Soluble factors in malignant ascites promote the metastatic adhesion of gastric adenocarcinoma cells.

BACKGROUND: Adenocarcinoma of the proximal stomach is the fastest rising malignancy in North America. It is commonly associated with peritoneal accumulation of malignant ascites (MA), a fluid containing cancer and inflammatory cells and soluble proteins. Peritoneal metastasis (PM) is the most common site of gastric cancer (GC) progression after curative-intent surgery and is the leading cause of death among GC patients. METHODS/RESULTS: Using a panel of gastric adenocarcinoma cell lines (human: MKN 45, SNU-5; murine: NCC-S1M), we demonstrate that prior incubation of GC cells with MA results in a significant (> 1.7-fold) increase in the number of cells capable of adhering to human peritoneal mesothelial cells (HPMC) (p < 0.05). We then corroborate these findings using an ex vivo PM model and show that MA also significantly enhances the ability of GC cells to adhere to strips of human peritoneum (p < 0.05). Using a multiplex ELISA, we identify MIF and VEGF as consistently elevated across MA samples from GC patients (p < 0.05). We demonstrate that agents that block the effects of MIF or VEGF abrogate the ability of MA to stimulate the adhesion of GC cells to adhere to human peritoneum and promote both ex vivo and in vivo metastases. CONCLUSION: Agents targeting MIF or VEGF may be relevant to the treatment or prevention of PM in GC patients.

C3D: a tool to predict 3D genomic interactions between cis-regulatory elements.

MOTIVATION: The 3D genome architecture influences the regulation of genes by facilitating chromatin interactions between distal cis-regulatory elements and gene promoters. We implement Cross Cell-type Correlation based on DNA accessibility (C3D), a customizable computational tool that predicts chromatin interactions using an unsupervised algorithm that utilizes correlations in chromatin measurements, such as DNaseI hypersensitivity signals. RESULTS: C3D accurately predicts 32.7%, 18.3% and 24.1% of interactions, validated by ChIA-PET assays, between promoters and distal regions that overlie DNaseI hypersensitive sites in K562, MCF-7 and GM12878 cells, respectively. AVAILABILITY AND IMPLEMENTATION: Source code is open-source and freely available on GitHub (https://github.com/LupienLabOrganization/C3D) under the GNU GPLv3 license. C3D is implemented in Bash and R; it runs on any platform with Bash (≥4.0), R (≥3.1.1) and BEDTools (≥2.19.0). It requires the following R packages: GenomicRanges, Sushi, data.table, preprocessCore and dynamicTreeCut. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Laying a solid foundation for Manhattan--'setting the functional basis for the post-GWAS era'.

Genome-wide association studies (GWAS) have identified more than 8900 genetic variants, mainly single-nucleotide polymorphisms (SNPs), associated with hundreds of human traits and diseases, which define risk-associated loci. Variants that map to coding regions can affect protein sequence, translation rate, and alternative splicing, all of which influence protein function. However, the vast majority of sequence variants map to non-coding intergenic and intronic regions, and it has been much more challenging to assess the functional nature of these variants. Recent work annotating the non-coding regions of the genome has contributed to post-GWAS studies by facilitating the identification of the functional targets of risk-associated loci. Many non-coding genetic variants within risk-associated loci alter gene expression by modulating the activity of cis-regulatory elements. We review here these recent findings, discuss their implication for the post-GWAS era, and relate their importance to the interpretation of disease-associated mutations identified through whole-genome sequencing.

ABC: a tool to identify SNVs causing allele-specific transcription factor binding from ChIP-Seq experiments.

MOTIVATION: Detection of allelic imbalances in ChIP-Seq reads is a powerful approach to identify functional non-coding single nucleotide variants (SNVs), either polymorphisms or mutations, which modulate the affinity of transcription factors for chromatin. We present ABC, a computational tool that identifies allele-specific binding of transcription factors from aligned ChIP-Seq reads at heterozygous SNVs. ABC controls for potential false positives resulting from biases introduced by the use of short sequencing reads in ChIP-Seq and can efficiently process a large number of heterozygous SNVs. RESULTS: ABC successfully identifies previously characterized functional SNVs, such as the rs4784227 breast cancer risk associated SNP that modulates the affinity of FOXA1 for the chromatin. AVAILABILITY AND IMPLEMENTATION: The code is open-source under an Artistic-2.0 license and versioned on GitHub (https://github.com/mlupien/ABC/). ABC is written in PERL and can be run on any platform with both PERL (≥5.18.1) and R (≥3.1.1) installed. The script requires the PERL Statistics::R module. CONTACT: mlupien@uhnres.utoronto.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrative functional genomics identifies an enhancer looping to the SOX9 gene disrupted by the 17q24.3 prostate cancer risk locus.

Genome-wide association studies (GWAS) are identifying genetic predisposition to various diseases. The 17q24.3 locus harbors the single nucleotide polymorphism (SNP) rs1859962 that is statistically associated with prostate cancer (PCa). It defines a 130-kb linkage disequilibrium (LD) block that lies in an ∼2-Mb gene desert area. The functional biology driving the risk associated with this LD block is unknown. Here, we integrate genome-wide chromatin landscape data sets, namely, epigenomes and chromatin openness from diverse cell types. This identifies a PCa-specific enhancer within the rs1859962 risk LD block that establishes a 1-Mb chromatin loop with the SOX9 gene. The rs8072254 and rs1859961 SNPs mapping to this enhancer impose allele-specific gene expression. The variant allele of rs8072254 facilitates androgen receptor (AR) binding driving increased enhancer activity. The variant allele of rs1859961 decreases FOXA1 binding while increasing AP-1 binding. The latter is key to imposing allele-specific gene expression. The rs8072254 variant in strong LD with the rs1859962 risk SNP can account for the risk associated with this locus, while rs1859961 is a rare variant less likely to contribute to the risk associated with this LD block. Together, our results demonstrate that multiple genetic variants mapping to a unique enhancer looping to the SOX9 oncogene can account for the risk associated with the PCa 17q24.3 locus. Allele-specific recruitment of the transcription factors androgen receptor (AR) and activating protein-1 (AP-1) account for the increased enhancer activity ascribed to this PCa-risk LD block. This further supports the notion that an integrative genomics approach can identify the functional biology disrupted by genetic risk variants.

Variation at the DPP4 locus influences apolipoprotein B levels in South Asians and exhibits heterogeneity in Europeans related to BMI.

AIMS/HYPOTHESIS: Dyslipidaemia, a common feature of type 2 diabetes, is characterised by an increase in atherogenic particles, quantifiable through apolipoprotein B (ApoB) levels. Genetic studies of lipid levels have focused on Europeans; a study in South Asians could identify novel genes. METHODS: We tested 31,739 single nucleotide polymorphisms (SNPs) from ∼ 2,000 genes in 2,573 South Asians from the epidemiological arm of the Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication (DREAM) study (EpiDREAM) for association with ApoB and we tested two novel associations for replication in 1,181 South Asians from the INTERHEART case-control study. RESULTS: The SNP, rs4664443, within DPP4 was associated with ApoB (p = 7.98 × 10(-5)) in EpiDREAM. The observed association was replicated in the INTERHEART South Asians (one-sided p = 9.65 × 10(-3); combined two-sided p = 4.68 × 10(-6)). The rs4664443 SNP was not associated with ApoB among five other EpiDREAM ethnicities. However, because South Asians had a significantly lower mean BMI compared with other EpiDREAM ethnicities, we tested for and found an interaction between rs4664443 and BMI for ApoB among the Europeans, the largest subgroup in EpiDREAM (p = 4.14 × 10(-3) for interaction), observing an association with ApoB in Europeans with a BMI <25 kg/m(2) (p = 2.35 × 10(-3)), but not with a BMI ≥ 25 kg/m(2) (p = 0.21). The association between rs4664443 and ApoB among all EpiDREAM individuals with BMI <25 kg/m(2) was significant (n = 2,972; p = 1.44 × 10(-5)) compared with those with a BMI ≥ 25 kg/m(2) (n = 11,559; p = 0.81), and there was evidence of association among all genotyped individuals with a BMI <25 kg/m(2), including the INTERHEART South Asians (n = 3,601; p = 9.52 × 10(-7)). CONCLUSION/INTERPRETATION: Variation at the DPP4 locus is associated with ApoB in South Asians and displays heterogeneity related to BMI in other ethnicities.

Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height.

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression.

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1 , ETV1 , CRKL , and ID4 . Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC , on the same complex amplicons such as ecDNA. We characterized a MYC - ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC 's enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression.

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1, ETV1, CRKL, and ID4. Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC, on the same complex amplicons such as ecDNA. We characterized a MYC-ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC's enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.

HiChIP-Based Epigenomic Footprinting Identifies a Promoter Variant of UXS1 That Confers Genetic Susceptibility to Gastroesophageal Cancer.

Genome-wide association studies (GWAS) have identified more than a hundred single nucleotide variants (SNV) associated with the risk of gastroesophageal cancer (GEC). The majority of the identified SNVs map to noncoding regions of the genome. Uncovering the causal SNVs and genes they modulate could help improve GEC prevention and treatment. Herein, we used HiChIP against histone 3 lysine 27 acetylation (H3K27ac) to simultaneously annotate active promoters and enhancers, identify the interactions between them, and detect nucleosome-free regions (NFR) harboring potential causal SNVs in a single assay. The application of H3K27ac HiChIP in GEC relevant models identified 61 potential functional SNVs that reside in NFRs and interact with 49 genes at 17 loci. The approach led to a 67% reduction in the number of SNVs in linkage disequilibrium at these 17 loci, and at 7 loci, a single putative causal SNV was identified. One SNV, rs147518036, located within the promoter of the UDP-glucuronate decarboxylase 1 (UXS1) gene, seemed to underlie the GEC risk association captured by the rs75460256 index SNV. The rs147518036 SNV creates a GABPA DNA recognition motif, resulting in increased promoter activity, and CRISPR-mediated inhibition of the UXS1 promoter reduced the viability of the GEC cells. These findings provide a framework that simplifies the identification of potentially functional regulatory SNVs and target genes underlying risk-associated loci. In addition, the study implicates increased expression of the enzyme UXS1 and activation of its metabolic pathway as a predisposition to gastric cancer, which highlights potential therapeutic avenues to treat this disease. Significance: Epigenomic footprinting using a histone posttranslational modification targeted 3D genomics methodology elucidates functional noncoding sequence variants and their target genes at cancer risk loci.