Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

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.

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.

DNA methylation and breast cancer-associated variants

BACKGROUND

A breast cancer polygenic risk score (PRS) comprising 313 common variants reliably predicts disease risk. We examined possible relationships between genetic variation, regulation, and expression to clarify the molecular alterations associated with these variants.

METHODS

Genome-wide methylomic variation was quantified (MethylationEPIC) in Asian breast cancer patients (1152 buffy coats from peripheral whole blood). DNA methylation (DNAm) quantitative trait loci (mQTL) mapping was performed for 235 of the 313 variants with minor allele frequencies > 5%. Stability of identified mQTLs (p < 5e-8) across lifetime was examined using a public mQTL database. Identified mQTLs were also mapped to expression quantitative trait loci (eQTLs) in the Genotype-Tissue Expression Project and the eQTLGen Consortium.

RESULTS

Breast cancer PRS was not associated with DNAm. A higher proportion of significant cis-mQTLs were observed. Of 822 significant cis-mQTLs (179 unique variants) identified in our dataset, 141 (59 unique variants) were significant (p < 5e-8) in a public mQTL database. Eighty-six percent (121/141) of the matched mQTLs were consistent at multiple time points (birth, childhood, adolescence, pregnancy, middle age, post-diagnosis, or treatment). Ninety-three variants associated with DNAm were also cis-eQTLs (35 variants not genome-wide significant). Multiple loci in the breast cancer PRS are associated with DNAm, contributing to the polygenic nature of the disease. These mQTLs are mostly stable over time.

CONCLUSIONS

Consistent results from DNAm and expression data may reveal new candidate genes not previously associated with breast cancer.

Circulating vitamin C concentration and risk of cancers: a Mendelian randomization study

BACKGROUND

Circulating vitamin C concentrations have been associated with several cancers in observational studies, but little is known about the causal direction of the associations. This study aims to explore the potential causal relationship between circulating vitamin C and risk of five most common cancers in Europe.

METHODS

We used summary-level data for genetic variants associated with plasma vitamin C in a large vitamin C genome-wide association study (GWAS) meta-analysis on 52,018 Europeans, and the corresponding associations with lung, breast, prostate, colon, and rectal cancer from GWAS consortia including up to 870,984 participants of European ancestry. We performed two-sample, bi-directional Mendelian randomization (MR) analyses using inverse-variance-weighted method as the primary approach, while using 6 additional methods (e.g., MR-Egger, weighted median-based, and mode-based methods) as sensitivity analysis to detect and adjust for pleiotropy. We also conducted a meta-analysis of prospective cohort studies and randomized controlled trials to examine the association of vitamin C intakes with cancer outcomes.

RESULTS

The MR analysis showed no evidence of a causal association of circulating vitamin C concentration with any examined cancer. Although the odds ratio (OR) per one standard deviation increase in genetically predicted circulating vitamin C concentration was 1.34 (95% confidence interval 1.14 to 1.57) for breast cancer in the UK Biobank, this association could not be replicated in the Breast Cancer Association Consortium with an OR of 1.05 (0.94 to 1.17). Smoking initiation, as a positive control for our reverse MR analysis, showed a negative association with circulating vitamin C concentration. However, there was no strong evidence of a causal association of any examined cancer with circulating vitamin C. Sensitivity analysis using 6 different analytical approaches yielded similar results. Moreover, our MR results were consistent with the null findings from the meta-analysis exploring prospective associations of dietary or supplemental vitamin C intakes with cancer risk, except that higher dietary vitamin C intake, but not vitamin C supplement, was associated with a lower risk of lung cancer (risk ratio: 0.84, 95% confidence interval 0.71 to 0.99).

CONCLUSIONS

These findings provide no evidence to support that physiological-level circulating vitamin C has a large effect on risk of the five most common cancers in European populations, but we cannot rule out very small effect sizes.

rs12537 Is a Novel Susceptibility SNP Associated With Estrogen Receptor Positive Breast Cancer in Chinese Han Population

Genetic testing is widely used in breast cancer and has identified a lot of susceptibility genes and single nucleotide polymorphisms (SNPs). However, for many SNPs, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are not in place. A recent genome-wide long non-coding RNA (lncRNA) association study in Chinese Han has verified a genetic association between rs12537 and breast cancer. This study is aimed at investigating the association between rs12537 and the phenotype. We collected the clinical information of 5,634 breast cancer patients and 6,308 healthy controls in the early study. And χ2 test was used for the comparison between different groups in genotype. The frequency of genotypic distribution among SNP rs12537 has no statistically significant correlation with family history (p = 0.8945), menopausal status (p = 0.3245) or HER-2 (p = 0.2987), but it is statistically and significantly correlated with ER (p = 0.004006) and PR (p = 0.01379). Most importantly, compared to the healthy control, rs12537 variant is significantly correlated with ER positive patients and the p-value has reached the level of the whole genome (p = 1.66E-08 <5.00E-08). Furthermore, we found rs12537 associated gene MTMR3 was lower expressed in breast cancer tissues but highly methylated. In conclusion, our findings indicate that rs12537 is a novel susceptibility gene in ER positive breast cancer in Chinese Han population and it may influence the methylation of MTMR3.

rs10514231 Leads to Breast Cancer Predisposition by Altering ATP6AP1L Gene Expression

Numerous genetic variants located in autophagy-related genes have been identified for association with various cancer risks, but the biological mechanisms underlying these associations remain largely unknown. Here we investigated their regulatory activity with a parallel reporter gene assay system in breast cancer cells and identified multiple regulatory SNP sites, including rs10514231. It was located in the second intron of ATG10 and showed gene regulatory activity in most breast cancer cells we used. Mechanistically, the T allele of rs10514231 led to ATP6AP1L downregulation by decreasing the binding affinity of TCF7L2. Overexpression of the ATP6AP1L gene in cancer cells diminished cell proliferation, migration, and invasion. Notably, ATP6AP1L downregulation correlated with breast cancer risk and with poor prognosis in patients. These results provide a plausible mechanism behind the association of rs10514231 with breast cancer risk and will be important for more effective therapeutic target identification for precision medicine.

Sequencing for germline mutations in Swedish breast cancer families reveals novel breast cancer risk genes

Identifying genetic cancer risk factors will lead to improved genetic counseling, cancer prevention and cancer care. Analyzing families with a strong history of breast cancer (BC) has been a successful method to identify genes that contribute to the disease. This has led to discoveries of high-risk genes like the BRCA-genes. Nevertheless, many BC incidences are of unknown causes. In this study, exome sequencing on 59 BC patients from 24 Swedish families with a strong history of BC was performed to identify variants in known and novel BC predisposing genes. First, we screened known BC genes and identified two pathogenic variants in the BRIP1 and PALB2 genes. Secondly, to identify novel BC genes, rare and high impact variants and segregating in families were analyzed to identify 544 variants in novel BC candidate genes. Of those, 22 variants were defined as high-risk variants. Several interesting genes, either previously linked with BC or in pathways that when flawed could contribute to BC, were among the detected genes. The strongest candidates identified are the FANCM gene, involved in DNA double-strand break repair, and the RAD54L gene, involved in DNA recombination. Our study shows identifying pathogenic variants is challenging despite a strong family history of BC. Several interesting candidates were observed here that need to be further studied.

Knowledge, views and expectations for cancer polygenic risk testing in clinical practice: A cross-sectional survey of health professionals

Polygenic risk scores (PRS) are becoming increasingly available in clinical practice to evaluate cancer risk. However, little is known about health professionals' knowledge, attitudes, and expectations of PRS. An online questionnaire was distributed by relevant health professional organisations predominately in Australia, Canada and the US to evaluate health professionals' knowledge, views and expectations of PRS. Eligible participants were health professionals who provide cancer risk assessments. Results from the questionnaire were analysed descriptively and content analysis was undertaken of free-text responses. In total, 105 health professionals completed the questionnaire (genetic counsellors 84%; oncologists 6%; clinical geneticists 4%; other 7%). Although responses differed between countries, most participants (61%) had discussed PRS with patients, 20% had ordered a test and 14% had returned test results to a patient. Confidence and knowledge around interpreting PRS were low. Although 69% reported that polygenic testing will certainly or likely influence patient care in the future, most felt unprepared for this. If scaled up to the population, 49% expect that general practitioners would have a primary role in the provision of PRS, supported by genetic health professionals. These findings will inform the development of resources to support health professionals offering polygenic testing, currently and in the future.

Role of Sex in the Therapeutic Targeting of p53 Circuitry

Sex profoundly affects cancer incidence and susceptibility to therapy, with sex hormones highly contributing to this disparity. Various studies and omics data suggest a relationship between sex and the oncosuppressor p53 circuitry, including its regulators MDM2 and MDM4. Association of this network with genetic variation underlies sex-related altered cancer risk, age of onset, and cancer sensitivity to therapy. Moreover, sex-related factors, mainly estrogenic hormones, can affect the levels and/or function of the p53 network both in hormone-dependent and independent cancer. Despite this evidence, preclinical and clinical studies aimed to evaluate p53 targeted therapy rarely consider sex and related factors. This review summarizes the studies reporting the relationship between sex and the p53 circuitry, including its associated regulators, MDM2 and MDM4, with particular emphasis on estrogenic hormones. Moreover, we reviewed the evaluation of sex/hormone in preclinical studies and clinical trials employing p53-target therapies, and discuss how patients’ sex and hormonal status could impact these therapeutic approaches.

Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants.

Serum iron status and the risk of breast cancer in the European population: a two-sample Mendelian randomisation study

BACKGROUND

Previous observational studies have provided conflicting results on the association between serum iron status and the risk of breast cancer. Considering the relevance of this relationship to breast cancer prevention, its elucidation is warranted.

OBJECT

We used a two-sample Mendelian randomisation (MR) study to explore the causal relationship between serum iron status and the risk of breast cancer.

METHOD

To select single nucleotide polymorphisms (SNPs) that could be used as instrumental variables for iron status, we used the Genetics of Iron Status consortium, which includes 11 discovery and 8 replication cohorts, encompassing 48,972 individuals of European descent. Moreover, we used the OncoArray network to select SNPs that could be considered instrumental variables for the outcome of interest (breast cancer); this dataset included 122,977 individuals of European descent with breast cancer and 105,974 peers without breast cancer. Both conservative (SNPs associated with overall iron status markers) and liberal (SNPs associated with the levels of at least one iron status marker) approaches were used as part of the MR analysis. For the former, we used an inverse-variance weighted (IVW) method, whereas for the latter, we used the IVW, MR-Egger regression, weighted median and simple mode methods.

RESULTS

When the conservative approach was used, iron status showed no significant association with the risk of breast cancer or any of its subtypes. However, when the liberal approach was used, transferrin levels were found to be positively associated with the risk of ER-negative breast cancer based on the simple mode method (OR for MR, 1.225; 95% CI, 1.064, 1.410; P = 0.030). Nevertheless, the levels of the other iron status markers showed no association with the risk of breast cancer or its subtypes (P > 0.05).

CONCLUSION

In our MR study, the liberal approach suggested that changes in the concentration of transferrin could increase the risk of ER-negative breast cancer, although the levels of other iron status markers had no effect on the risk of breast cancer or its subtypes. This should be verified in future studies.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

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).

Genetic Influences on Disease Subtypes

Disease classification, or nosology, was historically driven by careful examination of clinical features of patients. As technologies to measure and understand human phenotypes advanced, so too did classifications of disease, and the advent of genetic data has led to a surge in genetic subtyping in the past decades. Although the fundamental process of refining disease definitions and subtypes is shared across diverse fields, each field is driven by its own goals and technological expertise, leading to inconsistent and conflicting definitions of disease subtypes. Here, we review several classical and recent subtypes and subtyping approaches and provide concrete definitions to delineate subtypes. In particular, we focus on subtypes with distinct causal disease biology, which are of primary interest to scientists, and subtypes with pragmatic medical benefits, which are of primary interest to physicians. We propose genetic heterogeneity as a gold standard for establishing biologically distinct subtypes of complex polygenic disease. We focus especially on methods to find and validate genetic subtypes, emphasizing common pitfalls and how to avoid them.

Genetic variations in 3´UTRs of SMUG1 and NEIL2 genes modulate breast cancer risk, survival and therapy response

Breast cancer (BC) is the most frequent malignancy in women accounting for approximately 2 million new cases worldwide annually. Several genetic, epigenetic and environmental factors are known to be involved in BC development and progression, including alterations in post-transcriptional gene regulation mediated by microRNAs (miRNAs). Single nucleotide polymorphisms (SNPs) located in miRNA binding sites (miRSNPs) in 3'-untranslated (UTR) regions of target genes may affect miRNA-binding affinity and consequently modulate gene expression. We have previously reported a significant association of miRSNPs in the SMUG1 and NEIL2 genes with overall survival in colorectal cancer patients. SMUG1 and NEIL2 are DNA glycosylases involved in base excision DNA repair (BER). Assuming that certain genetic traits are common for solid tumours, we have investigated wherever variations in SMUG1 and NEIL2 genes display an association with BC risk, prognosis, and therapy response in a group of 673 BC patients and 675 healthy female controls. Patients with TC genotype of NEIL2 rs6997097 and receiving only hormonal therapy displayed markedly shorter overall survival (OS) (HR=4.15, 95% CI=1.7-10.16, P= 0.002) and disease-free survival (DFS) (HR=2.56, 95% CI=1.5-5.7, P= 0.02). Our results suggest that regulation of base excision repair glycosylases operated by miRNAs may modulate the prognosis of hormonally treated BC.

Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation (PERSPECTIVE I&I)

Early detection of breast cancer through screening reduces breast cancer mortality. The benefits of screening must also be considered within the context of potential harms (e.g., false positives, overdiagnosis). Furthermore, while breast cancer risk is highly variable within the population, most screening programs use age to determine eligibility. A risk-based approach is expected to improve the benefit-harm ratio of breast cancer screening programs. The PERSPECTIVE I&I (Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation) project seeks to improve personalized risk assessment to allow for a cost-effective, population-based approach to risk-based screening and determine best practices for implementation in Canada. This commentary describes the four inter-related activities that comprise the PERSPECTIVE I&I project. 1: Identification and validation of novel moderate to high-risk susceptibility genes. 2: Improvement, validation, and adaptation of a risk prediction web-tool for the Canadian context. 3: Development and piloting of a socio-ethical framework to support implementation of risk-based breast cancer screening. 4: Economic analysis to optimize the implementation of risk-based screening. Risk-based screening and prevention is expected to benefit all women, empowering them to work with their healthcare provider to make informed decisions about screening and prevention.

Quality and Quantity: How to Organize a Countrywide Genetic Counseling and Testing

BACKGROUND

About 30% of all women with breast or ovarian cancer exhibit a family history of the disease. So far, the genetic cause could be deciphered in about 30% of these cases. The results demonstrate a high genetic heterogeneity, with high-risk and moderate-risk genes and low-risk variants contributing alone or in concert to the development of cancer. Furthermore, it has been shown that the genotype significantly determines the phenotype and that knowledge of the phenotype is as important as the genotype to offer adequate and risk-adapted prevention to persons at risk. For newly identified risk genes, however, the phenotype is not sufficiently characterized at first, and thus prevention measures are not sufficiently evaluated.

SUMMARY

The German Consortium for Hereditary Breast and Ovarian Cancer has developed a concept for collecting the missing data in the context of knowledge-generating care and at the same time ensuring care based on the best available knowledge. Core elements of this concept are: structured and standardized care, an outcome-oriented evaluation based on a comprehensive registry, networking with certified breast and gynecological cancer centers combined with regular training on state-of-the-art care for doctors, and compilation of comprehensible patient information. This comprehensive concept has been incorporated into contracts for specialized care with health insurers and thus ensures nationwide care at the highest scientific and clinical levels.

KEY MESSAGES

This article describes how to implement a concept of evidence-generating care for risk-adjusted prevention in a nationwide health care system.

Update Breast Cancer 2021 Part 1 - Prevention and Early Stages

This review summarises not only the latest evidence on prevention, but also the current research on the treatment of early-stage breast cancer patients. Recent years have seen a growing body of evidence on the risk of high- and moderate-penetrance breast cancer susceptibility genes. A large international consortium has now been able to further refine the answer to the question of the significance of the so-called panel genes. Moreover, the data on treatment selection regarding endocrine efficacy and the decision for or against chemotherapy have also been advanced markedly. There is also new data on adjuvant CDK4/6 (cyclin-dependent kinase 4/6) inhibitors, which are standard in first-line treatment in patients with metastatic HER2-negative, hormone receptor-positive (HR+) breast cancer. For other therapies such as immune checkpoint inhibitors, which have successfully improved the rate of pathologic complete response (pCR) in neoadjuvant treatment settings for patients with triple-negative breast cancer (TNBC), there is a growing understanding of the quality of life and side effects. This is especially important in situations where patients could possibly be cured without such a regimen.

Leveraging eQTLs to identify individual-level tissue of interest for a complex trait

Genetic predisposition for complex traits often acts through multiple tissues at different time points during development. As a simple example, the genetic predisposition for obesity could be manifested either through inherited variants that control metabolism through regulation of genes expressed in the brain, or that control fat storage through dysregulation of genes expressed in adipose tissue, or both. Here we describe a statistical approach that leverages tissue-specific expression quantitative trait loci (eQTLs) corresponding to tissue-specific genes to prioritize a relevant tissue underlying the genetic predisposition of a given individual for a complex trait. Unlike existing approaches that prioritize relevant tissues for the trait in the population, our approach probabilistically quantifies the tissue-wise genetic contribution to the trait for a given individual. We hypothesize that for a subgroup of individuals the genetic contribution to the trait can be mediated primarily through a specific tissue. Through simulations using the UK Biobank, we show that our approach can predict the relevant tissue accurately and can cluster individuals according to their tissue-specific genetic architecture. We analyze body mass index (BMI) and waist to hip ratio adjusted for BMI (WHRadjBMI) in the UK Biobank to identify subgroups of individuals whose genetic predisposition act primarily through brain versus adipose tissue, and adipose versus muscle tissue, respectively. Notably, we find that these individuals have specific phenotypic features beyond BMI and WHRadjBMI that distinguish them from random individuals in the data, suggesting biological effects of tissue-specific genetic contribution for these traits.

Crohn's disease-associated ATG16L1 T300A genotype is associated with improved survival in gastric cancer

BACKGROUND

A non-synonymous single nucleotide polymorphism of the ATG16L1 gene, T300A, is a major Crohn's disease (CD) susceptibility allele, and is known to be associated with increased apoptosis induction in the small intestinal crypt base in CD subjects and mouse models. We hypothesized that ATG16L1 T300A genotype also correlates with increased tumor apoptosis and therefore could lead to superior clinical outcome in cancer subjects.

METHODS

T300A genotyping by Taqman assay was performed for gastric carcinoma subjects who underwent resection from two academic medical centers. Transcriptomic analysis was performed by RNA-seq on formalin-fixed paraffin-embedded cancerous tissue. Tumor apoptosis and autophagy were determined by cleaved caspase-3 and p62 immunohistochemistry, respectively. The subjects' genotypes were correlated with demographics, various histopathologic features, transcriptome, and clinical outcome.

FINDINGS

Of the 220 genotyped subjects, 163 (74%) subjects carried the T300A allele(s), including 55 (25%) homozygous and 108 (49%) heterozygous subjects. The T300A/T300A subjects had superior overall survival than the other groups. Their tumors were associated with increased CD-like lymphoid aggregates and increased tumor apoptosis without concurrent increase in tumor mitosis or defective autophagy. Transcriptomic analysis showed upregulation of WNT/β-catenin signaling and downregulation of PPAR, EGFR, and inflammatory chemokine pathways in tumors of T300A/T300A subjects.

INTERPRETATION

Gastric carcinoma of subjects with the T300A/T300A genotype is associated with repressed EGFR and PPAR pathways, increased tumor apoptosis, and improved overall survival. Genotyping gastric cancer subjects may provide additional insight for clinical stratification.

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants

BACKGROUND

Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers.

RESULTS

Transcriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype.

CONCLUSIONS

Using a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.

Personalizing Breast Cancer Screening Based on Polygenic Risk and Family History

BACKGROUND

We assessed the clinical utility of a first-degree breast cancer family history and polygenic risk score (PRS) to inform screening decisions among women aged 30-50 years.

METHODS

Two established breast cancer models evaluated digital mammography screening strategies in the 1985 US birth cohort by risk groups defined by family history and PRS based on 313 single nucleotide polymorphisms. Strategies varied in initiation age (30, 35, 40, 45, and 50 years) and interval (annual, hybrid, biennial, triennial). The benefits (breast cancer deaths averted, life-years gained) and harms (false-positive mammograms, overdiagnoses) were compared with those seen with 3 established screening guidelines.

RESULTS

Women with a breast cancer family history who initiated biennial screening at age 40 years (vs 50 years) had a 36% (model range = 29%-40%) increase in life-years gained and 20% (model range = 16%-24%) more breast cancer deaths averted, but 21% (model range = 17%-23%) more overdiagnoses and 63% (model range = 62%-64%) more false positives. Screening tailored to PRS vs biennial screening from 50 to 74 years had smaller positive effects on life-years gained (20%) and breast cancer deaths averted (11%) but also smaller increases in overdiagnoses (10%) and false positives (26%). Combined use of family history and PRS vs biennial screening from 50 to 74 years had the greatest increase in life-years gained (29%) and breast cancer deaths averted (18%).

CONCLUSIONS

Our results suggest that breast cancer family history and PRS could guide screening decisions before age 50 years among women at increased risk for breast cancer but expected increases in overdiagnoses and false positives should be expected.

Potential functional variants of KIAA genes are associated with breast cancer risk in a case control study

Background

KIAA genes identified in the Kazusa cDNA-sequencing project may play important roles in biological processes and are involved in carcinogenesis of many cancers. Genetic variants of KIAA genes are implicated in the abnormal expression of these genes and are linked to susceptibility of several human complex diseases.

Methods

The differentially expressed KIAA genes were screened and identified in The Cancer Genome Atlas (TCGA) database of breast cancer. A total of 48 variants located in the 28 KIAA genes were selected to investigate the associations between polymorphism and breast cancer in 1,032 cases and 1,063 cancer-free controls in a Chinese population.

Results

Two coding variants, which included a SNP rs2306369 in KIAA1109 and a SNP rs1205434 in KIAA1755, were identified to be associated with the incidences of breast cancer. Logistic regression analysis showed that the SNP rs2306369 G allele was associated with a decreased risk of breast cancer (additive model: OR =0.81, 95% CI: 0.66-0.99, P=0.038), whereas the SNP rs1205434 A allele was involved with a higher risk of breast cancer (additive model: OR =1.19, 95% CI: 1.02-1.38, P= 0.025). Further stratified analysis revealed that the SNP rs1205434 showed a significant difference for age at menarche strata (heterogeneity test P=0.009). Multiplicative interaction analysis indicated that there was positive multiplicative interaction between the SNP rs1205434 and menarche age (OR =1.09, 95% CI: 1.01-1.17, P=0.036). Additionally, expression quantitative trait loci analysis revealed that the SNP rs1205434 A allele could decrease the KIAA1755 expression in the Genotype-Tissue Expression (GTEx) database (P=0.002). The Kaplan-Meier plotter showed that breast cancer patients with high KIAA1755 expression have significantly better outcomes than those with low levels of expression (HR =0.84, 95% CI: 0.72-0.99, P=0.033).

Conclusions

The results indicate that the genetic variants (rs2306369 and rs1205434) in the coding region of KIAA1109 and KIAA1755 respectively may affect Chinese females' breast cancer susceptibility and act as potential predictive biomarkers for breast cancer.

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.

Variable expression quantitative trait loci analysis of breast cancer risk variants

Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations (p < 5 × 10^–8) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes (CYP11B1, CYP17A1 HSD3B2 and STAR) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO, suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.

Genome-wide long non-coding RNA association study on Han Chinese women identifies lncHSAT164 as a novel susceptibility gene for breast cancer

Background:

Single-nucleotide polymorphisms (SNPs)-associated genes and long non-coding RNAs (lncRNAs) can contribute to human disease. To comprehensively investigate the contribution of lncRNAs to breast cancer, we performed the first genome-wide lncRNA association study on Han Chinese women.

Methods:

We designed an lncRNA array containing >800,000 SNPs, which was incorporated into a 96-array plate by Affymetrix (CapitalBio Technology, China). Subsequently, we performed a two-stage genome-wide lncRNA association study on Han Chinese women covering 11,942 individuals (5634 breast cancer patients and 6308 healthy controls). Additionally, in vitro gain or loss of function strategies were performed to clarify the function of a novel SNP-associated gene.

Results:

We identified a novel breast cancer-associated susceptibility SNP, rs11066150 (P_meta = 2.34 × 10⁻⁸), and a previously reported SNP, rs9397435 (P_meta = 4.32 × 10⁻³⁸), in Han Chinese women. rs11066150 is located in NONHSAT164009.1 (lncHSAT164), which is highly expressed in breast cancer tissues and cell lines. lncHSAT164 overexpression promoted colony formation, whereas lncHSAT164 knockdown promoted cell apoptosis and reduced colony formation by regulating the cell cycle.

Conclusions:

Based on our lncRNA array, we identified a novel breast cancer-associated lncRNA and found that lncHSAT164 may contribute to breast cancer by regulating the cell cycle. These findings suggest a potential therapeutic target in breast cancer.

Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers

Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes rel to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.

Associations of MDM2 and MDM4 Polymorphisms with Early-Stage Breast Cancer

Breast cancer is one of the most common cancers worldwide. Single nucleotide polymorphisms (SNPs) in MDM2 and MDM4 have been associated with various cancers. However, the influence on clinical characteristics of breast cancer has not been sufficiently investigated yet. Thus, this study aimed to investigate the relationship between SNPs in MDM2 (rs2279744, rs937283, rs937282) and MDM4 (rs1380576, rs4245739) and I-II stage breast cancer. For analysis, the genomic DNA was extracted from 100 unrelated women peripheral blood. Polymorphisms were analyzed with polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. The study showed that MDM2 rs937283 and rs937282 were significantly associated with estrogen receptor status and human epidermal growth factor receptor 2 (HER2) status. SNPs rs1380576 and rs4245739, located in MDM4, were significantly associated with status of estrogen and progesterone receptors. Our findings suggest that rs937283 AG, rs937282 CG, rs1380576 CC, and rs4245739 AA genotypes were linked to hormonal receptor positive breast cancer and may be useful genetic markers for disease 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.

RNF168 regulates R-loop resolution and genomic stability in BRCA1/2-deficient tumors

Germline mutations in BRCA1 and BRCA2 (BRCA1/2) genes considerably increase breast and ovarian cancer risk. Given that tumors with these mutations have elevated genomic instability, they exhibit relative vulnerability to certain chemotherapies and targeted treatments based on poly (ADP-ribose) polymerase (PARP) inhibition. However, the molecular mechanisms that influence cancer risk and therapeutic benefit or resistance remain only partially understood. BRCA1 and BRCA2 have also been implicated in the suppression of R-loops, triple-stranded nucleic acid structures composed of a DNA:RNA hybrid and a displaced ssDNA strand. Here, we report that loss of RNF168, an E3 ubiquitin ligase and DNA double-strand break (DSB) responder, remarkably protected Brca1-mutant mice against mammary tumorigenesis. We demonstrate that RNF168 deficiency resulted in accumulation of R-loops in BRCA1/2-mutant breast and ovarian cancer cells, leading to DSBs, senescence, and subsequent cell death. Using interactome assays, we identified RNF168 interaction with DHX9, a helicase involved in the resolution and removal of R-loops. Mechanistically, RNF168 directly ubiquitylated DHX9 to facilitate its recruitment to R-loop-prone genomic loci. Consequently, loss of RNF168 impaired DHX9 recruitment to R-loops, thereby abrogating its ability to resolve R-loops. The data presented in this study highlight a dependence of BRCA1/2-defective tumors on factors that suppress R-loops and reveal a fundamental RNF168-mediated molecular mechanism that governs cancer development and vulnerability.

Assessment of ADCY9 polymorphisms and colorectal cancer risk in the Chinese Han population

BACKGROUND

Recently, ADCY9 has been found to be highly expressed in colon cancer, and high ADCY9 expressionis a poor prognostic factor of colon cancer. However, no study has reported on the relationship between single nucleotide polymorphisms (SNPs) of ADCY9 and colorectal cancer risk in the Chinese Han population.

METHODS

To evaluate the association between four ADCY9 SNPs and colorectal cancer risk, we performed a case-control study including 511 colorectal cancer patients and 511 healthy controls. SNPs were genotyped using the Agena MassARRAY platform (Agena Bioscience, San Diego, CA, USA). The distributions of alleles and genotypes frequencies between the case and control groups were compared using chi-squared. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by logistic regression adjusted for age and gender to assess the association between SNPs and colorectal cancer risk.

RESULTS

The overall analysis found that rs2230742 was associated with an increased risk of colorectal cancer (AA versus GG: OR = 3.54, 95% CI = 1.16-10.86, p = 0.027; recessive model: OR = 3.55, 95% CI = 1.16-10.85, p = 0.027). Stratification analysis showed that rs2230742 was associated with an increased rectal cancer risk; rs11076810 was associated with a reduced colorectal cancer risk for age > 59 years. No association was observed between other two SNPs and colorectal cancer risk.

CONCLUSIONS

Our findings suggest that ADCY9 polymorphisms (rs2230742 and rs11076810) have an effect on colorectal cancer risk in the Chinese Han population. Future association and functional studies are required to confirm our findings and explore the mechanism of ADCY2 in colorectal cancer.

Gene- and pathway-level analyses of iCOGS variants highlight novel signaling pathways underlying familial breast cancer susceptibility

Single‐nucleotide polymorphisms (SNPs) in over 180 loci have been associated with breast cancer (BC) through genome‐wide association studies involving mostly unselected population‐based case‐control series. Some of them modify BC risk of women carrying a BRCA1 or BRCA2 (BRCA1/2) mutation and may also explain BC risk variability in BC‐prone families with no BRCA1/2 mutation. Here, we assessed the contribution of SNPs of the iCOGS array in GENESIS consisting of BC cases with no BRCA1/2 mutation and a sister with BC, and population controls. Genotyping data were available for 1281 index cases, 731 sisters with BC, 457 unaffected sisters and 1272 controls. In addition to the standard SNP‐level analysis using index cases and controls, we performed pedigree‐based association tests to capture transmission information in the sibships. We also performed gene‐ and pathway‐level analyses to maximize the power to detect associations with lower‐frequency SNPs or those with modest effect sizes. While SNP‐level analyses identified 18 loci, gene‐level analyses identified 112 genes. Furthermore, 31 Kyoto Encyclopedia of Genes and Genomes and 7 Atlas of Cancer Signaling Network pathways were highlighted (false discovery rate of 5%). Using results from the “index case‐control” analysis, we built pathway‐derived polygenic risk scores (PRS) and assessed their performance in the population‐based CECILE study and in a data set composed of GENESIS‐affected sisters and CECILE controls. Although these PRS had poor predictive value in the general population, they performed better than a PRS built using our SNP‐level findings, and we found that the joint effect of family history and PRS needs to be considered in risk prediction models.

What's new?

Genetic studies have identified more than 180 single‐nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, but these studies are reaching their limits. Here, the authors evaluated SNPs in the iCOGS genotyping array using a multilevel approach, including single variant, gene, and pathway analyses. They measured the contribution of the SNPs to breast cancer in patients who have a sister with breast cancer but do not carry a BRCA1/2 mutation. They showed that a pathway‐derived polygenic risk score performed poorly in the general population, and that the best predictive model must include family history.

Relationships of physical and breast cancer phenotypes with three single-nucleotide polymorphisms (rs2046210, rs3757318, and rs3803662) associated with breast cancer risk in Japanese women

BACKGROUND

Recent genome-wide association studies have shown that many single-nucleotide polymorphisms (SNPs) are associated with breast cancer risk. However, it is often unclear how these SNPs are related to breast cancer. Analysis of associations between SNPs and phenotypes may be important for determining mechanisms of action, including carcinogenesis.

METHODS

In previous case-control studies, we found three SNPs (rs2046210, rs3757318, and rs3573318) associated with breast cancer risk in Japanese women. Among these SNPs, two (rs2046210 and rs3757318) are located at 6q25.1, in proximity to the estrogen receptor 1 gene (ESR1). Using data from these studies, we examined associations between factors related to breast cancer risk, such as height, weight, and breast density, and the three SNPs in cases and controls. We also investigated whether the SNPs correlated with breast cancer features, such as estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor type-2 (HER2) status, and clinical stage.

RESULTS

There was a significant difference in mean height between risk and non-risk allele carriers for rs2046210 (156.0 ± 5.8 vs. 154.3 ± 5.5 cm, p = 0.002), and rs3757318 (155.8 ± 5.7 vs. 154.7 ± 5.6 cm, p = 0.035) in cases, but no significant associations between height and these SNPs in controls. There was also a significant difference in breast density between risk and non-risk allele carriers for rs2046210 (p = 0.040) and rs3757318 (p = 0.044) in cases. rs2046210 and rs3757318 risk allele carriers tended to have higher breast density in all subjects and in controls. In cases, rs3757318 risk allele carriers were also significantly more likely to be ER-negative compared to non-risk allele carriers (ER-positive rate: 77% vs. 84%, p = 0.036).

CONCLUSIONS

SNPs rs2046210 and rs3757318, which are associated with breast cancer risk in Japanese women, were significantly associated with height and high breast density, and this association was particularly strong in those with breast cancer. These findings suggest that SNPs in the ESR1 gene region affect phenotypes such as height and breast density.

Update Breast Cancer 2020 Part 3 - Early Breast Cancer

The treatment of patients with early breast cancer has always been characterised by escalation by new therapies and de-escalation through identification of better treatment regimens or introduction of better tools to estimate prognosis. Efforts in some of these areas in the last few years have led to solid data. The results of the large studies of de-escalation through use of multi-gene tests are available, as are the results of some studies that investigated the new anti-HER2 substances T-DM1 and pertuzumab in the early treatment situation. Several large-scale studies examining the role of CDK4/6 inhibitors will soon be concluded so innovations can be anticipated in this area also. This review article will summarise and classify the results of the latest publications.

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.

Causal Inference between Rheumatoid Arthritis and Breast Cancer in East Asian and European Population: A Two-Sample Mendelian Randomization

Simple Summary

Rheumatoid arthritis (RA) is one of the chronic autoimmune diseases that affects about 0.5 to 1.0% of the general population worldwide. The main symptom of RA is the destruction of the synovial joint, leading to a reduced quality of life and increased mortality. RA may be accompanied by several comorbidities, on which several studies have been conducted on the association between RA and breast cancer. However, the association between RA and breast cancer has shown different directions and has not been clearly established. In this study, we tried to determine whether RA had a causal effect on breast cancer using Mendelian randomization (MR) analysis, but causal evidence was not found. Therefore, additional studies are needed to determine whether RA patients are at high risk of breast cancer, based on large-scale cohorts to validate these results.

Abstract

Previous studies have been reported that the association between rheumatoid arthritis (RA) and breast cancer remains inconclusive. A two-sample Mendelian randomization (MR) analysis can reveal the potential causal association between exposure and outcome. A two-sample MR analysis using the penalized robust inverse variance weighted (PRIVW) method was performed to analyze the association between RA and breast cancer risk based on the summary statistics of six genome-wide association studies (GWAS) targeting RA in an East Asian population along with summary statistics of the BioBank Japan (BBJ), Breast Cancer Association Consortium (BCAC), and Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) targeting breast cancer. We found that the direction of the effect of RA on breast cancer varied among GWAS-summary data from BBJ, BCAC, and CIMBA. Significant horizontal pleiotropy based on a penalized robust MR-Egger regression was observed only for BBJ and CIMBA BRCA2 carriers. As the results of the two-sample MR analyses were inconsistent, the causal association between RA and breast cancer was inconclusive. The biological mechanisms explaining the relationship between RA and breast cancer were unclear in Asian as well as in Caucasians. Further studies using large-scale patient cohorts are required for the validation of these results.

Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks

To facilitate scientific collaboration on polygenic risk scores (PRSs) research, we created an extensive PRS online repository for 35 common cancer traits integrating freely available genome-wide association studies (GWASs) summary statistics from three sources: published GWASs, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWASs. Our framework condenses these summary statistics into PRSs using various approaches such as linkage disequilibrium pruning/p value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRSs in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRSs. We expect this integrated platform to accelerate PRS-related cancer research.

Personalized early detection and prevention of breast cancer: ENVISION consensus statement

The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.

Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10-8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.

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.

Polygenic risk scores and breast and epithelial ovarian cancer risks for carriers of BRCA1 and BRCA2 pathogenic variants

PURPOSE

We assessed the associations between population-based polygenic risk scores (PRS) for breast (BC) or epithelial ovarian cancer (EOC) with cancer risks for BRCA1 and BRCA2 pathogenic variant carriers.

METHODS

Retrospective cohort data on 18,935 BRCA1 and 12,339 BRCA2 female pathogenic variant carriers of European ancestry were available. Three versions of a 313 single-nucleotide polymorphism (SNP) BC PRS were evaluated based on whether they predict overall, estrogen receptor (ER)-negative, or ER-positive BC, and two PRS for overall or high-grade serous EOC. Associations were validated in a prospective cohort.

RESULTS

The ER-negative PRS showed the strongest association with BC risk for BRCA1 carriers (hazard ratio [HR] per standard deviation = 1.29 [95% CI 1.25-1.33], P = 3×10-72). For BRCA2, the strongest association was with overall BC PRS (HR = 1.31 [95% CI 1.27-1.36], P = 7×10-50). HR estimates decreased significantly with age and there was evidence for differences in associations by predicted variant effects on protein expression. The HR estimates were smaller than general population estimates. The high-grade serous PRS yielded the strongest associations with EOC risk for BRCA1 (HR = 1.32 [95% CI 1.25-1.40], P = 3×10-22) and BRCA2 (HR = 1.44 [95% CI 1.30-1.60], P = 4×10-12) carriers. The associations in the prospective cohort were similar.

CONCLUSION

Population-based PRS are strongly associated with BC and EOC risks for BRCA1/2 carriers and predict substantial absolute risk differences for women at PRS distribution extremes.

Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification

BACKGROUND

External validation of risk models is critical for risk-stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) as a flexible tool for risk model development and comparative model validation and to make projections for population risk stratification.

METHODS

Performance of two recently developed models, one based on the Breast and Prostate Cancer Cohort Consortium analysis (iCARE-BPC3) and another based on a literature review (iCARE-Lit), were compared with two established models (Breast Cancer Risk Assessment Tool and International Breast Cancer Intervention Study Model) based on classical risk factors in a UK-based cohort of 64 874 white non-Hispanic women (863 patients) age 35-74 years. Risk projections in a target population of US white non-Hispanic women age 50-70 years assessed potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS).

RESULTS

The best calibrated models were iCARE-Lit (expected to observed number of cases [E/O] = 0.98, 95% confidence interval [CI] = 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O = 1.00, 95% CI = 0.93 to 1.09) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify approximately 500 000 women at moderate to high risk (>3% 5-year risk) in the target population. Addition of MD and a 313-variant PRS is expected to increase this number to approximately 3.5 million women, and among them, approximately 153 000 are expected to develop invasive breast cancer within 5 years.

CONCLUSIONS

iCARE models based on classical risk factors perform similarly to or better than BCRAT or IBIS in white non-Hispanic women. Addition of MD and PRS can lead to substantial improvements in risk stratification. However, these integrated models require independent prospective validation before broad clinical applications.

SNPs in the interleukin-12 signaling pathway are associated with breast cancer risk in Puerto Rican women

Interleukin-12 (IL-12) is a proinflammatory cytokine that links innate and adaptive immune responses against tumor cells. Single Nucleotide Polymorphisms (SNPs) in IL-12 genes have been associated with cancer risk. However, limited studies have assessed the role of IL-12 in breast cancer (BC) risk comprehensively, and these were done in European and Asian populations. Here, we evaluated the association of the IL-12 signaling pathway and BC risk in Puerto Rican women. A genetic association study was completed with 461 BC cases and 463 non-BC controls. By logistic regression, IL-12 signaling SNPs were associated with an increased BC risk, including rs2243123 (IL12A), rs3761041, rs401502 and rs404733 (IL12RB1), rs7849191 (JAK2), rs280500 (TYK2) and rs4274624 (STAT4). Conversely, other SNPs were associated with reduced BC risk including rs438421 (IL12RB1), rs6693065 (IL12RB2), rs10974947, and rs2274471 (JAK2), rs10168266 and rs925847 (STAT4), and rs2069718 (IFNG). Analyses based in hormone receptors such as estrogen (ER) and progesterone (PR) receptors also revealed protective (for SNPs rs3212227-IL12B; rs3024896 and rs3821236-STAT4) and predisposing (for rs2069705-IFNG SNP) BC associations. Haplotype analysis showed a decreased BC risk for IL12B and STAT4 SNPs, whereas increased risk for IL12RB1 SNPs. This study suggests a role of the IL-12 signaling axis and BC risk. SNPs in this pathway may alter IL-12 induced anti-tumor responses and modulate BC predisposition in a population-specific context. Functional studies will be necessary to confirm these findings, which potentially may benefit IL-12 related immunotherapeutic approaches towards BC.

Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer

Germline genetic variation has been suggested to influence the survival of breast cancer patients independently of tumor pathology. We have studied survival associations of genetic variants in two etiologically unique groups of breast cancer patients, the carriers of germline pathogenic variants in BRCA1 or BRCA2 genes. We found that rs57025206 was significantly associated with the overall survival, predicting higher mortality of BRCA1 carrier patients with estrogen receptor-negative breast cancer, with a hazard ratio 4.37 (95% confidence interval 3.03-6.30, P = 3.1 × 10-9). Multivariable analysis adjusted for tumor characteristics suggested that rs57025206 was an independent survival marker. In addition, our exploratory analyses suggest that the associations between genetic variants and breast cancer patient survival may depend on tumor biological subgroup and clinical patient characteristics.

Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

Targeting MDMX for Cancer Therapy: Rationale, Strategies, and Challenges

The oncogene MDMX, also known as MDM4 is a critical negative regulator of the tumor suppressor p53 and has been implicated in the initiation and progression of human cancers. Increasing evidence indicates that MDMX is often amplified and highly expressed in human cancers, promotes cancer cell growth, and inhibits apoptosis by dampening p53-mediated transcription of its target genes. Inhibiting MDMX-p53 interaction has been found to be effective for restoring the tumor suppressor activity of p53. Therefore, MDMX is becoming one of the most promising molecular targets for developing anticancer therapeutics. In the present review, we mainly focus on the current MDMX-targeting strategies and known MDMX inhibitors, as well as their mechanisms of action and in vitro and in vivo anticancer activities. We also propose other potential targeting strategies for developing more specific and effective MDMX inhibitors for cancer therapy.

Risk for breast cancer and management of unaffected individuals with non-BRCA hereditary breast cancer

About 5%-10% of breast cancer is hereditary with BRCA1 and BRCA2 being the most common genes associated with hereditary breast cancer (HBC). Several additional genes have recently been associated with HBC. These genes can be classified as highly or moderately penetrant genes with lifetime risk >30% or 17%-30%, respectively. Highly penetrant genes associated with HBC include TP53, PTEN, CDH1, STK11, and PALB2. While, moderately penetrant genes include CHEK2, ATM, BARD1, BRIP1, NBN, NF1, RAD51D, and MSH6. Breast cancer risk and recommendations for screening and risk-reduction vary by gene. In general, screening breast MRI is recommended for women at >20% lifetime risk, which includes women with mutations in highly penetrant genes and the majority (but not all) moderately penetrant genes. Consideration of chemoprevention is recommended for women with mutations in high and moderately penetrant genes. Risk-reducing mastectomy does reduce the risk of breast cancer to the greatest extent and can be considered for women with highly penetrant genes. However, this procedure is associated with significant morbidities that should be considered, especially given the benefit of using screening breast MRI for high-risk women. BSO is only recommended for women with mutations in genes associate with increased risk for ovarian cancer and not as a breast cancer risk-reducing strategy. As more women undergo testing, additional genes may be identified and risk estimates for current genes and management recommendations may be modified.

A meta-analysis and in silico analysis of polymorphic variants conferring breast cancer risk in the Indian subcontinent

Background: Genetic association studies on breast cancer on the Indian subcontinent have yielded conflicting results, and the precise effect of these variants on breast cancer pathogenesis is not known. Methods: Genomic variants, as obtained from selected studies from the Indian subcontinent, were subjected to random-effects and fixed-effect meta-analysis. Functional annotation of the relevant variants was done through a tried and tested in silico pipeline. Results: We found rs4646903/CYP1A1, rs1799814/CYP1A1, rs61886492/GCPII, del2/GSTM1, rs4680/COMT and rs1801394/MTRR to be associated with breast cancer. The del2/GSTM1 holds the association in premenopausal women. Conclusions: This is the first study of its kind from the Indian subcontinent analysing the extent of association of variants across populations followed by their functional annotation in the disease pathway.

Emerging Roles of Long Non-Coding RNAs in Renal Fibrosis

Renal fibrosis is an unavoidable consequence that occurs in nearly all of the nephropathies. It is characterized by a superabundant deposition and accumulation of extracellular matrix (ECM). All compartments in the kidney can be affected, including interstitium, glomeruli, vasculature, and other connective tissue, during the pathogenesis of renal fibrosis. The development of this process eventually causes destruction of renal parenchyma and end-stage renal failure, which is a devastating disease that requires renal replacement therapies. Recently, long non-coding RNAs (lncRNAs) have been emerging as key regulators governing gene expression and affecting various biological processes. These versatile roles include transcriptional regulation, organization of nuclear domains, and the regulation of RNA molecules or proteins. Current evidence proposes the involvement of lncRNAs in the pathologic process of kidney fibrosis. In this review, the biological relevance of lncRNAs in renal fibrosis will be clarified as important novel regulators and potential therapeutic targets. The biology, and subsequently the current understanding, of lncRNAs in renal fibrosis are demonstrated—highlighting the involvement of lncRNAs in kidney cell function, phenotype transition, and vascular damage and rarefaction. Finally, we discuss challenges and future prospects of lncRNAs in diagnostic markers and potential therapeutic targets, hoping to further inspire the management of renal fibrosis.