Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses

Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.

Prostate Cancer, Race, and Health Disparity: What We Know

ABSTRACT

Prostate cancer (PCa) in African American men is one of the most common cancers with a great disparity in outcomes. The higher incidence and tendency to present with more advanced disease have prompted investigators to postulate that this is a problem of innate biology. However, unequal access to health care and poorer quality of care raise questions about the relative importance of genetics versus social/health injustice. Although race is inconsistent with global human genetic diversity, we need to understand the sociocultural reality that race and racism impact biology. Genetic studies reveal enrichment of PCa risk alleles in populations of West African descent and population-level differences in tumor immunology. Structural racism may explain some of the differences previously reported in PCa clinical outcomes; fortunately, there is high-level evidence that when care is comparable, outcomes are comparable.

Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers

Transcriptome-wide association studies (TWAS) have successfully discovered many putative disease susceptibility genes. However, TWAS may suffer from inaccuracy of gene expression predictions due to inclusion of non-regulatory variants. By integrating prior knowledge of susceptible transcription factor occupied elements, we develop sTF-TWAS and demonstrate that it outperforms existing TWAS approaches in both simulation and real data analyses. Under the sTF-TWAS framework, we build genetic models to predict alternative splicing and gene expression in normal breast, prostate and lung tissues from the Genotype-Tissue Expression project and apply these models to data from large genome-wide association studies (GWAS) conducted among European-ancestry populations. At Bonferroni-corrected P < 0.05, we identify 354 putative susceptibility genes for these cancers, including 189 previously unreported in GWAS loci and 45 in loci unreported by GWAS. These findings provide additional insight into the genetic susceptibility of human cancers. Additionally, we show the generalizability of the sTF-TWAS on non-cancer diseases.

CASC11 and PVT1 spliced transcripts play an oncogenic role in colorectal carcinogenesis

Cancer is fundamentally a genetic disorder that alters cellular information flow toward aberrant growth. The coding part accounts for less than 2% of the human genome, and it has become apparent that aberrations within the noncoding genome drive important cancer phenotypes. The numerous carcinogenesis-related genomic variations in the 8q24 region include single nucleotide variations (SNVs), copy number variations (CNVs), and viral integrations occur in the neighboring areas of the MYC locus. It seems that MYC is not the only target of these alterations. The MYC-proximal mutations may act via regulatory noncoding RNAs (ncRNAs). In this study, gene expression analyses indicated that the expression of some PVT1 spliced linear transcripts, CircPVT1, CASC11, and MYC is increased in colorectal cancer (CRC). Moreover, the expression of these genes is associated with some clinicopathological characteristics of CRC. Also, in vitro studies in CRC cell lines demonstrated that CASC11 is mostly detected in the nucleus, and different transcripts of PVT1 have different preferences for nuclear and cytoplasmic parts. Furthermore, perturbation of PVT1 expression and concomitant perturbation in PVT1 and CASC11 expression caused MYC overexpression. It seems that transcription of MYC is under regulatory control at the transcriptional level, i.e., initiation and elongation of transcription by its neighboring genes. Altogether, the current data provide evidence for the notion that these noncoding transcripts can significantly participate in the MYC regulation network and in the carcinogenesis of colorectal cells.

Functional annotation of breast cancer risk loci: current progress and future directions

Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal "at risk" breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman's risk of breast cancer.

STAT3-mediated allelic imbalance of novel genetic variant Rs1047643 and B-cell-specific super-enhancer in association with systemic lupus erythematosus

Mapping of allelic imbalance (AI) at heterozygous loci has the potential to establish links between genetic risk for disease and biological function. Leveraging multi-omics data for AI analysis and functional annotation, we discovered a novel functional risk variant rs1047643 at 8p23 in association with systemic lupus erythematosus (SLE). This variant displays dynamic AI of chromatin accessibility and allelic expression on FDFT1 gene in B cells with SLE. We further found a B-cell restricted super-enhancer (SE) that physically contacts with this SNP-residing locus, an interaction that also appears specifically in B cells. Quantitative analysis of chromatin accessibility and DNA methylation profiles further demonstrated that the SE exhibits aberrant activity in B cell development with SLE. Functional studies identified that STAT3, a master factor associated with autoimmune diseases, directly regulates both the AI of risk variant and the activity of SE in cultured B cells. Our study reveals that STAT3-mediated SE activity and cis-regulatory effects of SNP rs1047643 at 8p23 locus are associated with B cell deregulation in SLE.

Alu insertion variants alter gene transcript levels

Alu are high copy number interspersed repeats that have accumulated near genes during primate and human evolution. They are a pervasive source of structural variation in modern humans. Impacts that Alu insertions may have on gene expression are not well understood, although some have been associated with expression quantitative trait loci (eQTLs). Here, we directly test regulatory effects of polymorphic Alu insertions in isolation of other variants on the same haplotype. To screen insertion variants for those with such effects, we used ectopic luciferase reporter assays and evaluated 110 Alu insertion variants, including more than 40 with a potential role in disease risk. We observed a continuum of effects with significant outliers that up- or down-regulate luciferase activity. Using a series of reporter constructs, which included genomic context surrounding the Alu, we can distinguish between instances in which the Alu disrupts another regulator and those in which the Alu introduces new regulatory sequence. We next focused on three polymorphic Alu loci associated with breast cancer that display significant effects in the reporter assay. We used CRISPR to modify the endogenous sequences, establishing cell lines varying in the Alu genotype. Our findings indicate that Alu genotype can alter expression of genes implicated in cancer risk, including PTHLH, RANBP9, and MYC These data show that commonly occurring polymorphic Alu elements can alter transcript levels and potentially contribute to disease risk.

Genetic Contributions to Prostate Cancer Disparities in Men of West African Descent

Prostate cancer (PCa) is the second most frequently diagnosed malignancy and the second leading cause of death in men worldwide, after adjusting for age. According to the International Agency for Research on Cancer, continents such as North America and Europe report higher incidence of PCa; however, mortality rates are highest among men of African ancestry in the western, southern, and central regions of Africa and the Caribbean. The American Cancer Society reports, African Americans (AAs), in the United States, have a 1.7 increased incidence and 2.4 times higher mortality rate, compared to European American's (EAs). Hence, early population history in west Africa and the subsequent African Diaspora may play an important role in understanding the global disproportionate burden of PCa shared among Africans and other men of African descent. Nonetheless, disparities involved in diagnosis, treatment, and survival of PCa patients has also been correlated to socioeconomic status, education and access to healthcare. Although recent studies suggest equal PCa treatments yield equal outcomes among patients, data illuminates an unsettling reality of disparities in treatment and care in both, developed and developing countries, especially for men of African descent. Yet, even after adjusting for the effects of the aforementioned factors; racial disparities in mortality rates remain significant. This suggests that molecular and genomic factors may account for much of PCa disparities.

Association between genetic variations at 8q24 and prostate cancer risk in Mexican Men

BACKGROUND

Variants of 8q24 locus have been associated with prostate cancer (PCa) susceptibility. This study aims to analyze the genetic basis of PCa susceptibility in Mexican men by analyzing SNPs in the 8q24 locus for the first time.

METHODS

A case-control study was performed in 875 men recruited from the Mexican Social Security Institute, 326 patients with PCa, and 549 non-PCa patients (88 with benign prostatic hyperplasia BPH and 461 healthy controls). The 8q24 locus SNPs: rs16901979, rs16983267, rs1447295, and rs7837328 were genotyped by allelic discrimination assays using TaqMan probes. Statistical analysis was performed using Epi Info statistical 7.0 and SNPstats softwares.

RESULTS

All genotype frequencies were in Hardy-Weinberg Equilibrium. No differences were observed in genotype distribution between PCa and non-PCa patients for rs6983267. Under different inheritance models, the rs16901979, rs1447295, and rs7837328 SNPs were associated with PCa (OR = 2.8, 1.8, and 1.72, respectively; Pc < 0.001) when comparing PCa patients against controls. This association remains between PCa and BPH patients under different models (OR = 8.5, 2.2, and 1.9, respectively; Pc < 0.001). There were no significant differences in allele and genotype distribution among BPH patients and controls. The combined effect of the alleles CGAA for the SNPs rs16901979, rs6983267, rs1447295, and rs7837328 showed significant differences between PCa patients and controls (OR = 2.9, 95% CI = 1.48-5.83, Pc = 0.008). Four 8q24 variants were not associated with D'Amico score, age at diagnosis, and bone metastases.

CONCLUSIONS

Our study provides the first confirmation that variants rs16901979, rs1447295, and 7837328 at 8q24 locus are associated with PCa susceptibility in Mexican men.

Genetic variations of DNA bindings of FOXA1 and co-factors in breast cancer susceptibility

Identifying transcription factors (TFs) whose DNA bindings are altered by genetic variants that regulate susceptibility genes is imperative to understand transcriptional dysregulation in disease etiology. Here, we develop a statistical framework to analyze extensive ChIP-seq and GWAS data and identify 22 breast cancer risk-associated TFs. We find that, by analyzing genetic variations of TF-DNA bindings, the interaction of FOXA1 with co-factors such as ESR1 and E2F1, and the interaction of TFs with chromatin features (i.e., enhancers) play a key role in breast cancer susceptibility. Using genetic variants occupied by the 22 TFs, transcriptome-wide association analyses identify 52 previously unreported breast cancer susceptibility genes, including seven with evidence of essentiality from functional screens in breast relevant cell lines. We show that FOXA1 and co-factors form a core TF-transcriptional network regulating the susceptibility genes. Our findings provide additional insights into genetic variations of TF-DNA bindings (particularly for FOXA1) underlying breast cancer susceptibility.

The identification of transcription factors (TFs) whose binding sites are affected by risk genetic variants remains crucial. Here, the authors develop a statistical framework to analyse ChIP-seq and GWAS data, identify 22 breast cancer risk-associated TFs and a core TF-transcriptional network for FOXA1 and co-factors.

Risks and Function of Breast Cancer Susceptibility Alleles

Family history remains one of the strongest risk factors for breast cancer. It is well established that women with a first-degree relative affected by breast cancer are twice as likely to develop the disease themselves. Twins studies indicate that this is most likely due to shared genetics rather than shared epidemiological/lifestyle risk factors. Linkage and targeted sequencing studies have shown that rare high- and moderate-penetrance germline variants in genes involved in the DNA damage response (DDR) including BRCA1, BRCA2, PALB2, ATM, and TP53 are responsible for a proportion of breast cancer cases. However, breast cancer is a heterogeneous disease, and there is now strong evidence that different risk alleles can predispose to different subtypes of breast cancer. Here, we review the associations between the different genes and subtype-specificity of breast cancer based on the most comprehensive genetic studies published. Genome-wide association studies (GWAS) have also been used to identify an additional hereditary component of breast cancer, and have identified hundreds of common, low-penetrance susceptibility alleles. The combination of these low penetrance risk variants, summed as a polygenic risk score (PRS), can identify individuals across the spectrum of disease risk. However, there remains a substantial bottleneck between the discovery of GWAS-risk variants and their contribution to tumorigenesis mainly because the majority of these variants map to the non-protein coding genome. A range of functional genomic approaches are needed to identify the causal risk variants and target susceptibility genes and establish their underlying role in disease biology. We discuss how the application of these multidisciplinary approaches to understand genetic risk for breast cancer can be used to identify individuals in the population that may benefit from clinical interventions including screening for early detection and prevention, and treatment strategies to reduce breast cancer-related mortalities.

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

BOP1 Silencing Suppresses Gastric Cancer Proliferation through p53 Modulation

Block of proliferation 1 (BOP1) is a key protein involved in ribosome maturation and affects cancer progression. However, its role in gastric cancer (GC) remains unknown. This study aimed to explore the expression of BOP1 in GC and its potential mechanisms in regulating GC growth, and the relationship between BOP1 level in cancer tissues and survival was also analyzed. The expression of BOP1 was examined by immunohistochemistry (IHC) in a cohort containing 387 patients with primary GC. Cultured GC cells were treated by siRNA to knock down the BOP1 expression, and examined by CCK-8 assay and plate clone formation to assess cell proliferation in vitro. Apoptotic rate of cultured GC cells was detected by flow cytometry with double staining of AnnxinV/PI. The xenografted mouse model was used to assess GC cell proliferation in vivo. Western blot and IHC were also performed to detect the expression levels of BOP1, p53 and p21. Patients with higher level of BOP1 in cancer tissues had significantly poorer survival. BOP1 silencing significantly suppressed GC cell proliferation both in vitro and in vivo. It blocked cell cycle at G0/G1 phase and led to apoptosis of GC cells via upregulating p53 and p21. BOP1 silencing-induced suppression of cell proliferation was partly reversed by pifithrin-α (a p53 inhibitor). Our study demonstrated that BOP1 up-regulation may be a hallmark of GC and it may regulate proliferation of GC cells by activating p53. BOP1 might be considered a novel biomarker of GC proliferation, and could be a potential indicator of prognosis of GC patients. BOP1 might also be a potential target for the treatment of GC patients if further researched.

An Enhancer-Based Analysis Revealed a New Function of Androgen Receptor in Tumor Cell Immune Evasion

Cancer is characterized by dysregulation at multiple levels, such as gene transcription. Enhancers are well-studied transcription regulators that can enhance target transcripts through DNA loop formation mediated by chromosome folding. The gain or loss of the interaction between an enhancer and its target gene has a critical effect on gene expression. In this study, we analyzed GRO-seq data to identify active enhancers from seven common cancer cell lines and studied the function of these enhancers across multiple cancer types. By constructing an "enhancer effect score" (EES), we found a significant correlation between EES and tumor-infiltrating lymphocytes (TILs) in prostate cancer. Further analysis revealed that androgen receptor (AR) plays an important role in regulating the immune checkpoint gene PVR via its enhancer. These results suggest that AR contributes to prostate cancer aggressiveness by promoting cancer cell immune evasion.

Fine-mapping of a novel premenopausal breast cancer susceptibility locus at Chr4q31.22 in Caucasian women and validation in African and Chinese women

We previously identified a novel breast cancer susceptibility variant on chromosome 4q31.22 locus (rs1429142) conferring risk among women of European ancestry. Here, we report replication of findings, validation of the variant in diverse populations and fine-mapping of the associated locus in Caucasian population. The SNP rs1429142 (C/T, minor allele frequency 18%) showed association for the overall breast cancer risk in Stages 1-4 (n = 4,331 cases/4271 controls; p = 4.35 × 10-8 ; odds ratio, ORC-allele ,1.25), and an elevated risk among premenopausal women (n = 1,503 cases/4271 controls; p = 5.81 × 10-10 ; ORC-allele 1.40) in European populations. SNP rs1429142 was associated with premenopausal breast cancer risk in women of African (T/C; p-value 1.45 × 10-02 ; ORC-allele 1.2) but not from Chinese ancestry. Fine-mapping of the locus revealed several potential causal variants which are present within a single association signal, revealed from the conditional regression analysis. Functional annotation of the potential causal variants revealed three putative SNPs rs1366691, rs1429139 and rs7667633 with active enhancer functions inferred based on histone marks, DNase hypersensitive sites in breast cell line data. These putative variants were bound by transcription factors (C-FOS, STAT1/3 and POL2/3) with known roles in inflammatory pathways. Furthermore, Hi-C data revealed several short-range interactions in the fine-mapped locus harboring the putative variants. The fine mapped locus was predicted to be within a single topologically associated domain, potentially facilitating enhancer-promoter interactions possibly leading to the regulation of nearby genes.

Variants in the 8q24 region associated with risk of breast cancer: Systematic research synopsis and meta-analysis

Breast cancer is a molecularly heterogeneous disorder associated with high lethal malignant tumors among women worldwide. Genetic factors play an important role in breast cancer development. Several single nucleotide polymorphisms in the 8q24 region associated with risk of breast cancer have been identified. Fifteen studies including 32,955 cases and 43,716 controls were collected to conduct a meta-analysis to evaluate the associations between variants in 8q24 region and risk of breast cancer. Our study showed that only rs13281615 is associated with breast cancer risk in this large-scale research synopsis and meta-analysis. Further studies are needed to explore the role of the 8q24 variants in the development of breast cancer.

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Long non-coding RNA PVT1 interacts with MYC and its downstream molecules to synergistically promote tumorigenesis

Numerous studies have shown that non-coding RNAs play crucial roles in the development and progression of various tumor cells. Plasmacytoma variant translocation 1 (PVT1) mainly encodes a long non-coding RNA (lncRNA) and is located on chromosome 8q24.21, which constitutes a fragile site for genetic aberrations. PVT1 is well-known for its interaction with its neighbor MYC, which is a qualified oncogene that plays a vital role in tumorigenesis. In the past several decades, increasing attention has been paid to the interaction mechanism between PVT1 and MYC, which will benefit the clinical treatment and prognosis of patients. In this review, we summarize the coamplification of PVT1 and MYC in cancer, the positive feedback mechanism, and the latest promoter competition mechanism of PVT1 and MYC, as well as how PVT1 participates in the downstream signaling pathway of c-Myc by regulating key molecules. We also briefly describe the treatment prospects and research directions of PVT1 and MYC.

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

Genetic susceptibility to radiation-induced breast cancer after Hodgkin lymphoma

Female Hodgkin lymphoma (HL) patients treated with chest radiotherapy (RT) have a very high risk of breast cancer. The contribution of genetic factors to this risk is unclear. We therefore examined 211 155 germline single-nucleotide polymorphisms (SNPs) for gene-radiation interaction on breast cancer risk in a case-only analysis including 327 breast cancer patients after chest RT for HL and 4671 first primary breast cancer patients. Nine SNPs showed statistically significant interaction with RT on breast cancer risk (false discovery rate, <20%), of which 1 SNP in the PVT1 oncogene attained the Bonferroni threshold for statistical significance. A polygenic risk score (PRS) composed of these SNPs (RT-interaction-PRS) and a previously published breast cancer PRS (BC-PRS) derived in the general population were evaluated in a case-control analysis comprising the 327 chest-irradiated HL patients with breast cancer and 491 chest-irradiated HL patients without breast cancer. Patients in the highest tertile of the RT-interaction-PRS had a 1.6-fold higher breast cancer risk than those in the lowest tertile. Remarkably, we observed a fourfold increased RT-induced breast cancer risk in the highest compared with the lowest decile of the BC-PRS. On a continuous scale, breast cancer risk increased 1.4-fold per standard deviation of the BC-PRS, similar to the effect size found in the general population. This study demonstrates that genetic factors influence breast cancer risk after chest RT for HL. Given the high absolute breast cancer risk in radiation-exposed women, these results can have important implications for the management of current HL survivors and future patients.

Deletion of the murine ortholog of the 8q24 gene desert has anti-cancer effects in transgenic mammary cancer models

Background

The gene desert on human chromosomal band 8q24 harbors multiple genetic variants associated with common cancers, including breast cancer. The locus, including the gene desert and its flanking genes, MYC, PVT1 and FAM84B, is also frequently amplified in human breast cancer. We generated a megadeletion (MD) mouse model lacking 430-Kb of sequence orthologous to the breast cancer-associated region in the gene desert. The goals were to examine the effect of the deletion on mammary cancer development and on transcript level regulation of the candidate genes within the locus.

Methods

The MD allele was engineered using the MICER system in embryonic stem cells and bred onto 3 well-characterized transgenic models for breast cancer, namely MMTV-PyVT, MMTV-neu and C3(1)-TAg. Mammary tumor growth, latency, multiplicity and metastasis were compared between homozygous MD and wild type mice carrying the transgenes. A reciprocal mammary gland transplantation assay was conducted to distinguish mammary cell-autonomous from non-mammary cell-autonomous anti-cancer effects. Gene expression analysis was done using quantitative real-time PCR. Chromatin interactions were evaluated by 3C. Gene-specific patient outcome data were analysed using the METABRIC and TCGA data sets through the cBioPortal website.

Results

Mice homozygous for the MD allele are viable, fertile, lactate sufficiently to nourish their pups, but maintain a 10% lower body weight mainly due to decreased adiposity. The deletion interferes with mammary tumorigenesis in mouse models for luminal and basal breast cancer. In the MMTV-PyVT model the mammary cancer-reducing effects of the allele are mammary cell-autonomous. We found organ-specific effects on transcript level regulation, with Myc and Fam84b being downregulated in mammary gland, prostate and mammary tumor samples. Through analysis using the METABRIC and TCGA datasets, we provide evidence that MYC and FAM84B are frequently co-amplified in breast cancer, but in contrast with MYC, FAM84B is frequently overexpressed in the luminal subtype, whereas MYC activity affect basal breast cancer outcomes.

Conclusion

Deletion of a breast cancer-associated non-protein coding region affects mammary cancer development in 3 transgenic mouse models. We propose Myc as a candidate susceptibility gene, regulated by the gene desert locus, and a potential role for Fam84b in modifying breast cancer development.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5109-8) contains supplementary material, which is available to authorized users.

Elucidating the Underlying Functional Mechanisms of Breast Cancer Susceptibility Through Post-GWAS Analyses

Genome-wide association studies (GWAS) have identified more than 170 single nucleotide polymorphisms (SNPs) associated with the susceptibility to breast cancer. Together, these SNPs explain 18% of the familial relative risk, which is estimated to be nearly half of the total familial breast cancer risk that is collectively explained by low-risk susceptibility alleles. An important aspect of this success has been the access to large sample sizes through collaborative efforts within the Breast Cancer Association Consortium (BCAC), but also collaborations between cancer association consortia. Despite these achievements, however, understanding of each variant's underlying mechanism and how these SNPs predispose women to breast cancer remains limited and represents a major challenge in the field, particularly since the vast majority of the GWAS-identified SNPs are located in non-coding regions of the genome and are merely tags for the causal variants. In recent years, fine-scale mapping studies followed by functional evaluation of putative causal variants have begun to elucidate the biological function of several GWAS-identified variants. In this review, we discuss the findings and lessons learned from these post-GWAS analyses of 22 risk loci. Identifying the true causal variants underlying breast cancer susceptibility and their function not only provides better estimates of the explained familial relative risk thereby improving polygenetic risk scores (PRSs), it also increases our understanding of the biological mechanisms responsible for causing susceptibility to breast cancer. This will facilitate the identification of further breast cancer risk alleles and the development of preventive medicine for those women at increased risk for developing the disease.

A Comprehensive cis-eQTL Analysis Revealed Target Genes in Breast Cancer Susceptibility Loci Identified in Genome-wide Association Studies

Genome-wide association studies (GWASs) have identified more than 150 common genetic loci for breast cancer risk. However, the target genes and underlying mechanisms remain largely unknown. We conducted a cis-expression quantitative trait loci (cis-eQTL) analysis using normal or tumor breast transcriptome data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project. We identified a total of 101 genes for 51 lead variants after combing the results of a meta-analysis of METABRIC and TCGA, and the results from GTEx at a Benjamini-Hochberg (BH)-adjusted p < 0.05. Using luciferase reporter assays in both estrogen-receptor positive (ER⁺) and negative (ER^-) cell lines, we showed that alternative alleles of potential functional single-nucleotide polymorphisms (SNPs), rs11552449 (DCLRE1B), rs7257932 (SSBP4), rs3747479 (MRPS30), rs2236007 (PAX9), and rs73134739 (ATG10), could significantly change promoter activities of their target genes compared to reference alleles. Furthermore, we performed in vitro assays in breast cancer cell lines, and our results indicated that DCLRE1B, MRPS30, and ATG10 played a vital role in breast tumorigenesis via certain disruption of cell behaviors. Our findings revealed potential target genes for associations of genetic susceptibility risk loci and provided underlying mechanisms for a better understanding of the pathogenesis of breast cancer.

Common Genetic Variation and Susceptibility to Ovarian Cancer: Current Insights and Future Directions

In this review, we summarize current progress in the genetic epidemiology of epithelial ovarian cancer (EOC), focusing exclusively on elucidating the role of common germline genetic variation in conferring susceptibility to EOC. We provide an overview of the more than 30 EOC risk loci identified to date by genome-wide association studies (GWAS) and describe the contribution of large-scale, cross-cancer type, custom genotyping projects, such as the OncoArray and the Collaborative Oncological Gene-Environment Study, to locus discovery and replication. We discuss the histotype-specific nature of these EOC risk loci, pleiotropy, or overlapping genetic effects between EOC and other hormone-related cancer types, and the application of findings to polygenic risk prediction for EOC. The second part of the article offers a concise review of primarily laboratory-based studies that have led to the identification of several putative EOC susceptibility genes using common variants at the known EOC risk loci as starting points. More global biological insights emerging from network- and pathway-based analyses of GWAS for EOC susceptibility are also highlighted. Finally, we delve into potential future directions, including the need to identify EOC risk loci in non-European populations and the next generation of GWAS functional studies that are likely to involve genome editing to establish the cell type-specific carcinogenic effects of EOC risk variants Cancer Epidemiol Biomarkers Prev; 27(4); 395-404. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Capture Hi-C identifies putative target genes at 33 breast cancer risk loci

Genome-wide association studies (GWAS) have identified approximately 100 breast cancer risk loci. Translating these findings into a greater understanding of the mechanisms that influence disease risk requires identification of the genes or non-coding RNAs that mediate these associations. Here, we use Capture Hi-C (CHi-C) to annotate 63 loci; we identify 110 putative target genes at 33 loci. To assess the support for these target genes in other data sources we test for associations between levels of expression and SNP genotype (eQTLs), disease-specific survival (DSS), and compare them with somatically mutated cancer genes. 22 putative target genes are eQTLs, 32 are associated with DSS and 14 are somatically mutated in breast, or other, cancers. Identifying the target genes at GWAS risk loci will lead to a greater understanding of the mechanisms that influence breast cancer risk and prognosis.

Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157–3.100), 2.013 (95% CI = 1.227–3.302) and 1.751 (95% CI = 1.073–2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint  = 0.77, 95% CI: 0.67-0.88, pint  = 1.8 × 10-4 ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16-1.59, pint  = 1.9 × 10-5 ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10-4 ) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint  = 0.89, 95% CI: 0.83-0.95, pint  = 5.2 × 10-4 ). While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

Association between 8q24 Gene Polymorphisms and the Risk of Prostate Cancer: A Systematic Review and Meta-Analysis

Though numerous studies have been conducted to investigate the associations between five 8q24 polymorphisms (rs6983267 T>G, rs1447295 C>A, rs16901979 C>A, rs6983561 A>C and rs10090154 C>T) and prostate cancer (PCa) risk, the available results remained contradictory. Therefore, we performed a comprehensive meta-analysis to derive a precise estimation of such associations. We searched electronic databases PubMed, EMBASE, Web of Science and Wan Fang for the relevant available studies up to February 1st, 2017, and 39 articles were ultimately adopted in this meta-analysis. All data were extracted independently by two investigators and recorded in a unified form. The strength of association between 8q24 polymorphisms and PCa susceptibility was evaluated by the pooled odds ratios (ORs) with 95% confidence intervals (CIs). Subgroup analysis was conducted based on ethnicity, source of controls and genotypic method. Overall, a total of 39 articles containing 80 studies were adopted in this meta-analysis. The results of this meta-analysis indicated that five 8q24 polymorphisms above were all related to PCa susceptibility. Besides, in the subgroup analysis by ethnicity, all selected 8q24 polymorphisms were significantly associated with PCa risk in Asian population. In addition, stratification analysis by source of controls showed that significant results were mostly concentrated in the studies' controls from general population. Moreover, when stratified by genotypic method, significant increased PCa risks were found by TaqMan method. Therefore, this meta-analysis demonstrated that 8q24 polymorphisms (rs6983267 T>G, rs1447295 C>A, rs16901979 C>A, rs6983561 A>C and rs10090154 C>T) were associated with the susceptibility to PCa, which held the potential biomarkers for PCa risk.

The association of rs710886 in lncRNA PCAT1 with bladder cancer risk in a Chinese population

OBJECTIVE

The long noncoding RNA PCAT1 is an important gene involved in urinary tumors. In this study, we aimed to explore the association between polymorphisms in PCAT1 and bladder cancer susceptibility.

METHODS

A two-stage case-control study was conducted to assess the association between four tagging SNPs (i.e., rs4871771, rs1902432, rs16901904 and rs710886) and bladder cancer risk. Odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated with unconditional univariate and multivariate logistic regression.

RESULTS

At the first stage of discovery, we identified that SNP rs710886A>G was significantly associated with bladder cancer risk (OR=0.86, 95% CI=0.74-0.99, P=0.046). At the following stage of validation, individuals with GG genotype were found to have a significant reduction in bladder cancer risk compared with those carrying AA genotype (adjusted OR=0.83, 95% CI=0.74-0.93, P=0.001). Furthermore, stratified analyses showed that protective effect of rs710886 was more pronounced in subgroup of age>60 and never smoking, and had little to do with sex. Besides, rs710886 was identified as an eQTL for PCAT1. G allele was consistent with lower PCAT1 expression.

CONCLUSION

This study indicates that genetic variants in lncRNA PCAT1 were associated with bladder cancer susceptibility and the SNP rs710886 may act as a potential biomarker for bladder cancer risk.

Saving the spandrels? Adaptive genomic variation in conservation and fisheries management

As highlighted by many of the papers in this issue, research on the genomic basis of adaptive phenotypic variation in natural populations has made spectacular progress in the past few years, largely due to the advances in sequencing technology and analysis. Without question, the resulting genomic data will improve the understanding of regions of the genome under selection and extend knowledge of the genetic basis of adaptive evolution. What is far less clear, but has been the focus of active discussion, is how such information can or should transfer into conservation practice to complement more typical conservation applications of genetic data. Before such applications can be realized, the evolutionary importance of specific targets of selection relative to the genome-wide diversity of the species as a whole must be evaluated. The key issues for the incorporation of adaptive genomic variation in conservation and management are discussed here, using published examples of adaptive genomic variation associated with specific phenotypes in salmonids and other taxa to highlight practical considerations for incorporating such information into conservation programmes. Scenarios are described in which adaptive genomic data could be used in conservation or restoration, constraints on its utility and the importance of validating inferences drawn from new genomic data before applying them in conservation practice. Finally, it is argued that an excessive focus on preserving the adaptive variation that can be measured, while ignoring the vast unknown majority that cannot, is a modern twist on the adaptationist programme that Gould and Lewontin critiqued almost 40 years ago.