Links between melanoma germline risk loci, driver genes and comorbidities: insight from a tissue-specific multi-omic analysis.

Genome-wide association studies (GWAS) have associated 76 loci with the risk of developing melanoma. However, understanding the molecular basis of such associations has remained a challenge because most of these loci are in non-coding regions of the genome. Here, we integrated data on epigenomic markers, three-dimensional (3D) genome organization, and expression quantitative trait loci (eQTL) from melanoma-relevant tissues and cell types to gain novel insights into the mechanisms underlying melanoma risk. This integrative approach revealed a total of 151 target genes, both near and far away from the risk loci in linear sequence, with known and novel roles in the etiology of melanoma. Using protein-protein interaction networks, we identified proteins that interact-directly or indirectly-with the products of the target genes. The interacting proteins were enriched for known melanoma driver genes. Further integration of these target genes into tissue-specific gene regulatory networks revealed patterns of gene regulation that connect melanoma to its comorbidities. Our study provides novel insights into the biological implications of genetic variants associated with melanoma risk.

Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis.

BACKGROUND: There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression. MAIN BODY: We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data. CONCLUSION: We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer.

Genetic variation as a long-distance modulator of RAD21 expression in humans.

Somatic mutations and changes in expression of RAD21 are common in many types of cancer. Moreover, sub-optimal levels of RAD21 expression in early development can result in cohesinopathies. Altered RAD21 levels can result directly from mutations in the RAD21 gene. However, whether DNA variants outside of the RAD21 gene could control its expression and thereby contribute to cancer and developmental disease is unknown. In this study, we searched for genomic variants that modify RAD21expression to determine their potential to contribute to development or cancer by RAD21 dysregulation. We searched 42,953,834 genomic variants for a spatial-eQTL association with the transcription of RAD21. We identified 123 significant associations (FDR < 0.05), which are local (cis) or long-distance (trans) regulators of RAD21 expression. The 123 variants co-regulate a further seven genes (AARD, AKAP11, GRID1, KCNIP4, RCN1, TRIOBP, and USP32), enriched for having Sp2 transcription factor binding sites in their promoter regions. The Sp2 transcription factor and six of the seven genes had previously been associated with cancer onset, progression, and metastasis. Our results suggest that genome-wide variation in non-coding regions impacts on RAD21 transcript levels in addition to other genes, which then could impact on oncogenesis and the process of ubiquitination. This identification of distant co-regulation of oncogenes represents a strategy for discovery of novel genetic regions influencing cancer onset and a potential for diagnostics.

Unravelling the Shared Genetic Mechanisms Underlying 18 Autoimmune Diseases Using a Systems Approach.

Autoimmune diseases (AiDs) are complex heterogeneous diseases characterized by hyperactive immune responses against self. Genome-wide association studies have identified thousands of single nucleotide polymorphisms (SNPs) associated with several AiDs. While these studies have identified a handful of pleiotropic loci that confer risk to multiple AiDs, they lack the power to detect shared genetic factors residing outside of these loci. Here, we integrated chromatin contact, expression quantitative trait loci and protein-protein interaction (PPI) data to identify genes that are regulated by both pleiotropic and non-pleiotropic SNPs. The PPI analysis revealed complex interactions between the shared and disease-specific genes. Furthermore, pathway enrichment analysis demonstrated that the shared genes co-occur with disease-specific genes within the same biological pathways. In conclusion, our results are consistent with the hypothesis that genetic risk loci associated with multiple AiDs converge on a core set of biological processes that potentially contribute to the emergence of polyautoimmunity.

Transcriptional Regulation of RUNX1: An Informatics Analysis.

The RUNX1/AML1 gene encodes a developmental transcription factor that is an important regulator of haematopoiesis in vertebrates. Genetic disruptions to the RUNX1 gene are frequently associated with acute myeloid leukaemia. Gene regulatory elements (REs), such as enhancers located in non-coding DNA, are likely to be important for Runx1 transcription. Non-coding elements that modulate Runx1 expression have been investigated over several decades, but how and when these REs function remains poorly understood. Here we used bioinformatic methods and functional data to characterise the regulatory landscape of vertebrate Runx1. We identified REs that are conserved between human and mouse, many of which produce enhancer RNAs in diverse tissues. Genome-wide association studies detected single nucleotide polymorphisms in REs, some of which correlate with gene expression quantitative trait loci in tissues in which the RE is active. Our analyses also suggest that REs can be variant in haematological malignancies. In summary, our analysis identifies features of the RUNX1 regulatory landscape that are likely to be important for the regulation of this gene in normal and malignant haematopoiesis.

3D interactions with the growth hormone locus in cellular signalling and cancer-related pathways.

Growth hormone (GH) is a peptide hormone predominantly produced by the anterior pituitary and is essential for normal growth and metabolism. The GH locus contains five evolutionarily related genes under the control of an upstream locus control region that coordinates tissue-specific expression of these genes. Compromised GH signalling and genetic variation in these genes has been implicated in various disorders including cancer. We hypothesised that regulatory regions within the GH locus coordinate expression of a gene network that extends the impact of the GH locus control region. We used the CoDeS3D algorithm to analyse 529 common single nucleotide polymorphisms (SNPs) across the GH locus. This algorithm identifies colocalised Hi-C and eQTL associations to determine which SNPs are associated with a change in gene expression at loci that physically interact within the nucleus. One hundred and eighty-one common SNPs were identified that interacted with 292 eGenes across 48 different tissues. One hundred and forty-five eGenes were regulated in trans. eGenes were found to be enriched in GH/GHR-related cellular signalling pathways including MAPK, PI3K-AKT-mTOR, ERBB and insulin signalling, suggesting that these pathways may be co-regulated with GH signalling. Enrichment was also observed in the Wnt and Hippo signalling pathways and in pathways associated with hepatocellular, colorectal, breast and non-small cell lung carcinoma. Thirty-three eQTL SNPs identified in our study were found to be of regulatory importance in a genome-wide Survey of Regulatory Elements reporter screen. Our data suggest that the GH locus functions as a complex regulatory region that coordinates expression of numerous genes in cis and trans, many of which may be involved in modulating GH function in normal and disease states.

Transcriptional profiling of the zebrafish proximal tubule.

The hepatocyte nuclear factor-1ß (Hnf1b) transcription factor is a key regulator of kidney tubule formation and is associated with a syndrome of renal cysts and early onset diabetes. To further our understanding of Hnf1b in the developing zebrafish kidney, we performed RNA sequencing analysis of proximal tubules from hnf1b-deficient larvae. This analysis revealed an enrichment of gene transcripts encoding transporters of the solute carrier (SLC) superfamily, including multiple members of slc2 and slc5 glucose transporters. An investigation of expression of slc2a1a, slc2a2, and slc5a2 as well as a poorly studied glucose/mannose transporter encoded by slc5a9 revealed that these genes undergo dynamic spatiotemporal changes during tubule formation and maturation. A comparative analysis of zebrafish SLC genes with those expressed in mouse proximal tubules showed a substantial overlap at the level of gene families, indicating a high degree of functional conservation between zebrafish and mammalian proximal tubules. Taken together, our findings are consistent with a role for Hnf1b as a critical determinant of proximal tubule transport function by acting upstream of a large number of SLC genes and validate the zebrafish as a physiologically relevant model of the mammalian proximal tubule.

Changes in long-range rDNA-genomic interactions associate with altered RNA polymerase II gene programs during malignant transformation.

The three-dimensional organization of the genome contributes to its maintenance and regulation. While chromosomal regions associate with nucleolar ribosomal RNA genes (rDNA), the biological significance of rDNA-genome interactions and whether they are dynamically regulated during disease remain unclear. rDNA chromatin exists in multiple inactive and active states and their transition is regulated by the RNA polymerase I transcription factor UBTF. Here, using a MYC-driven lymphoma model, we demonstrate that during malignant progression the rDNA chromatin converts to the open state, which is required for tumor cell survival. Moreover, this rDNA transition co-occurs with a reorganization of rDNA-genome contacts which correlate with gene expression changes at associated loci, impacting gene ontologies including B-cell differentiation, cell growth and metabolism. We propose that UBTF-mediated conversion to open rDNA chromatin during malignant transformation contributes to the regulation of specific gene pathways that regulate growth and differentiation through reformed long-range physical interactions with the rDNA.

The role of DNA methylation in human trophoblast differentiation.

The placenta is a vital fetal exchange organ connecting mother and baby. Specialised placental epithelial cells, called trophoblasts, are essential for adequate placental function. Trophoblasts transform the maternal vasculature to allow efficient blood flow to the placenta and facilitate adequate nutrient uptake. Placental development is in part regulated by epigenetic mechanisms. However, our understanding of how DNA methylation contributes to human trophoblast differentiation is limited. To better understand how genome-wide methylation differences affect trophoblast differentiation, reduced representation bisulfite sequencing (RRBS) was conducted on four matched sets of trophoblasts; side-population trophoblasts (a candidate human trophoblast stem cell population), cytotrophoblasts (an intermediate progenitor population), and extravillous trophoblasts (EVT, a terminally differentiated population) each isolated from the same first trimester placenta. Each trophoblast population had a distinct methylome. In line with their close differentiation relationship, the methylation profile of side-population trophoblasts was most similar to cytotrophoblasts, whilst EVT had the most distinct methylome. In comparison to mature trophoblast populations, side-population trophoblasts exhibited differential methylation of genes and miRNAs involved in cell cycle regulation, differentiation, and regulation of pluripotency. A combined methylomic and transcriptomic approach was taken to better understand cytotrophoblast differentiation to EVT. This revealed methylation of 41 genes involved in epithelial to mesenchymal transition and metastatic cancer pathways, which likely contributes to the acquisition of an invasive EVT phenotype. However, the methylation status of a gene did not always predict gene expression. Therefore, while CpG methylation plays a role in trophoblast differentiation, it is likely not the only regulatory mechanism involved in this process.

Identification of human skeletal muscle miRNA related to strength by high-throughput sequencing.

The loss of muscle size, strength, and quality with aging is a major determinant of morbidity and mortality in the elderly. The regulatory pathways that impact the muscle phenotype include the translational regulation maintained by microRNAs (miRNA). Yet the miRNAs that are expressed in human skeletal muscle and relationship to muscle size, strength, and quality are unknown. Using next-generation sequencing, we selected the 50 most abundantly expressed miRNAs and then analyzed them in vastus lateralis muscle, obtained by biopsy from middle-aged males ( n = 48; 50.0 ± 4.3 yr). Isokinetic strength testing and midthigh computed tomography was undertaken for muscle phenotype analysis. Muscle attenuation was measured by computerized tomography and is inversely proportional to myofiber lipid content. miR-486-5p accounted for 21% of total miR sequence reads, with miR-10b-5p, miR-133a-3p, and miR-22-3p accounting for a further 15, 12, and 10%, respectively. Isokinetic knee extension strength and muscle cross-sectional area were positively correlated with miR-100-5p, miR-99b-5p, and miR-191-5p expression. Muscle attenuation was negatively correlated to let-7f-5p, miR-30d-5p, and miR-125b-5p expression. In silico analysis implicates miRNAs related to strength and muscle size in the regulation of mammalian target of rapamycin, while miRNAs related to muscle attenuation may have potential roles regulating the transforming growth factor-ß/SMAD3 pathway.

Genome Modeling System: A Knowledge Management Platform for Genomics.

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

SciClone: inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution.

The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy.

Smooth muscle cells from abdominal aortic aneurysms are unique and can independently and synergistically degrade insoluble elastin.

BACKGROUND: The purpose of this study was to further elucidate the role of the vascular smooth muscle cells (SMCs) in abdominal aortic aneurysm (AAA) disease. We hypothesized that that AAA SMCs are unique and actively participate in the process of degrading the aortic matrix. METHODS: Whole-genome expression profiles of SMCs from AAAs, nondilated abdominal aorta (NAA), and carotid endarterectomy (CEA) were compared. We quantified elastolytic activity by culturing SMCs in [(3)H]elastin-coated plates and measuring solubilized tritium in the media after 7 days. Matrix metalloproteinase (MMP)-2 and MMP-9 production was assessed using real-time polymerase chain reaction, zymography, and Western blotting. RESULTS: Each SMC type exhibited a unique gene expression pattern. AAA SMCs had greater elastolytic activity than NAA-SMCs (+68%; P < .001) and CEA-SMCs (+45%; P < .001). Zymography showed an increase of active MMP-2 (62 kD) in media from AAA SMCs. AAA SMCs demonstrated twofold greater expression of MMP-2 messenger (m)RNA (P < .05) and 7.3-fold greater MMP-9 expression (P < .01) than NAA-SMCs. Culture with U937 monocytes caused a synergistic increase of elastolysis by AAA SMCs (41%; P < .001) but not NAA-SMCs or CEA-SMCs (P = .99). Coculture with U937 caused a large increase in MMP-9 mRNA in AAA-SMCs and NAA-SMCs (P < .001). MMP-2 mRNA expression was not affected. Western blots of culture media showed a fourfold increase of MMP-9 (92 kD) protein only in AAA-SMCs/U937 but not in NAA-SMCs/U937 (P < .001) and a large increase in active-MMP2 (62 kD), which was less apparent in NAA-SMCs/U937 media (P < .01). CONCLUSIONS: AAA-SMCs have a unique gene expression profile and a proelastolytic phenotype that is augmented by macrophages. This may occur by a failure of post-transcriptional control of MMP-9 synthesis.

MuSiC: identifying mutational significance in cancer genomes.

Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.

Whole-genome analysis informs breast cancer response to aromatase inhibition.

To correlate the variable clinical features of oestrogen-receptor-positive breast cancer with somatic alterations, we studied pretreatment tumour biopsies accrued from patients in two studies of neoadjuvant aromatase inhibitor therapy by massively parallel sequencing and analysis. Eighteen significantly mutated genes were identified, including five genes (RUNX1, CBFB, MYH9, MLL3 and SF3B1) previously linked to haematopoietic disorders. Mutant MAP3K1 was associated with luminal A status, low-grade histology and low proliferation rates, whereas mutant TP53 was associated with the opposite pattern. Moreover, mutant GATA3 correlated with suppression of proliferation upon aromatase inhibitor treatment. Pathway analysis demonstrated that mutations in MAP2K4, a MAP3K1 substrate, produced similar perturbations as MAP3K1 loss. Distinct phenotypes in oestrogen-receptor-positive breast cancer are associated with specific patterns of somatic mutations that map into cellular pathways linked to tumour biology, but most recurrent mutations are relatively infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing.

Genome remodelling in a basal-like breast cancer metastasis and xenograft.

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1, were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour.

Validation of the riboleukogram to detect ventilator-associated pneumonia after severe injury.

OBJECTIVE: We hypothesized that circulating leukocyte RNA profiles or "riboleukograms" detect ventilator-associated pneumonia after blunt trauma. SUMMARY BACKGROUND DATA: A pilot microarray study of 11 ventilator-associated pneumonia (VAP) patients suggested that 85 leukocyte genes can be used to diagnose VAP. Validation of this gene set to detect VAP was tested using data from an independent patient cohort. METHODS: A total of 158 intubated blunt trauma patients were enrolled at 5 centers, where 57 (36%) developed VAP. Patient age was 34.2 ± 11.1 years; 65% were male. Circulating leukocyte GeneChip U133 2.0 expression values were measured at time 0.5, 1, 4, 7, 14, 21, and 28 days after injury. DChip normalized leukocyte transcriptional profiles were analyzed using repeated measures logistic regression. A compound covariate model based on leukocyte gene transcriptional profiles in a training subset of patients was tested to determine predictive accuracy for VAP 4 days prior to clinical diagnosis in the test subset. RESULTS: Using gene expression values measured on each study day at an FDR <0.05, 27 (32%) of the 85 genes were associated with the diagnosis of VAP 1 to 4 days before diagnosis. However, the compound covariate model based on these 85-genes did not predict VAP in the test cohort better than chance (P = 0.27). In contrast, a compound covariate model based upon de novo transcriptional analysis of the 158 patients predicted VAP better than chance 4 days before diagnosis with a sensitivity of 57% and a specificity of 69%. CONCLUSION: Our results validate those described in a pilot study, confirming that riboleukograms are associated with the development of VAP days prior to clinical diagnosis. Similarly, a riboleukogram predictive model tested on a larger cohort of 158 patients was better than chance at predicting VAP days prior to clinical diagnosis.

Targeted delivery of siRNA to cell death proteins in sepsis.

Immune suppression is a major cause of morbidity and mortality in the patients with sepsis. Apoptotic loss of immune effector cells such as CD4 T and B cells is a key component in the loss of immune competence in sepsis. Inhibition of lymphocyte apoptosis has led to improved survival in animal models of sepsis. Using quantitative real-time polymerase chain reaction of isolated splenic CD4 T and B cells, we determined that Bim and PUMA, two key cell death proteins, are markedly upregulated during sepsis. Lymphocytes have been notoriously difficult to transfect with small interfering RNA (siRNA). Consequently a novel, cyclodextrin polymer-based, transferrin receptor-targeted, delivery vehicle was used to coadminister siRNA to Bim and PUMA to mice immediately after cecal ligation and puncture. Antiapoptotic siRNA-based therapy markedly decreased lymphocyte apoptosis and prevented the loss of splenic CD4 T and B cells. Flow cytometry confirmed in vivo delivery of siRNA to CD4 T and B cells and also demonstrated decreases in intracellular Bim and PUMA protein. In conclusion, Bim and PUMA are two critical mediators of immune cell death in sepsis. Use of a novel cyclodextrin polymer-based, transferrin receptor-targeted siRNA delivery vehicle enables effective administration of antiapoptotic siRNAs to lymphocytes and reverses the immune cell depletion that is a hallmark of this highly lethal disorder.

Myocardial transcriptional profiles in a murine model of sepsis: evidence for the importance of age.

BACKGROUND: Age influences outcome of sepsis and septic shock. The mechanism of this age-dependent vulnerability to sepsis remains largely unknown. Because much of the mortality and morbidity associated with sepsis and septic shock is the result of severe derangements in the cardiovascular system, it is possible that the myocardium responds to injury in a developmentally influenced manner. We hypothesized that analysis of cardiac RNA expression profiles may differentiate between the myocardial response to sepsis in young and old mice. METHODS AND RESULTS: Sixteen FVB/N male mice were stratified based on age. Young animals were 6 wks old, correlating to 4 to 6 human years, and aged animals were 20 months old correlating to 70 to 80 human years. Animals underwent either cecal ligation and puncture to produce polymicrobial sepsis or a sham operation. Both ventricles were excised after kill at 24 hrs. There were 53 genes that differed in RNA abundance between the four groups (false discovery rate of 0.005, p < 0.00001). Additionally, four genes were associated with an age-dependent response to sepsis: CYP2B2 (cytochrome P450, family 2, subfamily B, polypeptide 6), VGLL2 (vestigial like 2), and PAH (phenylalanine hydroxylase). The fourth gene is an expressed sequence tag, the function of which is related to the cytochrome P450 family. These genes play roles in phenylalanine, tyrosine, tryptophan, and fatty acid metabolism. CONCLUSIONS: This report describes the transcriptional response of the heart to sepsis. In addition, our findings suggest that these differences are in part age-dependent and serve as hypothesis generation.