Genome-wide copy number alterations in subtypes of invasive breast cancers in young white and African American women.

Genomic copy number alterations (CNA) are common in breast cancer. Identifying characteristic CNAs associated with specific breast cancer subtypes is a critical step in defining potential mechanisms of disease initiation and progression. We used genome-wide array comparative genomic hybridization to identify distinctive CNAs in breast cancer subtypes from 259 young (diagnosed with breast cancer at 40%) for TN breast tumors at 10q, 11p, 11q, 16q, 20p, and 20q. In addition, we report CNAs that differ in frequency between TN breast tumors of AA and CA women. This is of particular relevance because TN breast cancer is associated with higher mortality and young AA women have higher rates of TN breast tumors compared to CA women. These data support the possibility that higher overall frequency of genomic alteration events as well as specific focal CNAs in TN breast tumors might contribute in part to the poor breast cancer prognosis for young AA women

Supplementary Data Only: Genomic binding by the Drosophila Myc, Max, Mad/Mnt transcription factor network.

The Myc/Max/Mad transcription factor network is critically involved in cell behavior; however, there is relatively little information on its genomic binding sites. We have employed the DamID method to carry out global genomic mapping of the Drosophila Myc, Max, and Mad/Mnt proteins. Each protein was tethered to Escherichia coli DNA adenine-methyltransferase (Dam) permitting methylation proximal to in vivo binding sites in Kc cells. Microarray analyses of methylated DNA fragments reveals binding to multiple loci on all major Drosophila chromosomes. This approach also reveals dynamic interactions among network members as we find that increased levels of dMax influence the extent of dMyc, but not dMnt, binding. Computer analysis using the REDUCE algorithm demonstrates that binding regions correlate with the presence of E-boxes, CG repeats, and other sequence motifs. The surprisingly large number of directly bound loci ( approximately 15% of coding regions) suggests that the network interacts widely with the genome. Furthermore, we employ microarray expression analysis to demonstrate that hundreds of DamID-binding loci correspond to genes whose expression is directly regulated by dMyc in larvae. These results suggest that a fundamental aspect of Max network function involves widespread binding and regulation of gene expression

cis-Expression QTL Analysis of Established Colorectal Cancer Risk Variants in Colon Tumors and Adjacent Normal Tissue

Genome-wide association studies (GWAS) have identified 19 risk variants associated with colorectal cancer. As most of these risk variants reside outside the coding regions of genes, we conducted cis-expression quantitative trait loci (cis-eQTL) analyses to investigate possible regulatory functions on the expression of neighboring genes. Forty microsatellite stable and CpG island methylator phenotype-negative colorectal tumors and paired adjacent normal colon tissues were used for genome-wide SNP and gene expression profiling. We found that three risk variants (rs10795668, rs4444235 and rs9929218, using near perfect proxies rs706771, rs11623717 and rs2059252, respectively) were significantly associated (FDR q-value ≤0.05) with expression levels of nearby genes (<2 Mb up- or down-stream). We observed an association between the low colorectal cancer risk allele (A) for rs10795668 at 10p14 and increased expression of ATP5C1 (q = 0.024) and between the colorectal cancer high risk allele (C) for rs4444235 at 14q22.2 and increased expression of DLGAP5 (q = 0.041), both in tumor samples. The colorectal cancer low risk allele (A) for rs9929218 at 16q22.1 was associated with a significant decrease in expression of both NOL3 (q = 0.017) and DDX28 (q = 0.046) in the adjacent normal colon tissue samples. Of the four genes, DLGAP5 and NOL3 have been previously reported to play a role in colon carcinogenesis and ATP5C1 and DDX28 are mitochondrial proteins involved in cellular metabolism and division, respectively. The combination of GWAS findings, prior functional studies, and the cis-eQTL analyses described here suggest putative functional activities for three of the colorectal cancer GWAS identified risk loci as regulating the expression of neighboring genes

Trans-ethnic genome-wide association study of colorectal cancer identifies a new susceptibility locus in VTI1A

The genetic basis of sporadic colorectal cancer (CRC) is not well explained by known risk polymorphisms. Here we perform a meta-analysis of two genome-wide association studies in 2,627 cases and 3,797 controls of Japanese ancestry and 1,894 cases and 4,703 controls of African ancestry, to identify genetic variants that contribute to CRC susceptibility. We replicate genome-wide statistically significant associations (P < 5×10−8) in 16,823 cases and 18,211 controls of European ancestry. This study reveals a new pan-ethnic CRC risk locus at 10q25 (rs12241008, intronic to VTI1A; P=1.4×10−9), providing additional insight into the etiology of CRC and highlighting the value of association mapping in diverse populations

In silico pathway analysis and tissue specific cis-eQTL for colorectal cancer GWAS risk variants

Abstract Background Genome-wide association studies have identified 55 genetic variants associated with colorectal cancer risk to date. However, potential causal genes and pathways regulated by these risk variants remain to be characterized. Therefore, we performed gene ontology enrichment and pathway analyses to determine if there was an enrichment of genes in proximity to the colorectal cancer risk variants that could further elucidate the probable causal genes and pathways involved in colorectal cancer biology. Results For the 65 unique genes that either contained, or were immediately neighboring up- and downstream, of these variants there was a significant enrichment for the KEGG pathway, Pathways in Cancer (p-value = 2.67 × 10−5) and an enrichment for multiple biological processes (FDR < 0.05), such as cell junction organization, tissue morphogenesis, regulation of SMAD protein phosphorylation, and odontogenesis identified through Gene Ontology analysis. To identify potential causal genes, we conducted a cis-expression quantitative trait loci (cis-eQTL) analysis using gene expression and genotype data from the Genotype-Tissue Expression (GTEx) Project portal in normal sigmoid (n = 124) and transverse (n = 169) colon tissue. In addition, we also did a cis-eQTL analysis on colorectal tumor tissue (n = 147) from The Cancer Genome Atlas (TCGA). We identified two risk alleles that were significant cis-eQTLs for FADS2 (rs1535) and COLCA1 and 2 (rs3802842) genes in the normal transverse colon tissue and two risk alleles that were significant cis-eQTLs for the CABLES2 (rs2427308) and LIPG (rs7229639) genes in the normal sigmoid colon tissue, but not tumor tissue. Conclusions Our data reaffirm the potential to identify an enrichment for biological processes and candidate causal genes based on expression profiles correlated with genetic risk alleles of colorectal cancer, however, the identification of these significant cis-eQTLs is context and tissue specific

<i>In Silico</i> Functional Pathway Annotation of 86 Established Prostate Cancer Risk Variants

<div><p>Heritability is one of the strongest risk factors of prostate cancer, emphasizing the importance of the genetic contribution towards prostate cancer risk. To date, 86 established prostate cancer risk variants have been identified by genome-wide association studies (GWAS). To determine if these risk variants are located near genes that interact together in biological networks or pathways contributing to prostate cancer initiation or progression, we generated gene sets based on proximity to the 86 prostate cancer risk variants. We took two approaches to generate gene lists. The first strategy included all immediate flanking genes, up- and downstream of the risk variant, regardless of distance from the index variant, and the second strategy included genes closest to the index GWAS marker and to variants in high LD (r² ≥0.8 in Europeans) with the index variant, within a 100 kb window up- and downstream. Pathway mapping of the two gene sets supported the importance of the androgen receptor-mediated signaling in prostate cancer biology. In addition, the hedgehog and Wnt/β-catenin signaling pathways were identified in pathway mapping for the flanking gene set. We also used the HaploReg resource to examine the 86 risk loci and variants high LD (r² ≥0.8) for functional elements. We found that there was a 12.8 fold (p = 2.9 x 10^-4) enrichment for enhancer motifs in a stem cell line and a 4.4 fold (p = 1.1 x 10^-3) enrichment of DNase hypersensitivity in a prostate adenocarcinoma cell line, indicating that the risk and correlated variants are enriched for transcriptional regulatory motifs. Our pathway-based functional annotation of the prostate cancer risk variants highlights the potential regulatory function that GWAS risk markers, and their highly correlated variants, exert on genes. Our study also shows that these genes may function cooperatively in key signaling pathways in prostate cancer biology.</p></div

Gene-gene interactions among genes flanking prostate cancer risk alleles.

<p>A total of 97 unique genes contained or flanking the 86 prostate cancer risk loci. Gene-gene interactions were identified using the Ingenuity Pathway Analysis software. The most significant functional network demonstrating connectivity between genes was identified as having a potential function in <i>Organismal Development</i>, <i>Embryonic Development</i>, <i>and Organ Development</i>. The representative gene products are listed and putative functions listed in the legend. Gene products shaded in gray represent genes originating from the gene list.</p

Gene-gene interactions among genes neighboring SNPs in high LD with prostate cancer risk alleles.

<p>A total of 78 unique genes contained or were located within 100 Kb of SNPs in high LD (r²>0.80). Gene-gene interactions were identified using the Ingenuity Pathway Analysis software. The most significant functional network demonstrating connectivity between genes was identified as having a potential function in <i>Cancer</i>, <i>Cellular Growth and Proliferation</i>, <i>and Organismal Injury and Abnormalities</i>. Gene products shaded in gray represent genes originating from the gene list.</p

Upstream regulators among genes neighboring SNPs in high LD with prostate cancer risk alleles.

<p>The IPA Upstream Regulator tool was used to identify potential upstream regulators based on the statistical significance of genes in the gene list that function downstream of this regulator. The top 5 upstream regulators identified were flufenamic acid, androgen receptor (AR), cadmium chloride, prostate transmembrane protein, androgen induced 1 (PMEPA1), and prefoldin-like chaperone (URI1). Upstream regulators (red); upstream regulator and on the gene list (purple shading); genes from the gene list (blue).</p