Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170

Silencer variants are key drivers of gene upregulation in Alzheimer's disease

Alzheimer's disease (AD), particularly late-onset AD, stands as the most prevalent neurodegenerative disorder globally. Owing to its substantial heritability, genetic studies have emerged as indispensable for elucidating genes and biological pathways driving AD onset and progression. However, genetic and molecular mechanisms underlying AD remain poorly defined, largely due to the pronounced heterogeneity of AD and the intricate interactions among AD genetic factors. Notably, approximately 90% of AD-associated genetic variants reside in intronic and intergenic regions, yet their functional significance has remained largely uncharacterized. To address this challenge, we developed a deep learning framework combining bulk and single-cell epigenomic data to evaluate the regulatory potential (i.e., silencing and activating strength) of noncoding AD variants in the dorsolateral prefrontal cortex (DLPFCs) and its major cell types. This model identified 1,457 silencer and 3,084 enhancer AD-associated variants in the DLPFC and binned them into silencer variants only (SL), enhancer variants only (EN), or both variant types (ENSL) classes. Each class exerts distinct cellular and molecular influences on AD pathogenesis. EN loci predominantly regulate housekeeping metabolic processes, whereas SL loci (including the genes MS4A6A , TREM2 , USP6NL , HLA-D ) are selectively linked to immune responses. Notably, 71% of these genes are significantly upregulated in AD and pro-inflammation-stimulated microglia. Furthermore, genes associated with SL loci are, in neuronal cells, often responsive to glutamate receptor antagonists (e.g, NBQX) and anti-inflammatory perturbagens (such as D-64131), the compound classes known for reducing the AD risk. ENSL loci, in contrast, are uniquely implicated in memory maintenance, neurofibrillary tangle assembly, and are also shared by other neurological disorders such as Parkinson's disease and schizophrenia. Key genes in this class of loci, such as MAPT , CR1/2 , and CLU , are frequently upregulated in AD subtypes with hyperphosphorylated tau aggregates. Critically, our model can accurately predict the impact of regulatory variants, with an average Pearson correlation coefficient of 0.54 and a directional concordance rate of 70% between our predictions and experimental outcomes. This model identified rs636317 as a causal AD variant in the MS4A locus, distinguishing it from the 7bp-away allele-neutral variant rs636341. Similarly, rs7922621 was prioritized over its 54-bp-away allele-neutral rs7901634 in the TSPAN14 locus. Additional causal variants include rs6701713 in the CR1 locus, and rs28834970 and rs755951 in the PTK2B locus. Collectively, this work advances our understanding of the regulatory landscape of AD-associated genetic variants, providing a framework to explore their functional roles in the pathogenesis of this complex disease.

Investigations on the dysregulated genes in high-fat-fed mice infected with Prevotella intermedia and their possible role in the development of hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma (HCC) is a leading global cancer, often linked to various factors, including viral infections and metabolic disorders. Recent studies suggest that microbial infections, particularly from oral pathogens like Prevotellaintermedia (Pi), may elevate the progression of HCC through dysbiosis and chronic inflammation.

Alternative splicing of transposable elements in human breast cancer

Transposable elements (TEs) drive genome evolution and can affect gene expression through diverse mechanisms. In breast cancer, disrupted regulation of TE sequences may facilitate tumor-specific transcriptomic alterations. We examine 142,514 full-length isoforms derived from long-read RNA sequencing (LR-seq) of 30 breast samples to investigate the effects of TEs on the breast cancer transcriptome. Approximately half of these isoforms contain TE sequences, and these contribute to half of the novel annotated splice junctions. We quantify splicing of these LR-seq derived isoforms in 1,135 breast tumors from The Cancer Genome Atlas (TCGA) and 1,329 healthy tissue samples from the Genotype-Tissue Expression (GTEx), and find 300 TE-overlapping tumor-specific splicing events. Some splicing events are enriched in specific breast cancer subtypes - for example, a TE-driven transcription start site upstream of ERBB2 in HER2 + tumors, and several TE-mediated splicing events are associated with patient survival and poor prognosis. The full-length sequences we capture with LR-seq reveal thousands of isoforms with signatures of RNA editing, including a novel isoform belonging to RHOA; a gene previously implicated in tumor progression. We utilize our full-length isoforms to discover polymorphic TE insertions that alter splicing and validate one of these events in breast cancer cell lines. Together, our results demonstrate the widespread effects of dysregulated TEs on breast cancer transcriptomes and highlight the advantages of long-read isoform sequencing for understanding TE biology. TE-derived isoforms may alter the expression of genes important in cancer and can potentially be used as novel, disease-specific therapeutic targets or biomarkers.One sentence summary: Transposable elements generate alternative isoforms and alter post-transcriptional regulation in human breast cancer.

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

Rapid and quantitative functional interrogation of human enhancer variant activity in live mice

Functional analysis of non-coding variants associated with congenital disorders remains challenging due to the lack of efficient in vivo models. Here we introduce dual-enSERT, a robust Cas9-based two-color fluorescent reporter system which enables rapid, quantitative comparison of enhancer allele activities in live mice in less than two weeks. We use this technology to examine and measure the gain- and loss-of-function effects of enhancer variants previously linked to limb polydactyly, autism spectrum disorder, and craniofacial malformation. By combining dual-enSERT with single-cell transcriptomics, we characterise gene expression in cells where the enhancer is normally and ectopically active, revealing candidate pathways that may lead to enhancer misregulation. Finally, we demonstrate the widespread utility of dual-enSERT by testing the effects of fifteen previously uncharacterised rare and common non-coding variants linked to neurodevelopmental disorders. In doing so we identify variants that reproducibly alter the in vivo activity of OTX2 and MIR9-2 brain enhancers, implicating them in autism. Dual-enSERT thus allows researchers to go from identifying candidate enhancer variants to analysis of comparative enhancer activity in live embryos in under two weeks.

Ethnic-specific genetic susceptibility loci for endometriosis in Taiwanese-Han population: a genome-wide association study

Endometriosis is a common gynecological disorder affecting around 10% of reproductive-age women. Although many hypotheses were proposed, genetic alteration has been considered as one of the key factors promoting pathogenesis. Due to racial/ethnic disparities in the process of hormone regulation and nutrition metabolism, a genome-wide association study (GWAS) with 2794 cases and 27,940 controls was conducted in a Taiwanese-Han population. Our study identified five significant susceptibility loci for endometriosis, and three of them, WNT4 (on the 1p36.12), RMND1 (6q25.1), and CCDC170 (6q25.1), have been previously associated with endometriosis across different populations, including European and Japanese descent cohorts. Other two including C5orf66/C5orf66-AS2 (5q31.1) and STN1 (10q24.33) are newly identified ones. Functional network analysis of potent risk genes revealed the involvement of cancer susceptibility and neurodevelopmental disorders in endometriosis development. In addition, long non-coding RNAs (lncRNAs) C5orf66 and C5orf66-AS2 can interact with many RNA-binding proteins (RBPs) which can influence RNA metabolic process, mRNA stabilization, and mRNA splicing, leading to dysregulation in tumor-promoting gene expression. Those findings support clinical observations of differences in the presentation of endometriosis in Taiwanese-Han population with higher risks of developing deeply infiltrating/invasive lesions and the associated malignancies.

Alternative splicing of transposable elements in human breast cancer

Transposable elements (TEs) drive genome evolution and can affect gene expression through diverse mechanisms. In breast cancer, disrupted regulation of TE sequences may facilitate tumor-specific transcriptomic alterations. We examine 142,514 full-length isoforms derived from long-read RNA sequencing (LR-seq) of 30 breast samples to investigate the effects of TEs on the breast cancer transcriptome. Approximately half of these isoforms contain TE sequences, and these contribute to half of the novel annotated splice junctions. We quantify splicing of these LR-seq derived isoforms in 1,135 breast tumors from The Cancer Genome Atlas (TCGA) and 1,329 healthy tissue samples from the Genotype-Tissue Expression (GTEx), and find 300 TE-overlapping tumor-specific splicing events. Some splicing events are enriched in specific breast cancer subtypes - for example, a TE-driven transcription start site upstream of ERBB2 in HER2+ tumors, and several TE-mediated splicing events are associated with patient survival and poor prognosis. The full-length sequences we capture with LR-seq reveal thousands of isoforms with signatures of RNA editing, including a novel isoform belonging to RHOA; a gene previously implicated in tumor progression. We utilize our full-length isoforms to discover polymorphic TE insertions that alter splicing and validate one of these events in breast cancer cell lines. Together, our results demonstrate the widespread effects of dysregulated TEs on breast cancer transcriptomes and highlight the advantages of long-read isoform sequencing for understanding TE biology. TE-derived isoforms may alter the expression of genes important in cancer and can potentially be used as novel, disease-specific therapeutic targets or biomarkers.

Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.

The rs2046210 Polymorphism Is Associated with Endometriosis Risk and Elevated Estrogen Receptor 1 Expression in the Eutopic Endometrium of Women with the Disease

In this focused genetic case-control study, we analyzed two functional single-nucleotide variants (SNVs) associated with breast cancer risk (rs2046210, rs9383590) and one risk SNV for an implantation defect and infertility (rs9340799) for their association with endometriosis susceptibility, progression and ESR1 gene regulation in endometriosis patients. The rs2046210, rs9383590 and rs9340799 SNVs were genotyped in 153 endometriosis patients and 87 control subjects with Caucasian ancestry. We analyzed the association of all SNVs with endometriosis susceptibility in all patients and in subgroups and assessed the concordance between the SNVs. Quantitative reverse transcription PCR was used to determine ESR1 gene expression in the eutopic endometrial tissue of the controls and endometriosis patients. The heterozygous rs2046210 GA genotype was associated with significantly increased endometriosis risk, particularly in younger, leaner and infertile women and with an increased ESR1 gene expression in the eutopic endometrium of these patients, compared to controls. The minor AA genotype of rs2046210 was identified as a potential risk factor for endometriosis progression in women with mild endometriosis. The results from this analysis indicate that rs2046210 may be a functional genetic variant associated with endometriosis development and progression.

Pathogenesis of Endometriosis and Endometriosis-Associated Cancers

Endometriosis is a hormone-dependent, chronic inflammatory condition that affects 5-10% of reproductive-aged women. It is a complex disorder characterized by the growth of endometrial-like tissue outside the uterus, which can cause chronic pelvic pain and infertility. Despite its prevalence, the underlying molecular mechanisms of this disease remain poorly understood. Current treatment options are limited and focus mainly on suppressing lesion activity rather than eliminating it entirely. Although endometriosis is generally considered a benign condition, substantial evidence suggests that it increases the risk of developing specific subtypes of ovarian cancer. The discovery of cancer driver mutations in endometriotic lesions indicates that endometriosis may share molecular pathways with cancer. Moreover, the application of single-cell and spatial genomics, along with the development of organoid models, has started to illuminate the molecular mechanisms underlying disease etiology. This review aims to summarize the key genetic mutations and alterations that drive the development and progression of endometriosis to malignancy. We also review the significant recent advances in the understanding of the molecular basis of the disorder, as well as novel approaches and in vitro models that offer new avenues for improving our understanding of disease pathology and for developing new targeted therapies.

The contribution of silencer variants to human diseases

BACKGROUND

Although disease-causal genetic variants have been found within silencer sequences, we still lack a comprehensive analysis of the association of silencers with diseases. Here, we profiled GWAS variants in 2.8 million candidate silencers across 97 human samples derived from a diverse panel of tissues and developmental time points, using deep learning models.

RESULTS

We show that candidate silencers exhibit strong enrichment in disease-associated variants, and several diseases display a much stronger association with silencer variants than enhancer variants. Close to 52% of candidate silencers cluster, forming silencer-rich loci, and, in the loci of Parkinson's-disease-hallmark genes TRIM31 and MAL, the associated SNPs densely populate clustered candidate silencers rather than enhancers displaying an overall twofold enrichment in silencers versus enhancers. The disruption of apoptosis in neuronal cells is associated with both schizophrenia and bipolar disorder and can largely be attributed to variants within candidate silencers. Our model permits a mechanistic explanation of causative SNP effects by identifying altered binding of tissue-specific repressors and activators, validated with a 70% of directional concordance using SNP-SELEX. Narrowing the focus of the analysis to individual silencer variants, experimental data confirms the role of the rs62055708 SNP in Parkinson's disease, rs2535629 in schizophrenia, and rs6207121 in type 1 diabetes.

CONCLUSIONS

In summary, our results indicate that advances in deep learning models for the discovery of disease-causal variants within candidate silencers effectively "double" the number of functionally characterized GWAS variants. This provides a basis for explaining mechanisms of action and designing novel diagnostics and therapeutics.

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.

Association of ESR1 Germline Variants with TP53 Somatic Variants in Breast Tumors in a Genome-wide Study

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency.

SIGNIFICANCE

Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences.

Expression- and splicing-based multi-tissue transcriptome-wide association studies identified multiple genes for breast cancer by estrogen-receptor status

BACKGROUND

Although several transcriptome-wide association studies (TWASs) have been performed to identify genes associated with overall breast cancer (BC) risk, only a few TWAS have explored the differences in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) breast cancer. Additionally, these studies were based on gene expression prediction models trained primarily in breast tissue, and they did not account for alternative splicing of genes.

METHODS

In this study, we utilized two approaches to perform multi-tissue TWASs of breast cancer by ER subtype: (1) an expression-based TWAS that combined TWAS signals for each gene across multiple tissues and (2) a splicing-based TWAS that combined TWAS signals of all excised introns for each gene across tissues. To perform this TWAS, we utilized summary statistics for ER + BC from the Breast Cancer Association Consortium (BCAC) and for ER- BC from a meta-analysis of BCAC and the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA).

RESULTS

In total, we identified 230 genes in 86 loci that were associated with ER + BC and 66 genes in 29 loci that were associated with ER- BC at a Bonferroni threshold of significance. Of these genes, 2 genes associated with ER + BC at the 1q21.1 locus were located at least 1 Mb from published GWAS hits. For several well-studied tumor suppressor genes such as TP53 and CHEK2 which have historically been thought to impact BC risk through rare, penetrant mutations, we discovered that common variants, which modulate gene expression, may additionally contribute to ER + or ER- etiology.

CONCLUSIONS

Our study comprehensively examined how differences in common variation contribute to molecular differences between ER + and ER- BC and introduces a novel, splicing-based framework that can be used in future TWAS studies.

Leveraging GWAS: Path to Prevention?

Developing novel cancer prevention medication strategies is important for reducing mortality. Identification of common genetic variants associated with cancer risk suggests the potential to leverage these discoveries to define causal targets for cancer interception. Although each risk variant confers small increases in risk, researchers propose that blocking those that produce causal carcinogenic effects might have large impacts on cancer prevention. While a promising concept, we describe potential hurdles that may need to be scaled to reach this goal, including: (i) understanding the complexity of risk; (ii) achieving statistical power in studies with binary outcomes (cancer development: yes or no); (iii) characterization of cancer precursors; (iv) heterogeneity of cancer subtypes and the populations in which these diseases occur; (v) impact of static genetic markers across complex events of the life course; (vi) defining gene-gene and gene-environment interactions and (vii) demonstrating functional effects of markers in human populations. We assess short-term prospects for this research against the backdrop of these challenges and the potential to prevent cancer through other means. See related commentary by Peters and Tomlinson, p. 7.

Utilizing Human Genetics to Develop Chemoprevention for Cancer-Too Good an Opportunity to be Missed

Large-scale genetic studies are reliably identifying many risk factors for disease in the general population. Several of these genetic risk factors encode potential drug targets, and genetics has already helped to introduce targeted agents for some diseases, an example being lipid-lowering drugs to reduce the incidence of cardiovascular disease. Multiple drugs have been developed to treat cancers based on somatic mutations and genomics, but in stark contrast, there seems to be a reluctance to use germline genetic data to develop drugs to prevent malignancy, despite the large numbers of people who could benefit, the potential for lowering cancer rates, and the widespread current use of non-pharmaceutical measures to reduce cancer risk factors such as tobacco, alcohol, and infectious diseases. We argue that concerted efforts for cancer prevention based on genetics, including genes influenced by common polymorphisms that modulate cancer risk, are urgently needed. There are enormous, yet underutilized, opportunities to develop novel targeted agents for chemoprevention of cancer based on human germline genetics. Such efforts are likely to require the support of a dedicated funding program by national and international agencies. See related commentary by Winham and Sherman, p. 13.

Rapid and Quantitative Functional Interrogation of Human Enhancer Variant Activity in Live Mice

Functional analysis of non-coding variants associated with human congenital disorders remains challenging due to the lack of efficient in vivo models. Here we introduce dual-enSERT, a robust Cas9-based two-color fluorescent reporter system which enables rapid, quantitative comparison of enhancer allele activities in live mice of any genetic background. We use this new technology to examine and measure the gain- and loss-of-function effects of enhancer variants linked to limb polydactyly, autism, and craniofacial malformation. By combining dual-enSERT with single-cell transcriptomics, we characterize variant enhancer alleles at cellular resolution, thereby implicating candidate molecular pathways in pathogenic enhancer misregulation. We further show that independent, polydactyly-linked enhancer variants lead to ectopic expression in the same cell populations, indicating shared genetic mechanisms underlying non-coding variant pathogenesis. Finally, we streamline dual-enSERT for analysis in F0 animals by placing both reporters on the same transgene separated by a synthetic insulator. Dual-enSERT allows researchers to go from identifying candidate enhancer variants to analysis of comparative enhancer activity in live embryos in under two weeks.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study

Background

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

Methods

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

Results

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

Conclusions

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

Insights from Mendelian randomization and genetic correlation analyses into the relationship between endometriosis and its comorbidities

BACKGROUND

Endometriosis remains a poorly understood disease, despite its high prevalence and debilitating symptoms. The overlap in symptoms and the increased risk of multiple other traits in women with endometriosis is becoming increasingly apparent through epidemiological data. Genetic studies offer a method of investigating these comorbid relationships through the assessment of causal relationships with Mendelian randomization (MR), as well as identification of shared genetic variants and genes involved across traits. This has the capacity to identify risk factors for endometriosis as well as provide insight into the aetiology of disease.

OBJECTIVE AND RATIONALE

We aim to review the current literature assessing the relationship between endometriosis and other traits using genomic data, primarily through the methods of MR and genetic correlation. We critically examine the limitations of these studies in accordance with the assumptions of the utilized methods.

SEARCH METHODS

The PubMed database was used to search for peer-reviewed original research articles using the terms 'Mendelian randomization endometriosis' and '"genetic correlation" endometriosis'. Additionally, a Google Scholar search using the terms '"endometriosis" "mendelian randomization" "genetic correlation"' was performed. All relevant publications (n = 21) published up until 7 October 2022 were included in this review. Upon compilation of all traits with published MR and/or genetic correlation with endometriosis, additional epidemiological and genetic information on their comorbidity with endometriosis was sourced by searching for the trait in conjunction with 'endometriosis' on Google Scholar.

OUTCOMES

The association between endometriosis and multiple pain, gynaecological, cancer, inflammatory, gastrointestinal, psychological, and anthropometric traits has been assessed using MR analysis and genetic correlation analysis. Genetic correlation analyses provide evidence that genetic factors contributing to endometriosis are shared with multiple traits: migraine, uterine fibroids, subtypes of ovarian cancer, melanoma, asthma, gastro-oesophageal reflux disease, gastritis/duodenitis, and depression, suggesting the involvement of multiple biological mechanisms in endometriosis. The assessment of causality with MR has revealed several potential causes (e.g. depression) and outcomes (e.g. ovarian cancer and uterine fibroids) of a genetic predisposition to endometriosis; however, interpretation of these results requires consideration of potential violations of the MR assumptions.

WIDER IMPLICATIONS

Genomic studies have demonstrated that there is a molecular basis for the co-occurrence of endometriosis with other traits. Dissection of this overlap has identified shared genes and pathways, which provide insight into the biology of endometriosis. Thoughtful MR studies are necessary to ascertain causality of the comorbidities of endometriosis. Given the significant diagnostic delay of endometriosis of 7-11 years, determining risk factors is necessary to aid diagnosis and reduce the disease burden. Identification of traits for which endometriosis is a risk factor is important for holistic treatment and counselling of the patient. The use of genomic data to disentangle the overlap of endometriosis with other traits has provided insights into the aetiology of endometriosis.

Systematic analyses of GWAS summary statistics from UK Biobank identified novel susceptibility loci and genes for upper gastrointestinal diseases

In recent decades, upper gastrointestinal (GI) diseases have been highly prevalent worldwide. Although genome-wide association studies (GWASs) have identified thousands of susceptibility loci, only a few of them were conducted for chronic upper GI disorders, and most of them were underpowered and with small sample sizes. Additionally, for the known loci, only a tiny fraction of heritability can be explained and the underlying mechanisms and related genes remain unclear. In this study, we conducted a multi-trait analysis by the MTAG software and a two-stage transcriptome-wide association study (TWAS) with UTMOST and FUSION for seven upper GI diseases (oesophagitis, gastro-oesophageal reflux disease, other diseases of oesophagus, gastric ulcer, duodenal ulcer, gastritis and duodenitis and other diseases of stomach and duodenum) based on summary GWAS statistics from UK Biobank. In the MTAG analysis, we identified 7 loci associated with these upper GI diseases, including 3 novel ones at 4p12 (rs10029980), 12q13.13 (rs4759317) and 18p11.32 (rs4797954). In the TWAS analysis, we revealed 5 susceptibility genes in known loci and identified 12 novel potential susceptibility genes, including HOXC9 at 12q13.13. Further functional annotations and colocalization analysis indicated that rs4759317 (A>G) driven the association for GWAS signals and expression quantitative trait loci (eQTL) simultaneously at 12q13.13. The identified variant acted by decreasing the expression of HOXC9 to affect the risk of gastro-oesophageal reflux disease. This study provided insights into the genetic nature of upper GI diseases.

Evaluation of SNPs associated with mammographic density in European women with mammographic density in Asian women from South-East Asia

PURPOSE

Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown.

METHOD

Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls.

RESULTS

Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD.

CONCLUSION

Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.

Regulatory network and targeted interventions for CCDC family in tumor pathogenesis

CCDC (coiled-coil domain-containing) is a coiled helix domain that exists in natural proteins. There are about 180 CCDC family genes, encoding proteins that are involved in intercellular transmembrane signal transduction and genetic signal transcription, among other functions. Alterations in expression, mutation, and DNA promoter methylation of CCDC family genes have been shown to be associated with the pathogenesis of many diseases, including primary ciliary dyskinesia, infertility, and tumors. In recent studies, CCDC family genes have been found to be involved in regulation of growth, invasion, metastasis, chemosensitivity, and other biological behaviors of malignant tumor cells in various cancer types, including nasopharyngeal carcinoma, lung cancer, colorectal cancer, and thyroid cancer. In this review, we summarize the involvement of CCDC family genes in tumor pathogenesis and the relevant upstream and downstream molecular mechanisms. In addition, we summarize the potential of CCDC family genes as tumor therapy targets. The findings discussed here help us to further understand the role and the therapeutic applications of CCDC family genes in tumors.

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.

Association of the Estrogen Receptor 1 Polymorphisms rs2046210 and rs9383590 with the Risk, Age at Onset and Prognosis of Breast Cancer

Estrogen receptor α (ERα), encoded by the ESR1 gene, is a key prognostic and predictive biomarker firmly established in routine diagnostics and as a therapeutic target of breast cancer, and it has a central function in breast cancer biology. Genetic variants at 6q25.1, containing the ESR1 gene, were found to be associated with breast cancer susceptibility. The rs2046210 and rs9383590 single nucleotide variants (SNVs) are located in the same putative enhancer region upstream of ESR1 and were separately identified as candidate causal variants responsible for these associations. Here, both SNVs were genotyped in a hospital-based case-control study of 409 female breast cancer patients and 422 female controls of a Central European (Austrian) study population. We analyzed the association of both SNVs with the risk, age at onset, clinically and molecularly relevant characteristics and prognosis of breast cancer. We also assessed the concordances between both SNVs and the associations of each SNV conditional on the other SNV. The minor alleles of both SNVs were found to be non-significantly associated with an increased breast cancer risk. Significant associations were found in specific subpopulations, particularly in patients with an age younger than 55 years. The minor homozygotes of rs2046210 and the minor homozygotes plus heterozygotes of rs9383590 exhibited a several-years-younger age at onset than the common homozygotes, which was more pronounced in ER-positive and luminal patients. Importantly, the observed associations of each SNV were not consistently nullified upon correction for the other SNV nor upon analyses in common homozygotes for the other SNV. We conclude that both SNVs remain independent candidate causal variants.

Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

BACKGROUND

Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.

METHODS

We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.

RESULTS

In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10-6) and AC058822.1 (P = 1.47 × 10-4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.

CONCLUSIONS

Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10-5), demonstrating the importance of diversifying study cohorts.

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

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.

Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We propose an efficient and accurate frailty model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrate the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 individuals in FinnGen. We further analyzed 871 TTE phenotypes in the UK Biobank and presented the genome-wide scale phenome-wide association results with the PheWeb browser.

Association between Ancestry-Specific 6q25 Variants and Breast Cancer Subtypes in Peruvian Women

BACKGROUND

Breast cancer incidence in the United States is lower in Hispanic/Latina (H/L) compared with African American/Black or Non-Hispanic White women. An Indigenous American breast cancer-protective germline variant (rs140068132) has been reported near the estrogen receptor 1 gene. This study tests the association of rs140068132 and other polymorphisms in the 6q25 region with subtype-specific breast cancer risk in H/Ls of high Indigenous American ancestry.

METHODS

Genotypes were obtained for 5,094 Peruvian women with (1,755) and without (3,337) breast cancer. Associations between genotype and overall and subtype-specific risk for the protective variant were tested using logistic regression models and conditional analyses, including other risk-associated polymorphisms in the region.

RESULTS

We replicated the reported association between rs140068132 and breast cancer risk overall [odds ratio (OR), 0.53; 95% confidence interval (CI), 0.47-0.59], as well as the lower odds of developing hormone receptor negative (HR-) versus HR+ disease (OR, 0.77; 95% CI, 0.61-0.97). Models, including HER2, showed further heterogeneity with reduced odds for HR+HER2+ (OR, 0.68; 95% CI, 0.51-0.92), HR-HER2+ (OR, 0.63; 95% CI, 0.44-0.90) and HR-HER2- (OR, 0.77; 95% CI, 0.56-1.05) compared with HR+HER2-. Inclusion of other risk-associated variants did not change these observations.

CONCLUSIONS

The rs140068132 polymorphism is associated with decreased risk of breast cancer in Peruvians and is more protective against HR- and HER2+ diseases independently of other breast cancer-associated variants in the 6q25 region.

IMPACT

These results could inform functional analyses to understand the mechanism by which rs140068132-G reduces risk of breast cancer development in a subtype-specific manner. They also illustrate the importance of including diverse individuals in genetic studies.

The risk variant rs11836367 contributes to breast cancer onset and metastasis by attenuating Wnt signaling via regulating NTN4 expression

Most genome-wide association study (GWAS)-identified breast cancer-associated causal variants remain uncharacterized. To provide a framework of understanding GWAS-identified variants to function, we performed a comprehensive study of noncoding regulatory variants at the NTN4 locus (12q22) and NTN4 gene in breast cancer etiology. We find that rs11836367 is the more likely causal variant, disrupting enhancer activity in both enhancer reporter assays and endogenous genome editing experiments. The protective T allele of rs11837367 increases the binding of GATA3 to the distal enhancer and up-regulates NTN4 expression. In addition, we demonstrate that loss of NTN4 gene in mice leads to tumor earlier onset, progression, and metastasis. We discover that NTN4, as a tumor suppressor, can attenuate the Wnt signaling pathway by directly binding to Wnt ligands. Our findings bridge the gaps among breast cancer-associated single-nucleotide polymorphisms, transcriptional regulation of NTN4, and breast cancer biology, which provides previously unidentified insights into breast cancer prediction and prevention.

Update Breast Cancer 2022 Part 1 - Early Stage Breast Cancer

Evidence relating to the treatment of breast cancer patients with early-stage disease has increased significantly in the past year. Abemaciclib, olaparib, and pembrolizumab are new drugs with good efficacy in the relevant patient groups. However, some questions remain unanswered. In particular, it remains unclear which premenopausal patients with hormone receptor-positive breast cancer should be spared unnecessary treatment. The question of the degree to which chemotherapy exerts a direct cytotoxic effect on the tumor or reduces ovarian function through chemotherapy could be of key importance. This group of patients could potentially be spared chemotherapy. New, previously experimental biomarker analysis methods, such as spatial analysis of gene expression (spatial transcriptomics) are gradually finding their way into large randomized phase III trials, such as the NeoTRIP trial. This in turn leads to a better understanding of the predictive factors of new therapies, for example immunotherapy. This review summarizes the scientific innovations from recent congresses such as the San Antonio Breast Cancer Symposium 2021 but also from recent publications.

Fusion-associated carcinomas of the breast: Diagnostic, prognostic, and therapeutic significance

Recurrent gene fusions comprise a class of viable genetic targets in solid tumors that have culminated several recent breakthrough cancer therapies. Their role in breast cancer, however, remains largely underappreciated due to the complexity of genomic rearrangements in breast malignancy. Just recently, we and others have identified several recurrent gene fusions in breast cancer with important clinical and biological implications. Examples of the most significant recurrent gene fusions to date include (1) ESR1::CCDC170 gene fusions in luminal B and endocrine-resistant breast cancer that exert oncogenic function via modulating the HER2/HER3/SRC Proto-Oncogene (SRC) complex, (2) ESR1 exon 6 fusions in metastatic disease that drive estrogen-independent estrogen-receptor transcriptional activity, (3) BCL2L14::ETV6 fusions in a more aggressive form of the triple-negative subtype that prime epithelial-mesenchymal transition and endow paclitaxel resistance, (4) the ETV6::NTRK3 fusion in secretory breast carcinoma that constitutively activates NTRK3 kinase, (5) the oncogenic MYB-NFIB fusion as a genetic driver underpinning adenoid cystic carcinomas of the breast that activates MYB Proto-Oncogene (MYB) pathway, and (6) the NOTCH/microtubule-associated serine-threonine (MAST) kinase gene fusions that activate NOTCH and MAST signaling. Importantly, these fusions are enriched in more aggressive and lethal breast cancer presentations and appear to confer therapeutic resistance. Thus, these gene fusions could be utilized as genetic biomarkers to identify patients who require more intensive treatment and surveillance. In addition, kinase fusions are currently being evaluated in breast cancer clinical trials and ongoing mechanistic investigation is exposing therapeutic vulnerabilities in patients with fusion-positive disease.

Two distinct mechanisms underlie estrogen-receptor-negative breast cancer susceptibility at the 2p23.2 locus

Genome wide-association studies (GWAS) have established over 400 breast cancer risk loci defined by common single nucleotide polymorphisms (SNPs), including several associated with estrogen-receptor (ER)-negative disease. Most of these loci have not been studied systematically and the mechanistic underpinnings of risk are largely unknown. Here we explored the landscape of genomic features at an ER-negative breast cancer susceptibility locus at chromosome 2p23.2 and assessed the functionality of 81 SNPs with strong evidence of association from previous fine mapping. Five candidate regulatory regions containing risk-associated SNPs were identified. Regulatory Region 1 in the first intron of WDR43 contains SNP rs4407214, which showed allele-specific interaction with the transcription factor USF1 in in vitro assays. CRISPR-mediated disruption of Regulatory Region 1 led to expression changes in the neighboring PLB1 gene, suggesting that the region acts as a distal enhancer. Regulatory Regions 2, 4, and 5 did not provide sufficient evidence for functionality in in silico and experimental analyses. Two SNPs (rs11680458 and rs1131880) in Regulatory Region 3, mapping to the seed region for miRNA-recognition sites in the 3' untranslated region of WDR43, showed allele-specific effects of ectopic expression of miR-376 on WDR43 expression levels. Taken together, our data suggest that risk of ER-negative breast cancer associated with the 2p23.2 locus is likely driven by a combinatorial effect on the regulation of WDR43 and PLB1.

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.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes

BACKGROUND

Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

METHODS

Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

RESULTS

Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

CONCLUSION

This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

TranSNPs: A class of functional SNPs affecting mRNA translation potential revealed by fraction-based allelic imbalance

Few studies have explored the association between SNPs and alterations in mRNA translation potential. We developed an approach to identify SNPs that can mark allele-specific protein expression levels and could represent sources of inter-individual variation in disease risk. Using MCF7 cells under different treatments, we performed polysomal profiling followed by RNA sequencing of total or polysome-associated mRNA fractions and designed a computational approach to identify SNPs showing a significant change in the allelic balance between total and polysomal mRNA fractions. We identified 147 SNPs, 39 of which located in UTRs. Allele-specific differences at the translation level were confirmed in transfected MCF7 cells by reporter assays. Exploiting breast cancer data from TCGA we identified UTR SNPs demonstrating distinct prognosis features and altering binding sites of RNA-binding proteins. Our approach produced a catalog of tranSNPs, a class of functional SNPs associated with allele-specific translation and potentially endowed with prognostic value for disease risk.

Serum semaphorin 4C as a diagnostic biomarker in breast cancer: A multicenter retrospective study

Background

To date, there is no approved blood‐based biomarker for breast cancer detection. Herein, we aimed to assess semaphorin 4C (SEMA4C), a pivotal protein involved in breast cancer progression, as a serum diagnostic biomarker.

Methods

We included 6,213 consecutive inpatients from Tongji Hospital, Qilu Hospital, and Hubei Cancer Hospital. Training cohort and two validation cohorts were introduced for diagnostic exploration and validation. A pan‐cancer cohort was used to independently explore the diagnostic potential of SEMA4C among solid tumors. Breast cancer patients who underwent mass excision prior to modified radical mastectomy were also analyzed. We hypothesized that increased pre‐treatment serum SEMA4C levels, measured using optimized in‐house enzyme‐linked immunosorbent assay kits, could detect breast cancer. The endpoints were diagnostic performance, including area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Post‐surgery pathological diagnosis was the reference standard and breast cancer staging followed the TNM classification. There was no restriction on disease stage for eligibilities.

Results

We included 2667 inpatients with breast lesions, 2378 patients with other solid tumors, and 1168 healthy participants. Specifically, 118 patients with breast cancer were diagnosed with stage 0 (5.71%), 620 with stage I (30.00%), 966 with stage II (46.73%), 217 with stage III (10.50%), and 8 with stage IV (0.39%). Patients with breast cancer had significantly higher serum SEMA4C levels than benign breast tumor patients and normal controls (P < 0.001). Elevated serum SEMA4C levels had AUC of 0.920 (95% confidence interval [CI]: 0.900–0.941) and 0.932 (95%CI: 0.911–0.953) for breast cancer detection in the two validation cohorts. The AUCs for detecting early‐stage breast cancer (n = 366) and ductal carcinoma in situ (n = 85) were 0.931 (95%CI: 0.916–0.946) and 0.879 (95%CI: 0.832–0.925), respectively. Serum SEMA4C levels significantly decreased after surgery, and the reduction was more striking after modified radical mastectomy, compared with mass excision (P < 0.001). The positive rate of enhanced serum SEMA4C levels was 84.77% for breast cancer and below 20.75% for the other 14 solid tumors.

Conclusions

Serum SEMA4C demonstrated promising potential as a candidate biomarker for breast cancer diagnosis. However, validation in prospective settings and by other study groups is warranted.

Evaluation of early post-natal pig mammary gland development and human breast cancer gene expression

Breast cancer is the second leading cause of death in women after lung cancer, and only 5% of patients with metastatic breast cancer survive beyond ten years of diagnosis. Considering the heterogeneous subclasses of breast cancer, current cancer models have shortfalls due to copy number variants, and genetic differences of humans and immunocompromised animal models. Preclinical studies indicate stem cell activity in early post-natal mammary development may be reactivated in the human adult as a trigger to initiate cell proliferation leading to breast cancer. The goal of the work reported herein was to compare genetic expression of early development, post-natal pig mammary glands to the literature reported genes implicated in different subclasses of human breast cancer. Differentially expressed genes associated with breast cancer and present in early developing pig samples include NUCB2, ANGPTL4 and ACE. Histological staining confirmed E-cadherin, Vimentin, N-cadherin, and Claudin-1, which are all implicated in malignant cancer. Due to the homology of gene expression patterns in the developing pig mammary gland and reported genes in human breast cancer profiles, this research is worthy of further study to address a potential model using mammary development cues to unravel breast cancer biology.

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.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

Failure to Guard: Mitochondrial Protein Quality Control in Cancer

Mitochondria are energetic and dynamic organelles with a crucial role in bioenergetics, metabolism, and signaling. Mitochondrial proteins, encoded by both nuclear and mitochondrial DNA, must be properly regulated to ensure proteostasis. Mitochondrial protein quality control (MPQC) serves as a critical surveillance system, employing different pathways and regulators as cellular guardians to ensure mitochondrial protein quality and quantity. In this review, we describe key pathways and players in MPQC, such as mitochondrial protein translocation-associated degradation, mitochondrial stress responses, chaperones, and proteases, and how they work together to safeguard mitochondrial health and integrity. Deregulated MPQC leads to proteotoxicity and dysfunctional mitochondria, which contributes to numerous human diseases, including cancer. We discuss how alterations in MPQC components are linked to tumorigenesis, whether they act as drivers, suppressors, or both. Finally, we summarize recent advances that seek to target these alterations for the development of anti-cancer drugs.

A search for modifying genetic factors in CHEK2:c.1100delC breast cancer patients

The risk of breast cancer associated with CHEK2:c.1100delC is 2-threefold but higher in carriers with a family history of breast cancer than without, suggesting that other genetic loci in combination with CHEK2:c.1100delC confer an increased risk in a polygenic model. Part of the excess familial risk has been associated with common low-penetrance variants. This study aimed to identify genetic loci that modify CHEK2:c.1100delC-associated breast cancer risk by searching for candidate risk alleles that are overrepresented in CHEK2:c.1100delC carriers with breast cancer compared with controls. We performed whole-exome sequencing in 28 breast cancer cases with germline CHEK2:c.1100delC, 28 familial breast cancer cases and 70 controls. Candidate alleles were selected for validation in larger cohorts. One recessive synonymous variant, rs16897117, was suggested, but no overrepresentation of homozygous CHEK2:c.1100delC carriers was found in the following validation. Furthermore, 11 non-synonymous candidate alleles were suggested for further testing, but no significant difference in allele frequency could be detected in the validation in CHEK2:c.1100delC cases compared with familial breast cancer, sporadic breast cancer and controls. With this method, we found no support for a CHEK2:c.1100delC-specific genetic modifier. Further studies of CHEK2:c.1100delC genetic modifiers are warranted to improve risk assessment in clinical practice.

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).

Perspectives on Drug Repurposing

Complex common diseases are a significant burden for our societies and demand not only preventive measures but also more effective, safer, and more affordable treatments. The whole process of the current model of drug discovery and development implies a high investment by the pharmaceutical industry, which ultimately impact in high drug prices. In this sense, drug repurposing would help meet the needs of patients to access useful and novel treatments. Unlike the traditional approach, drug repurposing enters both the preclinical evaluation and clinical trials of the compound of interest faster, budgeting research and development costs, and limiting potential biosafety risks. The participation of government, society, and private investors is needed to secure the funds for experimental design and clinical development of repurposing candidates to have affordable, effective, and safe repurposed drugs. Moreover, extensive advertising of repurposing as a concept in the health community, could reduce prescribing bias when enough clinical evidence exists, which will support the employment of cheaper and more accessible repurposed compounds for common conditions.

A cross-tissue transcriptome-wide association study identifies novel susceptibility genes for lung cancer in Chinese populations

Although dozens of susceptibility loci have been identified for lung cancer in genome-wide association studies (GWASs), the susceptibility genes and underlying mechanisms remain unclear. In this study, we conducted a cross-tissue transcriptome-wide association study (TWAS) with UTMOST based on summary statistics from 13 327 lung cancer cases and 13 328 controls and the genetic-expression matrix over 44 human tissues in the Genotype-Tissue Expression (GTEx) project. After further evaluating the associations in each tissue, we revealed 6 susceptibility genes in known loci and identified 12 novel ones. Among those, five novel genes, including DCAF16 (Pcross-tissue = 2.57 × 10-5, PLung = 2.89 × 10-5), CBL (Pcross-tissue = 5.08 × 10-7, PLung = 1.82 × 10-4), ATR (Pcross-tissue = 1.45 × 10-5, PLung = 9.68 × 10-5), GYPE (Pcross-tissue = 1.45 × 10-5, PLung = 2.17 × 10-3) and PARD3 (Pcross-tissue = 5.79 × 10-6, PLung = 4.05 × 10-3), were significantly associated with the risk of lung cancer in both cross-tissue and lung tissue models. Further colocalization analysis indicated that rs7667864 (C > A) and rs2298650 (G > T) drove the GWAS association signals at 4p15.31-32 (OR = 1.09, 95%CI: 1.04-1.12, PGWAS = 5.54 × 10-5) and 11q23.3 (OR = 1.08, 95%CI: 1.04-1.13, PGWAS = 5.55 × 10-5), as well as the expression of DCAF16 (βGTEx = 0.24, PGTEx = 9.81 × 10-15; βNJLCC = 0.29, PNJLCC = 3.84 × 10-8) and CBL (βGTEx = -0.17, PGTEx = 2.82 × 10-8; βNJLCC = -0.32, PNJLCC = 2.61 × 10-7) in lung tissue. Functional annotations and phenotype assays supported the carcinogenic effect of these novel susceptibility genes in lung carcinogenesis.

Common Susceptibility Loci for Male Breast Cancer

BACKGROUND

The etiology of male breast cancer (MBC) is poorly understood. In particular, the extent to which the genetic basis of MBC differs from female breast cancer (FBC) is unknown. A previous genome-wide association study of MBC identified 2 predisposition loci for the disease, both of which were also associated with risk of FBC.

METHODS

We performed genome-wide single nucleotide polymorphism genotyping of European ancestry MBC case subjects and controls in 3 stages. Associations between directly genotyped and imputed single nucleotide polymorphisms with MBC were assessed using fixed-effects meta-analysis of 1380 cases and 3620 controls. Replication genotyping of 810 cases and 1026 controls was used to validate variants with P values less than 1 × 10-06. Genetic correlation with FBC was evaluated using linkage disequilibrium score regression, by comprehensively examining the associations of published FBC risk loci with risk of MBC and by assessing associations between a FBC polygenic risk score and MBC. All statistical tests were 2-sided.

RESULTS

The genome-wide association study identified 3 novel MBC susceptibility loci that attained genome-wide statistical significance (P < 5 × 10-08). Genetic correlation analysis revealed a strong shared genetic basis with estrogen receptor-positive FBC. Men in the top quintile of genetic risk had a fourfold increased risk of breast cancer relative to those in the bottom quintile (odds ratio = 3.86, 95% confidence interval = 3.07 to 4.87, P = 2.08 × 10-30).

CONCLUSIONS

These findings advance our understanding of the genetic basis of MBC, providing support for an overlapping genetic etiology with FBC and identifying a fourfold high-risk group of susceptible men.

From BRCA1 to Polygenic Risk Scores: Mutation-Associated Risks in Breast Cancer-Related Genes

Background

There has been huge progress over the last 30 years in identifying the familial component of breast cancer.

Summary

Currently around 20% is explained by the high-risk genes BRCA1 and BRCA2, a further 2% by other high-penetrance genes, and around 5% by the moderate risk genes ATM and CHEK2. In contrast, the more than 300 low-penetrance single-nucleotide polymorphisms (SNP) now account for around 28% and they are predicted to account for most of the remaining 45% yet to be found. Even for high-risk genes which confer a 40-90% risk of breast cancer, these SNP can substantially affect the level of breast cancer risk. Indeed, the strength of family history and hormonal and reproductive factors is very important in assessing risk even for a BRCA carrier. The risks of contralateral breast cancer are also affected by SNP as well as by the presence of high or moderate risk genes. Genetic testing using gene panels is now commonplace.

Key-Messages

There is a need for a more parsimonious approach to panels only testing those genes with a definite 2-fold increased risk and only testing those genes with challenging management implications, such as CDH1 and TP53, when there is strong clinical indication to do so. Testing of SNP alongside genes is likely to provide a more accurate risk assessment.

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10-8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.

Overcoming disparities: Multidisciplinary breast cancer care at a public safety net hospital

PURPOSE

Public safety net hospitals (SNH) serve a disparate patient population; however, little is known about long-term oncologic outcomes of patients receiving care at these facilities. This study is the first to examine overall survival (OS) and the initiation of treatment in breast cancer patients treated at a SNH.

METHODS

Patients presenting to a SNH with stage I-IV breast cancer from 2005 to 2017 were identified from the local tumor registry. The hospital has a weekly breast tumor board and a multidisciplinary approach to breast cancer care. Kaplan-Meier survival analysis was performed to identify patient, tumor, and treatment characteristics associated with OS. Factors with a p < 0.1 were included in the Cox proportional hazards model.

RESULTS

2709 breast cancer patients were evaluated from 2005 to 2017. The patient demographics, tumor characteristics, and treatments received were analyzed. Five-year OS was 78.4% (93.9%, 87.4%, 70.9%, and 23.5% for stages I, II, III, and IV, respectively). On multivariable analysis, higher stage, age > 70 years, higher grade, and non-Hispanic ethnicity were associated with worse OS. Patients receiving surgery (HR = 0.33, p < 0.0001), chemotherapy (HR = 0.71, p = 0.006), and endocrine therapy (HR = 0.61, p < 0.0001) had better OS compared to those who did not receive these treatments.

CONCLUSION

Despite serving a vulnerable minority population that is largely poor, uninsured, and presenting with more advanced disease, OS at our SNH approaches national averages. This novel finding indicates that in the setting of multidisciplinary cancer care and with appropriate initiation of treatment, SNHs can overcome socioeconomic barriers to achieve equitable outcomes in breast cancer care.