Gerhard A. Coetzee

The 8q24 cancer risk variant rs6983267 shows long-range interaction with MYC in colorectal cancer

An inherited variant on chromosome 8q24, rs6983267, is significantly associated with cancer pathogenesis. We present evidence that the region harboring this variant is a transcriptional enhancer, that the alleles of rs6983267 differentially bind transcription factor 7-like 2 (TCF7L2) and that the risk region physically interacts with the MYC proto-oncogene. These data provide strong support for a biological mechanism underlying this non-protein-coding risk variant.

Isothiocyanates, glutathione S-transferase M1 and T1 polymorphisms, and lung-cancer risk: a prospective study of men in Shanghai, China

BACKGROUND Dietary isothiocyanates inhibit lung carcinogenesis in laboratory animals but human data are limited. Glutathione S-transferases M1 and T1 (GSTM1 and GSTT1) conjugate isothiocyanates leading to more rapid elimination. Common deletion polymorphisms of GSTM1 and GSTT1 abolish enzyme activity. We hypothesised that chemopreventive effects of isothiocyanates might be heightened when enzymes that enhance their elimination are lacking. METHODS We examined the relation between total isothiocyanate concentrations in urine, collected before diagnosis, and the subsequent risk of lung cancer among 232 incident cases of lung cancer and 710 matched controls from a cohort of 18,244 men in Shanghai, China, followed from 1986 to 1997. Homozygous deletion of the GSTM1 and GSTT1 genes were determined by PCR. FINDINGS Individuals with detectable isothiocyanates in the urine were at decreased risk of lung cancer (smoking-adjusted relative risk for lung cancer=0.65 [95% CI 0.43-0.97]). This protective effect of isothiocyanates was seen primarily among individuals with homozygous deletion of GSTM1 (0.36 [0.20-0.63]) and particularly with deletion of both GSTM1 and GSTT1 (0.28 [0.13-0.57]). INTERPRETATION Isothiocyanates appeared to reduce lung-cancer risk in this cohort of Chinese men. Reduction in risk was strongest among persons genetically deficient in enzymes that rapidly eliminate these chemopreventive compounds.

Principles for the post-GWAS functional characterization of cancer risk loci

Genome wide association studies (GWAS) have identified more than 200 mostly new common low-penetrance susceptibility loci for cancers. The predicted risk associated with each locus is generally modest (with a per-allele odds ratio typically less than 2) and so, presumably, are the functional effects of individual genetic variants conferring disease susceptibility. Perhaps the greatest challenge in the ‘post-GWAS’ era is to understand the functional consequences of these loci. Biological insights can then be translated to clinical benefits, including reliable biomarkers and effective strategies for screening and disease prevention. The purpose of this article is to propose principles for the initial functional characterization of cancer risk loci, with a focus on non-coding variants, and to define ‘post-GWAS’ functional characterization. By December 2010, there were 1,212 published GWAS studies1 reporting significant (P < 5 × 10−8) associations for 210 traits (Table 1), and the Catalog of Published GWAS states that by March 2011, 812 publications reported 3,977 SNP associations1. This is likely a small fraction of the common susceptibility loci of low penetrance that will eventually be identified. Despite these successes in identifying risk loci, the causal variant and/or the molecular basis of risk etiology has been determined for only a small fraction of these associations2–4. Plausible candidate genes can be based on proximity to risk loci, but few have so far been defined in a more systematic manner (Supplementary Table 1). Table 1 The genomic context in which a variant is found can be used as preliminary functional analysis Increased investment in post-GWAS functional characterization of risk loci5 has now been advocated across diseases and for cardiovascular disease and diabetes6. For cancer biology, the complex interplay between genetics and the environment in many cancers poses a particularly exciting challenge for post-GWAS research. Here we suggest a systematic strategy for understanding how cancer-associated variants exert their effects. We mostly refer to SNPs throughout the paper, but we recognize that other types of common genetic (for example, copy number variants) or epigenetic variation may influence risk. Our understanding of the way in which a risk variant initiates disease pathogenesis progresses from statistical association between genetic variation and trait or disease variation to functionality and causality. The functional consequences of variants in protein-coding regions causing most monogenic disorders are more readily interpreted because we know the genetic code. For non-Mendelian or multifactorial traits, most of the common DNA variants have so far mapped to non-protein–coding regions2, where our understanding of functional consequences and causality is more rudimentary. Our hypothesis is that the trait-associated alleles exert their effects by influencing transcriptional output (such as transcript levels and splicing) through multiple mechanisms. We emphasize appropriate assays and models to test the functional effects of both SNPs and genes mapping to cancer predisposition loci. Although much of what is written is applicable to alleles discovered for any trait, the section on modeling gene effects will emphasize measuring cancer-related phenotypes. At some loci, multiple, independently associated risk alleles rather than single risk alleles may be functionally responsible for the occurrence of disease. Genotyping susceptibility loci (and their correlated variants) in multiple populations with different linkage disequilibrium (LD) structures may prove effective in substantially reducing the number of potentially causative variants (that is, the same causal variant may segregate in multiple populations), as shown for the FGFR2 locus in breast cancer7, but for most loci there will remain a set of potentially causative variants that cannot be separated at the statistical level from case-control genotype data. A susceptibility locus should be re-sequenced to ascertain all genetic variation, identifying candidate functional or causal variants and identifying candidate causal genes. Ideally, the identification of a causal SNP would be the next step to reveal the molecular mechanisms of risk modification. Practically, however, it is unclear what the criteria for causality should be, particularly in non-protein–coding regions. Thus, although we propose a framework set of analyses (Box 1), we acknowledge that the techniques and methods will continue to evolve with the field. Box 1 Strategies to progress from tag SNP to mechanism Target resequencing efforts using linkage disequilibrium (LD) structure. Use other populations to refine LD regions (for example African ancestry with shorter LD and more heterogeneity). Determine expression levels of nearby genes as a function of genotype at each locus (eQTL). Characterize gene regulatory regions by multiple empirical techniques bearing in mind that these are tissue and context specific. Combine regulatory regions with risk loci using coordinates from multiple reference genomes to capture all variation within the shorter regulatory regions that correlates with the tag SNP at each locus. Multiple experimental manipulations in model systems are needed to progressively implicate transcription units (genes) in mechanisms relevant to the associated loci: Knockouts of regulatory regions in animal (difficult and may be limited by functional redundancy, but new targeting methods in rat are promising) models followed by genome-wide expression analysis. Use chromatin association methods (3C, CHIA-PET) of regulatory regions to determine the identity of target genes (compare with eQTL data). Targeted gene perturbations in somatic cell models. Explore fully genome-wide eQTL and miRNA quantitative variation correlation in relevant tissues and cells. Explore epigenetic mechanisms in the context of genome-wide genetic polymorphism. Employ cell models and tissue reconstructions to evaluate mechanisms using gene perturbations and polymorphic variants. The human cancer cell xenograft has re-emerged as a minimal in vivo validation of these models. Above all, resist the temptation to equate any partial functional evidence as sufficient. Published claims of functional relevance should be fully evaluated using the steps detailed above.

Multiple signal input and output domains of the 160-kilodalton nuclear receptor coactivator proteins.

ABSTRACT Members of the 160-kDa nuclear receptor coactivator family (p160 coactivators) bind to the conserved AF-2 activation function found in the hormone binding domains of nuclear receptors (NR) and are potent transcriptional coactivators for NRs. Here we report that the C-terminal region of p160 coactivators glucocorticoid receptor interacting protein 1 (GRIP1), steroid receptor coactivator 1 (SRC-1a), and SRC-1e binds the N-terminal AF-1 activation function of the androgen receptor (AR), and p160 coactivators can thereby enhance transcriptional activation by AR. While they all interact efficiently with AR AF-1, these same coactivators have vastly different binding strengths with and coactivator effects on AR AF-2. p160 activation domain AD1, which binds secondary coactivators CREB binding protein (CBP) and p300, was previously implicated as the principal domain for transmitting the activating signal to the transcription machinery. We identified a new highly conserved motif in the AD1 region which is important for CBP/p300 binding. Deletion of AD1 only partially reduced p160 coactivator function, due to signaling through AD2, another activation domain located at the C-terminal end of p160 coactivators. C-terminal coactivator fragments lacking AD1 but containing AD2 and the AR AF-1 binding site served as efficient coactivators for full-length AR and AR AF-1. The two signal input domains (one that binds NR AF-2 domains and one that binds AF-1 domains of some but not all NRs) and the two signal output domains (AD1 and AD2) of p160 coactivators played different relative roles for two different NRs: AR and thyroid hormone receptor.

8q24 prostate, breast, and colon cancer risk loci show tissue-specific long-range interaction with MYC

The 8q24 gene desert contains risk loci for multiple epithelial cancers, including colon, breast, and prostate. Recent evidence suggests these risk loci contain enhancers. In this study, data are presented showing that each risk locus bears epigenetic marks consistent with enhancer elements and forms a long-range chromatin loop with the MYC proto-oncogene located several hundred kilobases telomeric and that these interactions are tissue-specific. We therefore propose that the 8q24 risk loci operate through a common mechanism—as tissue-specific enhancers of MYC.

Evidence of an X-linked or recessive genetic component to prostate cancer risk

We used data from a population-based cohort study of blacks, Hispanics, Japanese and whites to examine the frequency of prevalent prostate and breast cancer by family history status of first-degree relatives (parents and siblings). Independent of race, the age-adjusted relative risk for prevalent prostate cancer in subjects with affected brothers was approximately two times that in subjects with affected fathers (P < 0.00005). No such excess risk for breast cancer was observed among subjects with affected sisters compared to those with affected mothers (age- and race-adjusted relative risk = 1.10, P= 0.34). The magnitude of the relative risk for prostate cancer in sibling-versus parent-affected groups was significantly different from that of the comparable relative risk for breast cancer (P < 0.00005). An excess risk of prostate cancer in men with affected brothers compared to those with affected fathers is consistent with the hypothesis of an X-linked, or recessive, model of inheritance.

Androgen receptor inhibits estrogen receptor-alpha activity and is prognostic in breast cancer

There is emerging evidence that the balance between estrogen receptor-alpha (ER(alpha)) and androgen receptor (AR) signaling is a critical determinant of growth in the normal and malignant breast. In this study, we assessed AR status in a cohort of 215 invasive ductal breast carcinomas. AR and (ER(alpha)) were coexpressed in the majority (80-90%) of breast tumor cells. Kaplan-Meier product limit analysis and multivariate Cox regression showed that AR is an independent prognostic factor in (ER(alpha))-positive disease, with a low level of AR (less than median of 75% positive cells) conferring a 4.6-fold increased risk of cancer-related death (P = 0.002). Consistent with a role for AR in breast cancer outcome, AR potently inhibited (ER(alpha))transactivation activity and 17beta-estradiol-stimulated growth of breast cancer cells. Transfection of MDA-MB-231 breast cancer cells with either functionally impaired AR variants or the DNA-binding domain of the AR indicated that the latter is both necessary and sufficient for inhibition of (ER(alpha)) signaling. Consistent with molecular modeling, electrophoretic mobility shift assays showed binding of the AR to an estrogen-responsive element (ERE). Evidence for a functional interaction of the AR with an ERE in vivo was provided by chromatin immunoprecipitation data, revealing recruitment of the AR to the progesterone receptor promoter in T-47D breast cancer cells. We conclude that, by binding to a subset of EREs, the AR can prevent activation of target genes that mediate the stimulatory effects of 17beta-estradiol on breast cancer cells.

Functional Enhancers at the Gene-Poor 8q24 Cancer-Linked Locus

Multiple discrete regions at 8q24 were recently shown to contain alleles that predispose to many cancers including prostate, breast, and colon. These regions are far from any annotated gene and their biological activities have been unknown. Here we profiled a 5-megabase chromatin segment encompassing all the risk regions for RNA expression, histone modifications, and locations occupied by RNA polymerase II and androgen receptor (AR). This led to the identification of several transcriptional enhancers, which were verified using reporter assays. Two enhancers in one risk region were occupied by AR and responded to androgen treatment; one contained a single nucleotide polymorphism (rs11986220) that resides within a FoxA1 binding site, with the prostate cancer risk allele facilitating both stronger FoxA1 binding and stronger androgen responsiveness. The study reported here exemplifies an approach that may be applied to any risk-associated allele in non-protein coding regions as it emerges from genome-wide association studies to better understand the genetic predisposition of complex diseases.

Identification of genetic susceptibility loci for colorectal tumors in a genome-wide meta-analysis

BACKGROUND & AIMS Heritable factors contribute to the development of colorectal cancer. Identifying the genetic loci associated with colorectal tumor formation could elucidate the mechanisms of pathogenesis. METHODS We conducted a genome-wide association study that included 14 studies, 12,696 cases of colorectal tumors (11,870 cancer, 826 adenoma), and 15,113 controls of European descent. The 10 most statistically significant, previously unreported findings were followed up in 6 studies; these included 3056 colorectal tumor cases (2098 cancer, 958 adenoma) and 6658 controls of European and Asian descent. RESULTS Based on the combined analysis, we identified a locus that reached the conventional genome-wide significance level at less than 5.0 × 10(-8): an intergenic region on chromosome 2q32.3, close to nucleic acid binding protein 1 (most significant single nucleotide polymorphism: rs11903757; odds ratio [OR], 1.15 per risk allele; P = 3.7 × 10(-8)). We also found evidence for 3 additional loci with P values less than 5.0 × 10(-7): a locus within the laminin gamma 1 gene on chromosome 1q25.3 (rs10911251; OR, 1.10 per risk allele; P = 9.5 × 10(-8)), a locus within the cyclin D2 gene on chromosome 12p13.32 (rs3217810 per risk allele; OR, 0.84; P = 5.9 × 10(-8)), and a locus in the T-box 3 gene on chromosome 12q24.21 (rs59336; OR, 0.91 per risk allele; P = 3.7 × 10(-7)). CONCLUSIONS In a large genome-wide association study, we associated polymorphisms close to nucleic acid binding protein 1 (which encodes a DNA-binding protein involved in DNA repair) with colorectal tumor risk. We also provided evidence for an association between colorectal tumor risk and polymorphisms in laminin gamma 1 (this is the second gene in the laminin family to be associated with colorectal cancers), cyclin D2 (which encodes for cyclin D2), and T-box 3 (which encodes a T-box transcription factor and is a target of Wnt signaling to β-catenin). The roles of these genes and their products in cancer pathogenesis warrant further investigation.

Contribution of the Androgen Receptor to Prostate Cancer Predisposition and Progression

Although prostate cancer is heterogeneous in its etiology and progression, androgen signaling through the androgen receptor (AR) appears to be involved in all aspects of the disease, from initiation to development of treatment resistance. Lifetime exposure to a constitutively more active AR, encoded by AR alleles as defined by two translated polymorphic microsatellites (CAG and GGC), results in a significant increase in prostate cancer risk. The AR gene is amplified or a target for somatic gain-of-function mutations in metastatic prostate cancer. Gain-of-function AR gene mutations may result in inappropriate activation of the AR, thereby contributing to the failure of conventional androgen-ablation treatments. In cases where no genetically altered receptors are observed, altered signaling through the AR, achieved by cross-talk with other signaling pathways (e.g. kinase-mediated pathways) and/or inappropriate expression of coregulatory proteins, may contribute to disease progression. Thus, the AR-signaling axis contributes to many aspects of prostate cancer, including initiation, progression and resistance to current forms of therapy. This recognition represents a paradigm shift in our understanding of the molecular mechanisms involved in progression of prostate cancer, and provides insight into novel AR-targeted therapies which ultimately may be more effective than current forms of androgen ablation.