are involved in tumor development (discoidin domain receptor family, member 1 and 2, tropomyosin receptor kinase A (TRKA) and C, rearranged during transfection proto-oncogene [RET proto oncogene]), as well as in fibrotic diseases (e.g., DDRs). In tumor cell lines displaying molecular alterations in potential nintedanib targets, the inhibitor demonstrates direct antiproliferative effects: in the NSCLC cell line NCI-H1703 carrying a PDGFRα amplification (ampl.); the gastric cancer cell line KatoIII and the breast cancer cell line MFM223, both driven by a FGFR2 amplification; AN3CA (endometrial carcinoma) bearing a mutated FGFR2; the acute myeloid leukemia cell lines MOLM-13 and MV-4-11-B with FLT3 mutations; and the NSCLC adenocarcinoma LC-2/ad harboring a CCDC6-RET fusion. Potent kinase inhibition does not, however, strictly translate into antiproliferative activity, as demonstrated in the TRKA-dependent cell lines CUTO-3 and KM-12. Importantly, nintedanib treatment of NCI-H1703 tumor xenografts triggered effective tumor shrinkage, indicating a direct effect on the tumor cells in addition to the antiangiogenic effect on the tumor stroma. These findings will be instructive in guiding future genome-based clinical trials of nintedanib.

Integrative analysis of genome-wide gene copy number changes and gene expression in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) represents a genomically unstable cancer type with extensive copy number aberrations. The relationship of gene copy number alterations and subsequent mRNA levels has only fragmentarily been described. The aim of this study was to conduct a genome-wide analysis of gene copy number gains and corresponding gene expression levels in a clinically well annotated NSCLC patient cohort (n = 190) and their association with survival. While more than half of all analyzed gene copy number-gene expression pairs showed statistically significant correlations (10,296 of 18,756 genes), high correlations, with a correlation coefficient >0.7, were obtained only in a subset of 301 genes (1.6%), including KRAS, EGFR and MDM2. Higher correlation coefficients were associated with higher copy number and expression levels. Strong correlations were frequently based on few tumors with high copy number gains and correspondingly increased mRNA expression. Among the highly correlating genes, GO groups associated with posttranslational protein modifications were particularly frequent, including ubiquitination and neddylation. In a meta-analysis including 1,779 patients we found that survival associated genes were overrepresented among highly correlating genes (61 of the 301 highly correlating genes, FDR adjusted p<0.05). Among them are the chaperone CCT2, the core complex protein NUP107 and the ubiquitination and neddylation associated protein CAND1. In conclusion, in a comprehensive analysis we described a distinct set of highly correlating genes. These genes were found to be overrepresented among survival-associated genes based on gene expression in a large collection of publicly available datasets.

A random effects model for the identification of differential splicing (REIDS) using exon and HTA arrays

Background

Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes. Unfortunately, aberrant splicing events do occur which have been linked to genetic disorders, such as several types of cancer and neurodegenerative diseases (Fan et al., Theor Biol Med Model 3:19, 2006). Therefore, understanding the mechanism of alternative splicing and identifying the difference in splicing events between diseased and healthy tissue is crucial in biomedical research with the potential of applications in personalized medicine as well as in drug development.

Results

We propose a linear mixed model, Random Effects for the Identification of Differential Splicing (REIDS), for the identification of alternative splicing events. Based on a set of scores, an exon score and an array score, a decision regarding alternative splicing can be made. The model enables the ability to distinguish a differential expressed gene from a differential spliced exon. The proposed model was applied to three case studies concerning both exon and HTA arrays.

Conclusion

The REIDS model provides a work flow for the identification of alternative splicing events relying on the established linear mixed model. The model can be applied to different types of arrays.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1687-8) contains supplementary material, which is available to authorized users.

Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

BACKGROUND

Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes.

METHODS

Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering.

RESULTS

Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed.

CONCLUSIONS

The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.

Upregulation of HLA Expression in Primary Uveal Melanoma by Infiltrating Leukocytes

Introduction

Uveal melanoma (UM) with an inflammatory phenotype, characterized by infiltrating leukocytes and increased human leukocyte antigen (HLA) expression, carry an increased risk of death due to metastases. These tumors should be ideal for T-cell based therapies, yet it is not clear why prognostically-infaust tumors have a high HLA expression. We set out to determine whether the level of HLA molecules in UM is associated with other genetic factors, HLA transcriptional regulators, or microenvironmental factors.

Methods

28 enucleated UM were used to study HLA class I and II expression, and several regulators of HLA by immunohistochemistry, PCR microarray, qPCR and chromosome SNP-array. Fresh tumor samples of eight primary UM and four metastases were compared to their corresponding xenograft in SCID mice, using a PCR microarray and SNP array.

Results

Increased expression levels of HLA class I and II showed no dosage effect of chromosome 6p, but, as expected, were associated with monosomy of chromosome 3. Increased HLA class I and II protein levels were positively associated with their gene expression and with raised levels of the peptide-loading gene TAP1, and HLA transcriptional regulators IRF1, IRF8, CIITA, and NLRC5, revealing a higher transcriptional activity in prognostically-bad tumors. Implantation of fresh human tumor samples into SCID mice led to a loss of infiltrating leukocytes, and to a decreased expression of HLA class I and II genes, and their regulators.

Conclusion

Our data provides evidence for a proper functioning HLA regulatory system in UM, offering a target for T-cell based therapies.

Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations

A three-dimensional chromatin state underpins the structural and functional basis of the genome by bringing regulatory elements and genes into close spatial proximity to ensure proper, cell-type–specific gene expression profiles. Here, we performed Hi-C chromosome conformation capture sequencing to investigate how three-dimensional chromatin organization is disrupted in the context of copy-number variation, long-range epigenetic remodeling, and atypical gene expression programs in prostate cancer. We find that cancer cells retain the ability to segment their genomes into megabase-sized topologically associated domains (TADs); however, these domains are generally smaller due to establishment of additional domain boundaries. Interestingly, a large proportion of the new cancer-specific domain boundaries occur at regions that display copy-number variation. Notably, a common deletion on 17p13.1 in prostate cancer spanning the TP53 tumor suppressor locus results in bifurcation of a single TAD into two distinct smaller TADs. Change in domain structure is also accompanied by novel cancer-specific chromatin interactions within the TADs that are enriched at regulatory elements such as enhancers, promoters, and insulators, and associated with alterations in gene expression. We also show that differential chromatin interactions across regulatory regions occur within long-range epigenetically activated or silenced regions of concordant gene activation or repression in prostate cancer. Finally, we present a novel visualization tool that enables integrated exploration of Hi-C interaction data, the transcriptome, and epigenome. This study provides new insights into the relationship between long-range epigenetic and genomic dysregulation and changes in higher-order chromatin interactions in cancer.

miR-17-92 fine-tunes MYC expression and function to ensure optimal B cell lymphoma growth

The synergism between c-MYC and miR-17-19b, a truncated version of the miR-17-92 cluster, is well-documented during tumor initiation. However, little is known about miR-17-19b function in established cancers. Here we investigate the role of miR-17-19b in c-MYC-driven lymphomas by integrating SILAC-based quantitative proteomics, transcriptomics and 3′ untranslated region (UTR) analysis upon miR-17-19b overexpression. We identify over one hundred miR-17-19b targets, of which 40% are co-regulated by c-MYC. Downregulation of a new miR-17/20 target, checkpoint kinase 2 (Chek2), increases the recruitment of HuR to c-MYC transcripts, resulting in the inhibition of c-MYC translation and thus interfering with in vivo tumor growth. Hence, in established lymphomas, miR-17-19b fine-tunes c-MYC activity through a tight control of its function and expression, ultimately ensuring cancer cell homeostasis. Our data highlight the plasticity of miRNA function, reflecting changes in the mRNA landscape and 3′ UTR shortening at different stages of tumorigenesis.

The synergism between c-MYC and miR-17-19b plays an important role in lymphoma initiation. In this study, the authors identify a panel of targets co-regulated by miR-17-19b and in MYC-driven lymphoma and unravel the molecular mechanism through which miR-17-19b inhibits MYC translation.

Semaphorin and plexin gene expression is altered in the prefrontal cortex of schizophrenia patients with and without auditory hallucinations

Auditory hallucinations (AH) are clinical hallmarks of schizophrenia, however little is known about molecular genetics of these symptoms. In this study, gene expression profiling of postmortem brain samples from prefrontal cortex of schizophrenic patients without AH (SNA), patients with AH (SA) and control subjects were compared. Genome-wide expression analysis was conducted using samples of three individuals of each group and the Affymetrix GeneChip Human-Gene 1.0 ST-Array. This analysis identified the Axon Guidance pathway as one of the most differentially expressed network among SNA, SA and CNT. To confirm the transcriptome results, mRNA level quantification of seventeen genes involved in this pathway was performed in a larger sample. PLXNB1, SEMA3A, SEMA4D and SEM6C were upregulated in SNA or SA patients compared to controls. PLXNA1 and SEMA3D showed down-regulation in their expression in the patient's samples, but differences remained statistically significant between the SNA patients and controls. Differences between SNA and SA were found in PLXNB1 expression which is decreased in SA patients. This study strengthens the contribution of brain plasticity in pathophysiology of schizophrenia and shows that non-hallucinatory patients present more alterations in frontal regions than patients with hallucinations concerning neural plasticity.

Cytomegalovirus Immediate-Early Proteins Promote Stemness Properties in Glioblastoma

Glioblastoma (GBM) is the most common and aggressive human brain tumor. Human cytomegalovirus (HCMV) immediate-early (IE) proteins that are endogenously expressed in GBM cells are strong viral transactivators with oncogenic properties. Here, we show how HCMV IEs are preferentially expressed in glioma stem-like cells (GSC), where they colocalize with the other GBM stemness markers, CD133, Nestin, and Sox2. In patient-derived GSCs that are endogenously infected with HCMV, attenuating IE expression by an RNAi-based strategy was sufficient to inhibit tumorsphere formation, Sox2 expression, cell-cycle progression, and cell survival. Conversely, HCMV infection of HMCV-negative GSCs elicited robust self-renewal and proliferation of cells that could be partially reversed by IE attenuation. In HCMV-positive GSCs, IE attenuation induced a molecular program characterized by enhanced expression of mesenchymal markers and proinflammatory cytokines, resembling the therapeutically resistant GBM phenotype. Mechanistically, HCMV/IE regulation of Sox2 occurred via inhibition of miR-145, a negative regulator of Sox2 protein expression. In a spontaneous mouse model of glioma, ectopic expression of the IE1 gene (UL123) specifically increased Sox2 and Nestin levels in the IE1-positive tumors, upregulating stemness and proliferation markers in vivo. Similarly, human GSCs infected with the HCMV strain Towne but not the IE1-deficient strain CR208 showed enhanced growth as tumorspheres and intracranial tumor xenografts, compared with mock-infected human GSCs. Overall, our findings offer new mechanistic insights into how HCMV/IE control stemness properties in GBM cells.

Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

BACKGROUND

Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics.

RESULTS

These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses.

CONCLUSION

This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.

Overexpression of FGFR2 contributes to inherent resistance to MET inhibitors in MET-amplified patient-derived gastric cancer xenografts

Gastric cancer is one of the most malignant diseases and one of the leading causes of cancer-associated mortality worldwide. Although advances have been made in surgical techniques, perioperative management and the combined use of surgery with chemotherapy and/or radiotherapy, patients with advanced stage gastric cancer continue to face poor outcomes. Furthermore, it was reported that MET gene amplification and overexpression predicted the sensitivity to MET inhibitors in gastric cancer. However, the identification of drug-resistant tumors has encouraged the pre-emptive elucidation of the possible mechanisms of clinical resistance. The current study assessed a number of patient-derived gastric cancer models with MET amplification and overexpression, including CNGAS028. The tumor tissues were subjected to microarray analysis (using single nucleotide polymorphism 6.0 and human genome U133 arrays) followed by western blotting. The results demonstrated that CNGAS028 xenograft tumors did not respond to treatment with a selective MET inhibitor. Additional analysis indicated that FGFR2 overexpression contributed to the resistance to MET inhibitors. Furthermore, treatment with a combination of fibroblast growth factor receptor 2 and MET inhibitors inhibited the growth of CNGAS028 xenograft tumors in vivo. In conclusion, the current results aid in understanding the mechanism of inherent resistance to selective MET inhibitors as well as provide important information for patient selection and clinical treatment strategies.

Robust BRCA1-like classification of copy number profiles of samples repeated across different datasets and platforms

Breast cancers with BRCA1 germline mutation have a characteristic DNA copy number (CN) pattern. We developed a test that assigns CN profiles to be 'BRCA1-like' or 'non-BRCA1-like', which refers to resembling a BRCA1-mutated tumor or resembling a tumor without a BRCA1 mutation, respectively. Approximately one third of the BRCA1-like breast cancers have a BRCA1 mutation, one third has hypermethylation of the BRCA1 promoter and one third has an unknown reason for being BRCA1-like. This classification is indicative of patients' response to high dose alkylating and platinum containing chemotherapy regimens, which targets the inability of BRCA1 deficient cells to repair DNA double strand breaks. We investigated whether this classification can be reliably obtained with next generation sequencing and copy number platforms other than the bacterial artificial chromosome (BAC) array Comparative Genomic Hybridization (aCGH) on which it was originally developed. We investigated samples from 230 breast cancer patients for which a CN profile had been generated on two to five platforms, comprising low coverage CN sequencing, CN extraction from targeted sequencing panels (CopywriteR), Affymetrix SNP6.0, 135K/720K oligonucleotide aCGH, Affymetrix Oncoscan FFPE (MIP) technology, 3K BAC and 32K BAC aCGH. Pairwise comparison of genomic position-mapped profiles from the original aCGH platform and other platforms revealed concordance. For most cases, biological differences between samples exceeded the differences between platforms within one sample. We observed the same classification across different platforms in over 80% of the patients and kappa values of at least 0.36. Differential classification could be attributed to CN profiles that were not strongly associated to one class. In conclusion, we have shown that the genomic regions that define our BRCA1-like classifier are robustly measured by different CN profiling technologies, providing the possibility to retro- and prospectively investigate BRCA1-like classification across a wide range of CN platforms.

Family-Based Benchmarking of Copy Number Variation Detection Software

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

Identifying Human Genome-Wide CNV, LOH and UPD by Targeted Sequencing of Selected Regions

Copy-number variations (CNV), loss of heterozygosity (LOH), and uniparental disomy (UPD) are large genomic aberrations leading to many common inherited diseases, cancers, and other complex diseases. An integrated tool to identify these aberrations is essential in understanding diseases and in designing clinical interventions. Previous discovery methods based on whole-genome sequencing (WGS) require very high depth of coverage on the whole genome scale, and are cost-wise inefficient. Another approach, whole exome genome sequencing (WEGS), is limited to discovering variations within exons. Thus, we are lacking efficient methods to detect genomic aberrations on the whole genome scale using next-generation sequencing technology. Here we present a method to identify genome-wide CNV, LOH and UPD for the human genome via selectively sequencing a small portion of genome termed Selected Target Regions (SeTRs). In our experiments, the SeTRs are covered by 99.73%~99.95% with sufficient depth. Our developed bioinformatics pipeline calls genome-wide CNVs with high confidence, revealing 8 credible events of LOH and 3 UPD events larger than 5M from 15 individual samples. We demonstrate that genome-wide CNV, LOH and UPD can be detected using a cost-effective SeTRs sequencing approach, and that LOH and UPD can be identified using just a sample grouping technique, without using a matched sample or familial information.

Genetic Analysis of Substrain Divergence in Non-Obese Diabetic (NOD) Mice

The non-obese diabetic (NOD) mouse is a polygenic model for type 1 diabetes that is characterized by insulitis, a leukocytic infiltration of the pancreatic islets. During ~35 years since the original inbred strain was developed in Japan, NOD substrains have been established at different laboratories around the world. Although environmental differences among NOD colonies capable of impacting diabetes incidence have been recognized, differences arising from genetic divergence have not been analyzed previously. We use both mouse diversity array and whole-exome capture sequencing platforms to identify genetic differences distinguishing five NOD substrains. We describe 64 single-nucleotide polymorphisms, and two short indels that differ in coding regions of the five NOD substrains. A 100-kb deletion on Chromosome 3 distinguishes NOD/ShiLtJ and NOD/ShiLtDvs from three other substrains, whereas a 111-kb deletion in the Icam2 gene on Chromosome 11 is unique to the NOD/ShiLtDvs genome. The extent of genetic divergence for NOD substrains is compared with similar studies for C57BL6 and BALB/c substrains. As mutations are fixed to homozygosity by continued inbreeding, significant differences in substrain phenotypes are to be expected. These results emphasize the importance of using embryo freezing methods to minimize genetic drift within substrains and of applying appropriate genetic nomenclature to permit substrain recognition when one is used.

Mayer-Rokitansky-Küster-Hauser syndrome discordance in monozygotic twins: matrix metalloproteinase 14, low-density lipoprotein receptor-related protein 10, extracellular matrix, and neoangiogenesis genes identified as candidate genes in a tissue-specific mosaicism

OBJECTIVE

To find a potential underlying cause for Mayer-Rokitansky-Küster-Hauser syndrome (MRKHS) discordance in monozygotic twins.

DESIGN

Prospective comparative study.

SETTING

University hospital.

PATIENT(S)

Our study genetically analyzed 5 MRKHS-discordant monozygotic twin pairs with the unique opportunity to include saliva and rudimentary uterine tissue.

INTERVENTION(S)

Blood, saliva, or rudimentary uterine tissue from five MRKHS-discordant twins was analyzed and compared between twin pairs as well as within the same individual where applicable. We used copy number variations (CNVs) to identify differences.

MAIN OUTCOME MEASURE(S)

CNVs in blood, rudimentary uterine tissue, and saliva, network analysis, and review of the literature.

RESULT(S)

One duplication found in the affected twin included two genes, matrix metalloproteinase 14 (MMP14) and low-density lipoprotein receptor-related protein 10 (LRP10), which have known functions in the embryonic development of the uterus and endometrium. The duplicated region was detected in rudimentary uterine tissue from the same individual but not in saliva, making a tissue-specific mosaicism a possible explanation for twin discordance. Additional network analysis revealed important connections to differentially expressed genes from previous studies. These genes encode several molecules involved in extracellular matrix (ECM) remodeling and neoangiogenesis.

CONCLUSION(S)

MMP-14, LRP-10, ECM, and neoangiogenesis genes are identified as candidate genes in a tissue-specific mosaicism. The detected clusters provide evidence of deficient vascularization during uterine development and/or disturbed reorganization of ECM components, potentially during müllerian duct elongation signaled by the embryologically relevant phosphatidylinositol 3-kinase/protein kinase B pathway. Therefore, we consider these genes to be new candidates in the manifestation of MRKHS.

Stable phenotype of B-cell subsets following cryopreservation and thawing of normal human lymphocytes stored in a tissue biobank

BACKGROUND

Cryopreservation is an acknowledged procedure to store vital cells for future biomarker analyses. Few studies, however, have analyzed the impact of the cryopreservation on phenotyping.

METHODS

We have performed a controlled comparison of cryopreserved and fresh cellular aliquots prepared from individual healthy donors. We studied circulating B-cell subset membrane markers and global gene expression, respectively by multiparametric flow cytometry and microarray data. Extensive statistical analysis of the generated data tested the concept that "overall, there are no phenotypic differences between cryopreserved and fresh B-cell subsets." Subsequently, we performed an uncontrolled comparison of tonsil tissue samples.

RESULTS

By multiparametric flow analysis, we documented no significant changes following cryopreservation of subset frequencies or membrane intensity for the differentiation markers CD19, CD20, CD22, CD27, CD38, CD45, and CD200. By gene expression profiling following cryopreservation, across all samples, only 16 out of 18708 genes were significantly up or down regulated, including FOSB, KLF4, RBP7, ANXA1 or CLC, DEFA3, respectively. Implementation of cryopreserved tissue in our research program allowed us to present a performance analysis, by comparing cryopreserved and fresh tonsil tissue. As expected, phenotypic differences were identified, but to an extent that did not affect the performance of the cryopreserved tissue to generate specific B-cell subset associated gene signatures and assign subset phenotypes to independent tissue samples.

CONCLUSIONS

We have confirmed our working concept and illustrated the usefulness of vital cryopreserved cell suspensions for phenotypic studies of the normal B-cell hierarchy; however, storage procedures need to be delineated by tissue-specific comparative analysis.

Prognostic parameters in uveal melanoma and their association with BAP1 expression

AIM

To determine whether BAP1 gene and protein expression associates with different prognostic parameters in uveal melanoma and whether BAP1 expression correctly identifies patients as being at risk for metastases, following enucleation of the primary tumour.

METHODS

Thirty cases of uveal melanoma obtained by enucleation between 1999 and 2004 were analysed for a variety of prognostic markers, including histological characteristics, chromosome aberrations obtained by fluorescence in situ hybridisation (FISH) and single nucleotide polymorphism (SNP) analysis and gene expression profiling. These parameters were compared with BAP1 gene expression and BAP1 immunostaining.

RESULTS

The presence of monosomy of chromosome 3 as identified by the different chromosome 3 tests showed significantly increased HRs (FISH on isolated nuclei cut-off 30%: HR 11.6, p=0.002; SNP analysis: HR 20.3, p=0.004) for death due to metastasis. The gene expression profile class 2, based on the 15-gene expression profile, similarly provided a significantly increased HR for a poor outcome (HR 8.5, p=0.005). Lower BAP1 gene expression and negative BAP1 immunostaining (50% of 28 tumours were immunonegative) were both associated with these markers for prognostication: FISH cut-off 30% monosomy 3 (BAP1 gene expression: p=0.037; BAP1 immunostaining: p=0.001), SNP-monosomy 3 (BAP1 gene expression: p=0.008; BAP1 immunostaining: p=0.002) and class 2 profile (BAP1 gene expression: p<0.001; BAP1 immunostaining: p=0.001) and were themselves associated with an increased risk of death due to metastasis (BAP1 gene expression dichotomised: HR 8.7, p=0.006; BAP1 immunostaining: HR 4.0, p=0.010).

CONCLUSIONS

Loss of BAP1 expression associated well with all of the methods currently used for prognostication and was itself predictive of death due to metastasis in uveal melanoma after enucleation, thereby emphasising the importance of further research on the role of BAP1 in uveal melanoma.

Comprehensive study of tumour single nucleotide polymorphism array data reveals significant driver aberrations and disrupted signalling pathways in human hepatocellular cancer

The authors describe an integrated method for analysing cancer driver aberrations and disrupted pathways by using tumour single nucleotide polymorphism (SNP) arrays. The authors new method adopts a novel statistical model to explicitly quantify the SNP signals, and therefore infers the genomic aberrations, including copy number alteration and loss of heterozygosity. Examination on the dilution series dataset shows that this method can correctly identify the genomic aberrations even with the existence of severe normal cell contamination in tumour sample. Furthermore, with the results of the aberration identification obtained from multiple tumour samples, a permutation-based approach is proposed for identifying the statistically significant driver aberrations, which are further incorporated with the known signalling pathways for pathway enrichment analysis. By applying the approach to 286 hepatocellular tumour samples, they successfully uncover numerous driver aberration regions across the cancer genome, for example, chromosomes 4p and 5q, which harbour many known hepatocellular cancer related genes such as alpha-fetoprotein (AFP) and ectodermal-neural cortex (ENC1). In addition, they identify nine disrupted pathways that are highly enriched by the driver aberrations, including the systemic lupus erythematosus pathway, the vascular endothelial growth factor (VEGF) signalling pathway and so on. These results support the feasibility and the utility of the proposed method on the characterisation of the cancer genome and the downstream analysis of the driver aberrations and the disrupted signalling pathways.

Immunological visibility: posttranscriptional regulation of human NKG2D ligands by the EGF receptor pathway

Human cytolytic T lymphocytes and natural killer cells can limit tumor growth and are being increasingly harnessed for tumor immunotherapy. One way cytolytic lymphocytes recognize tumor cells is by engagement of their activating receptor, NKG2D, by stress antigens of the MICA/B and ULBP families. This study shows that surface up-regulation of NKG2D ligands by human epithelial cells in response to ultraviolet irradiation, osmotic shock, oxidative stress, and growth factor provision is attributable to activation of the epidermal growth factor receptor (EGFR). EGFR activation causes intracellular relocalization of AUF1 proteins that ordinarily destabilize NKG2D ligand mRNAs by targeting an AU-rich element conserved within the 3' ends of most human, but not murine, NKG2D ligand genes. Consistent with these findings, NKG2D ligand expression by primary human carcinomas positively correlated with EGFR expression, which is commonly hyperactivated in such tumors, and was reduced by clinical EGFR inhibitors. Therefore, stress-induced activation of EGFR not only regulates cell growth but also concomitantly regulates the cells' immunological visibility. Thus, therapeutics designed to limit cancer cell growth should also be considered in terms of their impact on immunosurveillance.

Identifying associations between genomic alterations in tumors

Single-nucleotide polymorphism (SNP) mapping arrays are a reliable method for identifying somatic copy number alterations in cancer samples. Though this is immensely useful to identify potential driver genes, it is not sufficient to identify genes acting in a concerted manner. In cancer cells, co-amplified genes have been shown to provide synergistic effects, and genomic alterations targeting a pathway have been shown to occur in a mutually exclusive manner. We therefore developed a bioinformatic method for detecting such gene pairs using an integrated analysis of genomic copy number and gene expression data. This approach allowed us to identify a gene pair that is co-amplified and co-expressed in high-grade serous ovarian cancer. This finding provided information about the interaction of specific genetic events that contribute to the development and progression of this disease.

Integrated genomic analysis of triple-negative breast cancers reveals novel microRNAs associated with clinical and molecular phenotypes and sheds light on the pathways they control

Background

This study focuses on the analysis of miRNAs expression data in a cohort of 181 well characterised breast cancer samples composed primarily of triple-negative (ER/PR/HER2-negative) tumours with associated genome-wide DNA and mRNA data, extensive patient follow-up and pathological information.

Results

We identified 7 miRNAs associated with prognosis in the triple-negative tumours and an additional 7 when the analysis was extended to the set of all ER-negative cases. miRNAs linked to an unfavourable prognosis were associated with a broad spectrum of motility mechanisms involved in the invasion of stromal tissues, such as cell-adhesion, growth factor-mediated signalling pathways, interaction with the extracellular matrix and cytoskeleton remodelling. When we compared different intrinsic molecular subtypes we found 46 miRNAs that were specifically expressed in one or more intrinsic subtypes. Integrated genomic analyses indicated these miRNAs to be influenced by DNA genomic aberrations and to have an overall influence on the expression levels of their predicted targets. Among others, our analyses highlighted the role of miR-17-92 and miR-106b-25, two polycistronic miRNA clusters with known oncogenic functions. We showed that their basal-like subtype specific up-regulation is influenced by increased DNA copy number and contributes to the transcriptional phenotype as well as the activation of oncogenic pathways in basal-like tumours.

Conclusions

This study analyses previously unreported miRNA, mRNA and DNA data and integrates these with pathological and clinical information, from a well-annotated cohort of breast cancers enriched for triple-negative subtypes. It provides a conceptual framework, as well as integrative methods and system-level results and contributes to elucidate the role of miRNAs as biomarkers and modulators of oncogenic processes in these types of tumours.

Integrative analysis of prostate cancer aggressiveness

BACKGROUND

Clinical management of prostate cancer (PC) is still highly demanding on the identification of robust biomarkers which will allow a more precise prediction of disease progression.

METHODS

We profiled both mRNA expression and DNA copy number alterations (CNAs) from laser capture microdissected cells from 31 PC patients and 17 patients with benign prostatic hyperplasia using Affymetrix GeneChip® technology. PC patients were subdivided into an aggressive (Gleason Score 8 or higher, and/or T3/T4 and/or N+/M+) and non-aggressive (all others) form of PC. Furthermore, we correlated the two datasets, as genes whose varied expression is due to a chromosomal alteration, may suggest a causal implication of these genes in the disease. All statistical analyses were performed in R version 2.15.0 and Bioconductor version 1.8.1., respectively.

RESULTS

We confirmed several common altered chromosomal regions as well as recently discovered loci such as deletions on chromosomes 3p14.1-3p13 and 13q13.3-13q14.11 supporting a possible role for RYBP, RGC32, and ELF1 in tumor suppression. Integrative analysis of expression and CN data combined with data retrieved from online databases propose PTP4A3 and ELF1 as possible factors for tumor progression.

CONCLUSIONS

Copy number data analysis revealed some significant differences between aggressive and non-aggressive tumors, while gene expression data alone could not define an aggressive group of patients. The assessment of CNA may have diagnostic and prognostic value in PC.

The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation

Differences between genomes can be due to single nucleotide variants, translocations, inversions, and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 500 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease. Hence there is a need for better-tailored and more robust tools for the detection and genome-wide analyses of CNVs. While a link between a given CNV and a disease may have often been established, the relative CNV contribution to disease progression and impact on drug response is not necessarily understood. In this review we discuss the progress, challenges, and limitations that occur at different stages of CNV analysis from the detection (using DNA microarrays and next-generation sequencing) and identification of recurrent CNVs to the association with phenotypes. We emphasize the importance of germline CNVs and propose strategies to aid clinicians to better interpret structural variations and assess their clinical implications.

The mutational landscape of adenoid cystic carcinoma

Adenoid cystic carcinomas (ACCs) are among the most enigmatic of human malignancies. These aggressive salivary cancers frequently recur and metastasize despite definitive treatment, with no known effective chemotherapy regimen. Here, we determined the ACC mutational landscape and report the exome or whole genome sequences of 60 ACC tumor/normal pairs. These analyses revealed a low exonic somatic mutation rate (0.31 non-silent events/megabase) and wide mutational diversity. Interestingly, mutations selectively involved chromatin state regulators, such as SMARCA2, CREBBP, and KDM6A, suggesting aberrant epigenetic regulation in ACC oncogenesis. Mutations in genes central to DNA damage and protein kinase A signaling also implicate these processes. We observed MYB-NFIB translocations and somatic mutations in MYB-associated genes, solidifying these aberrations as critical events. Lastly, we identified recurrent mutations in the FGF/IGF/PI3K pathway that may potentially offer new avenues for therapy (30%). Collectively, our observations establish a molecular foundation for understanding and exploring new treatments for ACC.

Functional analysis-make or break for cancer predictability

Copy number variations (CNVs) encompass a variety of genetic alterations including deletions and amplifications and cluster in regions of the human genome with intrinsic instability. Small-sized CNVs can act as initial genetic changes giving rise to larger CNVs such as acquired somatic copy number aberrations (CNAs) promoting cancer formation. Previous studies provided evidence for CNVs as an underlying cause of elevated breast cancer risk when targeting breast cancer susceptibility genes and of accelerated breast cancer progression when targeting oncogenes. With the development of novel techniques for genome-wide detection of CNVs at increasingly higher resolution, it became possible to qualitatively and quantitatively analyse manifestation of DNA damage resulting from defects in any of the large variety of DNA double-strand break (DSB) repair mechanisms. Breast carcinogenesis, particularly in familial cases, has been linked with a defect in the homologous recombination (HR) pathway, which in turn switches damage removal towards alternative, more error-prone DSB repair pathways such as microhomology-mediated non-homologous end joining (mmNHEJ). Indeed, increased error-prone DSB repair activities were detected in peripheral blood lymphocytes from individuals with familial breast cancer risk independently of specific gene mutations. Intriguingly, sequence analysis of breakpoint regions revealed that the majority of genome aberrations found in breast cancer specimens are formed by mmNHEJ. Detection of pathway-specific error-prone DSB repair activities by functional testing was proposed to serve as biomarker for hereditary breast cancer risk and responsiveness to therapies targeting HR dysfunction. Identification of specific error-prone DSB repair mechanisms underlying CNAs and ultimately mammary tumour formation highlights potential targets for future breast cancer prevention regimens.

Distinguishing somatic and germline copy number events in cancer patient DNA hybridized to whole-genome SNP genotyping arrays

Chromosomal aneuploidy and segmental copy number changes are common genomic aberrations in -cancer. Copy number alterations (CNAs) arise from deletions, insertions, or duplications resulting in -chromosomal aberrations and aneuploidy. Genomes of normal cells also exhibit variable copy number called germline copy number variants (CNVs). CNVs in the general population tend to confound interpretation of predictions when attempting to extract relevant driver somatic events in cancer. In large studies of CNAs in cancer patients, it becomes necessary to accurately identify and separate CNAs and CNVs so as to prioritize candidate tumor suppressors and oncogenes. We have developed a probabilistic approach, HMM-Dosage, for segmenting and distinguishing CNAs and CNVs as separate, discrete events in cancer SNP genotyping array data. We outline the steps and computer code for the analysis of whole-genome cancer DNA hybridized to SNP genotyping arrays, focusing on distinguishing somatic CNA and germline CNVs, and describe the combined approach of HMM-Dosage for probabilistic inference and classification of somatic and germline copy number changes.

Copy number variation signature to predict human ancestry

BACKGROUND

Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype.

RESULTS

We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry.

CONCLUSIONS

We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case-control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response.

STA1, an Arabidopsis pre-mRNA processing factor 6 homolog, is a new player involved in miRNA biogenesis

MicroRNAs (miRNAs) are small regulatory RNAs that have important regulatory roles in numerous developmental and metabolic processes in most eukaryotes. In Arabidopsis, DICER-LIKE1 (DCL1), HYPONASTIC LEAVES 1, SERRATE, HUA ENHANCER1 and HASTY are involved in processing of primary miRNAs (pri-miRNAs) to yield precursor miRNAs (pre-miRNAs) and eventually miRNAs. In addition to these components, mRNA cap-binding proteins, CBP80/ABA HYPERSENSITIVE1 and CBP20, also participate in miRNA biogenesis. Here, we show that STABILIZED1 (STA1), an Arabidopsis pre-mRNA processing factor 6 homolog, is also involved in the biogenesis of miRNAs. Similar to other miRNA biogenesis-defective mutants, sta1-1 accumulated significantly lower levels of mature miRNAs and concurrently higher levels of pri-miRNAs than wild type. The dramatic reductions of mature miRNAs were associated with the accumulation of their target gene transcripts and developmental defects. Furthermore, sta1-1 impaired splicing of intron containing pri-miRNAs and decreased transcript levels of DCL1. These results suggest that STA1 is involved in miRNA biogenesis directly by functioning in pri-miRNA splicing and indirectly by modulating the DCL1 transcript level.

High-resolution genomic profiling of chronic lymphocytic leukemia reveals new recurrent genomic alterations

To identify genomic alterations in chronic lymphocytic leukemia (CLL), we performed single-nucleotide polymorphism–array analysis using Affymetrix Version 6.0 on 353 samples from untreated patients entered in the CLL8 treatment trial. Based on paired-sample analysis (n = 144), a mean of 1.8 copy number alterations per patient were identified; approximately 60% of patients carried no copy number alterations other than those detected by fluorescence in situ hybridization analysis. Copy-neutral loss-of-heterozygosity was detected in 6% of CLL patients and was found most frequently on 13q, 17p, and 11q. Minimally deleted regions were refined on 13q14 (deleted in 61% of patients) to the DLEU1 and DLEU2 genes, on 11q22.3 (27% of patients) to ATM, on 2p16.1-2p15 (gained in 7% of patients) to a 1.9-Mb fragment containing 9 genes, and on 8q24.21 (5% of patients) to a segment 486 kb proximal to the MYC locus. 13q deletions exhibited proximal and distal breakpoint cluster regions. Among the most common novel lesions were deletions at 15q15.1 (4% of patients), with the smallest deletion (70.48 kb) found in the MGA locus. Sequence analysis of MGA in 59 samples revealed a truncating mutation in one CLL patient lacking a 15q deletion. MNT at 17p13.3, which in addition to MGA and MYC encodes for the network of MAX-interacting proteins, was also deleted recurrently.

High-resolution genomic profiling reveals clonal evolution and competition in gastrointestinal marginal zone B-cell lymphoma and its large cell variant

We studied marginal zone B-cell lymphomas of the gastrointestinal tract including seven small cell lymphomas, eight large cell areas of composite lymphomas and 13 large cell variants using SNP array profiling. We found an increase of genomic complexity with lymphoma progression from small to large cytology, and identified gains of prominent (proto) oncogenes such as REL, BCL11A, ETS1, PTPN1, PTEN and KRAS which were found exclusively in the large cell variants. Copy numbers of ADAM3A, SCAPER and SIRPB1 were varying between the three different modes of presentation, hence suggestive for aberrations associated with progression from small to large cell lymphoma. The number of aberrations was slightly higher in the large cell part of composite lymphomas than in large cell lymphomas, suggesting that clonal selection takes place and that composite lymphomas are in a transition state. To further investigate this, we comparatively analyzed samples of two morphologically different regions of the same small cell tumor with a BIRC3-MALT1 translocation, as well as material acquired at two different time points from one composite lymphoma. We found genomic heterogeneity in both cases, supporting the theory of competing subclones in the evolution and progression of extranodal marginal zone B-cell lymphoma.

Getting DNA copy numbers without control samples

Background

The selection of the reference to scale the data in a copy number analysis has paramount importance to achieve accurate estimates. Usually this reference is generated using control samples included in the study. However, these control samples are not always available and in these cases, an artificial reference must be created. A proper generation of this signal is crucial in terms of both noise and bias.

We propose NSA (Normality Search Algorithm), a scaling method that works with and without control samples. It is based on the assumption that genomic regions enriched in SNPs with identical copy numbers in both alleles are likely to be normal. These normal regions are predicted for each sample individually and used to calculate the final reference signal. NSA can be applied to any CN data regardless the microarray technology and preprocessing method. It also finds an optimal weighting of the samples minimizing possible batch effects.

Results

Five human datasets (a subset of HapMap samples, Glioblastoma Multiforme (GBM), Ovarian, Prostate and Lung Cancer experiments) have been analyzed. It is shown that using only tumoral samples, NSA is able to remove the bias in the copy number estimation, to reduce the noise and therefore, to increase the ability to detect copy number aberrations (CNAs). These improvements allow NSA to also detect recurrent aberrations more accurately than other state of the art methods.

Conclusions

NSA provides a robust and accurate reference for scaling probe signals data to CN values without the need of control samples. It minimizes the problems of bias, noise and batch effects in the estimation of CNs. Therefore, NSA scaling approach helps to better detect recurrent CNAs than current methods. The automatic selection of references makes it useful to perform bulk analysis of many GEO or ArrayExpress experiments without the need of developing a parser to find the normal samples or possible batches within the data. The method is available in the open-source R package NSA, which is an add-on to the aroma.cn framework. http://www.aroma-project.org/addons.