Genome wide association study in Swedish Labrador retrievers identifies genetic loci associated with hip dysplasia and body weight.

Genome wide association studies (GWAS) have been utilized to identify genetic risk loci associated with both simple and complex inherited disorders. Here, we performed a GWAS in Labrador retrievers to identify genetic loci associated with hip dysplasia and body weight. Hip dysplasia scores were available for 209 genotyped dogs. We identified a significantly associated locus for hip dysplasia on chromosome 24, with three equally associated SNPs (p = 4.3 × 10-7) in complete linkage disequilibrium located within NDRG3, a gene which in humans has been shown to be differentially expressed in osteoarthritic joint cartilage. Body weight, available for 85 female dogs, was used as phenotype for a second analysis. We identified two significantly associated loci on chromosome 10 (p = 4.5 × 10-7) and chromosome 31 (p = 2.5 × 10-6). The most associated SNPs within these loci were located within the introns of the PRKCE and CADM2 genes, respectively. PRKCE has been shown to play a role in regulation of adipogenesis whilst CADM2 has been associated with body weight in multiple human GWAS. In summary, we identified credible candidate loci explaining part of the genetic inheritance for hip dysplasia and body weight in Labrador retrievers with strong candidate genes in each locus previously implicated in the phenotypes investigated.

Evolutionary constraint and innovation across hundreds of placental mammals.

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

Leveraging base-pair mammalian constraint to understand genetic variation and human disease.

Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease.

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Genome-Wide Analyses for Osteosarcoma in Leonberger Dogs Reveal the CDKN2A/B Gene Locus as a Major Risk Locus.

Dogs represent a unique spontaneous cancer model. Osteosarcoma (OSA) is the most common primary bone tumor in dogs (OMIA 001441-9615), and strongly resembles human forms of OSA. Several large- to giant-sized dog breeds, including the Leonberger, have a greatly increased risk of developing OSA. We performed genome-wide association analysis with high-density imputed SNP genotype data from 273 Leonberger cases with a median age of 8.1 [3.1-13.5] years and 365 controls older than eight years. This analysis revealed significant associations at the CDKN2A/B gene locus on canine chromosome 11, mirroring previous findings in other dog breeds, such as the greyhound, that also show an elevated risk for OSA. Heritability (h2SNP) was determined to be 20.6% (SE = 0.08; p-value = 5.7 × 10-4) based on a breed prevalence of 20%. The 2563 SNPs across the genome accounted for nearly all the h2SNP of OSA, with 2183 SNPs of small effect, 316 SNPs of moderate effect, and 64 SNPs of large effect. As with many other cancers it is likely that regulatory, non-coding variants underlie the increased risk for cancer development. Our findings confirm a complex genetic basis of OSA, moderate heritability, and the crucial role of the CDKN2A/B locus leading to strong cancer predisposition in dogs. It will ultimately be interesting to study and compare the known genetic loci associated with canine OSA in human OSA.

Targeted sequencing reveals the somatic mutation landscape in a Swedish breast cancer cohort.

Breast cancer (BC) is a genetically heterogeneous disease with high prevalence in Northern Europe. However, there has been no detailed investigation into the Scandinavian somatic landscape. Here, in a homogeneous Swedish cohort, we describe the somatic events underlying BC, leveraging a targeted next-generation sequencing approach. We designed a 20.5 Mb array targeting coding and regulatory regions of genes with a known role in BC (n = 765). The selected genes were either from human BC studies (n = 294) or from within canine mammary tumor associated regions (n = 471). A set of predominantly estrogen receptor positive tumors (ER + 85%) and their normal tissue counterparts (n = 61) were sequenced to ~ 140 × and 85 × mean target coverage, respectively. MuTect2 and VarScan2 were employed to detect single nucleotide variants (SNVs) and copy number aberrations (CNAs), while MutSigCV (SNVs) and GISTIC (CNAs) algorithms estimated the significance of recurrent somatic events. The significantly mutated genes (q ≤ 0.01) were PIK3CA (28% of patients), TP53 (21%) and CDH1 (11%). However, histone modifying genes contained the largest number of variants (KMT2C and ARID1A, together 28%). Mutations in KMT2C were mutually exclusive with PI3KCA mutations (p ≤ 0. 001) and half of these affect the formation of a functional PHD domain. The tumor suppressor CDK10 was deleted in 80% of the cohort while the oncogene MDM4 was amplified. Mutational signature analyses pointed towards APOBEC deaminase activity (COSMIC signature 2) and DNA mismatch repair (COSMIC signature 6). We noticed two significantly distinct patterns related to patient age; TP53 being more mutated in the younger group (29% vs 9% of patients) and CDH23 mutations were absent from the older group. The increased somatic mutation prevalence in the histone modifying genes KMT2C and ARID1A distinguishes the Swedish cohort from previous studies. KMT2C regulates enhancer activation and assists tumor proliferation in a hormone-rich environment, possibly pointing to a role in ER + BC, especially in older cases. Finally, age of onset appears to affect the mutational landscape suggesting that a larger age-diverse population incorporating more molecular subtypes should be studied to elucidate the underlying mechanisms.

Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes.

BACKGROUND: Glioblastoma (GBM) has one of the worst 5-year survival rates of all cancers. While genomic studies of the disease have been performed, alterations in the non-coding regulatory regions of GBM have largely remained unexplored. We apply whole-genome sequencing (WGS) to identify non-coding mutations, with regulatory potential in GBM, under the hypothesis that regions of evolutionary constraint are likely to be functional, and somatic mutations are likely more damaging than in unconstrained regions. RESULTS: We validate our GBM cohort, finding similar copy number aberrations and mutated genes based on coding mutations as previous studies. Performing analysis on non-coding constraint mutations and their position relative to nearby genes, we find a significant enrichment of non-coding constraint mutations in the neighborhood of 78 genes that have previously been implicated in GBM. Among them, SEMA3C and DYNC1I1 show the highest frequencies of alterations, with multiple mutations overlapping transcription factor binding sites. We find that a non-coding constraint mutation in the SEMA3C promoter reduces the DNA binding capacity of the region. We also identify 1776 other genes enriched for non-coding constraint mutations with likely regulatory potential, providing additional candidate GBM genes. The mutations in the top four genes, DLX5, DLX6, FOXA1, and ISL1, are distributed over promoters, UTRs, and multiple transcription factor binding sites. CONCLUSIONS: These results suggest that non-coding constraint mutations could play an essential role in GBM, underscoring the need to connect non-coding genomic variation to biological function and disease pathology.

Nuclear Receptor Binding Protein 2 Is Downregulated in Medulloblastoma, and Reduces Tumor Cell Survival upon Overexpression.

Pseudokinases, comprising 10% of the human kinome, are emerging as regulators of canonical kinases and their functions are starting to be defined. We previously identified the pseudokinase Nuclear Receptor Binding Protein 2 (NRBP2) in a screen for genes regulated during neural differentiation. During mouse brain development, NRBP2 is expressed in the cerebellum, and in the adult brain, mainly confined to specific neuronal populations. To study the role of NRBP2 in brain tumors, we stained a brain tumor tissue array for NRPB2, and find its expression to be low, or absent, in a majority of the tumors. This includes medulloblastoma (MB), a pediatric tumor of the cerebellum. Using database mining of published MB data sets, we also find that NRBP2 is expressed at a lower level in MB than in the normal cerebellum. Recent studies indicate that MB exhibits frequent epigenetic alternations and we therefore treated MB cell lines with drugs inhibiting DNA methylation or histone deacetylation, which leads to an upregulation of NRBP2 mRNA expression, showing that it is under epigenetic regulation in cultured MB cells. Furthermore, forced overexpression of NRBP2 in MB cell lines causes a dramatic decrease in cell numbers, increased cell death, impaired cell migration and inhibited cell invasion in vitro. Taken together, our data indicate that downregulation of NRBP2 may be a feature by which MB cells escape growth regulation.

LGR5 promotes tumorigenicity and invasion of glioblastoma stem-like cells and is a potential therapeutic target for a subset of glioblastoma patients.

Glioblastoma (GBM) is the most common and lethal primary malignant brain tumor which lacks efficient treatment and predictive biomarkers. Expression of the epithelial stem cell marker Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been described in GBM, but its functional role has not been conclusively elucidated. Here, we have investigated the role of LGR5 in a large repository of patient-derived GBM stem cell (GSC) cultures. The consequences of LGR5 overexpression or depletion have been analyzed using in vitro and in vivo methods, which showed that, among those with highest LGR5 expression (LGR5high ), there were two phenotypically distinct groups: one that was dependent on LGR5 for its malignant properties and another that was unaffected by changes in LGR5 expression. The LGR5-responding cultures could be identified by their significantly higher self-renewal capacity as measured by extreme limiting dilution assay (ELDA), and these LGR5high -ELDAhigh cultures were also significantly more malignant and invasive compared to the LGR5high -ELDAlow cultures. This showed that LGR5 expression alone would not be a strict marker of LGR5 responsiveness. In a search for additional biomarkers, we identified LPAR4, CCND2, and OLIG2 that were significantly upregulated in LGR5-responsive GSC cultures, and we found that OLIG2 together with LGR5 were predictive of GSC radiation and drug response. Overall, we show that LGR5 regulates the malignant phenotype in a subset of patient-derived GSC cultures, which supports its potential as a predictive GBM biomarker. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

SETD2 Is Recurrently Mutated in Whole-Exome Sequenced Canine Osteosarcoma.

Osteosarcoma is a debilitating bone cancer that affects humans, especially children and adolescents. A homologous form of osteosarcoma spontaneously occurs in dogs, and its differential incidence observed across breeds allows for the investigation of tumor mutations in the context of multiple genetic backgrounds. Using whole-exome sequencing and dogs from three susceptible breeds (22 golden retrievers, 21 Rottweilers, and 23 greyhounds), we found that osteosarcoma tumors show a high frequency of somatic copy-number alterations (SCNA), affecting key oncogenes and tumor-suppressor genes. The across-breed results are similar to what has been observed for human osteosarcoma, but the disease frequency and somatic mutation counts vary in the three breeds. For all breeds, three mutational signatures (one of which has not been previously reported) and 11 significantly mutated genes were identified. TP53 was the most frequently altered gene (83% of dogs have either mutations or SCNA in TP53), recapitulating observations in human osteosarcoma. The second most frequently mutated gene, histone methyltransferase SETD2, has known roles in multiple cancers, but has not previously been strongly implicated in osteosarcoma. This study points to the likely importance of histone modifications in osteosarcoma and highlights the strong genetic similarities between human and dog osteosarcoma, suggesting that canine osteosarcoma may serve as an excellent model for developing treatment strategies in both species.Significance: Canine osteosarcoma genomics identify SETD2 as a possible oncogenic driver of osteosarcoma, and findings establish the canine model as a useful comparative model for the corresponding human disease. Cancer Res; 78(13); 3421-31. ©2018 AACR.

Membrane-Depolarizing Channel Blockers Induce Selective Glioma Cell Death by Impairing Nutrient Transport and Unfolded Protein/Amino Acid Responses.

Glioma-initiating cells (GIC) are considered the underlying cause of recurrences of aggressive glioblastomas, replenishing the tumor population and undermining the efficacy of conventional chemotherapy. Here we report the discovery that inhibiting T-type voltage-gated Ca2+ and KCa channels can effectively induce selective cell death of GIC and increase host survival in an orthotopic mouse model of human glioma. At present, the precise cellular pathways affected by the drugs affecting these channels are unknown. However, using cell-based assays and integrated proteomics, phosphoproteomics, and transcriptomics analyses, we identified the downstream signaling events these drugs affect. Changes in plasma membrane depolarization and elevated intracellular Na+, which compromised Na+-dependent nutrient transport, were documented. Deficits in nutrient deficit acted in turn to trigger the unfolded protein response and the amino acid response, leading ultimately to nutrient starvation and GIC cell death. Our results suggest new therapeutic targets to attack aggressive gliomas. Cancer Res; 77(7); 1741-52. ©2017 AACR.

Heparanase Promotes Glioma Progression and Is Inversely Correlated with Patient Survival.

Malignant glioma continues to be fatal, despite improved insight into its underlying molecular mechanisms. The most malignant form, glioblastoma (GBM), is characterized by aberrant activation of receptor tyrosine kinases (RTK) and infiltrative growth. Heparan sulfate proteoglycans (HSPG), integral components of the extracellular matrix of brain tumors, can regulate activation of many RTK pathways. This prompted us to investigate heparanase (HPSE), which cleaves HSPGs, for its role in glioma. This hypothesis was evaluated using tissue microarrays, GBM cells derived from patients, murine in vitro and in vivo models of glioma, and public databases. Downregulation of HPSE attenuated glioma cell proliferation, whereas addition of HPSE stimulated growth and activated ERK and AKT signaling. Using HPSE transgenic and knockout mice, it was demonstrated that tumor development in vivo was positively correlated to HPSE levels in the brain. HPSE also modified the tumor microenvironment, influencing reactive astrocytes, microglia/monocytes, and tumor angiogenesis. Furthermore, inhibition of HPSE reduces tumor cell numbers, both in vitro and in vivo HPSE was highly expressed in human glioma and GBM cell lines, compared with normal brain tissue. Indeed, a correlation was observed between high levels of HPSE and shorter survival of patients with high-grade glioma. In conclusion, these data provide proof-of-concept for anti-HPSE treatment of malignant glioma, as well as novel insights for the development of HPSE as a therapeutic target. IMPLICATIONS: This study aims to target both the malignant brain tumor cells per se and their microenvironment by changing the level of an enzyme, HPSE, that breaks down modified sugar chains on cell surfaces and in the extracellular space. Mol Cancer Res; 14(12); 1243-53. ©2016 AACR.

High levels of WNT-5A in human glioma correlate with increased presence of tumor-associated microglia/monocytes.

Malignant gliomas are among the most severe types of cancer, and the most common primary brain tumors. Treatment options are limited and the prognosis is poor. WNT-5A, a member of the WNT family of lipoglycoproteins, plays a role in oncogenesis and tumor progression in various cancers, whereas the role of WNT-5A in glioma remains obscure. Based on the role of WNT-5A as an oncogene, its potential to regulate microglia cells and the glioma-promoting capacities of microglia cells, we hypothesize that WNT-5A has a role in regulation of immune functions in glioma. We investigated WNT-5A expression by in silico analysis of the cancer genome atlas (TCGA) transcript profiling of human glioblastoma samples and immunohistochemistry experiments of human glioma tissue microarrays (TMA). Our results reveal higher WNT-5A protein levels and mRNA expression in a subgroup of gliomas (WNT-5A(high)) compared to non-malignant control brain tissue. Furthermore, we show a significant correlation between WNT-5A in the tumor and presence of major histocompatibility complex Class II-positive microglia/monocytes. Our data pinpoint a positive correlation between WNT-5A and a proinflammatory signature in glioma. We identify increased presence of microglia/monocytes as an important aspect in the inflammatory transformation suggesting a novel role for WNT-5A in human glioma.

Glioma-derived plasminogen activator inhibitor-1 (PAI-1) regulates the recruitment of LRP1 positive mast cells.

Glioblastoma (GBM) is a high-grade glioma with a complex microenvironment, including various inflammatory cells and mast cells (MCs) as one of them. Previously we had identified glioma grade-dependent MC recruitment. In the present study we investigated the role of plasminogen activator inhibitor 1 (PAI-1) in MC recruitment.PAI-1, a primary regulator in the fibrinolytic cascade is capable of forming a complex with fibrinolytic system proteins together with low-density lipoprotein receptor-related protein 1 (LRP1). We found that neutralizing PAI-1 attenuated infiltration of MCs. To address the potential implication of LRP1 in this process, we used a LRP1 antagonist, receptor-associated protein (RAP), and demonstrated the attenuation of MC migration. Moreover, a positive correlation between the number of MCs and the level of PAI-1 in a large cohort of human glioma samples was observed. Our study demonstrated the expression of LRP1 in human MC line LAD2 and in MCs in human high-grade glioma. The activation of potential PAI-1/LRP1 axis with purified PAI-1 promoted increased phosphorylation of STAT3 and subsequently exocytosis in MCs.These findings indicate the influence of the PAI-1/LRP1 axis on the recruitment of MCs in glioma. The connection between high-grade glioma and MC infiltration could contribute to patient tailored therapy and improve patient stratification in future therapeutic trials.

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content.

Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets.

START: an automated tool for serial analysis of chromatin occupancy data.

UNLABELLED: The serial analysis of chromatin occupancy technique (SACO) promises to become a widely used method for the unbiased genome-wide experimental identification of loci bound by a transcription factor of interest. We describe the first web-based automatic tool, termed sequence tag analysis and reporting tool (START), for processing SACO data generated by experiments performed for the yeast, fruit fly, mouse, rat or human genomes. The program uses as input sequences of inserts from a SACO library from which it extracts all SACO tags, maps them to genomic locations and annotates them. START returns detailed information about these tags including the genes, the genomic elements and the miRNA precursors found in their vicinity, and makes use of the MAPPER database to identify putative transcription factor binding sites located close to the tags. AVAILABILITY: The program is available at http://bio.chip.org/start/. SUPPLEMENTARY INFORMATION: SUPPLEMENTARY INFORMATION is available at http://bio.chip.org/doc/start/START-supplementary.pdf

MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes.

BACKGROUND: Cis-regulatory modules are combinations of regulatory elements occurring in close proximity to each other that control the spatial and temporal expression of genes. The ability to identify them in a genome-wide manner depends on the availability of accurate models and of search methods able to detect putative regulatory elements with enhanced sensitivity and specificity. RESULTS: We describe the implementation of a search method for putative transcription factor binding sites (TFBSs) based on hidden Markov models built from alignments of known sites. We built 1,079 models of TFBSs using experimentally determined sequence alignments of sites provided by the TRANSFAC and JASPAR databases and used them to scan sequences of the human, mouse, fly, worm and yeast genomes. In several cases tested the method identified correctly experimentally characterized sites, with better specificity and sensitivity than other similar computational methods. Moreover, a large-scale comparison using synthetic data showed that in the majority of cases our method performed significantly better than a nucleotide weight matrix-based method. CONCLUSION: The search engine, available at http://mapper.chip.org, allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, fly, worm and yeast genomes. In addition it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. Due to its extensive database of models, powerful search engine and flexible interface, MAPPER represents an effective resource for the large-scale computational analysis of transcriptional regulation.

The MAPPER database: a multi-genome catalog of putative transcription factor binding sites.

We describe a comprehensive map of putative transcription factor binding sites (TFBSs) across multiple genomes created using a search method that relies on hidden Markov models built from experimentally determined TFBSs. Using the information in the TRANSFAC and JASPAR databases, we built 1134 models for TFBSs and used them to scan regions 10 kb upstream of the start of the transcript for all known genes in the human, mouse and Drosophila melanogaster genomes. The results, together with homology information on clusters of ortholog genes across the three genomes, were used to create a multi-organism catalog of annotated TFBSs. The catalog can be queried through a web interface accessible at http://bio.chip.org/mapper that allows the identification, visualization and selection of TFBSs occurring in the promoter of a gene of interest and also the common factors predicted to bind across the cluster of orthologs that includes that gene. Alternatively, the interface allows the user to retrieve binding sites for a single transcription factor of interest in a single gene or in all genes of the human, mouse or fruit fly genomes.

Bayesian approach to discovering pathogenic SNPs in conserved protein domains.

The success rate of association studies can be improved by selecting better genetic markers for genotyping or by providing better leads for identifying pathogenic single nucleotide polymorphisms (SNPs) in the regions of linkage disequilibrium with positive disease associations. We have developed a novel algorithm to predict pathogenic single amino acid changes, either nonsynonymous SNPs (nsSNPs) or missense mutations, in conserved protein domains. Using a Bayesian framework, we found that the probability of a microbial missense mutation causing a significant change in phenotype depended on how much difference it made in several phylogenetic, biochemical, and structural features related to the single amino acid substitution. We tested our model on pathogenic allelic variants (missense mutations or nsSNPs) included in OMIM, and on the other nsSNPs in the same genes (from dbSNP) as the nonpathogenic variants. As a result, our model predicted pathogenic variants with a 10% false-positive rate. The high specificity of our prediction algorithm should make it valuable in genetic association studies aimed at identifying pathogenic SNPs.