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

A Swedish Familial Genome-Wide Haplotype Analysis Identified Five Novel Breast Cancer Susceptibility Loci on 9p24.3, 11q22.3, 15q11.2, 16q24.1 and Xq21.31

Most breast cancer heritability is unexplained. We hypothesized that analysis of unrelated familial cases in a GWAS context could enable the identification of novel susceptibility loci. In order to examine the association of a haplotype with breast cancer risk, we performed a genome-wide haplotype association study using a sliding window analysis of window sizes 1-25 SNPs in 650 familial invasive breast cancer cases and 5021 controls. We identified five novel risk loci on 9p24.3 (OR 3.4; p 4.9 × 10^-11), 11q22.3 (OR 2.4; p 5.2 × 10^-9), 15q11.2 (OR 3.6; p 2.3 × 10^-8), 16q24.1 (OR 3; p 3 × 10^-8) and Xq21.31 (OR 3.3; p 1.7 × 10^-8) and confirmed three well-known loci on 10q25.13, 11q13.3, and 16q12.1. In total, 1593 significant risk haplotypes and 39 risk SNPs were distributed on the eight loci. In comparison with unselected breast cancer cases from a previous study, the OR was increased in the familial analysis in all eight loci. Analyzing familial cancer cases and controls enabled the identification of novel breast cancer susceptibility loci.

Integration of a Cross-Ancestry Polygenic Model With Clinical Risk Factors Improves Breast Cancer Risk Stratification

PURPOSE

To develop and validate a cross-ancestry integrated risk score (caIRS) that combines a cross-ancestry polygenic risk score (caPRS) with a clinical estimator for breast cancer (BC) risk. We hypothesized that the caIRS is a better predictor of BC risk than clinical risk factors across diverse ancestry groups.

METHODS

We used diverse retrospective cohort data with longitudinal follow-up to develop a caPRS and integrate it with the Tyrer-Cuzick (T-C) clinical model. We tested the association between the caIRS and BC risk in two validation cohorts including > 130,000 women. We compared model discrimination for 5-year and remaining lifetime BC risk between the caIRS and T-C and assessed how the caIRS would affect screening in the clinic.

RESULTS

The caIRS outperformed T-C alone for all populations tested in both validation cohorts and contributed significantly to risk prediction beyond T-C. The area under the receiver operating characteristic curve improved from 0.57 to 0.65, and the odds ratio per standard deviation increased from 1.35 (95% CI, 1.27 to 1.43) to 1.79 (95% CI, 1.70 to 1.88) in validation cohort 1 with similar improvements observed in validation cohort 2. We observed the largest gain in positive predictive value using the caIRS in Black/African American women across both validation cohorts, with an approximately two-fold increase and an equivalent negative predictive value as the T-C. In a multivariate, age-adjusted logistic regression model including both caIRS and T-C, caIRS remained significant, indicating that caIRS provides information over T-C alone.

CONCLUSION

Adding a caPRS to the T-C model improves BC risk stratification for women of multiple ancestries, which could have implications for screening recommendations and prevention.

Polygenic risk scores and breast cancer risk prediction

Polygenic Risk Scores (PRS) are a major component of accurate breast cancer risk prediction and have the potential to improve screening and prevention strategies. PRS combine the risk from Single nucleotide polymorphisms (SNPs) associated with breast cancer in Genome Wide Association Studies (GWAS) and explain over 30% of breast cancer heritability. When incorporated into risk models, the more personalised risk assessment derived from PRS, help identify women at higher risk of breast cancer development and enables the implementation of stratified screening and prevention approaches. This review describes the role of PRS in breast cancer risk prediction including the development of PRS and their clinical application. We have also examined the role of PRS within more well-established risk prediction models which incorporate known classic risk factors and discuss the interaction of PRS with these factors and their capacity to predict breast cancer subtypes. Before PRS can be implemented on a population-wide scale, there are several challenges that must be addressed. Perhaps the most pressing of these is the use of PRS in women of non-White European origin, where PRS have been shown to have attenuated risk prediction both in discrimination and calibration. We discuss progress in developing and applying PRS in non-white European populations. PRS represent a significant advance in breast cancer risk prediction and their further development will undoubtedly enhance personalisation.

Inositol 1,4,5-trisphosphate receptor gene variants are related to the risk of breast cancer in a Chinese population

BACKGROUND

Mammalian inositol 1,4,5-trisphosphate receptor (ITPR) genes encode ubiquitously expressed endoplasmic reticulum Ca²⁺ channels that have recently been shown to be closely linked to the pathogenesis of several cancers. However, few studies to date have explored associations between ITPR gene family single nucleotide polymorphisms (SNPs) and breast cancer risk.

METHODS

In the present case-control study, 12 SNPs in the potential functional regions of the ITPR1, ITPR2, and ITPR3 genes were genotyped using an Illumina Infinium® Beadchip in 2095 Chinese women (1032 cases and 1063 controls).

RESULTS

Multivariate logistic regression analyses indicated that a missense SNP in the ITPR3 coding region (rs2229642) was significantly related to breast cancer risk when using an additive model in this study (rs2229642-adjusted odds ratio = 1.40, 95% confidence interval = 1.12-1.74, p = 2.97 × 10^-3 ). Expression quantitative trait loci analyses indicated that the SNP rs2229642 was associated with reduced ITPR3 expression levels (p = 3.2 × 10^-7 ) and with marked reductions in the expressions of several proximal genes, including BAK1, GRM4, HLA-DOB, and UQCC2 (p = 0.013, 0.018, 3.4 × 10^-3 , 3.8 × 10^-5 ), suggesting that it may further regulate other genes associated with oncogenic susceptibility. Kaplan-Meier analyses indicated that the patients with higher ITPR3 expression exhibited significantly poorer outcomes compared to the patients with lower expression of this gene (hazard ratio = 1.11, 95% confidence interval = 1-1.23, p = 0.046).

CONCLUSIONS

The results indicated that genetic variant in the coding region of ITPR3 gene may regulate the expressions of its host and some other cancer-related genes, as well as act as potential predictive biomarker for susceptibility to breast cancer in the Chinese population.

Variable number tandem repeats (VNTRs) as modifiers of breast cancer risk in carriers of BRCA1 185delAG

Despite substantial efforts in identifying both rare and common variants affecting disease risk, in the majority of diseases, a large proportion of unexplained genetic risk remains. We propose that variable number tandem repeats (VNTRs) may explain a proportion of the missing genetic risk. Herein, in a pilot study with a retrospective cohort design, we tested whether VNTRs are causal modifiers of breast cancer risk in 347 female carriers of the BRCA1 185delAG pathogenic variant, an important group given their high risk of developing breast cancer. We performed targeted-capture to sequence VNTRs, called genotypes with adVNTR, tested the association of VNTRs and breast cancer risk using Cox regression models, and estimated the effect size using a retrospective likelihood approach. Of 303 VNTRs that passed quality control checks, 4 VNTRs were significantly associated with risk to develop breast cancer at false discovery rate [FDR] < 0.05 and an additional 4 VNTRs had FDR < 0.25. After determining the specific risk alleles, there was a significantly earlier age at diagnosis of breast cancer in carriers of the risk alleles compared to those without the risk alleles for seven of eight VNTRs. One example is a VNTR in exon 2 of LINC01973 with a per-allele hazard ratio of 1.58 (1.07-2.33) and 5.28 (2.79-9.99) for the homozygous risk-allele genotype. Results from this first systematic study of VNTRs demonstrate that VNTRs may explain a proportion of the unexplained genetic risk for breast cancer.

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.

MiXcan: a framework for cell-type-aware transcriptome-wide association studies with an application to breast cancer

Human bulk tissue samples comprise multiple cell types with diverse roles in disease etiology. Conventional transcriptome-wide association study approaches predict genetically regulated gene expression at the tissue level, without considering cell-type heterogeneity, and test associations of predicted tissue-level expression with disease. Here we develop MiXcan, a cell-type-aware transcriptome-wide association study approach that predicts cell-type-level expression, identifies disease-associated genes via combination of cell-type-level association signals for multiple cell types, and provides insight into the disease-critical cell type. As a proof of concept, we conducted cell-type-aware analyses of breast cancer in 58,648 women and identified 12 transcriptome-wide significant genes using MiXcan compared with only eight genes using conventional approaches. Importantly, MiXcan identified genes with distinct associations in mammary epithelial versus stromal cells, including three new breast cancer susceptibility genes. These findings demonstrate that cell-type-aware transcriptome-wide analyses can reveal new insights into the genetic and cellular etiology of breast cancer and other diseases.

Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease

BACKGROUND

Three partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors.

OBJECTIVE

To assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study.

RESULTS

All three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS₃₁₃ in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively).

CONCLUSION

Our results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2.

Hereditary breast cancer: syndromes, tumour pathology and molecular testing

Hereditary factors account for a significant proportion of breast cancer risk. Approximately 20% of hereditary breast cancers are attributable to pathogenic variants in the highly penetrant BRCA1 and BRCA2 genes. A proportion of the genetic risk is also explained by pathogenic variants in other breast cancer susceptibility genes, including ATM, CHEK2, PALB2, RAD51C, RAD51D and BARD1, as well as genes associated with breast cancer predisposition syndromes - TP53 (Li-Fraumeni syndrome), PTEN (Cowden syndrome), CDH1 (hereditary diffuse gastric cancer), STK11 (Peutz-Jeghers syndrome) and NF1 (neurofibromatosis type 1). Polygenic risk, the cumulative risk from carrying multiple low-penetrance breast cancer susceptibility alleles, is also a well-recognised contributor to risk. This review provides an overview of the established breast cancer susceptibility genes as well as breast cancer predisposition syndromes, highlights distinct genotype-phenotype correlations associated with germline mutation status and discusses molecular testing and therapeutic implications in the context of hereditary breast cancer.

The causal relationship between psoriasis, psoriatic arthritis, and inflammatory bowel diseases

Psoriasis is more common in patients with inflammatory bowel disease (IBD) than in the general population. Similarly, patients with psoriasis or psoriatic arthritis (PsA) have a higher incidence of IBD. However, whether this association is causal remains unknown. Therefore, we used a two-sample bidirectional Mendelian randomization (MR) analysis to identify this relationship. According to MR analysis, psoriasis and PsA causally increased the odds of developing Crohn's disease (OR = 1.350 (1.066-1.709) P = 0.013; OR = 1.319 (1.166-1.492) P < 0.001). In contrast, MR estimates gave little support to a possible causal effect of psoriasis, PsA, on ulcerative colitis (OR = 1.101 (0.905-1.340) P = 0.335; OR = 1.007 (0.941-1.078) P = 0.831). Similarly, the reverse analysis suggested the Crohn's disease causally increased the odds of psoriasis and PsA (OR = 1.425 (1.174-1.731) P < 0.001; OR = 1.448 (1.156-1.182) P = 0.001), whereas there are no causal association between ulcerative colitis and psoriasis, PsA (OR = 1.192 (0.921-1.542) P = 0.182; OR = 1.166 (0.818-1.664) P = 0.396). In summary, our MR analysis strengthens the evidence for the bidirectional dual causality between psoriasis (including PsA) and Crohn's disease.

Associations between circulating proteins and risk of breast cancer by intrinsic subtypes: a Mendelian randomisation analysis

BACKGROUND

The aetiologic role of circulating proteins in the development of breast cancer subtypes is not clear. We aimed to examine the potential causal effects of circulating proteins on the risk of breast cancer by intrinsic-like subtypes within the Mendelian randomisation (MR) framework.

METHODS

MR was performed using summary statistics from two sources: the INTERVAL protein quantitative trait loci (pQTL) Study (1890 circulating proteins and 3301 healthy individuals) and the Breast Cancer Association Consortium (BCAC; 106,278 invasive cases and 91,477 controls). The inverse-variance (IVW)-weighted method was used as the main analysis to evaluate the associations between genetically predicted proteins and the risk of five different intrinsic-like breast cancer subtypes and the weighted median MR method, the Egger regression, the MR-PRESSO, and the MRLocus method were performed as secondary analysis.

RESULTS

We identified 98 unique proteins significantly associated with the risk of one or more subtypes (Benjamini-Hochberg false discovery rate < 0.05). Among them, 51 were potentially specific to luminal A-like subtype, 14 to luminal B/Her2-negative-like, 11 to triple negative, 3 to luminal B-like, and 2 to Her2-enriched-like breast cancer (ntotal = 81). Associations for three proteins (ICAM1, PLA2R1 and TXNDC12) showed evident heterogeneity across the subtypes. For example, higher levels of genetically predicted ICAM1 (per unit of increase) were associated with an increased risk of luminal B/HER2-negative-like cancer (OR = 1.06, 95% CI = 1.03-1.08, BH-FDR = 2.43 × 10-4) while inversely associated with triple-negative breast cancer with borderline significance (OR = 0.97, 95% CI = 0.95-0.99, BH-FDR = 0.065, Pheterogeneity < 0.005).

CONCLUSIONS

Our study found potential causal associations with the risk of subtypes of breast cancer for 98 proteins. Associations of ICAM1, PLA2R1 and TXNDC12 varied substantially across the subtypes. The identified proteins may partly explain the heterogeneity in the aetiology of distinct subtypes of breast cancer and facilitate the personalised risk assessment of the malignancy.

Metabolomics in Diabetic Retinopathy: From Potential Biomarkers to Molecular Basis of Oxidative Stress

Diabetic retinopathy (DR), the leading cause of blindness in working-age adults, is one of the most common complications of diabetes mellitus (DM) featured by metabolic disorders. With the global prevalence of diabetes, the incidence of DR is expected to increase. Prompt detection and the targeting of anti-oxidative stress intervention could effectively reduce visual impairment caused by DR. However, the diagnosis and treatment of DR is often delayed due to the absence of obvious signs of retina imaging. Research progress supports that metabolomics is a powerful tool to discover potential diagnostic biomarkers and therapeutic targets for the causes of oxidative stress through profiling metabolites in diseases, which provides great opportunities for DR with metabolic heterogeneity. Thus, this review summarizes the latest advances in metabolomics in DR, as well as potential diagnostic biomarkers, and predicts molecular targets through the integration of genome-wide association studies (GWAS) with metabolomics. Metabolomics provides potential biomarkers, molecular targets and therapeutic strategies for controlling the progress of DR, especially the interventions at early stages and precise treatments based on individual patient variations.

Breast cancer polygenic risk scores are associated with short-term risk of poor prognosis breast cancer

PURPOSE

Polygenic risk scores (PRS) for breast cancer may help guide screening decisions. However, few studies have examined whether PRS are associated with risk of short-term or poor prognosis breast cancers. The study purpose was to evaluate the association of the 313 SNP breast cancer PRS with 2-year risk of poor prognosis breast cancer.

METHODS

We evaluated the association of breast cancer PRS with breast cancer overall, ER + and ER- breast cancer, and poor prognosis breast cancer diagnosed within 2 years of a negative mammogram among a cohort of 3657 women using logistic regression adjusted for age, breast density, race/ethnicity, year of screening, and genetic ancestry principal components. Breast cancers were considered poor prognosis if they were metastatic, positive lymph nodes, ER/PR + HER2- and > 2 cm, ER/PR/HER2-, or HER2 + and > 1 cm.

RESULTS

Of the 308 breast cancers, 137 (44%) were poor prognosis. The overall breast cancer PRS was significantly associated with breast cancer diagnosis within 2 years (OR 1.39, 95% CI 1.23-1.57, p < 0.001). The breast cancer PRS was also associated specifically with diagnosis of poor prognosis disease (OR 1.24, 95% CI 1.03-1.49, p = 0.018), but was more strongly associated with good prognosis cancer (OR 1.52 95% CI 1.29-1.80 p = 3.60 × 10^-7) The ER + PRS was significantly associated with ER/PR + breast cancer (OR 1.41, 95% CI 1.24-1.61, p < 0.001) and the ER- PRS was significantly associated with ER- breast cancer (OR 1.48, 95% CI 1.08-2.02, p = 0.015).

CONCLUSION

Breast cancer PRS was independently and significantly associated with diagnosis of both breast cancer overall and poor prognosis breast cancer within 2 years of a negative mammogram, suggesting PRS may help guide decisions about screening intervals and supplemental screening.

Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Genetic Causal Association between Iron Status and Osteoarthritis: A Two-Sample Mendelian Randomization

Objective: Observational studies have shown the association between iron status and osteoarthritis (OA). However, due to difficulties of determining sequential temporality, their causal association is still elusive. Based on the summary data of genome-wide association studies (GWASs) of a large-scale population, this study explored the genetic causal association between iron status and OA. Methods: First, we took a series of quality control steps to select eligible instrumental SNPs which were strongly associated with exposure. The genetic causal association between iron status and OA was analyzed using the two-sample Mendelian randomization (MR). Inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods were used for analysis. The results were mainly based on IVW (random effects), followed by sensitivity analysis. IVW and MR-Egger were used for heterogeneity testing. MR-Egger was also used for pleiotropy testing. Leave-one-SNP-out analysis was used to identify single nucleotide polymorphisms (SNPs) with potential impact. Maximum likelihood, penalized weighted median, and IVW (fixed effects) were performed to further validate the reliability of results. Results: IVW results showed that transferrin saturation had a positive causal association with knee osteoarthritis (KOA), hip osteoarthritis (HOA) and KOA or HOA (p < 0.05, OR > 1), and there was a negative causal association between transferrin and HOA and KOA or HOA (p < 0.05, OR < 1). The results of heterogeneity test showed that our IVW analysis results were basically free of heterogeneity (p > 0.05). The results of the pleiotropy test showed that there was no pleiotropy in our IVW analysis (p > 0.05). The analysis results of maximum likelihood, penalized weighted median and IVW (fixed effects) were consistent with our IVW results. No genetic causal association was found between serum iron and ferritin and OA. Conclusions: This study provides evidence of the causal association between iron status and OA, which provides novel insights to the genetic research of OA.

Combining Organoid Models with Next-Generation Sequencing to Reveal Tumor Heterogeneity and Predict Therapeutic Response in Breast Cancer

Estrogen receptor-positive (ER+) breast cancer (BC) is a common subtype of BC with a relatively good prognosis. However, recurrence and death from ER+ BC occur because of tumor heterogeneity. This study aimed to explore tumor heterogeneity using next-generation sequencing (NGS) and tumor-organoid models to promote BC precise therapy. We collected needle biopsy, surgical excision, and cerebrospinal fluid (CSF) samples to establish tumor organoids. We found that the histological characteristics of organoids were consistent with original lesions and recapitulated their heterogenicity. In addition, the NGS results showed that PIK3CA and TP53 genes had detrimental mutations. BAP1, RET, AXIN2, and PPP2R2A genes had mutations with unknown function. The score for homologous recombination deficiency (HRD) of genome was 56, indicating that the tumor was likely sensitive to PARPi. The mutant-allele tumor heterogeneity (MATH) value of the tumor genome was 68.03, indicating high tumor heterogeneity. At last, we performed a drug screening on organoids. The toxicity of different drugs toward BC organoids originated from needle biopsy and surgical excision was tested, respectively. The IC50 values in the needle biopsy groups were paclitaxel 2.83 μM, carboplatin 61.47 μM, neratinib 0.8 μM, lapatinib >100 μM; in the surgical excision groups: trastuzumab >100 μM, docetaxel 0.036 μM, tamoxifen 20.54 μM, olaparib 5.478 μM, BYL719 < 0.1 μM. The toxicity data showed that the BC organoids could show dynamic characteristics of tumor progression and reflect the heterogeneity of BC. Our study demonstrates that the combined use of tumor organoids and NGS is a potential way to test tumor heterogeneity and predict drug response in ER + BC, which contributes to the development of personalized therapy.

Investigating the shared genetic architecture of uterine leiomyoma and breast cancer: A genome-wide cross-trait analysis

Little is known regarding the shared genetic architecture or causality underlying the phenotypic association observed for uterine leiomyoma (UL) and breast cancer (BC). Leveraging summary statistics from the hitherto largest genome-wide association study (GWAS) conducted in each trait, we investigated the genetic overlap and causal associations of UL with BC overall, as well as with its subtypes defined by the status of estrogen receptor (ER). We observed a positive genetic correlation between UL and BC overall (rg = 0.09, p = 6.00 × 10-3), which was consistent in ER+ subtype (rg = 0.06, p = 0.01) but not in ER- subtype (rg = 0.06, p = 0.08). Partitioning the whole genome into 1,703 independent regions, local genetic correlation was identified at 22q13.1 for UL with BC overall and with ER+ subtype. Significant genetic correlation was further discovered in 9 out of 14 functional categories, with the highest estimates observed in coding, H3K9ac, and repressed regions. Cross-trait meta-analysis identified 9 novel loci shared between UL and BC. Mendelian randomization demonstrated a significantly increased risk of BC overall (OR = 1.09, 95% CI = 1.01-1.18) and ER+ subtype (OR = 1.09, 95% CI = 1.01-1.17) for genetic liability to UL. No reverse causality was found. Our comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis, pleiotropic loci, as well as a putative causal relationship between UL and BC, highlighting an intrinsic link underlying these two complex female diseases.

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.

Identification and Management of Pathogenic Variants in BRCA1, BRCA2, and PALB2 in a Tumor-Only Genomic Testing Program

PURPOSE

Tumor-only genomic testing can uncover somatic and germline pathogenic variants [pathogenic/likely pathogenic (P/LP)] in cancer predisposition genes. We describe the prevalence of P/LPs in BRCA1/2 and PALB2 (B1B2P2) across malignancies and the frequency of clinical germline testing (CGT) in patients with P/LPs in B1B2P2 identified on tumor-only testing.

EXPERIMENTAL DESIGN

Among 7,575 patients with cancer tested between 2016 and 2018 with the OncoPanel tumor-only sequencing assay, we characterized P/LP frequencies by tumor type, receipt of CGT prior to or within 12 months after OncoPanel, and factors associated with CGT.

RESULTS

272 (3.6%) patients had OncoPanel-detected P/LPs in B1B2P2: 37.5% of P/LPs were in BRCA-related cancers; the remainder were in non-BRCA tumors. P/LPs were detected in ≥5% of breast, pancreatic, prostate, ovarian, nonmelanoma skin, endometrial, small cell lung, and colorectal cancers. 37.9% of patients with P/LPs received CGT prior to OncoPanel; an additional 10.7% underwent CGT within 12 months of OncoPanel. Among 132 with CGT, 88.6% had ≥1 clinical factor for CGT compared with 47.1% who did not undergo CGT. Patients with BRCA tumors were more likely to have CGT compared with those without (81.4% vs. 29.0%, P < 0.0001). Among patients with CGT, 70.5% (93/132) of P/LPs were germline.

CONCLUSIONS

Tumor-only genomic testing identified P/LPs in B1B2P2 in 3.6% of patients. 52.9% of patients with tumor-detected P/LPs and without CGT did not meet personal or family history criteria for CGT. In addition, some patients with tumor-detected P/LPs were not referred for CGT, especially those with non-BRCA tumors. Given implications for treatment selection and familial cancer risk, processes to reliably trigger CGT from tumor-genomic findings are needed.

Lipid exposure activates gene expression changes associated with estrogen receptor negative breast cancer

Improved understanding of local breast biology that favors the development of estrogen receptor negative (ER-) breast cancer (BC) would foster better prevention strategies. We have previously shown that overexpression of specific lipid metabolism genes is associated with the development of ER- BC. We now report results of exposure of MCF-10A and MCF-12A cells, and mammary organoids to representative medium- and long-chain polyunsaturated fatty acids. This exposure caused a dynamic and profound change in gene expression, accompanied by changes in chromatin packing density, chromatin accessibility, and histone posttranslational modifications (PTMs). We identified 38 metabolic reactions that showed significantly increased activity, including reactions related to one-carbon metabolism. Among these reactions are those that produce S-adenosyl-L-methionine for histone PTMs. Utilizing both an in-vitro model and samples from women at high risk for ER- BC, we show that lipid exposure engenders gene expression, signaling pathway activation, and histone marks associated with the development of ER- BC.

Pathogenic BRCA1 variants disrupt PLK1-regulation of mitotic spindle orientation

Preneoplastic mammary tissues from human female BRCA1 mutation carriers, or Brca1-mutant mice, display unexplained abnormalities in luminal differentiation. We now study the division characteristics of human mammary cells purified from female BRCA1 mutation carriers or non-carrier donors. We show primary BRCA1 mutant/+ cells exhibit defective BRCA1 localization, high radiosensitivity and an accelerated entry into cell division, but fail to orient their cell division axis. We also analyse 15 genetically-edited BRCA1 mutant/+ human mammary cell-lines and find that cells carrying pathogenic BRCA1 mutations acquire an analogous defect in their division axis accompanied by deficient expression of features of mature luminal cells. Importantly, these alterations are independent of accumulated DNA damage, and specifically dependent on elevated PLK1 activity induced by reduced BRCA1 function. This essential PLK1-mediated role of BRCA1 in controlling the cell division axis provides insight into the phenotypes expressed during BRCA1 tumorigenesis.

Polygenic and Network-Based Studies in Risk Identification and Demystification of cancer

INTRODUCTION

Diseases were initially thought to be the consequence of a single gene mutation. Advances in DNA sequencing tools and our understanding of gene behavior have revealed that complex diseases, such as cancer, are the product of genes cooperating with each other and with their environment in orchestrated communication networks. Seeing that the function of individual genes is still used to analyze cancer, the shift to using functionally interacting groups of genes as a new unit of study holds promise for demystifying cancer.

AREAS COVERED

The literature search focused on three types of cancer, namely breast, lung, and prostate, but arguments from other cancers were also included. The aim was to prove that multigene analyses can accurately predict and prognosticate cancer risk, subtype cancer for more personalized and effective treatments, and discover anti-cancer therapies. Computational intelligence is being harnessed to analyze this type of data and is proving indispensable to scientific progress.

EXPERT OPINION

In the future, comprehensive profiling of all kinds of patient data (e.g., serum molecules, environmental exposures) can be used to build universal networks that should help us elucidate the molecular mechanisms underlying diseases and provide appropriate preventive measures, ensuring lifelong health and longevity.

Modification of BRCA1-associated breast cancer risk by HMMR overexpression

Breast cancer risk for carriers of BRCA1 pathological variants is modified by genetic factors. Genetic variation in HMMR may contribute to this effect. However, the impact of risk modifiers on cancer biology remains undetermined and the biological basis of increased risk is poorly understood. Here, we depict an interplay of molecular, cellular, and tissue microenvironment alterations that increase BRCA1-associated breast cancer risk. Analysis of genome-wide association results suggests that diverse biological processes, including links to BRCA1-HMMR profiles, influence risk. HMMR overexpression in mouse mammary epithelium increases Brca1-mutant tumorigenesis by modulating the cancer cell phenotype and tumor microenvironment. Elevated HMMR activates AURKA and reduces ARPC2 localization in the mitotic cell cortex, which is correlated with micronucleation and activation of cGAS-STING and non-canonical NF-κB signaling. The initial tumorigenic events are genomic instability, epithelial-to-mesenchymal transition, and tissue infiltration of tumor-associated macrophages. The findings reveal a biological foundation for increased risk of BRCA1-associated breast cancer.

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.

Causal relationship between genetically predicted depression and cancer risk: a two-sample bi-directional mendelian randomization

BACKGROUND

Depression has been reported to be associated with some types of cancer in observational studies. However, the direction and magnitude of the causal relationships between depression and different types of cancer remain unclear.

METHODS

We performed the two-sample bi-directional mendelian randomization with the publicly available GWAS summary statistics to investigate the causal relationship between the genetically predicted depression and the risk of multiple types of cancers, including ovarian cancer, breast cancer, lung cancer, glioma, pancreatic cancer, lymphoma, colorectal cancer, thyroid cancer, bladder cancer, and kidney cancer. The total sample size varies from 504,034 to 729,150. Causal estimate was calculated by inverse variance weighted method. We also performed additional sensitivity tests to evaluate the validity of the causal relationship.

RESULTS

After correction for heterogeneity and horizontal pleiotropy, we only detected suggestive evidence for the causality of genetically predicted depression on breast cancer (OR = 1.09, 95% CI: 1.03-1.15, P = 0.0022). The causal effect of depression on breast cancer was consistent in direction and magnitude in the sensitivity analysis. No evidence of causal effects of depression on other types of cancer and reverse causality was detected.

CONCLUSIONS

The result of this study suggests a causative effect of genetically predicted depression on specific type of cancer. Our findings emphasize the importance of depression in the prevention and treatment of breast cancer.

Assessing the causal role of epigenetic clocks in the development of multiple cancers: a Mendelian randomization study

Background

Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.

Methods

We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671-13,879; N controls = 173,493-372,016), FinnGen (N cases = 719-8401; N controls = 74,685-174,006) and several international cancer genetic consortia (N cases = 11,348-122,977; N controls = 15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.

Results

Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04-1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09-1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97-1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers.

Conclusions

GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.

Funding

FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.

Polygenic risk scores for prediction of breast cancer risk in Asian populations

PURPOSE

Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.

METHODS

The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).

RESULTS

The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.

CONCLUSION

PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.

A Swedish Genome-Wide Haplotype Association Analysis Identifies a Novel Breast Cancer Susceptibility Locus in 8p21.2 and Characterizes Three Loci on Chromosomes 10, 11 and 16

(1) Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility. (2) Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1−25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls. (3) Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08; p 3.92 × 10−8), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2−25 and 113 risk haplotypes of window size 50 at p < 5 × 10−8 on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68. (4) Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.

A Mild Causal Relationship Between Tea Consumption and Obesity in General Population: A Two-Sample Mendelian Randomization Study

Evidence from observational studies for the effect of tea consumption on obesity is inconclusive. This study aimed to verify the causal association between tea consumption and obesity through a two-sample Mendelian randomization (MR) analysis in general population-based datasets. The genetic instruments, single nucleotide polymorphisms (SNPs) associated with tea consumption habits, were obtained from genome-wide association studies (GWAS): UK Biobank, Nurses' Health Study, Health Professionals Follow-up Study, and Women's Genome Health Study. The effect of the genetic instruments on obesity was analyzed using the UK Biobank dataset (among ∼500,000 participants). The causal relationship between tea consumption and obesity was analyzed by five methods of MR analyses: inverse variance weighted (IVW) method, MR-Egger regression method, weighted median estimator (WME), weighted mode, and simple mode. Ninety-one SNPs were identified as genetic instruments in our study. A mild causation was found by IVW (odds ratio [OR] = 0.998, 95% confidence interval [CI] = 0.996 to 1.000, p = 0.049]), which is commonly used in two-sample MR analysis, indicating that tea consumption has a statistically significant but medically weak effect on obesity control. However, the other four approaches did not show significance. Since there was no heterogeneity and pleiotropy in this study, the IVW approach has the priority of recommendation. Further studies are needed to clarify the effects of tea consumption on obesity-related health problems in detail.

Somatic mutational profiles and germline polygenic risk scores in human cancer

BACKGROUND

The mutational profile of cancer reflects the activity of the mutagenic processes which have been operative throughout the lineage of the cancer cell. These processes leave characteristic profiles of somatic mutations called mutational signatures. Mutational signatures, including single-base substitution (SBS) signatures, may reflect the effects of exogenous or endogenous exposures.

METHODS

We used polygenic risk scores (PRS) to summarize common germline variation associated with cancer risk and other cancer-related traits and examined the association between somatic mutational profiles and germline PRS in 12 cancer types from The Cancer Genome Atlas. Somatic mutational profiles were constructed from whole-exome sequencing data of primary tumors. PRS were calculated for the 12 selected cancer types and 9 non-cancer traits, including cancer risk determinants, hormonal factors, and immune-mediated inflammatory diseases, using germline genetic data and published summary statistics from genome-wide association studies.

RESULTS

We found 17 statistically significant associations between somatic mutational profiles and germline PRS after Bonferroni correction (p < 3.15 × 10^-5), including positive associations between germline inflammatory bowel disease PRS and number of somatic mutations attributed to signature SBS1 in prostate cancer and APOBEC-related signatures in breast cancer. Positive associations were also found between age at menarche PRS and mutation counts of SBS1 in overall and estrogen receptor-positive breast cancer. Consistent with prior studies that found an inverse association between the pubertal development PRS and risk of prostate cancer, likely reflecting hormone-related mechanisms, we found an inverse association between age at menarche PRS and mutation counts of SBS1 in prostate cancer. Inverse associations were also found between several cancer PRS and tumor mutation counts.

CONCLUSIONS

Our analysis suggests that there are robust associations between tumor somatic mutational profiles and germline PRS. These may reflect the mechanisms through hormone regulation and immune responses that contribute to cancer etiology and drive cancer progression.

Aberrant epigenetic and transcriptional events associated with breast cancer risk

BACKGROUND

Genome-wide association studies have identified several breast cancer susceptibility loci. However, biomarkers for risk assessment are still missing. Here, we investigated cancer-related molecular changes detected in tissues from women at high risk for breast cancer prior to disease manifestation. Disease-free breast tissue cores donated by healthy women (N = 146, median age = 39 years) were processed for both methylome (MethylCap) and transcriptome (Illumina's HiSeq4000) sequencing. Analysis of tissue microarray and primary breast epithelial cells was used to confirm gene expression dysregulation.

RESULTS

Transcriptomic analysis identified 69 differentially expressed genes between women at high and those at average risk of breast cancer (Tyrer-Cuzick model) at FDR < 0.05 and fold change ≥ 2. Majority of the identified genes were involved in DNA damage checkpoint, cell cycle, and cell adhesion. Two genes, FAM83A and NEK2, were overexpressed in tissue sections (FDR < 0.01) and primary epithelial cells (p < 0.05) from high-risk breasts. Moreover, 1698 DNA methylation changes were identified in high-risk breast tissues (FDR < 0.05), partially overlapped with cancer-related signatures, and correlated with transcriptional changes (p < 0.05, r ≤ 0.5). Finally, among the participants, 35 women donated breast biopsies at two time points, and age-related molecular alterations enhanced in high-risk subjects were identified.

CONCLUSIONS

Normal breast tissue from women at high risk of breast cancer bears molecular aberrations that may contribute to breast cancer susceptibility. This study is the first molecular characterization of the true normal breast tissues, and provides an opportunity to investigate molecular markers of breast cancer risk, which may lead to new preventive approaches.

Knockdown of NAA25 Suppresses Breast Cancer Progression by Regulating Apoptosis and Cell Cycle

NAA25 gene variants were reported as risk factors for type 1 diabetes, rheumatoid arthritis and acute arterial stroke. But it’s unknown whether it could contribute to breast cancer. We identified rs11066150 in lncHSAT164, which contributes to breast cancer, in our earlier genome-wide long non-coding RNA association study on Han Chinese women. However, rs11066150 A/G variant is also located in NAA25 intron. Based on the public database, such as TCGA and Curtis dataset, NAA25 gene is highly expressed in breast cancer tissues and this result has also been proved in our samples and cell lines through RT-qPCR and western blot analysis. To better understand the function of NAA25 in breast cancer, we knocked down the expression of NAA25 in breast cancer cell lines, FACS was used to detect cell apoptosis and cell cycle and colony formation assay was used to detect cell proliferation. We found that NAA25-deficient cells could increase cell apoptosis, delay G2/M phase cell and decrease cell clone formation. RNA sequencing was then applied to analyze the molecular profiles of NAA25−deficient cells, and compared to the control group, NAA25 knockdown could activate apoptosis-related pathways, reduce the activation of tumor-associated signaling pathways and decrease immune response-associated pathways. Additionally, RT-qPCR was employed to validate these results. Taken together, our results revealed that NAA25 was highly expressed in breast cancer, and NAA25 knockdown might serve as a therapeutic target in breast cancer.

Identification of the genetic mechanism that associates L3MBTL3 to multiple sclerosis

Multiple sclerosis (MS) is a complex and demyelinating disease of the central nervous system. One of the challenges of the post-GWAS era is to understand the molecular basis of statistical associations to reveal gene networks and potential therapeutic targets. The L3MBTL3 locus has been associated with MS risk by GWAS. To identify the causal variant of the locus, we performed fine mapping in a cohort of 3440 MS patients and 1688 healthy controls. The variant that best explained the association was rs6569648 (P = 4.13E-10, OR = 0.71, 95% CI = 0.64-0.79), which tagged rs7740107, located in intron 7 of L3MBTL3. The rs7740107 (A/T) variant has been reported to be the best expression and splice quantitative trait locus (eQTL and sQTL) of the region in up to 35 human GTEx tissues. By sequencing RNA from blood of 17 MS patients and quantification by digital qPCR, we determined that this eQTL/sQTL originated from the expression of a novel short transcript starting in intron 7 near rs7740107. The short transcript was translated into three proteins starting at different translation initiation codons. These N-terminal truncated proteins lacked the region where L3MBTL3 interacts with the transcriptional regulator RBPJ (Recombination Signal Binding Protein for Immunoglobulin Kappa J Region) which, in turn, regulates the Notch signaling pathway. Our data and other functional studies suggest that the genetic mechanism underlying the MS association of rs7740107 affects not only the expression of L3MBTL3 isoforms, but might also involve the Notch signaling pathway.

Rare germline copy number variants (CNVs) and breast cancer risk

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

Associations of genetic susceptibility to 16 cancers with risk of breast cancer overall and by intrinsic subtypes

Certain genetic variants are associated with risks of multiple cancers. We investigated breast cancer risk with overall genetic susceptibility to each of 16 other cancers. We constructed polygenic risk scores (PRS) for 16 cancers using risk variants identified by genome-wide association studies. We evaluated the associations of these PRSs with breast cancer risk (overall and by subtypes) using Breast Cancer Association Consortium data, including 106,278 cases and 91,477 controls of European ancestry. Odds ratios (OR) and 95% confidence intervals (CIs) were estimated to measure the association of each PRS with breast cancer risk. Data from the UK Biobank, including 4,337 cases and 209,983 non-cases, were used to replicate the findings. A 5%-8% significantly elevated risk of overall breast cancer was associated with per unit increase of the PRS for glioma and cancers of the corpus uteri, stomach, or colorectum. Analyses by subtype revealed that the PRS for corpus uteri cancer (OR = 1.09; 95% CI, 1.03-1.15) and stomach cancer (OR = 1.07; 95% CI, 1.03-1.12) were associated with estrogen receptor-positive breast cancer, while ovarian cancer PRS was associated with triple-negative breast cancer (OR = 1.25; 95% CI, 1.01-1.55). UK Biobank data supported the positive associations of overall breast cancer risk with PRS for melanoma and cancers of the stomach, colorectum, and ovary. Our study provides strong evidence for shared genetic susceptibility of breast cancer with several other cancers. Results from our study help uncover the genetic basis for breast and other cancers and identify individuals at high risk for multiple cancers.

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

Standard transcriptome-wide association study (TWAS) methods first train gene expression prediction models using reference transcriptomic data and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we developed Transcriptome-Integrated Genetic Association Resource V2 (TIGAR-V2), which directly reads Variant Call Format (VCF) files, enables parallel computation, and reduces up to 90% of computation cost (mainly due to loading genotype data) compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet process regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWASs using either individual-level or summary-level genome-wide association study (GWAS) data, and implement both burden and variance-component statistics for gene-based association tests. We trained gene expression prediction models by DPR for 49 tissues using Genotype-Tissue Expression (GTEx) V8 by TIGAR-V2 and illustrated the usefulness of these Bayesian cis-expression quantitative trait locus (eQTL) weights through TWASs of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes, respectively, for breast and ovarian cancer, most of which are either known or near previously identified GWAS (∼95%) or TWAS (∼40%) risk genes and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWASs can provide biological insight into the transcriptional regulation of complex diseases. The TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and linkage disequilibrium (LD) information from GTEx V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

Breast and Prostate Cancer Risks for Male BRCA1 and BRCA2 Pathogenic Variant Carriers Using Polygenic Risk Scores

BACKGROUND

Recent population-based female breast cancer and prostate cancer polygenic risk scores (PRS) have been developed. We assessed the associations of these PRS with breast and prostate cancer risks for male BRCA1 and BRCA2 pathogenic variant carriers.

METHODS

483 BRCA1 and 1318 BRCA2 European ancestry male carriers were available from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). A 147-single nucleotide polymorphism (SNP) prostate cancer PRS (PRSPC) and a 313-SNP breast cancer PRS were evaluated. There were 3 versions of the breast cancer PRS, optimized to predict overall (PRSBC), estrogen receptor (ER)-negative (PRSER-), or ER-positive (PRSER+) breast cancer risk.

RESULTS

PRSER+ yielded the strongest association with breast cancer risk. The odds ratios (ORs) per PRSER+ standard deviation estimates were 1.40 (95% confidence interval [CI] =1.07 to 1.83) for BRCA1 and 1.33 (95% CI = 1.16 to 1.52) for BRCA2 carriers. PRSPC was associated with prostate cancer risk for BRCA1 (OR = 1.73, 95% CI = 1.28 to 2.33) and BRCA2 (OR = 1.60, 95% CI = 1.34 to 1.91) carriers. The estimated breast cancer odds ratios were larger after adjusting for female relative breast cancer family history. By age 85 years, for BRCA2 carriers, the breast cancer risk varied from 7.7% to 18.4% and prostate cancer risk from 34.1% to 87.6% between the 5th and 95th percentiles of the PRS distributions.

CONCLUSIONS

Population-based prostate and female breast cancer PRS are associated with a wide range of absolute breast and prostate cancer risks for male BRCA1 and BRCA2 carriers. These findings warrant further investigation aimed at providing personalized cancer risks for male carriers and informing clinical management.

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.

Whole-Genome Genotyping Using DNA Microarrays for Population Genetics

The field of population genetics has exploded in the last two decades following the sequencing of the human genome in 2001 (Green et al. Nature 526:29-31, 2015). Tools to measure genetic variation have matured significantly throughout this advancement in knowledge (Lenoir and Giannella. J Biomed Discov Collab 1:11, 2006; Marzancola et al. Methods Mol Biol 1368:161-178, 2016). In this chapter, the focus is on the laboratory methods developed to perform genome-wide genotyping utilizing DNA microarrays, which is one of the most commonly used molecular techniques to assess global genetic variation (Heller MJ, Annu Rev Biomed Eng 4:129-153, 2002). DNA microarrays allow for the interrogation of hundreds of thousands of SNPs (single nucleotide polymorphisms) at once utilizing array-based technology in conjunction with fluorescent molecular labels in a process referred to as genotyping (Marzancola et al. Methods Mol Biol 1368:161-178, 2016). Genotype data can be utilized to associate certain phenotypes in relation with specific genetic variants within a population in a process known as genome-wide association studies or GWAS (Charlesworth and Charlesworth. Heredity (Edinb) 118(1):2-9, 2017; Casillas and Barbadilla. Genetics 205(3):1003-1035, 2017). This experimental technique is a multiple-day process involving the combination of DNA extraction, amplification, fragmentation, binding, and staining (Illumina Infinium HTS Assay Protocol Guide, 2013). Many vendors supply platforms and products to assess global genetic variation using DNA microarrays (Illumina Infinium HTS Assay Protocol Guide, 2013). In this chapter, the focus is on the methods utilized to generate high-quality genotype data with the Illumina^® Infinium Global Screening Array. Although data analysis and quality control are not the focus for this chapter, they are also briefly addressed.

Long Non-Coding RNAs at the Chromosomal Risk Loci Identified by Prostate and Breast Cancer GWAS

Long non-coding RNAs (lncRNAs) are emerging as key players in a variety of cellular processes. Deregulation of the lncRNAs has been implicated in prostate and breast cancers. Recently, germline genetic variations associated with cancer risk have been correlated with lncRNA expression and/or function. In addition, single nucleotide polymorphisms (SNPs) at well-characterized cancer-associated lncRNAs have been analyzed for their association with cancer risk. These SNPs may occur within the lncRNA transcripts or spanning regions that may alter the structure, function, and expression of these lncRNA molecules and contribute to cancer progression and may have potential as therapeutic targets for cancer treatment. Additionally, some of these lncRNA have a tissue-specific expression profile, suggesting them as biomarkers for specific cancers. In this review, we highlight some of the cancer risk-associated SNPs that modulated lncRNAs with a potential role in prostate and breast cancers and speculate on how these lncRNAs may contribute to cancer development.

Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention

Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual's genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.

Exploring Implementation of Personal Breast Cancer Risk Assessments

Personal Breast Cancer (BC) Risk Assessments (PBCRA) have potential to stratify women into clinically-actionable BC risk categories. As this could involve population-wide genomic testing, women's attitudes to PBCRA and views on acceptable implementation platforms must be considered to ensure optimal population participation. We explored these issues with 31 women with different BC risk profiles through semi-structured focus group discussions or interviews. Inductive thematic coding of transcripts was performed. Subsequently, women listed factors that would impact on their decision to participate. Participants' attitudes to PBCRA were positive. Identified themes included that PBCRA acceptance hinges on result actionability. Women value the ability to inform decision-making. Participants reported anxiety, stress, and genetic discrimination as potential barriers. The age at which PBCRA was offered, ease of access, and how results are returned held importance. Most women value the opportunity for PBCRA to inform increased surveillance, while highlighting hesitance to accept reduced surveillance as they find reassurance in regular screening. Women with BRCA pathogenic variants value the potential for PBCRA to identify a lower cancer risk and potentially inform delayed prophylactic surgery. This study highlights complexities in adopting advances in BC early detection, especially for current users who value existing processes as a social good.

B4GALNT2 Gene Promotes Proliferation, and Invasiveness and Migration Abilities of Model Triple Negative Breast Cancer (TNBC) Cells by Interacting With HLA-B Protein

B4GALNT2 gene encodes the enzyme β1,4-N-acetylgalactosaminyltransferase 2 that biosynthesizes the histo-blood group antigen Sda, which is expressed on the surface of erythrocytes and in body secretions. Analysis of The Cancer Genome Atlas (TCGA) database revealed that this gene was highly expressed in breast cancer tissues in comparison with adjacent healthy ones. In-vitro lentivirus-assisted B4GALNT2 gene knockdown experiments in model triple negative breast cancer (TNBC) cell lines (HCC1937 and MDA-MB-231) showed inhibition in cell proliferation, decrease in cell viability, promotion of cell apoptosis and inhibitions in cell migration and invasiveness abilities in comparison with empty lentivirus transfectant controls. Also, in cell cycle tests, the number of cells in the G1 phase increased, in the S phase decreased and did not change in the G2/M phase (indicative of the presence of a block in the G1 phase). In-vivo tumor formation experiments in mice revealed that knockdown of the B4GALNT2 gene in MDA-MB-231 cells inhibited their proliferation. Using co-immunoprecipitation (Co-IP) mass spectroscopy-assisted analysis, it was found that HLA-B protein [a product of the human leukocyte antigen (HLA) class I gene] interacts with B4GALNT2 protein. In-vitro overexpression of HLA-B in B4GALNT2-knocked down MDA-MB-231 cell lines significantly recovered the cell proliferation, viability and migration ability of B4GALNT2 gene. These indicate that HLA-B is one of the interaction proteins in the downstream pathway of the B4GALNT2 gene.

Evaluating Polygenic Risk Scores for Breast Cancer in Women of African Ancestry

BACKGROUND

Polygenic risk scores (PRSs) have been demonstrated to identify women of European, Asian, and Latino ancestry at elevated risk of developing breast cancer (BC). We evaluated the performance of existing PRSs trained in European ancestry populations among women of African ancestry.

METHODS

We assembled genotype data for women of African ancestry, including 9241 case subjects and 10 193 control subjects. We evaluated associations of 179- and 313-variant PRSs with overall and subtype-specific BC risk. PRS discriminatory accuracy was assessed using area under the receiver operating characteristic curve. We also evaluated a recalibrated PRS, replacing the index variant with variants in each region that better captured risk in women of African ancestry and estimated lifetime absolute risk of BC in African Americans by PRS category.

RESULTS

For overall BC, the odds ratio per SD of the 313-variant PRS (PRS313) was 1.27 (95% confidence interval [CI] = 1.23 to 1.31), with an area under the receiver operating characteristic curve of 0.571 (95% CI = 0.562 to 0.579). Compared with women with average risk (40th-60th PRS percentile), women in the top decile of PRS313 had a 1.54-fold increased risk (95% CI = 1.38-fold to 1.72-fold). By age 85 years, the absolute risk of overall BC was 19.6% for African American women in the top 1% of PRS313 and 6.7% for those in the lowest 1%. The recalibrated PRS did not improve BC risk prediction.

CONCLUSION

The PRSs stratify BC risk in women of African ancestry, with attenuated performance compared with that reported in European, Asian, and Latina populations. Future work is needed to improve BC risk stratification for women of African ancestry.

Altered regulation of BRCA1 exon 11 splicing is associated with breast cancer risk in carriers of BRCA1 pathogenic variants

Germline pathogenic variants in BRCA1 confer a high risk of developing breast and ovarian cancer. The BRCA1 exon 11 (formally exon 10) is one of the largest exons and codes for the nuclear localization signals of the corresponding gene product. This exon can be partially or entirely skipped during pre-mRNA splicing, leading to three major in-frame isoforms that are detectable in most cell types and tissue, and in normal and cancer settings. However, it is unclear whether the splicing imbalance of this exon is associated with cancer risk. Here we identify a common genetic variant in intron 10, rs5820483 (NC_000017.11:g.43095106_43095108dup), which is associated with exon 11 isoform expression and alternative splicing, and with the risk of breast cancer, but not ovarian cancer, in BRCA1 pathogenic variant carriers. The identification of this genetic effect was confirmed by analogous observations in mouse cells and tissue in which a loxP sequence was inserted in the syntenic intronic region. The prediction that the rs5820483 minor allele variant would create a binding site for the splicing silencer hnRNP A1 was confirmed by pull-down assays. Our data suggest that perturbation of BRCA1 exon 11 splicing modifies the breast cancer risk conferred by pathogenic variants of this gene.

Gene expression atlas of energy balance brain regions

Energy balance is controlled by interconnected brain regions in the hypothalamus, brainstem, cortex, and limbic system. Gene expression signatures of these regions can help elucidate the pathophysiology underlying obesity. RNA sequencing was conducted on P56 C57BL/6NTac male mice and E14.5 C57BL/6NTac embryo punch biopsies in 16 obesity-relevant brain regions. The expression of 190 known obesity-associated genes (monogenic, rare, and low-frequency coding variants; GWAS; syndromic) was analyzed in each anatomical region. Genes associated with these genetic categories of obesity had localized expression patterns across brain regions. Known monogenic obesity causal genes were highly enriched in the arcuate nucleus of the hypothalamus and developing hypothalamus. The obesity-associated genes clustered into distinct “modules” of similar expression profile, and these were distinct from expression modules formed by similar analysis with genes known to be associated with other disease phenotypes (type 1 and type 2 diabetes, autism, breast cancer) in the same energy balance–relevant brain regions.

Coding variants in the PCNT and CEP295 genes contribute to breast cancer risk in Chinese women

BACKGROUND

Centrioles play pivotal roles in the assembly of centrosomes, their dysfunction is associated with multiple inherited diseases or cancers. To date, few studies have focused on the associations between coding single nucleotide polymorphisms (SNPs) in the centriole duplication cycle genes and the risk of breast cancer in Chinese women.

METHODS

Twenty-one SNPs were selected from the coding regions of 10 critical centriole genes. The associations between the selected SNPs and breast cancer susceptibility were assessed in a case-control study of Chinese women, which included 1032 cases and 1063 controls. Potential biological functions in the influence of protein stability and the profile of expression quantitative trait loci (eQTL) of the identified SNPs were further evaluated using in silico databases.

RESULTS

Multivariate logistic regression analyses revealed that a missense SNP rs7279204 in PCNT was significantly associated with an increased risk of breast cancer (additive model: adjusted OR=1.19, 95% CI: 1.02-1.38), while a missense SNP rs77922978 in CEP295 was significantly associated with a decreased risk of breast cancer (additive model: adjusted OR=0.74, 95% CI: 0.56-0.97). Stratification analyses suggested that rs7279204 and rs77922978 exhibited different effects among later first live birth, ER-negative and PR-negative women (P<0.05). Moreover, rs77922978 showed significant differences for ER and PR status strata (heterogeneity test P=0.028, P=0.046). In addition, bioinformatic analyses indicated that the two variants may possess potential functions of reducing the protein stability of their host genes. Further eQTL analysis showed that the rs7279204 was not only correlated with the expression of its host gene PCNT, but also correlated with the expression of its nearby genes, implying its potential roles in regulation of some cancer susceptibility genes.

CONCLUSIONS

The SNPs rs7279204 and rs77922978 within the coding region of the PCNT and CEP295 genes may contribute to the susceptibility of breast cancer in Han Chinese population.

Joint Genome-Wide Association Analyses Identified 49 Novel Loci For Age at Natural Menopause

BACKGROUND

Age at natural menopause (ANM) is an important index for women's health. Either early or late ANM is associated with a series of adverse outcomes later in life. Despite being an inheritable trait, its genetic determinant has not yet been fully understood.

METHODS

Aiming to better characterize the genetic architecture of ANM, we conducted genome-wide association study (GWAS) meta-analyses in European-specific as well as trans-ancestry samples by using GWAS summary statistics from the following 3 large studies: the Reproductive Genetics Consortium (ReproGen; N = 69 626), the UK Biobank cohort (UKBB; N = 111 593) and the BioBank Japan Project (BBJ; N = 43 861), followed by a series of bioinformatical assessments and functional annotations.

RESULTS

By integrating the summary statistics from the 3 GWAS of up to 225 200 participants, this largest meta-analysis identified 49 novel loci and 3 secondary signals that were associated with ANM at the genome-wide significance level (P < 5 × 10-8). No population specificity or heterogeneity was observed at most of the associated loci. Functional annotations prioritized 90 candidate genes at the newly identified loci. Among the 26 traits that were genetically correlated with ANM, hormone replacement therapy (HRT) exerted a causal relationship, implying a causal pattern by which HRT was determined by ANM.

CONCLUSION

Our findings improved our understanding of the etiology of female menopause, as well as shed light on potential new therapies for abnormal menopause.

Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

BACKGROUND

Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.

METHODS

We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15).

RESULTS

Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy.

CONCLUSIONS

We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.