A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1)

A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.

Gender-Specific Genetic Predisposition to Breast Cancer: BRCA Genes and Beyond

Among neoplastic diseases, breast cancer (BC) is one of the most influenced by gender. Despite common misconceptions associating BC as a women-only disease, BC can also occur in men. Additionally, transgender individuals may also experience BC. Genetic risk factors play a relevant role in BC predisposition, with important implications in precision prevention and treatment. The genetic architecture of BC susceptibility is similar in women and men, with high-, moderate-, and low-penetrance risk variants; however, some sex-specific features have emerged. Inherited high-penetrance pathogenic variants (PVs) in BRCA1 and BRCA2 genes are the strongest BC genetic risk factor. BRCA1 and BRCA2 PVs are more commonly associated with increased risk of female and male BC, respectively. Notably, BRCA-associated BCs are characterized by sex-specific pathologic features. Recently, next-generation sequencing technologies have helped to provide more insights on the role of moderate-penetrance BC risk variants, particularly in PALB2, CHEK2, and ATM genes, while international collaborative genome-wide association studies have contributed evidence on common low-penetrance BC risk variants, on their combined effect in polygenic models, and on their role as risk modulators in BRCA1/2 PV carriers. Overall, all these studies suggested that the genetic basis of male BC, although similar, may differ from female BC. Evaluating the genetic component of male BC as a distinct entity from female BC is the first step to improve both personalized risk assessment and therapeutic choices of patients of both sexes in order to reach gender equality in BC care. In this review, we summarize the latest research in the field of BC genetic predisposition with a particular focus on similarities and differences in male and female BC, and we also discuss the implications, challenges, and open issues that surround the establishment of a gender-oriented clinical management for BC.

Nanomaterials for detection of biomolecules and delivering therapeutic agents in theragnosis: A review

Nanomaterials are emerging facts used to deliver therapeutic agents in living systems. Nanotechnology is used as a compliment by implementing different kinds of nanotechnological applications such as nano-porous structures, functionalized nanomaterials, quantum dots, carbon nanomaterials, and polymeric nanostructures. The applications are in the initial stage, which led to achieving several diagnoses and therapy in clinical practice. This review conveys the importance of nanomaterials in post-genomic employment, which includes the design of immunosensors, immune assays, and drug delivery. In this view, genomics is a molecular tool containing large databases that are useful in choosing an apt molecular inhibitor such as drug, ligand and antibody target in the drug delivery process. This study identifies the expression of genes and proteins in analysis and classification of diseases. Experimentally, the study analyses the design of a disease model. In particular, drug delivery is a boon area to treat cancer. The identified drugs enter different phase trails (Trails I, II, and III). The genomic information conveys more essential entities to the phase I trials and helps to move further for other trails such as trails-II and III. In such cases, the biomarkers play a crucial role by monitoring the unique pathological process. Genetic engineering with recombinant DNA techniques can be employed to develop genetically engineered disease models. Delivering drugs in a specific area is one of the challenging issues achieved using nanoparticles. Therefore, genomics is considered as a vast molecular tool to identify drugs in personalized medicine for cancer therapy.

Single nucleotide polymorphisms associated with female breast cancer susceptibility in Chinese population

Breast cancer is a complex disease influenced by both external and internal factors, among which genetic factors play a critical role. Single-nucleotide polymorphisms (SNPs) are major contributors to the heritability of breast cancer, and their frequencies vary across ethnic groups. In this study, we aimed to investigate the association between 34 SNPs identified in previous genome-wide association studies (GWAS) and overall breast cancer risk, as well as breast cancer subtypes, in the Chinese female population. To accomplish this, we conducted an extensive association analysis using the high-throughput Sequenom MassARRAY® platform in a case-control study comprising 1848 breast cancer patients and 709 healthy controls. Our analysis, which utilized the SNPassoc package in R based on chi-squared (χ2) test and genetic model analysis, identified significant associations between breast cancer risk and SNP rs12493607 (TGFBR2, risk allele C, OR = 1.28 [1.11-1.47], P = 0.0005), as well as a less conservatively significant association with rs4784227 (CASC16, risk allele T, OR = 1.24 [1.08-1.42], P = 0.0017) and rs2046210 (ESR1, risk allele A, OR = 1.50 [1.16-1.95], P = 0.0016). Furthermore, our stratified analyses revealed that rs12493607 was significantly associated with invasive carcinoma, estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, HER2-negative, and young (aged younger than 45) breast cancer. SNP rs4784227 and rs3803662 (CASC16) were associated with invasive carcinoma and ER-positive breast cancer, while rs2046210 was linked to ductal carcinoma in situ, ER-negative, PR-negative, HER2-positive, and elder (aged more than 45) breast cancers. SNPs rs10484919 (ESR1) and rs1038304 (CCDC170) showed links to HER2-positive breast cancer, and rs616488 (PEX14) with premenopausal breast cancer. In summary, our study shed light on the relationship between SNPs and breast cancer susceptibility within a vast Chinese cohort, supporting the development of polygenetic risk scores for the Chinese population. These findings provide valuable insights into the genetic basis of breast cancer and have important implications for risk prediction, early detection, and personalized treatment of this disease.

A truncating variant of RAD51B associated with primary ovarian insufficiency provides insights into its meiotic and somatic functions

Primary ovarian insufficiency (POI) causes female infertility by abolishing normal ovarian function. Although its genetic etiology has been extensively investigated, most POI cases remain unexplained. Using whole-exome sequencing, we identified a homozygous variant in RAD51B -(c.92delT) in two sisters with POI. In vitro studies revealed that this variant leads to translation reinitiation at methionine 64. Here, we show that this is a pathogenic hypomorphic variant in a mouse model. Rad51bc.92delT/c.92delT mice exhibited meiotic DNA repair defects due to RAD51 and HSF2BP/BMRE1 accumulation in the chromosome axes leading to a reduction in the number of crossovers. Interestingly, the interaction of RAD51B-c.92delT with RAD51C and with its newly identified interactors RAD51 and HELQ was abrogated or diminished. Repair of mitomycin-C-induced chromosomal aberrations was impaired in RAD51B/Rad51b-c.92delT human and mouse somatic cells in vitro and in explanted mouse bone marrow cells. Accordingly, Rad51b-c.92delT variant reduced replication fork progression of patient-derived lymphoblastoid cell lines and pluripotent reprogramming efficiency of primary mouse embryonic fibroblasts. Finally, Rad51bc.92delT/c.92delT mice displayed increased incidence of pituitary gland hyperplasia. These results provide new mechanistic insights into the role of RAD51B not only in meiosis but in the maintenance of somatic genome stability.

Comprehensive Analysis of the Expression and Prognosis for RAD51 Family in Human Breast Cancer

Purpose

The RAD51 family of genes, including RAD51 and the five RAD51-like paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3), are known to be crucially associated with DNA damage repair pathway. Increasing evidence indicated that RAD51 family members were implicated in breast cancer tumorigenesis. However, their biological roles and prognostic values in breast cancer have yet to be clarified.

Methods

In this study, by using the Oncomine and GEPIA databases, we explored the transcriptional levels of RAD51 family members in breast cancer. Besides, the associations between RAD51 family expression and clinical features were evaluated by using the UALCAN database and Kaplan-Meier (KM) Plotter. We also analyzed the mutations of the RAD51 family and differentially altered genes from the cBioPortal database.

Results

We found that RAD51 mRNA was significantly elevated in breast cancer samples than in normal tissues, while XRCC2 mRNA was downregulated. Besides, a remarkable correlation was detected between the expression of RAD51/RAD51B/XRCC2 genes and the breast cancer stage. Survival analysis utilizing the KM Plotter indicated that high RAD51 and XRCC3 mRNA was associated with a poor prognosis. Conversely, RFS data suggested that high levels of RAD51B/RAD51C/RAD51D/XRCC2 were associated with a favorable prognosis. Moreover, a high genetic variation rate of RAD51C (7%) was detected in breast cancer patients.

Conclusion

Conclusively, we implied that RAD51 and XRCC3 might be potential targets for precision therapy in breast cancer and the RAD51B/RAD51C/RAD51D/XRCC2 genes have significant values for breast cancer prognosis.

2q35-rs13387042 variant and the risk of breast cancer: a case-control study

BACKGROUND

Breast Cancer is the most frequent neoplasm diagnosed among women worldwide. Genetic background and lifestyle/environment play a significant role in the disease etiology. According to Genome-wide association studies, some single-nucleotide polymorphisms such as 2q35-rs13387042-(G/A) have been introduced to be associated with breast cancer risk and features. In this study, we aimed to evaluate the association between this variant and the risk of breast cancer in a cohort of Iranian women.

METHODS

Demographics and clinical information were collected by interview and using patients' medical records, respectively. DNA was extracted from 506 blood samples, including 184 patients and 322 controls, and genotyping was performed using allele specific-PCR. SPSS v16 was used for statistical analysis.

RESULT

Statistically significant association was observed between AA genotype and disease risk in all patients [p_adj = 0.048; OR_adj = 2.13, 95% CI (1.01-4.50)] and also ER-positive breast cancers [p_adj = 0.015; OR_adj = 2.12, 95% CI (1.16-3.88)]. There was no association between rs13387042 and histopathological characteristics of the disease. Furthermore, overall survival was not statistically associated with genotype and allelic models even after adjustment for stage and receptor status (p > 0.05).

CONCLUSION

There is a statistically significant association between 2q35-rs13387042 and breast cancer risk. rs13387042-AA genotype might be a risk-conferring factor for breast cancer development in the Iranian population. However, further consideration is suggested to confirm its role in risk assessment and probable association with other genetic markers.

The African Female Breast Cancer Epidemiology Study Protocol

Breast cancer is now the commonest cancer in most sub-Saharan African countries. Few studies of the epidemiology and genomics of breast cancer and its molecular subtypes in these countries have been done. The African Female Breast Cancer Epidemiology (AFBRECANE) study, a part of the Human Heredity and Health in Africa (H3Africa) initiative, is designed to study the genomics and epidemiology of breast cancer and its molecular subtypes in Nigerian women. We link recruitment of breast cancer cases at study sites with population-based cancer registries activities to enable ascertainment of the incidence of breast cancer and its molecular subtypes. We use centralized laboratory processing to characterize the histopathological and molecular diagnosis of breast cancer and its subtypes using multiple technologies. By combining genome-wide association study (GWAS) data from this study with that generated from 12,000 women participating in our prospective cohort study of cervical cancer, we conduct GWAS of breast cancer in an entirely indigenous African population. We test associations between dietary intakes and breast cancer and focus on vitamin D which we measure using dietary intakes, serum vitamin D, and Mendelian randomization. This paper describes the AFBRECANE project, its design, objectives and anticipated contributions to knowledge and understanding of breast cancer.

Four differentially expressed genes can predict prognosis and microenvironment immune infiltration in lung cancer: a study based on data from the GEO

Background

Lung cancer is among the major diseases threatening human health. Although the immune response plays an important role in tumor development, its exact mechanisms are unclear.

Materials and methods

Here, we used CIBERSORT and ESTIMATE algorithms to determine the proportion of tumor-infiltrating immune cells (TICs) as well as the number of immune and mesenchymal components from the data of 474 lung cancer patients from the Gene Expression Omnibus database. And we used data from The Cancer Genome Atlas database (TCGA) for validation.

Results

We observed that immune, stromal, and assessment scores were only somewhat related to survival with no statistically significant differences. Further investigations revealed these scores to be associated with different pathology types. GO and KEGG analyses of differentially expressed genes revealed that they were strongly associated with immunity in lung cancer. In order to determine whether the signaling pathways identified by GO and KEGG signaling pathway enrichment analyses were up- or down-regulated, we performed a gene set enrichment analysis using the entire matrix of differentially expressed genes. We found that signaling pathways involved in hallmark allograft rejection, hallmark apical junction, hallmark interferon gamma response, the hallmark P53 pathway, and the hallmark TNF-α signaling via NF-ĸB were up-regulated in the high-ESTIMATE-score group. CIBERSORT analysis for the proportion of TICs revealed that different immune cells were positively correlated with the ESTIMATE score. Cox regression analysis of the differentially expressed genes revealed that CPA3, C15orf48, FCGR1B, and GNG4 were associated with patient prognosis. A prognostic model was constructed wherein patients with high-risk scores had a worse prognosis (p < 0.001 using the log-rank test). The Area Under Curve (AUC)value for the risk model in predicting the survival was 0.666. The validation set C index was 0.631 (95% CI: 0.580–0.652). The AUC for the risk formula in the validation set was 0.560 that confirmed predictivity of the signature.

Conclusion

We found that immune-related gene expression models could predict patient prognosis. Moreover, high- and low-ESTIMATE-score groups had different types of immune cell infiltration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09296-8.

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.

Combination of a 15-SNP Polygenic Risk Score and Classical Risk Factors for the Prediction of Breast Cancer Risk in Cypriot Women

Simple Summary

Breast cancer is the most commonly diagnosed type of cancer in women worldwide. Stratification of women based on their individual breast cancer risk could guide targeted preventative strategies and population screening. Integrated models that combine the effects of a polygenic risk score (PRS) with classical breast cancer risk factors could provide an individualized breast-cancer risk estimation. Although various studies have extensively evaluated the performance of such integrated models in populations of European ancestry, no previous studies have included individuals of Greek-Cypriot origin. To this end, we have assessed the predictive performance of a 15-SNP PRS (PRS₁₅), in combination with classical breast-cancer risk factors, in women of Greek-Cypriot origin. This proof-of-concept study suggests that models combining genetic data with classical risk factors may be used in the future for the prediction of breast-cancer risk and, therefore, supports their potential clinical utility for targeted preventative strategies in Cypriot women.

Abstract

The PRS combines multiplicatively the effects of common low-risk single nucleotide polymorphisms (SNPs) and has the potential to be used for the estimation of an individual’s risk for a trait or disease. PRS has been successfully implemented for the prediction of breast cancer risk. The combination of PRS with classical breast cancer risk factors provides a more comprehensive risk estimation and could, thus, improve risk stratification and personalized preventative strategies. In this study, we assessed the predictive performance of the combined effect of PRS₁₅ with classical breast-cancer risk factors in Cypriot women using 1109 cases and 1177 controls from the MASTOS study. The PRS₁₅ was significantly associated with an increased breast cancer risk in Cypriot women OR (95% CI) 1.66 (1.25–2.19). The integrated risk model obtained an AUC (95% CI) 0.70 (0.67–0.72) and had the ability to stratify women according to their disease status at the extreme deciles. These results provide evidence that the combination of PRS with classical risk factors may be used in the future for the stratification of Cypriot women based on their disease risk, and support its potential clinical utility for targeted preventative actions and population screening.

Potential biomarkers and lncRNA-mRNA regulatory networks in invasive growth hormone-secreting pituitary adenomas

PURPOSE

Growth hormone-secreting pituitary adenomas (GH-PAs) are common subtypes of functional PAs. Invasive GH-PAs play a key role in restricting poor outcomes. The transcriptional changes in GH-PAs were evaluated.

METHODS

In this study, the transcriptome analysis of six different GH-PA samples was performed. The functional roles, co-regulatory network, and chromosome location of differentially expressed (DE) genes in invasive GH-PAs were explored.

RESULTS

Bioinformatic analysis revealed 101 DE mRNAs and 70 DE long non-coding RNAs (lncRNAs) between invasive and non-invasive GH-PAs. Functional enrichment analysis showed that epithelial cell differentiation and development pathways were suppressed in invasive GH-PAs, whereas the pathways of olfactory transduction, retinol metabolism, drug metabolism-cytochrome P450, and metabolism of xenobiotics by cytochrome P450 had an active trend. In the protein-protein interaction network, 11 main communities were characterized by cell- adhesion, -motility, and -cycle; transport process; phosphorus and hormone metabolic processes. The SGK1 gene was suggested to play a role in the invasiveness of GH-PAs. Furthermore, the up-regulated genes OR51B6, OR52E4, OR52E8, OR52E6, OR52N2, MAGEA6, MAGEC1, ST8SIA6-AS1, and the down-regulated genes GAD1-AS1 and SPINT1-AS1 were identified in the competing endogenous RNA network. The RT-qPCR results further supported the aberrant expression of those genes. Finally, the enrichment of DE genes in chromosome 11p15 and 12p13 regions were detected.

CONCLUSION

Our findings provide a new perspective for studies evaluating the underlying mechanism of invasive GH-PAs.

A Personal Breast Cancer Risk Stratification Model Using Common Variants and Environmental Risk Factors in Japanese Females

Simple Summary

Breast cancer remains the most common cancer in females, warranting the development of new approaches to prevention. One such approach is personalized prevention using genetic risk models. Here, we developed a risk model using both genetic and environmental risk factors. Results showed that a genetic risk score defined by the number of risk alleles for 14 breast cancer risk SNPs clearly stratified breast cancer risk. Moreover, the combination of this genetic risk score model with an environmental risk model which included established environmental risk factors showed significantly better C-statistics than the environmental risk model alone. This genetic risk score model in combination with the environmental model may be suitable for stratifying individual breast cancer risk, and may form the basis for a new personalized approach to breast cancer prevention.

Abstract

Personalized approaches to prevention based on genetic risk models have been anticipated, and many models for the prediction of individual breast cancer risk have been developed. However, few studies have evaluated personalized risk using both genetic and environmental factors. We developed a risk model using genetic and environmental risk factors using 1319 breast cancer cases and 2094 controls from three case–control studies in Japan. Risk groups were defined based on the number of risk alleles for 14 breast cancer susceptibility loci, namely low (0–10 alleles), moderate (11–16) and high (17+). Environmental risk factors were collected using a self-administered questionnaire and implemented with harmonization. Odds ratio (OR) and C-statistics, calculated using a logistic regression model, were used to evaluate breast cancer susceptibility and model performance. Respective breast cancer ORs in the moderate- and high-risk groups were 1.69 (95% confidence interval, 1.39–2.04) and 3.27 (2.46–4.34) compared with the low-risk group. The C-statistic for the environmental model of 0.616 (0.596–0.636) was significantly improved by combination with the genetic model, to 0.659 (0.640–0.678). This combined genetic and environmental risk model may be suitable for the stratification of individuals by breast cancer risk. New approaches to breast cancer prevention using the model are warranted.

Exploration of therapeutic applicability and different signaling mechanism of various phytopharmacological agents for treatment of breast cancer

BACKGROUND

Cancer is one of the most dreaded diseases characterized by uncontrolled proliferation of abnormal cells that occurs due to impairment of cell division and apoptosis process. Cancer is categorized into several types on the basis of affected organs and breast cancer (BC) is the most predominant cause of mortality among women. Although, several synthetic and semi-synthetic therapies have been developed for the treatment of BC but they exhibit numerous serious adverse effects therefore; pharmacological agents with fewer/no side effects need to be explored. Plants and phytoconstituents perhaps fulfill the aforementioned requirement and could serve as a potential and alternative therapy for BC treatment. The ongoing biomedical research, clinical trials and number of patents granted have further boosted the acceptance of the plants and plant-derived constituents in the effective treatment of BC.

PURPOSE OF STUDY

Various treatment strategies such as checkpoint inhibitors, targeting micro RNA, apoptotic pathway, BRCA-1 gene, P53 protein, P13K/Akt/mTOR pathway, notch signaling pathway, hedgehog/gli-1 signaling pathway, poly-ADP ribose polymerase inhibitors, mitogen-activated protein kinase inhibitors etc. are available for BC. In addition to these synthetic and semi-synthetic drug therapies, several natural constituents such as alkaloids, sesquiterpenes, polyphenols, flavonoids and diterpenoids from medicinal plants, vegetables and fruits are reported to possess promising anti-cancer activity. The purpose of the present review is to highlight the various signaling pathways through which plants/herbs show the anti-cancer potential especially against the BC.

STUDY DESIGN

The literature for the present study was collected from various databases such as Pubmed, Scopus, Chemical Abstracts, Medicinal and aromatic plant abstracts, Web of Science etc. The different patent databases were also reviewed for the anti-cancer (BC) potential of the particular herbs/plants and their formulations.

RESULT AND CONCLUSION

In this review, we have discussed the number of plants along with their patents of different herbal formulations which are being used for the treatment of BC and other types of cancers. We have also delineated the different signaling mechanisms through which they inhibit the growth of BC cells. In nutshell, we can conclude that large numbers of herbs or their extracts are reported for the treatment of BC. But still, there is further need for research in-depth to translate the use of natural products clinically BC treatment.

TBX15 rs98422, DNM3 rs1011731, RAD51B rs8017304, and rs2588809 Gene Polymorphisms and Associations With Pituitary Adenoma

BACKGROUND

Pituitary adenoma (PA) is a benign tumor of parenchymal cells in the adenohypophysis, and it's development is strongly associated with genetic factors.This study aim was to find whether TBX15 rs98422, DNM3 rs1011731, RAD51B rs8017304, and rs2588809 single nucleotide polymorphisms can be associated with pituitary adenoma. While the TBX15 gene belongs to the T-box family of genes and is a transcription factor involved in many developmental processes, the DNM3 encodes a protein that is a member of the dynamin family with mechanochemical properties involved in actin-membrane processes, predominantly in membrane budding, and the RAD51B gene plays a significant role in homologous recombination in DNA repair for genome stability.

MATERIALS AND METHODS

The study enrolled 113 patients with pituitary adenoma and 283 healthy control subjects. DNA samples were extracted and purified from peripheral blood leukocytes. Genotyping was carried out using real-time polymerase chain reaction. The results were assessed using binomial logistic regression.

RESULTS

Our study revealed that RAD51B rs2588809 TT genotype could be associated with PA development in the co-dominant (OR=6.833; 95% CI=2.557-18.262; p<0.001) and recessive (OR=7.066; 95% CI=2.667-18.722; p<0.001) models. The same results were observed in females but not in males and PA without recurrence, while in PA with recurrence, no statistically significant results were obtained.

CONCLUSION

RAD51B rs2588809 TT genotype may increase the odds of PA development in women; it may also be associated with non-recurrent PA development.

NOTCH Single Nucleotide Polymorphisms in the Predisposition of Breast and Colorectal Cancers in Saudi Patients

Breast cancer (BC) is a heterogeneous disease and is one of the most common malignancy affecting women worldwide while colorectal cancer (CRC) is estimated to be the third common cancer and second leading cause of cancer related death globally. Both BC and CRC involve multiple genetic and epigenetic alterations in genes belonging to various signaling pathways including NOTCH that has been implicated in the development of these cancers. We investigated four single nucleotide polymorphisms, each in genes encoding NOTCH1-4 receptors for their role in susceptibility to breast and colorectal cancers in Saudi population. In this case-control study, TaqMan genotypic analysis of rs3124591 in NOTCH1 and rs3820041 in NOTCH4 did not exhibit association with breast as well as colorectal cancers. However, a strong association of rs11249433 which is in close proximity to NOTCH2 was observed with breast cancer susceptibility especially with those having an early onset of the disease. Interestingly, the rs1043994 located in NOTCH3 showed gender preference and was found to be significantly associated with colorectal cancers in males. Validation of these findings in bigger populations of different ethnicities may prove beneficial in identifying rs11249433 and rs1043994 as genetic screening markers for early detection of breast and colorectal carcinomas, respectively.

Common Susceptibility Loci for Male Breast Cancer

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Background

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

Summary

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

Key-Messages

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

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

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

Integrative genomic analysis implicates ERCC6 and its interaction with ERCC8 in susceptibility to breast cancer

Up to 30% of all breast cancer cases may be inherited and up to 85% of those may be due to segregation of susceptibility genes with low and moderate risk [odds ratios (OR) ≤ 3] for (mostly peri- and post-menopausal) breast cancer. The majority of low/moderate-risk genes, particularly those with minor allele frequencies (MAF) of < 30%, have not been identified and/or validated due to limitations of conventional association testing approaches, which include the agnostic nature of Genome Wide Association Studies (GWAS). To overcome these limitations, we used a hypothesis-driven integrative genomics approach to test the association of breast cancer with candidate genes by analyzing multi-omics data. Our candidate-gene association analyses of GWAS datasets suggested an increased risk of breast cancer with ERCC6 (main effect: 1.29 ≤ OR ≤ 2.91, 0.005 ≤ p ≤ 0.04, 11.8 ≤ MAF ≤ 40.9%), and implicated its interaction with ERCC8 (joint effect: 3.03 ≤ OR ≤ 5.31, 0.01 ≤ pinteraction ≤ 0.03). We found significant upregulation of ERCC6 (p = 7.95 × 10-6) and ERCC8 (p = 4.67 × 10-6) in breast cancer and similar frequencies of ERCC6 (1.8%) and ERCC8 (0.3%) mutations in breast tumors to known breast cancer susceptibility genes such as BLM (1.9%) and LSP1 (0.3%). Our integrative genomics approach suggests that ERCC6 may be a previously unreported low- to moderate-risk breast cancer susceptibility gene, which may also interact with ERCC8.

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.

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.

DOT: Gene-set analysis by combining decorrelated association statistics

Historically, the majority of statistical association methods have been designed assuming availability of SNP-level information. However, modern genetic and sequencing data present new challenges to access and sharing of genotype-phenotype datasets, including cost of management, difficulties in consolidation of records across research groups, etc. These issues make methods based on SNP-level summary statistics particularly appealing. The most common form of combining statistics is a sum of SNP-level squared scores, possibly weighted, as in burden tests for rare variants. The overall significance of the resulting statistic is evaluated using its distribution under the null hypothesis. Here, we demonstrate that this basic approach can be substantially improved by decorrelating scores prior to their addition, resulting in remarkable power gains in situations that are most commonly encountered in practice; namely, under heterogeneity of effect sizes and diversity between pairwise LD. In these situations, the power of the traditional test, based on the added squared scores, quickly reaches a ceiling, as the number of variants increases. Thus, the traditional approach does not benefit from information potentially contained in any additional SNPs, while our decorrelation by orthogonal transformation (DOT) method yields steady gain in power. We present theoretical and computational analyses of both approaches, and reveal causes behind sometimes dramatic difference in their respective powers. We showcase DOT by analyzing breast cancer and cleft lip data, in which our method strengthened levels of previously reported associations and implied the possibility of multiple new alleles that jointly confer disease risk.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

DNA repair and cancer in colon and rectum: Novel players in genetic susceptibility

Interindividual differences in DNA repair systems may play a role in modulating the individual risk of developing colorectal cancer. To better ascertain the role of DNA repair gene polymorphisms on colon and rectal cancer risk individually, we evaluated 15,419 single nucleotide polymorphisms (SNPs) within 185 DNA repair genes using GWAS data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), which included 8,178 colon cancer, 2,936 rectum cancer cases and 14,659 controls. Rs1800734 (in MLH1 gene) was associated with colon cancer risk (p-value = 3.5 × 10-6 ) and rs2189517 (in RAD51B) with rectal cancer risk (p-value = 5.7 × 10-6 ). The results had statistical significance close to the Bonferroni corrected p-value of 5.8 × 10-6 . Ninety-four SNPs were significantly associated with colorectal cancer risk after Binomial Sequential Goodness of Fit (BSGoF) procedure and confirmed the relevance of DNA mismatch repair (MMR) and homologous recombination pathways for colon and rectum cancer, respectively. Defects in MMR genes are known to be crucial for familial form of colorectal cancer but our findings suggest that specific genetic variations in MLH1 are important also in the individual predisposition to sporadic colon cancer. Other SNPs associated with the risk of colon cancer (e.g., rs16906252 in MGMT) were found to affect mRNA expression levels in colon transverse and therefore working as possible cis-eQTL suggesting possible mechanisms of carcinogenesis.

Applications of Next Generation Sequencing to the Analysis of Familial Breast/Ovarian Cancer

Next generation sequencing (NGS) provides a powerful tool in the field of medical genetics, allowing one to perform multi-gene analysis and to sequence entire exomes (WES), transcriptomes or genomes (WGS). The generated high-throughput data are particularly suitable for enhancing the understanding of the genetic bases of complex, multi-gene diseases, such as cancer. Among the various types of tumors, those with a familial predisposition are of great interest for the isolation of novel genes or gene variants, detectable at the germline level and involved in cancer pathogenesis. The identification of novel genetic factors would have great translational value, helping clinicians in defining risk and prevention strategies. In this regard, it is known that the majority of breast/ovarian cases with familial predisposition, lacking variants in the highly penetrant BRCA1 and BRCA2 genes (non-BRCA), remains unexplained, although several less penetrant genes (e.g., ATM, PALB2) have been identified. In this scenario, NGS technologies offer a powerful tool for the discovery of novel factors involved in familial breast/ovarian cancer. In this review, we summarize and discuss the state of the art applications of NGS gene panels, WES and WGS in the context of familial breast/ovarian cancer.

Identification of two novel breast cancer loci through large-scale genome-wide association study in the Japanese population

Genome-wide association studies (GWAS) have successfully identified about 70 genomic loci associated with breast cancer. Owing to the complexity of linkage disequilibrium and environmental exposures in different populations, it is essential to perform regional GWAS for better risk prediction. This study aimed to investigate the genetic architecture and to assess common genetic risk model of breast cancer with 6,669 breast cancer patients and 21,930 female controls in the Japanese population. This GWAS identified 11 genomic loci that surpass genome-wide significance threshold of P < 5.0 × 10⁻⁸ with nine previously reported loci and two novel loci that include rs9862599 on 3q13.11 (ALCAM) and rs75286142 on 21q22.12 (CLIC6-RUNX1). Validation study was carried out with 981 breast cancer cases and 1,394 controls from the Aichi Cancer Center. Pathway analyses of GWAS signals identified association of dopamine receptor medicated signaling and protein amino acid deacetylation with breast cancer. Weighted genetic risk score showed that individuals who were categorized in the highest risk group are approximately 3.7 times more likely to develop breast cancer compared to individuals in the lowest risk group. This well-powered GWAS is a representative study to identify SNPs that are associated with breast cancer in the Japanese population.

Exon1 and -116 C/G Promoter Polymorphism on the X-Box DNA Binding Protein- 1 Gene is not Associated with Breast Cancer among Jordanian Women

Background: Human X -box binding protein 1 (XBP1), a critical gene in the endoplasmic reticulum stress response, is located on chromosome 22q12, which has been linked with the pathogenesis of many diseases, particularly cancers such as breast cancer (BC). Single nucleotide polymorphisms (SNPs) in the XBP1 gene can alter structure and function of the gene. In this study, polymorphism in the promoter region and exon1 of the gene XBP1 and its association with BC in Jordanian women was investigated. Methods: Polymorphism in the promoter and exon1 of XBP1 was analyzed in 100 subjects (controls: n=40; BC patients=60). −116 C/G SNP was genotyped by Polymerase Chain Reaction (PCR)-sequence specific primer technique. The odd ratios (ORs) at 95% confidence intervals (CIs) were computed to assess the strength of this association. Results: The three genotypes of the SNP (GG, GC, CC) and their allelic frequencies have nonsignificant differences between patients and control group. It was noticed that the frequencies of the mutant allele (G) were (75.8% versus 24.2%)) in the patients and control groups, respectively, while those of the normal allele (C) were (67.5% versus 32.5%). XBP1 (-116 G→C) G allele did not show significant association with BC risk (confidence interval = 0.3534- 1.2395, odds ratio = 0.6619, P= 0.197). Moreover, there were no significant mutations in the XBP1 exon1 neither in BC subjects nor control subjects. Conclusions: This is the first study to evaluate the effect of polymorphism in the promoter and exon1 of XBP1 gene in the pathogenesis of BC in Jordanian women. The results do not support a role for polymorphism in development of BC and further studies with a larger sample size and detailed data should be performed in other populations.

Application of simulation-based CYP26 SNP-environment barcodes for evaluating the occurrence of oral malignant disorders by odds ratio-based binary particle swarm optimization: A case-control study in the Taiwanese population

Introduction

Genetic polymorphisms and social factors (alcohol consumption, betel quid (BQ) usage, and cigarette consumption), both separately or jointly, play a crucial role in the occurrence of oral malignant disorders such as oral and pharyngeal cancers and oral potentially malignant disorders (OPMD).

Material and methods

Simultaneous analyses of multiple single nucleotide polymorphisms (SNPs) and environmental effects on oral malignant disorders are essential to examine, albeit challenging. Thus, we conducted a case-control study (N = 576) to analyze the risk of occurrence of oral malignant disorders by using binary particle swarm optimization (BPSO) with an odds ratio (OR)-based method.

Results

We demonstrated that a combination of SNPs (CYP26B1 rs887844 and CYP26C1 rs12256889) and socio-demographic factors (age, ethnicity, and BQ chewing), referred to as the combined effects of SNP-environment, correlated with maximal risk diversity of occurrence observed between the oral malignant disorder group and the control group. The risks were more prominent in the oral and pharyngeal cancers group (OR = 10.30; 95% confidence interval (CI) = 4.58–23.15) than in the OPMD group (OR = 5.42; 95% CI = 1.94–15.12).

Conclusions

Simulation-based “SNP-environment barcodes” may be used to predict the risk of occurrence of oral malignant disorders. Applying simulation-based “SNP-environment barcodes” may provide insight into the importance of screening tests in preventing oral and pharyngeal cancers and OPMD.

Consistent Biomarkers and Related Pathogenesis Underlying Asthma Revealed by Systems Biology Approach

Asthma is a common chronic airway disease worldwide. Due to its clinical and genetic heterogeneity, the cellular and molecular processes in asthma are highly complex and relatively unknown. To discover novel biomarkers and the molecular mechanisms underlying asthma, several studies have been conducted by focusing on gene expression patterns in epithelium through microarray analysis. However, few robust specific biomarkers were identified and some inconsistent results were observed. Therefore, it is imperative to conduct a robust analysis to solve these problems. Herein, an integrated gene expression analysis of ten independent, publicly available microarray data of bronchial epithelial cells from 348 asthmatic patients and 208 healthy controls was performed. As a result, 78 up- and 75 down-regulated genes were identified in bronchial epithelium of asthmatics. Comprehensive functional enrichment and pathway analysis revealed that response to chemical stimulus, extracellular region, pathways in cancer, and arachidonic acid metabolism were the four most significantly enriched terms. In the protein-protein interaction network, three main communities associated with cytoskeleton, response to lipid, and regulation of response to stimulus were established, and the most highly ranked 6 hub genes (up-regulated CD44, KRT6A, CEACAM5, SERPINB2, and down-regulated LTF and MUC5B) were identified and should be considered as new biomarkers. Pathway cross-talk analysis highlights that signaling pathways mediated by IL-4/13 and transcription factor HIF-1α and FOXA1 play crucial roles in the pathogenesis of asthma. Interestingly, three chemicals, polyphenol catechin, antibiotic lomefloxacin, and natural alkaloid boldine, were predicted and may be potential drugs for asthma treatment. Taken together, our findings shed new light on the common molecular pathogenesis mechanisms of asthma and provide theoretical support for further clinical therapeutic studies.

RAD51B (rs8017304 and rs2588809), TRIB1 (rs6987702, rs4351379, and rs4351376), COL8A1 (rs13095226), and COL10A1 (rs1064583) Gene Variants with Predisposition to Age-Related Macular Degeneration

Background

Age-related macular degeneration (AMD) is a progressive neurodegenerative disease of a central part of the neural retina (macula) and a leading cause of blindness in elderly people. While it is known that the AMD is a multifactorial disease, genetic factors involved in lipid metabolism, inflammation, and neovascularization are currently being widely studied in genome-wide association studies (GWAS). The aim of our study was to evaluate the impact of new single nucleotide polymorphisms (SNPs) in RAD51B, TRIB1, COL8A1, and COL10A1 genes on AMD development.

Methods

Case-control study involved 254 patients diagnosed with early AMD, 244 patients with exudative AMD, and 942 control subjects. The genotyping of RAD51B (rs8017304 and rs2588809), TRIB1 (rs6987702, rs4351379, and rs4351376), COL8A1 (rs13095226), and COL10A1 (rs1064583) was carried out using TaqMan assays by a real-time polymerase chain reaction (RT-PCR) method.

Results

Statistically significant difference was found in genotype (TT, TC, and CC) distribution of COL8A1 rs13095226 between exudative AMD and control groups (60.2%, 33.6%, and 6.1% vs. 64.9%, 32.3%, and 2.9%, respectively, p = 0.036). Also, comparing with TT+TC, rs13095226 CC genotype was associated with 3.5-fold increased odds of exudative AMD development (OR = 3.540; 95% CI: 1.415-8.856; p = 0.007).

Conclusion

Our study revealed a strong association between a variant in COL8A1 (rs13095226) and exudative AMD development.

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients

Purpose

Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods

In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses’ Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results

Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion

After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

BACKGROUND

Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk.

METHODS

Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies.

RESULTS

Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile.

CONCLUSIONS

The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

Genetic Epidemiology of Breast Cancer in Latin America

The last 10 years witnessed an acceleration of our understanding of what genetic factors underpin the risk of breast cancer. Rare high- and moderate-penetrance variants such as those in the BRCA genes account for a small proportion of the familial risk of breast cancer. Low-penetrance alleles are expected to underlie the remaining heritability. By now, there are about 180 genetic polymorphisms that are associated with risk, most of them of modest effect. In combination, they can be used to identify women at the lowest or highest ends of the risk spectrum, which might lead to more efficient cancer prevention strategies. Most of these variants were discovered in populations of European descent. As a result, we might be failing to discover additional polymorphisms that could explain risk in other groups. This review highlights breast cancer genetic epidemiology studies conducted in Latin America, and summarizes the information that they provide, with special attention to similarities and differences with studies in other populations. It includes studies of common variants, as well as moderate- and high-penetrance variants. In addition, it addresses the gaps that need to be bridged in order to better understand breast cancer genetic risk in Latin America.

Identifying breast cancer susceptibility genes - a review of the genetic background in familial breast cancer

INTRODUCTION

Heritage is the most important risk factor for breast cancer. About 15-20% of breast cancer is familial, referring to affected women who have one or more first- or second-degree relatives with the disease. The heritable component in these families is substantial, especially in families with aggregation of breast cancer with low age at onset. Identifying breast cancer susceptibility genes: Since the discovery of the highly penetrant autosomal dominant susceptibility genes BRCA1 and BRCA2 in the 1990s, several more breast cancer genes that confer a moderate to high risk of breast cancer have been identified. Furthermore, during the last decade, advances in genomic technologies have led to large scale genotyping in genome-wide association studies that have identified a considerable amount of common low penetrance loci. In total, the high risk genes, BRCA1, BRCA2, TP53, STK11, CD1 and PTEN account for approximately 20% of the familial risk. Moderate risk variants account for up to 5% of the inherited familial risk. The more than 180 identified low-risk loci explain 18% of the familial risk. Altogether more than half of the genetic background in familial breast cancer remains unclear. Other genes and low risk loci that explain a part the remaining fraction will probably be identified. Clinical aspects and future perspectives: Definitive clinical recommendations can be drawn only for carriers of germline variants in a limited number of high and moderate risk genes for which an association with breast cancer has been established. Future progress in evaluating previously identified breast cancer candidate variants and low risk loci as well as exploring new ones can play an important role in improving individual risk prediction in familial breast cancer.

Identification of novel common breast cancer risk variants at the 6q25 locus among Latinas

Background

Breast cancer is a partially heritable trait and genome-wide association studies (GWAS) have identified over 180 common genetic variants associated with breast cancer. We have previously performed breast cancer GWAS in Latinas and identified a strongly protective single nucleotide polymorphism (SNP) at 6q25, with the protective minor allele originating from indigenous American ancestry. Here we report on fine mapping of the 6q25 locus in an expanded sample of Latinas.

Methods

We performed GWAS in 2385 cases and 6416 controls who were either US Latinas or Mexican women. We replicated the top SNPs in 2412 cases and 1620 controls of US Latina, Mexican, and Colombian women. In addition, we validated the top novel variants in studies of African, Asian and European ancestry. In each dataset we used logistic regression models to test the association between SNPs and breast cancer risk and corrected for genetic ancestry using either principal components or genetic ancestry inferred from ancestry informative markers using a model-based approach.

Results

We identified a novel set of SNPs at the 6q25 locus associated with genome-wide levels of significance (p = 3.3 × 10^− 8 - 6.0 × 10^− 9) not in linkage disequilibrium (LD) with variants previously reported at this locus. These SNPs were in high LD (r² > 0.9) with each other, with the top SNP, rs3778609, associated with breast cancer with an odds ratio (OR) and 95% confidence interval (95% CI) of 0.76 (0.70–0.84). In a replication in women of Latin American origin, we also observed a consistent effect (OR 0.88; 95% CI 0.78–0.99; p = 0.037). We also performed a meta-analysis of these SNPs in East Asians, African ancestry and European ancestry populations and also observed a consistent effect (rs3778609, OR 0.95; 95% CI 0.91–0.97; p = 0.0017).

Conclusion

Our study adds to evidence about the importance of the 6q25 locus for breast cancer susceptibility. Our finding also highlights the utility of performing additional searches for genetic variants for breast cancer in non-European populations.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1085-9) contains supplementary material, which is available to authorized users.

Enhancer Domains in Gastrointestinal Stromal Tumor Regulate KIT Expression and Are Targetable by BET Bromodomain Inhibition

Gastrointestinal stromal tumor (GIST) is a mesenchymal neoplasm characterized by activating mutations in the related receptor tyrosine kinases KIT and PDGFRA. GIST relies on expression of these unamplified receptor tyrosine kinase (RTK) genes through a large enhancer domain, resulting in high expression levels of the oncogene required for tumor growth. Although kinase inhibition is an effective therapy for many patients with GIST, disease progression from kinase-resistant mutations is common and no other effective classes of systemic therapy exist. In this study, we identify regulatory regions of the KIT enhancer essential for KIT gene expression and GIST cell viability. Given the dependence of GIST upon enhancer-driven expression of RTKs, we hypothesized that the enhancer domains could be therapeutically targeted by a BET bromodomain inhibitor (BBI). Treatment of GIST cells with BBIs led to cell-cycle arrest, apoptosis, and cell death, with unique sensitivity in GIST cells arising from attenuation of the KIT enhancer domain and reduced KIT gene expression. BBI treatment in KIT-dependent GIST cells produced genome-wide changes in the H3K27ac enhancer landscape and gene expression program, which was also seen with direct KIT inhibition using a tyrosine kinase inhibitor (TKI). Combination treatment with BBI and TKI led to superior cytotoxic effects in vitro and in vivo, with BBI preventing tumor growth in TKI-resistant xenografts. Resistance to select BBI in GIST was attributable to drug efflux pumps. These results define a therapeutic vulnerability and clinical strategy for targeting oncogenic kinase dependency in GIST. SIGNIFICANCE: Expression and activity of mutant KIT is essential for driving the majority of GIST neoplasms, which can be therapeutically targeted using BET bromodomain inhibitors.

A genome wide SNP genotyping study in the Tunisian population: specific reporting on a subset of common breast cancer risk loci

Background

Breast cancer is the most common cancer in women worldwide. Around 50% of breast cancer familial risk has been so far explained by known susceptibility alleles with variable levels of risk and prevalence. The vast majority of these breast cancer associated variations reported to date are from populations of European ancestry. In spite of its heterogeneity and genetic wealth, North-African populations have not been studied by the HapMap and the 1000Genomes projects. Thus, very little is known about the genetic architecture of these populations.

Methods

This study aimed to investigate a subset of common breast cancer loci in the general Tunisian population and to compare their genetic composition to those of other ethnic groups. We undertook a genome-wide haplotype study by genotyping 135 Tunisian subjects using the Affymetrix 6.0-Array. We compared Tunisian allele frequencies and linkage disequilibrium patterns to those of HapMap populations and we performed a comprehensive assessment of the functional effects of several selected variants.

Results

Haplotype analyses showed that at risk haplotypes on 2p24, 4q21, 6q25, 9q31, 10q26, 11p15, 11q13 and 14q32 loci are considerably frequent in the Tunisian population (> 20%). Allele frequency comparison showed that the frequency of rs13329835 is significantly different between Tunisian and all other HapMap populations. LD-blocks and Principle Component Analysis revealed that the genetic characteristics of breast cancer variants in the Tunisian, and so probably the North-African populations, are more similar to those of Europeans than Africans.

Using eQTl analysis, we characterized rs9911630 as the most strongly expression-associated SNP that seems to affect the expression levels of BRCA1 and two long non coding RNAs (NBR2 and LINC008854). Additional in-silico analysis also suggested a potential functional significance of this variant.

Conclusions

We illustrated the utility of combining haplotype analysis in diverse ethnic groups with functional analysis to explore breast cancer genetic architecture in Tunisia. Results presented in this study provide the first report on a large number of common breast cancer genetic polymorphisms in the Tunisian population which may establish a baseline database to guide future association studies in North Africa.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5133-8) contains supplementary material, which is available to authorized users.

Update Breast Cancer 2018 (Part 3) - Genomics, Individualized Medicine and Immune Therapies - in the Middle of a New Era: Prevention and Treatment Strategies for Early Breast Cancer

In primary early breast cancer, the aim of treatment planning is to obtain an increasingly better understanding of the disease. The identification of patients with an excellent prognosis could help this group avoid unnecessary treatments. Furthermore, the planning of treatment is becoming increasingly patient-focussed. There is a growing understanding of those patients who benefit particularly from chemotherapy, as well as of those who could benefit from immunotherapy. Studies conducted on immunotherapies will be published shortly. Smaller individual studies offer an initial insight into the efficacy of checkpoint inhibitors (anti-PD1/PDL1 therapies). Not least, one of the largest breast cancer studies of all times has recently come to an end. The use of a multigene test has shown that it is sufficient to identify patients with such a good prognosis that chemotherapy is unnecessary. This review article is intended to summarise the current studies and give an outlook on current developments.

Association of SNP-SNP Interactions Between RANKL, OPG, CHI3L1, and VDR Genes With Breast Cancer Risk in Egyptian Women

BACKGROUND

Genetic susceptibility for breast cancer (BC) is still poorly understood. A combination of multiple low-penetrant alleles of cancer-related genes and gene-gene interactions (epistasis) contributes to BC risk. Genetic variants in receptor activator of nuclear factor κB ligand (RANKL), osteoprotegerin (OPG), chitinase-3-like protein 1 (CHI3L1), and vitamin D receptor (VDR) genes are implicated in breast carcinogenesis; however, the influence of their epistatic effects on BC susceptibility has not yet been studied. We investigated the association of single nucleotide polymorphism (SNP)-SNP interactions and haplotypes of 6 SNPs in these 4 genes with the genetic predisposition of BC in Egyptian women.

PATIENTS AND METHODS

Data of 115 BC patients and 120 cancer-free controls were studied. Association tests were conducted using logistic regression models.

RESULTS

Individual SNPs showed weak statistical significance with BC susceptibility. The interactions between RANKL-rs9533156 and OPG-rs2073618; OPG-rs2073618 with CHI3L1-rs4950928, VDR-rs2228570 and VDR-rs1544410; OPG-rs2073617 and VDR-rs1544410; VDR-rs2228570 and VDR-rs1544410 were strongly associated with increased BC risk after adjustment for multiple comparisons. No SNPs were in strong linkage disequilibrium. The TCTCTG-rs9533156-rs2073618-rs2073617-rs4950928-rs2228570-rs1544410 haplotype was significantly associated with increased BC risk (adjusted odds ratio = 8.33; 95% confidence interval, 1.32-52.46; P = .025) compared with controls. TCCCTG haplotype stratified BC patients according to estrogen receptor/progesterone receptor status. TCTCTA was positively associated, and TCTCTG and TGTCTG haplotypes inversely correlated with bone metastasis. Bioinformatic analysis revealed 13 proteins commonly interacting with our 4 genes; the most significant was signal transducer and activator of transcription 5B.

CONCLUSION

Our results suggested that a stronger combined effect of SNPs in RANKL, OPG, CHI3L1, and VDR genes via gene-gene interaction may help predict BC risk and prognosis.

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

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

Polymorphisms of 5’-UTR of rad51 gene in prostate cancer

Background. Notwithstanding that prostate cancer is largely studied all over the world for many decades, its etiology is not known and there is an intensive work to elucidate the cause and molecular markers for the development of this male cancer. Polymorphisms in DNA repairing genes may affect the DNA repairing capacity that in turn contributes to cancer development. This study aims to explore the polymorphisms of homologous recombination (HR) RAD51 gene (rs1801320 and rs1801321) as a possible risk factor for developing prostate cancer. Sequencing of 5'-UTR of RAD51 gene (rs1801320 and rs1801321) was studied in 80 DNA samples of prostate cancer and 50 DNA samples from a control group. Our results revealed a significant correlation between rs1801320 GC polymorphism and the presence of prostate cancer in the Jordanian population (p = 0.041, X2 = 6.377). On the other hand, the rs1801321 GT polymorphism was not associated with the presence of prostate cancer in the study population (p = 0.27, X2 = 2.6). In conclusion, our results shed a light on the possible role of RAD51 gene polymorphisms in the development of prostate cancer; however, a larger representative study is needed to elucidate a possible role of RAD51 gene polymorphisms in development and prognosis of prostate cancer.

Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data

Over the last two decades genetic testing for mutations in BRCA1 and BRCA2 has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that – together with previously identified common variants – more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.

Novel genetic loci associated with long-term deterioration in blood lipid concentrations and coronary artery disease in European adults

Background

Cross-sectional genome-wide association studies have identified hundreds of loci associated with blood lipids and related cardiovascular traits, but few genetic association studies have focused on long-term changes in blood lipids.

Methods

Participants from the GLACIER Study (Nmax = 3492) were genotyped with the MetaboChip array, from which 29 387 SNPs (single nucleotide polymorphisms; replication, fine-mapping regions and wildcard SNPs for lipid traits) were extracted for association tests with 10-year change in total cholesterol (ΔTC) and triglycerides (ΔTG). Four additional prospective cohort studies (MDC, PIVUS, ULSAM, MRC Ely; Nmax = 8263 participants) were used for replication. We conducted an in silico look-up for association with coronary artery disease (CAD) in the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAMplusC4D) Consortium (N ∼ 190 000) and functional annotation for the top ranking variants.

Results

In total, 956 variants were associated (P < 0.01) with either ΔTC or ΔTG in GLACIER. In GLACIER, chr19:50121999 at APOE was associated with ΔTG and multiple SNPs in the APOA1/A4/C3/A5 region at genome-wide significance (P < 5 × 10-8), whereas variants in four loci, DOCK7, BRE, SYNE1 and KCNIP1, reached study-wide significance (P < 1.7 × 10-6). The rs7412 variant at APOE was associated with ΔTC in GLACIER (P < 1.7 × 10-6). In pooled analyses of all cohorts, 139 SNPs at six and five loci were associated with ΔTC and for ΔTG, respectively (P < 10-3). Of these, a variant at CAPN3 (P = 1.2 × 10-4), multiple variants at HPR (Pmin = 1.5 × 10-6) and a variant at SIX5 (P = 1.9 × 10-4) showed evidence for association with CAD.

Conclusions

We identified seven novel genomic regions associated with long-term changes in blood lipids, of which three also raise CAD risk.

Genetic Modifiers of the Breast Tumor Microenvironment

Multiple nonmalignant cell types in the tumor microenvironment (TME) impact breast cancer risk, metastasis, and response to therapy, yet most heritable mechanisms that influence TME cell function and breast cancer outcomes are largely unknown. Breast cancer risk is ∼30% heritable and >170 genetic loci have been associated with breast cancer traits. However, the majority of candidate genes have poorly defined mechanistic roles in breast cancer biology. Research indicates that breast cancer risk modifiers directly impact cancer cells, yet it is equally plausible that some modifier alleles impact the nonmalignant TME. The objective of this review is to examine the list of current breast cancer candidate genes that may modify breast cancer risk and outcome through the TME.

Breast Cancer Family History and Contralateral Breast Cancer Risk in Young Women: An Update From the Women's Environmental Cancer and Radiation Epidemiology Study

Purpose The Women's Environmental Cancer and Radiation Epidemiology (WECARE) study demonstrated the importance of breast cancer family history on contralateral breast cancer (CBC) risk, even for noncarriers of deleterious BRCA1/2 mutations. With the completion of WECARE II, updated risk estimates are reported. Additional analyses that exclude women negative for deleterious mutations in ATM, CHEK2*1100delC, and PALB2 were performed. Patients and Methods The WECARE Study is a population-based case-control study that compared 1,521 CBC cases with 2,212 individually matched unilateral breast cancer (UBC) controls. Participants were younger than age 55 years when diagnosed with a first invasive breast cancer between 1985 and 2008. Women were interviewed about breast cancer risk factors, including family history. A subset of women was screened for deleterious mutations in BRCA1/2, ATM, CHEK2*1100delC, and PALB2. Rate ratios (RRs) were estimated using multivariable conditional logistic regression. Cumulative absolute risks (ARs) were estimated by combining RRs from the WECARE Study and population-based SEER*Stat cancer incidence data. Results Women with any first-degree relative with breast cancer had a 10-year AR of 8.1% for CBC (95% CI, 6.7% to 9.8%). Risks also were increased if the relative was diagnosed at an age younger than 40 years (10-year AR, 13.5%; 95% CI, 8.8% to 20.8%) or with CBC (10-year AR, 14.1%; 95% CI, 9.5% to 20.7%). These risks are comparable with those seen in BRCA1/2 deleterious mutation carriers (10-year AR, 18.4%; 95% CI, 16.0% to 21.3%). In the subset of women who tested negative for deleterious mutations in BRCA1/2, ATM, CHEK2*1100delC, and PALB2, estimates were unchanged. Adjustment for known breast cancer single-nucleotide polymorphisms did not affect estimates. Conclusion Breast cancer family history confers a high CBC risk, even after excluding women with deleterious mutations. Clinicians are urged to use detailed family histories to guide treatment and future screening decisions for young women with breast cancer.