Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation

Creation of signatures and identification of molecular subtypes based on disulfidptosis-related genes for glioblastoma patients' prognosis and immunological activity

BACKGROUND

In recent times, disulfidptosis, an intricate form of cellular demise, has garnered attention due to its impact on prognosis, tumor progression and treatment response. Nevertheless, the exact significance of disulfidptosis-related genes (DisRGs) in glioblastoma (GBM) remains enigmatic.

METHODS

The GEO and TCGA databases provided transcriptional and clinically relevant data on tumor samples, while the GTEx database provided data on healthy tissues. Disulfidptosis-related genes (DisRGs) were procured from previous scholarly investigations. The expression profile of DisRGs was initially scrutinized among patients diagnosed with GBM, subsequent to which their prognostic value was explored. Through consensus clustering, we constructed DisRGs-related clusters and gene subtypes. Our results established that the DisRG-related clusters had differentially expressed genes, resulting in a DisulfidptosisScore model, which had a positive prognostic value.

RESULTS

The differential expression profile of 24 DisRGs between GBM samples and healthy samples was acquired. Through consensus cluster analysis, two distinct disulfidptosis subtypes, namely DisRGcluster A and DisRGcluster B, were identified. Then, the DisulfidptosisScore model including 4 characteristic genes was constructed.Notably, patients with GBM assigned with lower score demonstrated a considerably longer overall survival (OS) compared to those with higher score.

CONCLUSION

We have effectively devised a prognostic model associated with disulfidptosis, presenting autonomous prognostic predictions for patients with GBM. These findings serve as a valuable addition to the current comprehension of disulfidptosis and offer fresh theoretical substantiation for the development of enhanced treatment strategies.

Comprehensive analysis of glycolysis mediated pattern clusters and immune infiltration characterization of tumor microenvironment in triple-negative breast cancer

Background

The involvement of glycolysis in carcinogenesis and the tumor microenvironment is being increasingly supported by the available data. The aim of this work was to develop a triple-negative breast cancer predictive model based on glycolysis.

Methods

Glycolysis mediated pattern clusters were created using the R "ConsensusClusterPlus" package. The variations in the tumor microenvironment between the pattern clusters were examined using the R "GSVA", "ESTIMATE", and "CIBERSORT" package. The risk score and nomogram were established to assess clinical outcomes of patients.

Results

Substantial differences were observed in the immunological landscape between the glycolysis-mediated pattern clusters. When it came to predicting survival and immunotherapy response, the developed risk score showed promising predictive power. Nomogram was designed to be used in therapeutic settings due to its remarkable predictive accuracy.

Conclusions

The immune microenvironment varied among cases of triple-negative breast cancer. The nomogram and the risk score based on glycolysis could both be used to help create more effective treatments.

CRISPR screens identify gene targets at breast cancer risk loci

Background

Genome-wide association studies (GWAS) have identified > 200 loci associated with breast cancer risk. The majority of candidate causal variants are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS.

Results

Here, we show that pooled CRISPR screens are highly effective at identifying GWAS target genes and defining the cancer phenotypes they mediate. Following CRISPR mediated gene activation or suppression, we measure proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We perform 60 CRISPR screens and identify 20 genes predicted with high confidence to be GWAS targets that promote cancer by driving proliferation or modulating the DNA damage response in breast cells. We validate the regulation of a subset of these genes by breast cancer risk variants.

Conclusions

We demonstrate that phenotypic CRISPR screens can accurately pinpoint the gene target of a risk locus. In addition to defining gene targets of risk loci associated with increased breast cancer risk, we provide a platform for identifying gene targets and phenotypes mediated by risk variants.

Chromatin Variants Reveal the Genetic Determinants of Oncogenesis in Breast Cancer

Breast cancer presents as multiple distinct disease entities. Each tumor harbors diverse cell populations defining a phenotypic heterogeneity that impinges on our ability to treat patients. To date, efforts mainly focused on genetic variants to find drivers of inter- and intratumor phenotypic heterogeneity. However, these efforts have failed to fully capture the genetic basis of breast cancer. Through recent technological and analytical approaches, the genetic basis of phenotypes can now be decoded by characterizing chromatin variants. These variants correspond to polymorphisms in chromatin states at DNA sequences that serve a distinct role across cell populations. Here, we review the function and causes of chromatin variants as they relate to breast cancer inter- and intratumor heterogeneity and how they can guide the development of treatment alternatives to fulfill the goal of precision cancer medicine.

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

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.

Health influenced by genetics: A first comprehensive analysis of breast cancer high and moderate penetrance susceptibility genes in the Tunisian population

Significant advances have been made to understand the genetic basis of breast cancer. High, moderate and low penetrance variants have been identified with inter-ethnic variability in mutation frequency and spectrum. Genome wide association studies (GWAS) are widely used to identify disease-associated SNPs. Understanding the functional impact of these risk-SNPs will help the translation of GWAS findings into clinical interventions. Here we aim to characterize the genetic patterns of high and moderate penetrance breast cancer susceptibility genes and to assess the functional impact of non-coding SNPs. We analyzed BRCA1/2, PTEN, STK11, TP53, ATM, BRIP1, CHEK2 and PALB2 genotype data obtained from 135 healthy participants genotyped using Affymetrix Genome-Wide Human SNP-Array 6.0. Haplotype analysis was performed using Haploview.V4.2 and PHASE.V2.1. Population structure and genetic differentiation were assessed using principal component analysis (PCA) and fixation index (FST). Functional annotation was performed using In Silico web-based tools including RegulomeDB and VARAdb. Haplotype analysis showed distinct LD patterns with high levels of recombination and haplotype blocks of moderate to small size. Our findings revealed also that the Tunisian population tends to have a mixed origin with European, South Asian and Mexican footprints. Functional annotation allowed the selection of 28 putative regulatory variants. Of special interest were BRCA1_ rs8176318 predicted to alter the binding sites of a tumor suppressor miRNA hsa-miR-149 and PALB2_ rs120963 located in tumorigenesis-associated enhancer and predicted to strongly affect the binding of P53. Significant differences in allele frequencies were observed with populations of African and European ancestries for rs8176318 and rs120963 respectively. Our findings will help to better understand the genetic basis of breast cancer by guiding upcoming genome wide studies in the Tunisian population. Putative functional SNPs may be used to develop an efficient polygenic risk score to predict breast cancer risk leading to better disease prevention and management.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

Energy homeostasis genes modify the association between serum concentrations of IGF-1 and IGFBP-3 and breast cancer risk

Breast cancer is a multifactorial disease in which the interplay among multiple risk factors remains unclear. Energy homeostasis genes play an important role in carcinogenesis and their interactions with the serum concentrations of IGF-1 and IGFBP-3 on the risk of breast cancer have not yet been investigated. The aim of this study was to assess the modifying effect of the genetic variation in some energy homeostasis genes on the association of serum concentrations of IGF-1 and IGFBP-3 with breast cancer risk. We analyzed 78 SNPs from 10 energy homeostasis genes in premenopausal women from the 4-Corner’s Breast Cancer Study (61 cases and 155 controls) and the Mexico Breast Cancer Study (204 cases and 282 controls). After data harmonization, 71 SNPs in HWE were included for interaction analysis. Two SNPs in two genes (MBOAT rs13272159 and NPY rs16131) showed an effect modification on the association between IGF-1 serum concentration and breast cancer risk (P_interaction < 0.05, adjusted P_interaction < 0.20). In addition, five SNPs in three genes (ADIPOQ rs182052, rs822391 and rs7649121, CARTPT rs3846659, and LEPR rs12059300) had an effect modification on the association between IGFBP-3 serum concentration and breast cancer risk (P_interaction < 0.05, adjusted P_interaction < 0.20). Our findings showed that variants of energy homeostasis genes modified the association between the IGF-1 or IGFBP-3 serum concentration and breast cancer risk in premenopausal women. These findings contribute to a better understanding of this multifactorial pathology.

Deciphering the Role of 3D Genome Organization in Breast Cancer Susceptibility

Cancer risk by environmental exposure is modulated by an individual's genetics and age at exposure. This age-specific period of susceptibility is referred to as the "Window of Susceptibility" (WOS). Rats have a similar WOS for developing breast cancer. A previous study in rat identified an age-specific long-range regulatory interaction for the cancer gene, Pappa, that is associated with breast cancer susceptibility. However, the global role of three-dimensional genome organization and downstream gene expression programs in the WOS is not known. Therefore, we generated Hi-C and RNA-seq data in rat mammary epithelial cells within and outside the WOS. To systematically identify higher-order changes in 3D genome organization, we developed NE-MVNMF that combines network enhancement followed by multitask non-negative matrix factorization. We examined three-dimensional genome organization dynamics at the level of individual loops as well as higher-order domains. Differential chromatin interactions tend to be associated with differentially up-regulated genes with the WOS and recapitulate several human SNP-gene interactions associated with breast cancer susceptibility. Our approach identified genomic blocks of regions with greater overall differences in contact count between the two time points when the cluster assignments change and identified genes and pathways implicated in early carcinogenesis and cancer treatment. Our results suggest that WOS-specific changes in 3D genome organization are linked to transcriptional changes that may influence susceptibility to breast cancer.

Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)⁺ progesterone receptor (PR)⁺ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit. IMPLICATIONS: Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.

Biological effects and regulation of IGFBP5 in breast cancer

The insulin-like growth factor receptor (IGF1R) pathway plays an important role in cancer progression. In breast cancer, the IGF1R pathway is linked to estrogen-dependent signaling. Regulation of IGF1R activity is complex and involves the actions of its ligands IGF1 and IGF2 and those of IGF-binding proteins (IGFBPs). Six IGFBPs are known that share the ability to form complexes with the IGFs, by which they control the bioavailability of these ligands. Besides, each of the IGFBPs have specific features. In this review, the focus lies on the biological effects and regulation of IGFBP5 in breast cancer. In breast cancer, estrogen is a critical regulator of IGFBP5 transcription. It exerts its effect through an intergenic enhancer loop that is part of the chromosomal breast cancer susceptibility region 2q35. The biological effects of IGFBP5 depend upon the cellular context. By inhibiting or promoting IGF1R signaling, IGFBP5 can either act as a tumor suppressor or promoter. Additionally, IGFBP5 possesses IGF-independent activities, which contribute to the complexity by which IGFBP5 interferes with cancer cell behavior.

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.

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).

Systematic interrogation of mutation groupings reveals divergent downstream expression programs within key cancer genes

Background

Genes implicated in tumorigenesis often exhibit diverse sets of genomic variants in the tumor cohorts within which they are frequently mutated. For many genes, neither the transcriptomic effects of these variants nor their relationship to one another in cancer processes have been well-characterized. We sought to identify the downstream expression effects of these mutations and to determine whether this heterogeneity at the genomic level is reflected in a corresponding heterogeneity at the transcriptomic level.

Results

By applying a novel hierarchical framework for organizing the mutations present in a cohort along with machine learning pipelines trained on samples’ expression profiles we systematically interrogated the signatures associated with combinations of mutations recurrent in cancer. This allowed us to catalogue the mutations with discernible downstream expression effects across a number of tumor cohorts as well as to uncover and characterize over a hundred cases where subsets of a gene’s mutations are clearly divergent in their function from the remaining mutations of the gene. These findings successfully replicated across a number of disease contexts and were found to have clear implications for the delineation of cancer processes and for clinical decisions.

Conclusions

The results of cataloguing the downstream effects of mutation subgroupings across cancer cohorts underline the importance of incorporating the diversity present within oncogenes in models designed to capture the downstream effects of their mutations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04147-y.

Identifying high-confidence capture Hi-C interactions using CHiCANE

The ability to identify regulatory interactions that mediate gene expression changes through distal elements, such as risk loci, is transforming our understanding of how genomes are spatially organized and regulated. Capture Hi-C (CHi-C) is a powerful tool to delineate such regulatory interactions. However, primary analysis and downstream interpretation of CHi-C profiles remains challenging and relies on disparate tools with ad-hoc input/output formats and specific assumptions for statistical modeling. Here we present a data processing and interaction calling toolkit (CHiCANE), specialized for the analysis and meaningful interpretation of CHi-C assays. In this protocol, we demonstrate applications of CHiCANE to region capture Hi-C (rCHi-C) and promoter capture Hi-C (pCHi-C) libraries, followed by quality assessment of interaction peaks, as well as downstream analysis specific to rCHi-C and pCHi-C to aid functional interpretation. For a typical rCHi-C/pCHi-C dataset this protocol takes up to 3 d for users with a moderate understanding of R programming and statistical concepts, although this is dependent on dataset size and compute power available. CHiCANE is freely available at https://cran.r-project.org/web/packages/chicane .

VARAdb: a comprehensive variation annotation database for human

With the study of human diseases and biological processes increasing, a large number of non-coding variants have been identified and facilitated. The rapid accumulation of genetic and epigenomic information has resulted in an urgent need to collect and process data to explore the regulation of non-coding variants. Here, we developed a comprehensive variation annotation database for human (VARAdb, http://www.licpathway.net/VARAdb/), which specifically considers non-coding variants. VARAdb provides annotation information for 577,283,813 variations and novel variants, prioritizes variations based on scores using nine annotation categories, and supports pathway downstream analysis. Importantly, VARAdb integrates a large amount of genetic and epigenomic data into five annotation sections, which include ‘Variation information’, ‘Regulatory information’, ‘Related genes’, ‘Chromatin accessibility’ and ‘Chromatin interaction’. The detailed annotation information consists of motif changes, risk SNPs, LD SNPs, eQTLs, clinical variant-drug-gene pairs, sequence conservation, somatic mutations, enhancers, super enhancers, promoters, transcription factors, chromatin states, histone modifications, chromatin accessibility regions and chromatin interactions. This database is a user-friendly interface to query, browse and visualize variations and related annotation information. VARAdb is a useful resource for selecting potential functional variations and interpreting their effects on human diseases and biological processes.

Supervariants identification for breast cancer

In genome-wide association studies, signals associated with rare variants and interactions between genes are hard to detect even when the sample size is in tens of thousands. To overcome these problems, we examine the concept of supervariant. Like the classic concept of the gene, a supervariant is a combination of alleles in multiple loci, but the contributing loci can be anywhere in the genome. We hypothesize that supervariants are easy to detect and the aggregated signals are more stable in their associations with the disease than that from a single nucleoid polymorphism. Using the UK Biobank databases, we develop a ranking and aggregation method for identifying supervariants. Specifically, we examine 9,377 breast cancer cases with 46,861 controls matched by sex and age. In our simulations, the use of supervariants outperforms single-nucleotide polymorphism-based association method in detecting rare variants and signals with interactive structure. In real data analysis, we identify supervariants on Chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 16, and 22 which cover previously reported loci that have associations with breast or other cancers, and several novel loci on Chromosomes 2, 5, 9, and 12. These findings demonstrate the validity of supervariants and its potential of discovering replicable and novel results for complex disease.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure.. [DOI: 10.1101/2020.10.06.328567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging. In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants. Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

eQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene

Breast cancer genome-wide association studies (GWASs) have identified 150 genomic risk regions containing more than 13,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements. However, the genes underlying breast cancer risk associations are largely unknown. Here, we used genetic colocalization analysis to identify loci at which gene expression could potentially explain breast cancer risk phenotypes. Using data from the Breast Cancer Association Consortium (BCAC) and quantitative trait loci (QTL) from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Project (TCGA), we identify shared genetic relationships and reveal novel associations between cancer phenotypes and effector genes. Seventeen genes, including NTN4, were identified as potential mediators of breast cancer risk. For NTN4, we showed the rs61938093 CCV at this region was located within an enhancer element that physically interacts with the NTN4 promoter, and the risk allele reduced NTN4 promoter activity. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. These data provide evidence linking risk-associated variation to genes that may contribute to breast cancer predisposition.

The Multi-Faced Role of PAPP-A in Post-Partum Breast Cancer: IGF-Signaling is Only the Beginning

Insulin-like growth factor (IGF) signaling and control of local bioavailability of free IGF by the IGF binding proteins (IGFBP) are important regulators of both mammary development and breast cancer. A recent genome-wide association study (GWAS) identified small nucleotide polymorphisms that reduce the expression of IGFBP-5 as a risk factor of developing breast cancer. This observation suggests that genetic alterations leading to a decreased level of IGFBP-5 may also contribute to breast cancer. In the current review, we focus on Pregnancy-Associated Plasma Protein A (PAPP-A), a protease involved in the degradation of IGFBP-5. PAPP-A is overexpressed in the majority of breast cancers but its role in cancer has only begun to be explored. More specifically, this review aims at highlighting the role of post-partum involution in the oncogenic function of PAPP-A. Notably, we summarize recent studies indicating that PAPP-A plays a role not only in the degradation of IGFBP-5 but also in the deposition of collagen and activation of the collagen receptor discoidin 2 (DDR2) during post-partum involution. Finally, considering the immunosuppressive microenvironment of post-partum involution, we also discuss the unexpected finding made in Ewing Sarcoma that PAPP-A plays a role in immune evasion. While the immunosuppressive role of PAPP-A in breast cancer remains to be determined, collectively these studies highlight the multifaced role of PAPP-A in cancer that extends well beyond its effect on IGF-signaling.

Gene expression of the IGF hormones and IGF binding proteins across time and tissues in a model reptile

The insulin and insulin-like signaling (IIS) network regulates cellular processes including pre- and postnatal growth, cellular development, wound healing, reproduction, and longevity. Despite their importance in the physiology of vertebrates, the study of the specific functions of the top regulators of the IIS network, insulin-like growth factors (IGFs) and IGF binding proteins (IGFBPs), has been mostly limited to a few model organisms. To expand our understanding of this network, we performed quantitative gene expression of IGF hormones in liver and qualitative expression of IGFBPs across tissues and developmental stages in a model reptile, the brown anole lizard (Anolis sagrei). We found that lizards express IGF2 across all life stages (preoviposition embryos to adulthood) and at a higher level than IGF1, which is opposite to patterns seen in laboratory rodents but similar to those seen in humans and other vertebrate models. IGFBP expression was ubiquitous across tissues (brain, gonad, heart, liver, skeletal muscle, tail, and regenerating tail) in adults, apart from IGFBP5, which was variable. These findings provide an essential foundation for further developing the anole lizard as a physiological and biomedical reptile model, as well as expanding our understanding of the function of the IIS network across species.

ABC-GWAS: Functional Annotation of Estrogen Receptor-Positive Breast Cancer Genetic Variants

Over the past decade, hundreds of genome-wide association studies (GWAS) have implicated genetic variants in various diseases, including cancer. However, only a few of these variants have been functionally characterized to date, mainly because the majority of the variants reside in non-coding regions of the human genome with unknown function. A comprehensive functional annotation of the candidate variants is thus necessary to fill the gap between the correlative findings of GWAS and the development of therapeutic strategies. By integrating large-scale multi-omics datasets such as the Cancer Genome Atlas (TCGA) and the Encyclopedia of DNA Elements (ENCODE), we performed multivariate linear regression analysis of expression quantitative trait loci, sequence permutation test of transcription factor binding perturbation, and modeling of three-dimensional chromatin interactions to analyze the potential molecular functions of 2,813 single nucleotide variants in 93 genomic loci associated with estrogen receptor-positive breast cancer. To facilitate rapid progress in functional genomics of breast cancer, we have created "Analysis of Breast Cancer GWAS" (ABC-GWAS), an interactive database of functional annotation of estrogen receptor-positive breast cancer GWAS variants. Our resource includes expression quantitative trait loci, long-range chromatin interaction predictions, and transcription factor binding motif analyses to prioritize putative target genes, causal variants, and transcription factors. An embedded genome browser also facilitates convenient visualization of the GWAS loci in genomic and epigenomic context. ABC-GWAS provides an interactive visual summary of comprehensive functional characterization of estrogen receptor-positive breast cancer variants. The web resource will be useful to both computational and experimental biologists who wish to generate and test their hypotheses regarding the genetic susceptibility, etiology, and carcinogenesis of breast cancer. ABC-GWAS can also be used as a user-friendly educational resource for teaching functional genomics. ABC-GWAS is available at http://education.knoweng.org/abc-gwas/.

Overexpression of IGFBP5 Enhances Radiosensitivity Through PI3K-AKT Pathway in Prostate Cancer

Background

Radiotherapy is the main treatment for localized prostate cancer. The therapeutic effects of radiotherapy are highly dependent on radiosensitivity of target tumors. Here, we investigated the impact of insulin-like growth factor-binding protein 5 (IGFBP5) on irradiation therapy in prostate cancer.

Methods

IGFBP5 gene was overexpressed in human prostate cancer cell lines, PC3 and DU145, with transfection of lentivirus expression vector. Radiosensitivity of the cell lines was assessed with colony formation, cell cycle and cell proliferation assays. The expression of proteins associated with the PI3K-AKT pathway was determined by Western blotting. The effect of IGFBP5 knockdown on PI3K-AKT pathway was tested using PI3K inhibitor.

Results

Higher expression of IGFBP5 improved the efficacy of radiotherapy for prostate cancer patients. The effects of IGFBP5 were linked to the PI3K-AKT signaling pathway. Overexpression of IGFBP5 enhanced radiosensitivity and induced G2/M phase arrest in prostate cancer cells. In contrast, it decreased PI3K, p-AKT expression and cell viability. These effects were reversed by IGFBP5 knockdown.

Conclusion

Our results reveal that IGFBP5 regulates radiosensitivity in prostate cancer via the PI3K-AKT pathway. It is, therefore, a potential biomarker of tumors that influences the therapeutic effect of radiotherapy.

Postpartum Involution and Cancer: An Opportunity for Targeted Breast Cancer Prevention and Treatments?

Childbirth at any age confers a transient increased risk for breast cancer in the first decade postpartum and this window of adverse effect extends over two decades in women with late-age first childbirth (>35 years of age). Crossover to the protective effect of pregnancy is dependent on age at first pregnancy, with young mothers receiving the most benefit. Furthermore, breast cancer diagnosis during the 5- to 10-year postpartum window associates with high risk for subsequent metastatic disease. Notably, lactation has been shown to be protective against breast cancer incidence overall, with varying degrees of protection by race, multiparity, and lifetime duration of lactation. An effect for lactation on breast cancer outcome after diagnosis has not been described. We discuss the most recent data and mechanistic insights underlying these epidemiologic findings. Postpartum involution of the breast has been identified as a key mediator of the increased risk for metastasis in women diagnosed within 5-10 years of a completed pregnancy. During breast involution, immune avoidance, increased lymphatic network, extracellular matrix remodeling, and increased seeding to the liver and lymph node work as interconnected pathways, leading to the adverse effect of a postpartum diagnosis. We al discuss a novel mechanism underlying the protective effect of breastfeeding. Collectively, these mechanistic insights offer potential therapeutic avenues for the prevention and/or improved treatment of postpartum breast cancer.

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

BACKGROUND

Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.

METHODS

Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.

RESULTS

Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.

CONCLUSIONS

Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

Candidate Causal Variants at the 8p12 Breast Cancer Risk Locus Regulate DUSP4

Genome-wide association studies have revealed a locus at 8p12 that is associated with breast cancer risk. Fine-mapping of this locus identified 16 candidate causal variants (CCVs). However, as these variants are intergenic, their function is unclear. To map chromatin looping from this risk locus to a previously identified candidate target gene, DUSP4, we performed chromatin conformation capture analyses in normal and tumoural breast cell lines. We identified putative regulatory elements, containing CCVs, which looped to the DUSP4 promoter region. Using reporter gene assays, we found that the risk allele of CCV rs7461885 reduced the activity of a DUSP4 enhancer element, consistent with the function of DUSP4 as a tumour suppressor gene. Furthermore, the risk allele of CCV rs12155535, located in another DUSP4 enhancer element, was negatively correlated with looping of this element to the DUSP4 promoter region, suggesting that this allele would be associated with reduced expression. These findings provide the first evidence that CCV risk alleles downregulate DUSP4 expression, suggesting that this gene is a regulatory target of the 8p12 breast cancer risk locus.

Chromatin interactome mapping at 139 independent breast cancer risk signals

BACKGROUND

Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression.

RESULTS

We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region.

CONCLUSIONS

Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

Insulin-Like Growth Factor Binding Protein-5 in Physiology and Disease

Insulin-like growth factor (IGF) signaling is regulated by a conserved family of IGF binding proteins (IGFBPs) in vertebrates. Among the six distinct types of IGFBPs, IGFBP-5 is the most highly conserved across species and has the broadest range of biological activities. IGFBP-5 is expressed in diverse cell types, and its expression level is regulated by a variety of signaling pathways in different contexts. IGFBP-5 can exert a range of biological actions including prolonging the half-life of IGFs in the circulation, inhibition of IGF signaling by competing with the IGF-1 receptor for ligand binding, concentrating IGFs in certain cells and tissues, and potentiation of IGF signaling by delivery of IGFs to the IGF-1 receptor. IGFBP-5 also has IGF-independent activities and is even detected in the nucleus. Its broad biological activities make IGFBP-5 an excellent representative for understanding IGFBP functions. Despite its evolutionary conservation and numerous biological activities, knockout of IGFBP-5 in mice produced only a negligible phenotype. Recent research has begun to explain this paradox by demonstrating cell type-specific and physiological/pathological context-dependent roles for IGFBP-5. In this review, we survey and discuss what is currently known about IGFBP-5 in normal physiology and human disease. Based on recent in vivo genetic evidence, we suggest that IGFBP-5 is a multifunctional protein with the ability to act as a molecular switch to conditionally regulate IGF signaling.

Cistrome Partitioning Reveals Convergence of Somatic Mutations and Risk Variants on Master Transcription Regulators in Primary Prostate Tumors

Thousands of noncoding somatic single-nucleotide variants (SNVs) of unknown function are reported in tumors. Partitioning the genome according to cistromes reveals the enrichment of somatic SNVs in prostate tumors as opposed to adjacent normal tissue cistromes of master transcription regulators, including AR, FOXA1, and HOXB13. This parallels enrichment of prostate cancer genetic predispositions over these transcription regulators' tumor cistromes, exemplified at the 8q24 locus harboring both risk variants and somatic SNVs in cis-regulatory elements upregulating MYC expression. However, Massively Parallel Reporter Assays reveal that few SNVs can alter the transactivation potential of individual cis-regulatory elements. Instead, similar to inherited risk variants, SNVs accumulate in cistromes of master transcription regulators required for prostate cancer development.

Collagen and PAPP-A in the Etiology of Postpartum Breast Cancer

Pregnancy has a dual effect on the risk of breast cancer. On one hand, pregnancy at a young age is known to be protective. However, pregnancy is also associated with a transient increased risk of breast cancer. For women that have children after the age of 30, the risk remains higher than women who never had children for decades. Involution of the breast has been identified as a window of mammary development associated with the adverse effect of pregnancy. In this review, we summarize the current understanding of the role of involution and describe the role of collagen in this setting. We also discuss the role of a collagen-dependent protease, pappalysin-1, in postpartum breast cancer and its role in activating both insulin-like growth factor signaling and discoidin domain collagen receptor 2, DDR2. Together, these novel advances in our understanding of postpartum breast cancer open the way to targeted therapies against this aggressive breast cancer sub-type.

The Cancer-Associated Genetic Variant Rs3903072 Modulates Immune Cells in the Tumor Microenvironment

Genome-wide association studies (GWAS) have hitherto identified several germline variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of noncoding GWAS SNPs using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast-cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor-infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3' end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant could regulate a gene not only in the cell of cancer origin but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells.

Copy number alternations of the 17q23-rs6504950 locus are associated with advanced breast cancers in Taiwanese women

Objective:

Breast cancer is one of the most common malignancies and a leading cause of cancer-related death in women worldwide. Both hormone-related factors and genetic aberrations could cause breast cancer. We investigated copy number alternations (CNAs) on four breast cancer-susceptible loci, namely 2q35-rs13387042, 3p24-rs4973768, 17q23-rs6504950, and fibroblast growth factor receptor 2 (FGFR2)-rs2981578, in Taiwanese women.

Patients and Methods:

Breast cancer tissues and blood samples from 66 patients and their clinical data were collected from a human biobank. The copy numbers of the germline samples (from blood) and cancer tissues from each patient on the susceptible loci – 2q35, 3p24, 17q23, and FGFR2 – were obtained using TaqMan probes in the Applied Biosystems Inc., (ABI) StepOnePlus Real-Time Polymerase Chain Reaction instrument and CopyCaller^® Software v1.0 (ABI, CA, USA).

Results:

The mean copy numbers output by CopyCaller^® Software v1.0 of the cancer tissues on these susceptible loci (2q35, 3p24, 17q23, and FGFR2) from the 66 patients were higher than those of the blood samples (2.0 vs. 1.9); however, significantly higher copy numbers for cancer tissues compared with germline samples were discovered only on 2q35-rs13387042 (P = 0.035). In addition, patients with advanced breast cancers had relatively many CNAs between their cancer tissues and germline samples on 17q23-rs6504950 (P = 0.008). Multivariate analysis revealed that the risk factor for patients with advanced breast cancers was CNAs between cancer tissues and germline samples on 17q23-rs6504950 (odds ratio = 13.337, 95% confidence interval: 1.525–122.468).

Conclusions:

CNAs on 17q23-rs6504950 between cancer tissues and germline samples could affect cancer progression in Taiwanese women with breast cancer. Further investigations regarding the role of CNAs on 17q23-rs6504950 in cancer progression are necessary to elucidate the pathogenesis of breast cancer.

Parity predisposes breasts to the oncogenic action of PAPP-A and activation of the collagen receptor DDR2

Background

Women who had children at a young age (less than 25) show a reduced overall risk of breast cancer. However, epidemiological studies showed that for all other women, pregnancy increases the risk of breast cancer and the risk remains higher for decades. Further, even in women who had children at a young age, there is a transient increase risk that peaks 6 years after pregnancy. Women diagnosed with breast cancer following pregnancy show a higher rate of metastasis. Yet, the factors that increase the predisposition of post-partum breasts to more aggressive cancers remain unknown. Pregnancy-associated plasma protein A (PAPP-A) is a secreted protease that is overexpressed in more than 70% of breast cancers. However, PAPP-A is a collagen-dependent oncogene. We initiated this study to test the effect of PAPP-A on the predisposition of post-partum breasts.

Methods

We used PAPP-A mouse models for the analysis of its effect on virgin, involuting, or post-partum mammary glands. We performed second-harmonic generation microscopy for the analysis of collagen, defined tumor-associated collagen signature (TACS), the rate of mammary tumors, and the status of the collagen-DDR2-Snail axis of metastasis. We knockdown DDR2 by CRISPR and performed invasion assays. A transcriptomic approach was used to define a PAPP-A and parity-dependent genetic signature and assess its correlation with breast cancer recurrence in humans.

Results

We confirmed that post-partum mammary glands have a higher level of collagen than virgin glands and that this collagen is characterized by an anti-proliferative architecture. However, PAPP-A converts the anti-proliferative post-partum collagen into pro-tumorigenic collagen. We show that PAPP-A activates the collagen receptor DDR2 and metastasis. Further, deletion of DDR2 by CRISPR abolished the effect of PAPP-A on invasion. We defined a PAPP-A-driven genetic signature that identifies patients at higher risk of metastasis.

Conclusions

These results support the notion that information about pregnancy may be critical in the prognosis of breast cancer as passage through a single pregnancy predisposes to the oncogenic action of PAPP-A. Our data indicate that history of pregnancy combined with the expression of PAPP-A-driven genetic signature may be useful to identify patients at higher risk of metastatic disease.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1142-z) contains supplementary material, which is available to authorized users.

Higher order genomic organization and epigenetic control maintain cellular identity and prevent breast cancer

Cells establish and sustain structural and functional integrity of the genome to support cellular identity and prevent malignant transformation. In this review, we present a strategic overview of epigenetic regulatory mechanisms including histone modifications and higher order chromatin organization (HCO) that are perturbed in breast cancer onset and progression. Implications for dysfunctions that occur in hormone regulation, cell cycle control, and mitotic bookmarking in breast cancer are considered, with an emphasis on epithelial-to-mesenchymal transition and cancer stem cell activities. The architectural organization of regulatory machinery is addressed within the contexts of translating cancer-compromised genomic organization to advances in breast cancer risk assessment, diagnosis, prognosis, and identification of novel therapeutic targets with high specificity and minimal off target effects.

Functional Variant rs4442975 Modulating FOXA1 Binding Affinity Can Influence Bone Marrow Suppression during Neoadjuvant Chemotherapy for Luminal A Type Breast Cancer

The expression of the transcription factor FOXA1 is associated with the prognosis of estrogen receptor (ER)-positive breast cancer, and the genetic variant rs4442975 can affect FOXA1 function. Therefore, we investigated the association between rs4442975 and the efficacy of neoadjuvant chemotherapy for luminal A type breast cancer and evaluated its toxic side effects in a Chinese population. One hundred seventy-five patients with luminal A type breast cancer receiving neoadjuvant chemotherapy with a combination protocol of epirubicin and docetaxel (ET protocol) were enrolled in the study. Genotyping was performed in a randomized manner to identify candidate genetic variants. Unconditional logistic regression analysis was used to analyze the association of the variant with the efficacy and side effects of neoadjuvant chemotherapy. The results did not reveal any positive association with the efficacy of neoadjuvant chemotherapy, with an odds ratio (OR) of 0.73 (95% confidence interval = 0.27-1.94) in the additive model. However, analysis of the toxic side effects of neoadjuvant chemotherapy showed that rs4442975 was associated with bone marrow suppression, with an OR of 0.38 (95% confidence interval = 0.17-0.73, p = 0.005) in the dominant model. In summary, the functional genetic variant rs4442975 was associated with bone marrow suppression during neoadjuvant chemotherapy for luminal A type breast cancer. These results may help establish reliable molecular markers for predicting the prognosis of personalized treatment for luminal A type breast cancer and thereby contribute to the development of appropriate therapies.

Interaction between genetic ancestry and common breast cancer susceptibility variants in Colombian women

Latino women show lower incidences of breast cancer (BC) than non-Hispanic whites. Large-scale genetic association studies have identified variants robustly associated with BC risk in European women. We examine here the relevance of these variants to Colombian BC and possible interactions with genetic ancestry. Native American, European and African proportions were estimated for 1022 Colombian BC cases and 1023 controls. Logistic regression was applied to assess the association between 78 variants and BC risk and interactions between the variants and ancestry proportions. We constructed a multifactorial risk score combining established BC risk factors, associated risk variants and individual ancestry proportions. Each 1% increase in the Native American proportion translated into a 2.2% lower BC risk (95% CI: 1.4-2.9). Thirteen variants were associated with BC in Colombian women, with allele frequencies and risk effects partially different from European women. Ancestry proportions moderated the risk effects of two variants. The ability of Native American proportions to separate Colombian cases and controls (area-under-the-curve (AUC) = 0.61) was similar to the discriminative ability of family history of BC in first-degree female relatives (AUC = 0.58) or the combined effect of all 13 associated risk variants (AUC = 0.57). Our findings demonstrate ample potential for individualized BC prevention in Hispanic women taking advantage of individual Native American proportions, information on established susceptibility factors and recently identified common risk variants.

Genetics in ankylosing spondylitis - Current state of the art and translation into clinical outcomes

Ankylosing spondylitis (AS) is the prototypic form of axial spondyloarthritis (axSpA). It is highly heritable, with studies conducted in twins and in unrelated cases and controls showing that the heritability for AS is much higher than those for inflammatory bowel disease or rheumatoid arthritis. To date, 116 loci have been identified, contributing to 28% of the genetic variation in the disease. These loci provide important clues into pathogenic pathways in the disease that have led to therapeutic advances such as the repositioning of IL-17 inhibitors in the disease. Much more research is currently required to determine the functional mechanisms by which the genetic associations operate, from which it is likely that novel therapeutic approaches will be developed.

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 transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Methamphetamine exposure triggers apoptosis and autophagy in neuronal cells by activating the C/EBPβ-related signaling pathway

Methamphetamine (Meth) is a widely abused psychoactive drug that primarily damages the nervous system, notably causing dopaminergic neuronal apoptosis. CCAAT-enhancer binding protein (C/EBPβ) is a transcription factor and an important regulator of cell apoptosis and autophagy. Insulin-like growth factor binding protein (IGFBP5) is a proapoptotic factor that mediates Meth-induced neuronal apoptosis, and Trib3 (tribbles pseudokinase 3) is an endoplasmic reticulum (ER) stress-inducible gene involved in autophagic cell death through the mammalian target of rapamycin (mTOR) signaling pathway. To test the hypothesis that C/EBPβ is involved in Meth-induced IGFBP5-mediated neuronal apoptosis and Trib3-mediated neuronal autophagy, we measured the protein expression of C/EBPβ after Meth exposure and evaluated the effects of silencing C/EBPβ, IGFBP5, or Trib3 on Meth-induced apoptosis and autophagy in neuronal cells and in the rat striatum after intrastriatal Meth injection. We found that, at relatively high doses, Meth exposure increased C/EBPβ protein expression, which was accompanied by increased neuronal apoptosis and autophagy; triggered the IGFBP5-mediated, p53-up-regulated modulator of apoptosis (PUMA)-related mitochondrial apoptotic signaling pathway; and stimulated the Trib3-mediated ER stress signaling pathway through the Akt-mTOR signaling axis. We also found that autophagy is an early response to Meth-induced stress upstream of apoptosis and plays a detrimental role in Meth-induced neuronal cell death. These results suggest that Meth exposure induces C/EBPβ expression, which plays an essential role in the neuronal apoptosis and autophagy induced by relatively high doses of Meth; however, relatively low concentrations of Meth did not change the expression of C/EBPβ in vitro. Further studies are needed to elucidate the role of C/EBPβ in low-dose Meth-induced neurotoxicity.-Xu, X., Huang, E., Luo, B., Cai, D., Zhao, X., Luo, Q., Jin, Y., Chen, L., Wang, Q., Liu, C., Lin, Z., Xie, W.-B., Wang, H. Methamphetamine exposure triggers apoptosis and autophagy in neuronal cells by activating the C/EBPβ-related signaling pathway.

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.

The Post-GWAS Era: From Association to Function

During the past 12 years, genome-wide association studies (GWASs) have uncovered thousands of genetic variants that influence risk for complex human traits and diseases. Yet functional studies aimed at delineating the causal genetic variants and biological mechanisms underlying the observed statistical associations with disease risk have lagged. In this review, we highlight key advances in the field of functional genomics that may facilitate the derivation of biological meaning post-GWAS. We highlight the evidence suggesting that causal variants underlying disease risk often function through regulatory effects on the expression of target genes and that these expression effects might be modest and cell-type specific. We moreover discuss specific studies as proof-of-principle examples for current statistical, bioinformatic, and empirical bench-based approaches to downstream elucidation of GWAS-identified disease risk loci.

Common breast cancer risk alleles and risk assessment: a study on 35 441 individuals from the Danish general population

Background

We hypothesized that common breast cancer risk alleles are associated with incidences of breast cancer and other cancers in the general population, and identify low risk women among those invited for screening mammography.

Participants and Methods

About 35 441 individuals from the Danish general population were followed in Danish health registries for up to 21 years after blood sampling. After genotyping 72 breast cancer risk loci, each with 0–2 alleles, the sum for each individual was calculated. We used the simple allele sum instead of the conventional polygenic risk score, as it is likely more sensitive in detecting associations with risks of other endpoints than breast cancer.

Results

Breast cancer incidence in the 19 010 women was increased across allele sum quintiles (log-rank trend test; P = 1×10 − 12), but not incidence of other cancers (P = 0.41). Age- and study-adjusted hazard ratio for the fifth versus the first allele sum quintile was 1.82 (95% confidence interval; 1.53–2.18). Corresponding hazard ratios per allele were 1.04 (1.03–1.05) and 1.05 (1.02–1.08) for breast cancer incidence and mortality, similar across risk factors. In 50-year-old women, the starting age for screening mammography in Denmark, the average 5-year breast cancer risk was 1.5%, overall and 1.1%, 1.4%, 1.6%, 1.7%, 2.1%, for the first through fifth quintile, respectively. Based on age, nulliparity, familial history, and allele sum, 25% of women aged 50–69 years, and 94% of women aged 40–49 years, had absolute 5-year breast cancer risks ≤ 1.5%. Using polygenic risk score led to similar results.

Conclusion

Common breast cancer risk alleles are associated with incidence and mortality of breast cancer in the general population, but not with other cancers. After including breast cancer allele sum in risk assessment, 25% of women currently being offered screening mammography had an absolute 5-year risk below the cutoff of average risk for a 50-year-old woman.

ER-positive breast cancer cells are poised for RET-mediated endocrine resistance

The RET tyrosine kinase signaling pathway is involved in the development of endocrine resistant ER+ breast cancer. However, we know little about how ER+ cells activate RET signaling and initiate an endocrine resistant phenotype. Here we show that both ER+ endocrine resistant and sensitive breast cancers have a functional RET tyrosine kinase signaling pathway, but that endocrine sensitive breast cancer cells lack RET ligands that are necessary to drive endocrine resistance. Transcription of one RET ligand, GDNF, is necessary and sufficient to confer resistance in the ER+ MCF-7 cell line. Endogenous GDNF produced by endocrine resistant cells is translated, secreted into the media, and activates RET signaling in nearby cells. In patients, RET ligand expression predicts responsiveness to endocrine therapies and correlates with survival. Collectively, our findings show that ER+ tumor cells are "poised" for RET mediated endocrine resistance, expressing all components of the RET signaling pathway, but endocrine sensitive cells lack high expression of RET ligands that are necessary to initiate the resistance phenotype.

Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future

Breast cancer is the most common cancer among women in the United States, with up to 30% of those diagnosed displaying a family history of breast cancer. To date, 18% of the familial risk of breast cancer can be explained by SNPs. This review summarizes the discovery of risk-associated SNPs using candidate gene and genome-wide association studies (GWAS), including discovery and replication in large collaborative efforts such as The Collaborative Oncologic Gene-environment Study and OncoArray. We discuss the evolution of GWAS studies, efforts to discover additional SNPs, and methods for identifying causal variants. We summarize findings associated with overall breast cancer, pathologic subtypes, and mutation carriers (BRCA1, BRCA2, and CHEK2). In addition, we summarize the development of polygenic risk scores (PRS) using the risk-associated SNPs and show how PRS can contribute to estimation of individual risks for developing breast cancer. Cancer Epidemiol Biomarkers Prev; 27(4); 380-94. ©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.

Computational and functional characterization of four SNPs in the SOST locus associated with osteoporosis

The SOST gene encodes sclerostin, a C-terminal cysteine knot-like domain containing key negative regulator of osteoblastic bone formation that inhibits LRP5/6-mediated canonical Wnt signaling. Numerous single nucleotide polymorphisms (SNPs) in the SOST locus are firmly associated with bone mineral density (BMD) and fracture in genome-wide association studies (GWAS) and candidate gene association studies. However, the validation and mechanistic elucidation of causal genetic variants, especially for SNPs located beyond the promoter-proximal region, remain largely unresolved. By employing computational and experimental approaches, here we identify four SNPs rs1230399, rs7220711, rs1107748 and rs75901553 as functional variants which display allelic variation in SOST gene expression. The osteoporosis associated SNP rs1230399 in the SOST distal upstream regulatory region shows FOXA1 binding activity with subsequent transinactivation in a T allele-specific manner. The BMD GWAS lead SNPs rs7220711 and rs1107748 both reside in the 52-kb regulatory element deletion 35-kb downstream of the SOST gene which leads to Van Buchem disease. The rs7220711-A has a higher affinity for the transcriptional repressors MAFF or MAFK homodimers than rs7220711-G, while rs1107748 confers C allele specific transcriptional enhancer activity via a CTCF binding element. The variant rs75901553 C>T located in a conserved site of the SOST 3' UTR abolishes a target binding site for miR-98-5p which is negatively responsive to parathyroid hormone or 17β-estradiol in osteoblastic cell lines. Our findings uncover the biological consequences of four independent genetic variants in the SOST region and their important roles in SOST expression via diverse mechanisms, providing new insights into the genetics and molecular pathogenesis of osteoporosis.