Common breast cancer risk variants in the post-COGS era: a comprehensive review

Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia

BACKGROUND

Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs.

METHODS

We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG).

RESULTS

In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16).

CONCLUSION

The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

The largest genome-wide association study for breast cancer in Taiwanese Han population

PURPOSE

Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap.

METHODS

A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched.

RESULTS

The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79-7.66) and 3.55 (2.13-6.14), respectively.

CONCLUSION

In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women.

Breast cancer prediction model based on clinical and biochemical characteristics: clinical data from patients with benign and malignant breast tumors from a single center in South China

OBJECTIVE

Breast cancer is the most prevalent cancer and is second leading cause of death from malignancy among women worldwide. In addition to tumor factors, the host characteristics of tumors have been paid more and more attention by the medical community. This study aimed to develop a breast cancer prediction model for the Chinese population using clinical and biochemical characteristics.

METHODS

This is a retrospective study. From 2012 to 2021, we selected 19,751 patients with breast diseases from the Guangdong Hospital of Traditional Chinese Medicine, which included 5660 patients with breast cancer and 14,091 patients with benign breast diseases-75% of patients were randomly assigned to the training group and 25% to the test group using a total of 34 clinical and biochemical characteristics. Significant clinical signs were investigated, and logistic regression with recursive feature elimination (RFE) model was used to develop a prediction model for distinguishing benign from malignant breast diseases. The prediction model's accuracy, precision, sensitivity, specificity, and area under the ROC curve (AUC) were calculated.

RESULTS

Clinical statistics demonstrated that the prediction model comprised 19 clinical characteristics had statistical separability in both the training group and the test group, as well as good sensitivity and prediction.

CONCLUSIONS

This model based on biochemical parameters demonstrates a significant predictive effect for breast cancer and may be useful as a reference for invasive tissue biopsy in patients undergoing BI-RADS 3 and 4A breast imaging.

The Role of Some Selenoproteins in the Etiopathogenesis of Breast Cancer

Amaç: Meme kanseri, kadınlarda kanser kaynaklı ölümlerde akciğer kanserinden sonra ikinci sırada yer alır. Çeşitli çalışmalarda, selenoproteinlerin kanserogenezin bazı evrelerini baskıladığı ve kanser hücrelerinin çoğalma hızını azalttığı gösterilmiştir. Ancak bu mekanizmalar tam olarak açıklanamamıştır. Kanser tedavisinde radyoterapi, kemoterapiyle birlikte en çok tercih edilen tedavi yöntemlerindendir. Çalışmanın amacı, radyoterapi alan meme kanserli hastaların tedavi öncesi ve sonrası selenoprotein düzeylerindeki değişiklikleri değerlendirerek hastalığın etiyopatogenezine olası etkilerini incelemektir.Yöntem: Çalışmamıza meme kanseri teşhisi konmuş, radyoterapi öncesi ve radyoterapi sonrası örnekleri alınan 35 kadın hasta ile herhangi bir ilaç tedavisi almayan 25 sağlıklı kadın gönüllü dahil edildi. Hasta ve sağlıklı kontrol gruplarını oluşturan bireylerden kan örnekleri alındı. Serum örneklerinde selenoprotein K (Sel-K), selenoprotein W1 (Sel-W1) ve selenoprotein P (Sel-P) düzeyleri ELISA (Enzyme-Linked Immunosorbent Assay) yöntemi ile ölçüldü. İstatistiksel analiz, Wilcoxon ve Mann-Whitney U testleri kullanılarak yapıldı. Hesaplamalar için Statistical Package for the Social Sciences – SPSS 21.0 for Windows (SPSS Inc, Chicago, IL, ABD) kullanıldı. p<0.05, istatistiksel olarak anlamlı bir farkı belirtmek için kabul edildi.Bulgular: Serum Sel-K düzeyleri tedavi öncesi ve kontrol grubu karşılaştırıldığında, tedavi öncesi grupta anlamlı olarak düşük bulundu. Sel- P düzeyleri hem tedavi öncesi hem de tedavi sonrasında kontrol grubu ile karşılaştırıldığında her iki grupta da kontrol grubuna göre düşük bulundu. Sel-W1 düzeylerinde gruplar arasında herhangi bir anlamlılık bulunmadı.Sonuç: Meme kanserinde bazı selenoproteinlerin hastalığın etiyopatogenezinde önemli bir rolü olmakla birlikte daha fazla örneklem grubu ve ileri çalışmalar ile hastalığın progresyonu ve selenoprotein düzeyleri arasındaki ilişkinin araştırılmasına ihtiyaç duyulmaktadır.

Psychological and health behaviour outcomes following multi-gene panel testing for hereditary breast and ovarian cancer risk: a mini-review of the literature

INTRODUCTION

Knowledge of the genetic mechanisms driving hereditary breast and ovarian cancer (HBOC) has recently expanded due to advances in gene sequencing technologies. Genetic testing for HBOC risk now involves multi-gene panel testing, which includes well characterized high-penetrance genes (e.g. BRCA1 and BRCA2), as well as moderate- and low-penetrance genes. Certain moderate and low penetrance genes are associated with limited data to inform cancer risk estimates and clinical management recommendations, which create new sources of genetic and clinical uncertainty for patients.

PURPOSE

The aim of this review is to evaluate the psychological and health behaviour outcomes associated with multi-gene panel testing for HBOC risk. The search was developed in collaboration with an Information Specialist (Princess Margaret Cancer Centre) and conducted in the following databases: MEDLINE, EMBASE, EMCare, PsycINFO, Epub Ahead of Publication.

RESULTS

Similar to the BRCA1/2 literature, individuals with a pathogenic variant (PV) reported higher levels of testing-related concerns and cancer-specific distress, as well as higher uptake of prophylactic surgery in both affected and unaffected individuals compared to those with variant of uncertain significance (VUS) or negative result. A single study demonstrated that individuals with a PV in a moderate penetrance gene reported higher rates of cancer worry, genetic testing concerns and cancer-related distress when compared to women with high penetrance PV. Analysis of cancer screening and prevention outcomes based upon gene penetrance were limited to two studies, with conflicting findings.

CONCLUSION

The findings in this review emphasize the need for studies examining psychological and health behavior outcomes associated with panel testing to include between group differences based upon both variant pathogenicity and gene penetrance. Future studies evaluating the impact of gene penetrance on patient-reported and clinical outcomes will require large samples to be powered for these analyses given that a limited number of tested individuals are found to have a PV.

Prediction of Breast Cancer using Machine Learning Approaches

BACKGROUND

Breast cancer is considered one of the most common cancers in women caused by various clinical, lifestyle, social, and economic factors. Machine learning has the potential to predict breast cancer based on features hidden in data.

OBJECTIVE

This study aimed to predict breast cancer using different machine-learning approaches applying demographic, laboratory, and mammographic data.

MATERIAL AND METHODS

In this analytical study, the database, including 5,178 independent records, 25% of which belonged to breast cancer patients with 24 attributes in each record was obtained from Motamed cancer institute (ACECR), Tehran, Iran. The database contained 5,178 independent records, 25% of which belonged to breast cancer patients containing 24 attributes in each record. The random forest (RF), neural network (MLP), gradient boosting trees (GBT), and genetic algorithms (GA) were used in this study. Models were initially trained with demographic and laboratory features (20 features). The models were then trained with all demographic, laboratory, and mammographic features (24 features) to measure the effectiveness of mammography features in predicting breast cancer.

RESULTS

RF presented higher performance compared to other techniques (accuracy 80%, sensitivity 95%, specificity 80%, and the area under the curve (AUC) 0.56). Gradient boosting (AUC=0.59) showed a stronger performance compared to the neural network.

CONCLUSION

Combining multiple risk factors in modeling for breast cancer prediction could help the early diagnosis of the disease with necessary care plans. Collection, storage, and management of different data and intelligent systems based on multiple factors for predicting breast cancer are effective in disease management.

Association of a Polygenic Risk Score With Breast Cancer Among Women Carriers of High- and Moderate-Risk Breast Cancer Genes

Importance

To date, few studies have examined the extent to which polygenic single-nucleotide variation (SNV) (formerly single-nucleotide polymorphism) scores modify risk for carriers of pathogenic variants (PVs) in breast cancer susceptibility genes. In previous reports, polygenic risk modification was reduced for BRCA1 and BRCA2 PV carriers compared with noncarriers, but limited information is available for carriers of CHEK2, ATM, or PALB2 PVs.

Objective

To examine an 86-SNV polygenic risk score (PRS) for BRCA1, BRCA2, CHEK2, ATM, and PALB2 PV carriers.

Design, Setting, and Participants

A retrospective case-control study using data on 150 962 women tested with a multigene hereditary cancer panel between July 19, 2016, and January 11, 2019, was conducted in a commercial testing laboratory. Participants included women of European ancestry between the ages of 18 and 84 years.

Main Outcomes and Measures

Multivariable logistic regression was used to examine the association of the 86-SNV score with invasive breast cancer after adjusting for age, ancestry, and personal and/or family cancer history. Effect sizes, expressed as standardized odds ratios (ORs) with 95% CIs, were assessed for carriers of PVs in each gene as well as for noncarriers.

Results

The median age at hereditary cancer testing of the population was 48 years (range, 18-84 years); there were 141 160 noncarriers in addition to carriers of BRCA1 (n = 2249), BRCA2 (n = 2638), CHEK2 (n = 2564), ATM (n = 1445), and PALB2 (n = 906) PVs included in the analysis. The 86-SNV score was associated with breast cancer risk in each of the carrier populations (P < 1 × 10-4). Stratification was more pronounced for noncarriers (OR, 1.47; 95% CI, 1.45-1.49) and CHEK2 PV carriers (OR, 1.49; 95% CI, 1.36-1.64) than for carriers of BRCA1 (OR, 1.20; 95% CI, 1.10-1.32) or BRCA2 (OR, 1.23; 95% CI, 1.12-1.34) PVs. Odds ratios for ATM (OR, 1.37; 95% CI, 1.21-1.55) and PALB2 (OR, 1.34; 95% CI, 1.16-1.55) PV carrier populations were intermediate between those for BRCA1/2 and CHEK2 noncarriers.

Conclusions and Relevance

In this study, the 86-SNV score was associated with modified risk for carriers of BRCA1, BRCA2, CHEK2, ATM, and PALB2 PVs. This finding supports previous reports of reduced PRS stratification for BRCA1 and BRCA2 PV carriers compared with noncarriers. Modification of risk in CHEK2 carriers associated with the 86-SNV score appeared to be similar to that observed in women without a PV. Larger studies are needed to provide more refined estimates of polygenic modification of risk for women with PVs in other moderate-penetrance genes.

DNA repair genes hOGG1, XRCC1 and ERCC2 polymorphisms and their molecular mapping in breast cancer patients from India

Identification of modifier genes predisposing to breast cancer (BC) phenotype remains a significant challenge and varies with ethnicity. The genetic variability observed in DNA repair genes may modulate the cell's ability to repair the damaged DNA and hence, evaluation of genetic variants in crucial DNA damage repair genes is of clinical importance. We performed the present study to evaluate the role of ERCC2-Lys751Gln, hOGG1-Ser326Cys, and XRCC1-Arg399Gln gene polymorphisms on the risk of BC development and its molecular profile in Indian women. Three non-synonymous variants (rs13181, rs1052133, and rs25487) were genotyped in 464 BC patients and 450 healthy controls. Logistic regression was employed to evaluate the association of genotypes with BC risk. Also, in silico analysis was carried out to map the Arg399Gln variant on the BRCT1 domain of XRCC1 protein. XRCC1 Gln/Gln genotype frequency was significantly elevated in BC patients [odd ratio (OR) = 1.73; 95% confidence interval (CI) = 1.13-2.65]. No significant association was observed between hOGG1-Ser326Cys and ERCC2-Lys751Gln variants and BC risk. Subgroup analysis revealed that ERCC2-Lys751Gln and XRCC1-Arg399Gln variants contributed towards tumor progression. A positive interaction between the investigated SNPs and BC was revealed by MDR analysis. Arg399Gln variant resulted in a change in the surface charge of XRCC1 protein. The rs25487 variant of XRCC1 might be associated with an elevated risk of BC. Furthermore, we demonstrated that high order gene-gene interaction plays a significant role in BC etiology. Hence, understanding the impact of low penetrant gene polymorphisms might enable a better understanding of the genetic background of breast cancer.

Prediagnosis aspirin use, DNA methylation, and mortality after breast cancer: A population-based study

BACKGROUND

The authors hypothesized that epigenetic changes may help to clarify the underlying biologic mechanism linking aspirin use to breast cancer prognosis. To the authors' knowledge, this is the first epidemiologic study to examine whether global methylation and/or tumor promoter methylation of breast cancer-related genes interact with aspirin use to impact mortality after breast cancer.

METHODS

Prediagnosis aspirin use was assessed through in-person interviews within a population-based cohort of 1508 women diagnosed with a first primary breast cancer in 1996 and 1997. Global methylation in peripheral blood was assessed by long interspersed elements-1 (LINE-1) and the luminometric methylation assay. Promoter methylation of 13 breast cancer-related genes was measured in tumor by methylation-specific polymerase chain reaction and the MethyLight assay. Vital status was determined by the National Death Index through December 31, 2014 (N = 202/476 breast cancer-specific/all-cause deaths identified among 1266 women with any methylation assessment and complete aspirin data). Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% CIs, and the likelihood ratio test was used to evaluate multiplicative interactions.

RESULTS

All-cause mortality was elevated among aspirin users who had methylated promotor of BRCA1 (HR, 1.67; 95% CI, 1.26-2.22), but not among those with unmethylated promoter of BRCA1 (HR, 0.99; 95% CI, 0.67-1.45; P for interaction ≤.05). Decreased breast cancer-specific mortality was observed among aspirin users who had unmethylated promotor of BRCA1 and PR and global hypermethylation of LINE-1 (HR, 0.60, 0.78, and 0.63, respectively; P for interaction ≤.05), although the 95% CIs included the null.

CONCLUSIONS

The current study suggests that the LINE-1 global methylation and promoter methylation of BRCA1 and PR in tumor may interact with aspirin use to influence mortality after breast cancer.

Consanguinity and Inbreeding in Health and Disease in North African Populations

North Africa is defined as the geographical region separated from the rest of the continent by the Sahara and from Europe by the Mediterranean Sea. The main demographic features of North African populations are their familial structure and high rates of familial and geographic endogamy, which have a proven impact on health, particularly the occurrence of genetic diseases, with a greater effect on the frequency and spectrum of the rarest forms of autosomal recessive genetic diseases. More than 500 different genetic diseases have been reported in this region, most of which are autosomal recessive. During the last few decades, there has been great interest in the molecular investigation of large consanguineous North African families. The development of local capacities has brought a substantial improvement in the molecular characterization of these diseases, but the genetic bases of half of them remain unknown. Diseases of known molecular etiology are characterized by their genetic and mutational heterogeneity, although some founder mutations are encountered relatively frequently. Some founder mutations are specific to a single country or a specific ethnic or geographic group, and others are shared by all North African countries or worldwide. The impact of consanguinity on common multifactorial diseases is less evident.

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.

Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants

The predictive capability of combining demographic risk factors, germline genetic variants, and mammogram abnormality features for breast cancer risk prediction is poorly understood. We evaluated the predictive performance of combinations of demographic risk factors, high risk single nucleotide polymorphisms (SNPs), and mammography features for women recommended for breast biopsy in a retrospective case-control study (n = 768) with four logistic regression models. The AUC of the baseline demographic features model was 0.580. Both genetic variants and mammography abnormality features augmented the performance of the baseline model: demographics + SNP (AUC =0.668), demographics + mammography (AUC =0.702). Finally, we found that the demographics + SNP + mammography model (AUC = 0.753) had the greatest predictive power, with a significant performance improvement over the other models. The combination of demographic risk factors, genetic variants and imaging features improves breast cancer risk prediction over prior methods utilizing only a subset of these features.

Comprehensive Analysis of Germline Variants in Mexican Patients with Hereditary Breast and Ovarian Cancer Susceptibility

Hereditary breast and ovarian cancer syndrome (HBOC) represents 5⁻10% of all patients with breast cancer and is associated with high-risk pathogenic alleles in BRCA1/2 genes, but only for 25% of cases. We aimed to find new pathogenic alleles in a panel of 143 cancer-predisposing genes in 300 Mexican cancer patients with suspicion of HBOC and 27 high-risk patients with a severe family history of cancer, using massive parallel sequencing. We found pathogenic variants in 23 genes, including BRCA1/2. In the group of cancer patients 15% (46/300) had a pathogenic variant; 11% (33/300) harbored variants with unknown clinical significance (VUS) and 74% (221/300) were negative. The high-risk group had 22% (6/27) of patients with pathogenic variants, 4% (1/27) had VUS and 74% (20/27) were negative. The most recurrent mutations were the Mexican founder deletion of exons 9-12 and the variant p.G228fs in BRCA1, each found in 5 of 17 patients with alterations in this gene. Rare VUS with potential impact at the protein level were found in 21 genes. Our results show for the first time in the Mexican population a higher contribution of pathogenic alleles in other susceptibility cancer genes (54%) than in BRCA1/2 (46%), highlighting the high locus heterogeneity of HBOC and the necessity of expanding genetic tests for this disease to include broader gene panels.

High-risk women's risk perception after receiving personalized polygenic breast cancer risk information

Evidence is accumulating of the clinical utility of single nucleotide polymorphisms to effectively stratify risk of breast cancer. Yet for this personalized polygenic information to be translated to clinical practice, consideration is needed about how this personalized risk information should be communicated and the impact on risk perception. This study examined the psychosocial implications and the impact on risk perception of communicating personalized polygenic breast cancer risk to high-risk women. High-risk women with a personal history of breast cancer and an uninformative BRCA1/2 result were genotyped in the Variants in Practice study for 22 breast cancer single nucleotide polymorphisms. Participants in the highest quartile of polygenic breast cancer risk were invited to receive their individual research results. Two personalized visual risk communication tools were used to facilitate communication of the polygenic information. Participants subsequently undertook a semi-structured interview examining their experience of receiving their polygenic breast cancer risk and their breast cancer risk perception. Thirty-nine women opted to receive their results and were interviewed. The women described the risk communication tools as helpful as the tool enabled comparison of their personalized breast cancer risk to the general population. Participants incorporated the polygenic risk information into their breast cancer risk perception, which for some reawakened feelings of being at risk years after an uninformative BRCA1/2 result. However, few reported any detrimental emotional impact. The delivery of personalized polygenic breast cancer risk to high-risk women informed and modified their breast cancer risk perception with little emotional impact.

Family specific genetic predisposition to breast cancer: results from Tunisian whole exome sequenced breast cancer cases

BACKGROUND

A family history of breast cancer has long been thought to indicate the presence of inherited genetic events that predispose to this disease. In North Africa, many specific epidemio-genetic characteristics have been observed in breast cancer families when compared to Western populations. Despite these specificities, the majority of breast cancer genetics studies performed in North Africa remain restricted to the investigation of the BRCA1 and BRCA2 genes. Thus, comprehensive data at a whole exome or whole genome level from local patients are lacking.

METHODS

A whole exome sequencing (WES) of seven breast cancer Tunisian families have been performed using a family-based approach. We focused our analysis on BC-TN-F001 family that included two affected members that have been sequenced using WES. Relevant variants identified in BC-TN-F001 have been confirmed using Sanger sequencing. Then, we conducted an integrative analysis by combining our results with those from other WES studies in order to figure out the genetic transmission model of the newly identified genes. Biological network construction and protein-protein interactions analyses have been performed to decipher the molecular mechanisms likely accounting for the role of these genes in breast cancer risk.

RESULTS

Sequencing, filtering strategies, and validation analysis have been achieved. For BC-TN-F001, no deleterious mutations have been identified on known breast cancer genes. However, 373 heterozygous, exonic and rare variants have been identified on other candidate genes. After applying several filters, 12 relevant high-risk variants have been selected. Our results showed that these variants seem to be inherited in a family specific model. This hypothesis has been confirmed following a thorough analysis of the reported WES studies. Enriched biological process and protein-protein interaction networks resulted in the identification of four novel breast cancer candidate genes namely MMS19, DNAH3, POLK and KATB6.

CONCLUSIONS

In this first WES application on Tunisian breast cancer patients, we highlighted the impact of next generation sequencing technologies in the identification of novel breast cancer candidate genes which may bring new insights into the biological mechanisms of breast carcinogenesis. Our findings showed that the breast cancer predisposition in non-BRCA families may be ethnic and/or family specific.

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

Background

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

Participants and Methods

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

Results

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

Conclusion

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

Polymorphisms in the TOX3/LOC643714 and risk of breast cancer in south China

OBJECTIVE

Breast cancer is the most widespread cancer in women, with a high mortality rate. This study aims to assess the association between single nucleotide polymorphisms (SNPs) of LOC643714 (rs12922061) and TOX3 (rs3803662) and breast cancer, as well as the clinical characteristics of tumors.

MATERIALS AND METHODS

In total, 104 breast cancer patients and 118 healthy controls were recruited to our study. The genotyping was performed by the SNP scan method. General characteristics, the clinical characteristics of tumors and reproductive factors were included in the analysis. Statistical tests included the Student t-test, the Chi-square test (X2) or Fisher's exact test, and unconditional logistic regression analysis. The receiver operating characteristic curves were used to evaluate the predictive role of rs12922061 in breast cancer.

RESULTS

The LOC643714 polymorphism was a risk factor for breast cancer under a dominant model (TT+TC vs. CC: OR 1.801; 95% CI 1.048, 3.095; statistical power=60%), recessive model (TT vs. TC + CC: OR 4.297; 95% CI 1.164, 15.867; statistical power=64%) and log-additive (TT vs. CC: OR 5.163; 95% CI 1.368, 19.485; statistical power= 73%). Furthermore, the rs12922061 polymorphism was associated with menopause status in patients ( P=0.005). No statistically significant association was found between the rs3803662 polymorphism and breast cancer in patients or healthy controls.

CONCLUSIONS

Our study found that rs12922061 of LOC643714 was related to breast cancer risk. With a limited sample size and statistical power, further multi-center studies are needed to confirm the influence of the LOC643714 polymorphisms on breast cancer based on larger populations.

Thyroid-associated genetic polymorphisms in relation to breast cancer risk in the Malmö Diet and Cancer Study

Previous studies have suggested that thyroid function is associated with breast cancer risk, which could have an important clinical impact, as one in eight women will develop a thyroid disorder during her lifetime. However, the underlying pathomechanism behind the association is still unknown. We used the Malmö Diet and Cancer Study (a population-based prospective study consisting of 17,035 women) to examine 17 single nucleotide polymorphisms (SNPs) previously related to levels of free thyroxine (free T4) and thyroid peroxidase antibodies (TPO-Ab) as potential genetic risk factors for breast cancer. A baseline examination including free T4 and TPO-Ab levels was conducted at the time of inclusion. Genotyping was performed on 901 breast cancer patients and 3335 controls. Odds ratios (95% confidence intervals) for high free T4, TPO-Ab positivity, and breast cancer were calculated by logistic regression and adjusted for confounders. We identified one free T4-related SNP (rs2235544, D101 gene) that was significantly associated with both free T4 level and breast cancer risk. There was a suggested association between rs11675434 (TPO gene) and TPO-Ab level, and TPO-Ab-related rs11675434 (TPO), rs3094228 (HCP5), rs1033662 (no registered gene), and rs301806 (RERE) were associated with breast cancer risk. There was an indicated interaction between rs6485050 (no registered gene) and free T4 level in regards to breast cancer risk. This is the first study to suggest an association between thyroid-related SNPs and breast cancer risk. All SNPs have a biological plausibility of being associated with breast cancer risk, and may contribute to the genetic predisposition to breast cancer.

Specific killing of DNA damage-response deficient cells with inhibitors of poly(ADP-ribose) glycohydrolase

Poly(ADP-ribosylation) of proteins following DNA damage is well studied and the use of poly(ADP-ribose) polymerase (PARP) inhibitors as therapeutic agents is an exciting prospect for the treatment of many cancers. Poly(ADP-ribose) glycohydrolase (PARG) has endo- and exoglycosidase activities which can cleave glycosidic bonds, rapidly reversing the action of PARP enzymes. Like addition of poly(ADP-ribose) (PAR) by PARP, removal of PAR by PARG is also thought to be required for repair of DNA strand breaks and for continued replication at perturbed forks. Here we use siRNA to show a synthetic lethal relationship between PARG and BRCA1, BRCA2, PALB2, FAM175A (ABRAXAS) and BARD1. In addition, we demonstrate that MCF7 cells depleted of these proteins are sensitive to Gallotannin and a novel and specific PARG inhibitor PDD00017273. We confirm that PARG inhibition increases endogenous DNA damage, stalls replication forks and increases homologous recombination, and propose that it is the lack of homologous recombination (HR) proteins at PARG inhibitor-induced stalled replication forks that induces cell death. Interestingly not all genes that are synthetically lethal with PARP result in sensitivity to PARG inhibitors, suggesting that although there is overlap, the functions of PARP and PARG may not be completely identical. These data together add further evidence to the possibility that single treatment therapy with PARG inhibitors could be used for treatment of certain HR deficient tumours and provide insight into the relationship between PARP, PARG and the processes of DNA repair.

CURRENT CONCEPTS ON THE GENETIC FACTORS IN ROTATOR CUFF PATHOLOGY AND FUTURE IMPLICATIONS FOR SPORTS PHYSICAL THERAPISTS

CONTEXT

Recent advances within the field of genetics are currently changing many of the methodologies in which medicine is practiced. These advances are also beginning to influence the manner in which physical therapy services are rendered. Rotator cuff pathology is one of the most common diagnoses treated by the sports physical therapist. The purpose of this commentary is to educate sports physical therapists on the recent advances regarding how genetics influences rotator cuff pathology, including rotator cuff tears, and provide a perspective on how this information will likely influence post-operative shoulder rehabilitation in the near future.

EVIDENCE ACQUISITION

A comprehensive review of the literature was completed using the Medline database along with individual searches of relevant physical therapy, surgical, cell biology, and sports medicine journals. Search terms included: shoulder, rotator cuff pathology, genetics, apoptosis, and physical therapy. Search results were compiled and evaluated; relevant primary studies and review articles were gathered; the results from this comprehensive review are summarized here.

STUDY DESIGN

Clinical Commentary, Review of the Literature.

RESULTS

Recent advances within the understanding of rotator cuff pathology have further elucidated the cellular and molecular mechanisms associated with rotator cuff tears. There appears to be a hypoxic-induced apoptotic cellular pathway that contributes to rotator cuff tears. Activation of specific proteins termed matrix metalloproteinases appear to be involved in not only primary rotator cuff tears, but also may influence the re-tear rate after surgical intervention. Further advancements in the understanding of the cellular mechanisms contributing to rotator cuff tears and postoperative techniques to help prevent re-tears, may soon influence the methodology in which physical therapy services are provided to patients sustaining a rotator cuff injury.

CONCLUSIONS

At this time continued research is required to more fully develop a comprehensive understanding of the role of genetic variables both within primary rotator cuff tears and their influences on post-operative rehabilitation from rotator cuff repair surgery.

LEVEL OF EVIDENCE

Level 5.

Racial Differences in Cancer Susceptibility and Survival: More Than the Color of the Skin?

Epidemiological studies point to race as a determining factor in cancer susceptibility. In US registries recording cancer incidence and survival by race (distinguishing 'black versus white'), individuals of African ancestry have a globally increased risk of malignancies compared with Caucasians and Asian Americans. Differences in socioeconomic status and health-care access play a key role. However, the lesser disease susceptibility of Hispanic populations with comparable lifestyles and socioeconomic status as African Americans (Hispanic paradox) points to the concomitant importance of genetic determinants. Here, we overview the molecular basis of racial disparity in cancer susceptibility ranging from genetic polymorphisms and cancer-driver gene mutations to obesity, chronic inflammation, and immune responses. We discuss implications for race-adapted cancer screening programs and clinical trials to reduce disparities in cancer burden.

Admixture Mapping of African-American Women in the AMBER Consortium Identifies New Loci for Breast Cancer and Estrogen-Receptor Subtypes

Recent genetic admixture coupled with striking differences in incidence of estrogen receptor (ER) breast cancer subtypes, as well as severity, between women of African and European ancestry, provides an excellent rationale for performing admixture mapping in African American women with breast cancer risk. We performed the largest breast cancer admixture mapping study with in African American women to identify novel genomic regions associated with the disease. We conducted a genome-wide admixture scan using 2,624 autosomal ancestry informative markers (AIMs) in 3,629 breast cancer cases (including 1,968 ER-positive, 1093 ER-negative, and 601 triple-negative) and 4,658 controls from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, a collaborative study of four large geographically different epidemiological studies of breast cancer in African American women. We used an independent case-control study to test for SNP association in regions with genome-wide significant admixture signals. We found two novel genome-wide significant regions of excess African ancestry, 4p16.1 and 17q25.1, associated with ER-positive breast cancer. Two regions known to harbor breast cancer variants, 10q26 and 11q13, were also identified with excess of African ancestry. Fine-mapping of the identified genome-wide significant regions suggests the presence of significant genetic associations with ER-positive breast cancer in 4p16.1 and 11q13. In summary, we identified three novel genomic regions associated with breast cancer risk by ER status, suggesting that additional previously unidentified variants may contribute to the racial differences in breast cancer risk in the African American population.

Multigene testing of moderate-risk genes: be mindful of the missense

BACKGROUND

Moderate-risk genes have not been extensively studied, and missense substitutions in them are generally returned to patients as variants of uncertain significance lacking clearly defined risk estimates. The fraction of early-onset breast cancer cases carrying moderate-risk genotypes and quantitative methods for flagging variants for further analysis have not been established.

METHODS

We evaluated rare missense substitutions identified from a mutation screen of ATM, CHEK2, MRE11A, RAD50, NBN, RAD51, RINT1, XRCC2 and BARD1 in 1297 cases of early-onset breast cancer and 1121 controls via scores from Align-Grantham Variation Grantham Deviation (GVGD), combined annotation dependent depletion (CADD), multivariate analysis of protein polymorphism (MAPP) and PolyPhen-2. We also evaluated subjects by polygenotype from 18 breast cancer risk SNPs. From these analyses, we estimated the fraction of cases and controls that reach a breast cancer OR≥2.5 threshold.

RESULTS

Analysis of mutation screening data from the nine genes revealed that 7.5% of cases and 2.4% of controls were carriers of at least one rare variant with an average OR≥2.5. 2.1% of cases and 1.2% of controls had a polygenotype with an average OR≥2.5.

CONCLUSIONS

Among early-onset breast cancer cases, 9.6% had a genotype associated with an increased risk sufficient to affect clinical management recommendations. Over two-thirds of variants conferring this level of risk were rare missense substitutions in moderate-risk genes. Placement in the estimated OR≥2.5 group by at least two of these missense analysis programs should be used to prioritise variants for further study. Panel testing often creates more heat than light; quantitative approaches to variant prioritisation and classification may facilitate more efficient clinical classification of variants.

Discriminatory power of common genetic variants in personalized breast cancer diagnosis

Technology advances in genome-wide association studies (GWAS) has engendered optimism that we have entered a new age of precision medicine, in which the risk of breast cancer can be predicted on the basis of a person's genetic variants. The goal of this study is to evaluate the discriminatory power of common genetic variants in breast cancer risk estimation. We conducted a retrospective case-control study drawing from an existing personalized medicine data repository. We collected variables that predict breast cancer risk: 153 high-frequency/low-penetrance genetic variants, reflecting the state-of-the-art GWAS on breast cancer, mammography descriptors and BI-RADS assessment categories in the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We trained and tested naïve Bayes models by using these predictive variables. We generated ROC curves and used the area under the ROC curve (AUC) to quantify predictive performance. We found that genetic variants achieved comparable predictive performance to BI-RADS assessment categories in terms of AUC (0.650 vs. 0.659, p-value = 0.742), but significantly lower predictive performance than the combination of BI-RADS assessment categories and mammography descriptors (0.650 vs. 0.751, p-value < 0.001). A better understanding of relative predictive capability of genetic variants and mammography data may benefit clinicians and patients to make appropriate decisions about breast cancer screening, prevention, and treatment in the era of precision medicine.

The relationship between apolipoprotein E gene ε2/ε3/ε4 polymorphism and breast cancer risk: a systematic review and meta-analysis

Objective

We conducted a systematic review and meta-analysis aiming to assess the relationship between apolipoprotein E (APOE) gene ε2/ε3/ε4 polymorphism and breast cancer risk.

Methods

Yun-Long Liu and Hao-Min Zhang independently completed literature retrieval and data collection, and statistical analyses were performed by Stata. Individual odds ratio (OR) and 95% confidence interval (CI) were pooled in a random-effects model using the DerSimonian–Laird method. Heterogeneity was evaluated by I² statistic at a significance level of 50%. Publication bias was assessed by Egger’s test.

Results

Eleven articles including 2,074 breast cancer patients and 2,372 controls were summarized. Using the most common allele ε3 as a reference, the ε2 (OR =0.87, 95% CI =0.72–1.05, P=0.154, I²=0.0%) and ε4 (OR =1.07, 95% CI =0.80–1.42, P=0.654, I²=71.8%) alleles were not found to be significantly associated with breast cancer risk in the overall analyses. Subgroup analyses revealed that the comparison of allele ε4 with ε3 was significant in Asians (OR =1.58, 95% CI =1.17–6.32, P=0.003, I²=12.1%) and in studies that used the restriction fragment length polymorphism (RFLP) genotyping method (OR =1.27; 95% CI =1.01–1.61, P=0.045, I²=34.3%), and was marginally significant in hospital-based studies (OR =1.33; 95% CI =0.98–1.79, P=0.065, I²=30.2%), without heterogeneity. Moreover, the presence of the ε2 allele was significantly associated with breast cancer in small studies (total sample size <500) (OR =0.73, 95% CI =0.54–1.00, P=0.052, I²=0.0%) without heterogeneity. The Egger’s test indicated low probabilities of publication bias.

Conclusion

We observed a significant association between APOE gene ε4 allele and breast cancer risk in Asian populations. Moreover, the findings of our subgroup analyses suggest that source of controls, genotyping platform, and sample size might be the potential causes of heterogeneity.

Novel polymorphisms in caspase-8 are associated with breast cancer risk in the California Teachers Study

BACKGROUND

The ability of tamoxifen and raloxifene to decrease breast cancer risk varies among different breast cancer subtypes. It is important to determine one's subtype-specific breast cancer risk when considering chemoprevention. A number of single nucleotide polymorphisms (SNPs), including one in caspase-8 (CASP8), have been previously associated with risk of developing breast cancer. Because caspase-8 is an important protein involved in receptor-mediated apoptosis whose activity is affected by estrogen, we hypothesized that additional SNPs in CASP8 could be associated with breast cancer risk, perhaps in a subtype-specific manner.

METHODS

Twelve tagging SNPs of CASP8 were analyzed in a nested case control study (1,353 cases and 1,384 controls) of non-Hispanic white women participating in the California Teachers Study. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each SNP using all, estrogen receptor (ER)-positive, ER-negative, human epidermal growth factor receptor 2 (HER2)-positive, and HER2-negative breast cancers as separate outcomes.

RESULTS

Several SNPs were associated with all, ER-positive, and HER2-positive breast cancers; however, after correcting for multiple comparisons (i.e., p < 0.0008), only rs2293554 was statistically significantly associated with HER2-positive breast cancer (OR = 1.98, 95% CI 1.34-2.92, uncorrected p = 0.0005).

CONCLUSIONS

While our results for CASP8 SNPs should be validated in other cohorts with subtype-specific information, we conclude that some SNPs in CASP8 are associated with subtype-specific breast cancer risk. This study contributes to our understanding of CASP8 SNPs and breast cancer risk by subtype.

Genomic Biomarkers for Breast Cancer Risk

Clinical risk assessment for cancer predisposition includes a three-generation pedigree and physical examination to identify inherited syndromes. Additionally genetic and genomic biomarkers may identify individuals with a constitutional basis for their disease that may not be evident clinically. Genomic biomarker testing may detect molecular variations in single genes, panels of genes, or entire genomes. The strength of evidence for the association of a genomic biomarker with disease risk may be weak or strong. The factors contributing to clinical validity and utility of genomic biomarkers include functional laboratory analyses and genetic epidemiologic evidence. Genomic biomarkers may be further classified as low, moderate or highly penetrant based on the likelihood of disease. Genomic biomarkers for breast cancer are comprised of rare highly penetrant mutations of genes such as BRCA1 or BRCA2, moderately penetrant mutations of genes such as CHEK2, as well as more common genomic variants, including single nucleotide polymorphisms, associated with modest effect sizes. When applied in the context of appropriate counseling and interpretation, identification of genomic biomarkers of inherited risk for breast cancer may decrease morbidity and mortality, allow for definitive prevention through assisted reproduction, and serve as a guide to targeted therapy .

Novel and known genetic variants for male breast cancer risk at 8q24.21, 9p21.3, 11q13.3 and 14q24.1: results from a multicenter study in Italy

Increasing evidence indicates that common genetic variants may contribute to the heritable risk of breast cancer (BC). In this study, we investigated whether single nucleotide polymorphisms (SNPs), within the 8q24.21 multi-cancer susceptibility region and within BC-associated loci widespread in the genome, may influence the risk of BC in men, and whether they may be associated with specific clinical-pathologic characteristics of male BC (MBC). In the frame of the ongoing Italian Multicenter Study on MBC, we performed a case-control study on 386 MBC cases, including 50 BRCA1/2 mutation carriers, and 1105 healthy male controls, including 197 unaffected BRCA1/2 mutation carriers. All 1491 subjects were genotyped by Sequenom iPLEX technology for a total of 29 susceptibility SNPs. By logistic regression models, we found a significant association with MBC risk for five SNPs: rs1562430 (p=0.002) and rs445114 (p=0.026) both within the 8q24.21 region; rs1011970/9p21.3 (p=0.011), rs614367/11q13.3 (p=0.016) and rs1314913/14q24.1 (p<0.0001). Differences in the distribution of rs614367/11q13.3 genotypes according to oestrogen receptor (ER) status (p=0.006), and of rs1011970/9p21.3 genotypes according to human epidermal growth factor receptor 2 (HER2) status (p=0.002) emerged. Association of rs1011970/9p21.3 risk genotype with HER2+MBC was confirmed by a multivariate analysis. rs1314913/14q24.1 was associated with increased MBC risk in analyses restricted to male BRCA1/2 mutation carriers (p=0.041). In conclusion, we provided the first evidence that the 8q24.21 region is associated with MBC risk. Furthermore, we showed that the SNPs rs1562430/8q24.21 and rs1314913/14q24.1 strongly influence BC risk in men and suggested that the SNP rs1314913/14q24.1 may act as a risk modifier locus in male BRCA1/2 mutation carriers.

Breast cancer risk associated with CHEK2 mutations

Most efforts to identify individuals who have a hereditary predisposition for developing breast cancer had focused on the BRCA1 and BRCA2 genes. Less common susceptibility genes also are associated with increased risk for developing breast cancer, but until recently have often gone undetected. With the advent of next generation sequencing (NGS), many families with suspected hereditary risk are undergoing testing for multiple genes associated with increased cancer risk (Mahon, 2013a). One gene that is commonly included on NGS hereditary breast cancer panels is CHEK2. Increasingly, oncology nurses will encounter patients and families affected with mutations on this gene and need to understand the implications it has for screening and treatment.

Identifying Etiologically Distinct Sub-Types of Cancer: A Demonstration Project Involving Breast Cancer

With the advent of increasingly detailed molecular portraits of tumor specimens, much attention has been directed toward identifying clinically distinct subtypes of cancer. Subtyping of tumors can also be accomplished with the goal of identifying distinct etiologies. We demonstrate the use of new methodologies to identify genes that distinguish etiologically heterogeneous subtypes of breast cancer using data from the case-control Cancer and Steroid Hormone Study. Tumor specimens were evaluated using a breast cancer expression panel of 196 genes. Using a statistical measure that distinguishes the degree of etiologic heterogeneity in tumor subtypes, each gene is ranked on the basis of its ability to distinguish etiologically distinct subtypes. This is accomplished independently using case-control comparisons and by examining the concordance odds ratios in double primaries. The estrogen receptor gene, and others in this pathway with expression levels that correlated strongly with estrogen receptor levels, demonstrate high degrees of etiologic heterogeneity in both methods. Our results are consistent with a growing literature that confirms the distinct etiologies of breast cancers classified on the basis of estrogen receptor expression levels. This proof-of-principle project demonstrates the viability of new strategies to identify genomic features that distinguish subtypes of cancer from an etiologic perspective.

Leveraging Interaction between Genetic Variants and Mammographic Findings for Personalized Breast Cancer Diagnosis

Recent large-scale genome-wide association studies (GWAS) have identified a number of genetic variants associated with breast cancer which showed great potential for clinical translation, especially in breast cancer diagnosis via mammograms. However, the amount of interaction between these genetic variants and mammographic features that can be leveraged for personalized diagnosis remains unknown. Our study utilizes germline genetic variants and mammographic features that we collected in a breast cancer case-control study. By computing the conditional mutual information between the genetic variants and mammographic features given the breast cancer status, we identified six interaction pairs which elevate breast cancer risk and five interaction pairs which reduce breast cancer risk.

Polymorphisms in circadian genes, night work and breast cancer: results from the GENICA study

OBJECTIVES

The role of genetic variants and environmental factors in breast cancer etiology has been intensively studied in the last decades. Gene-environment interactions are now increasingly being investigated to gain more insights into the development of breast cancer, specific subtypes, and therapeutics. Recently, night shift work that involves circadian disruption has gained rising interest as a potential non-genetic breast cancer risk factor. Here, we analyzed genetic polymorphisms in genes of cellular clocks, melatonin biosynthesis and signaling and their association with breast cancer as well as gene-gene and gene-night work interactions in a German case-control study on breast cancer.

METHODS

GENICA is a population-based case-control study on breast cancer conducted in the Greater Region of Bonn. Associations between seven polymorphisms in circadian genes (CLOCK, NPAS2, ARTNL, PER2 and CRY2), genes of melatonin biosynthesis and signaling (AANAT and MTNR1B) and breast cancer were analyzed with conditional logistic regression models, adjusted for potential confounders for 1022 cases and 1014 controls. Detailed shift-work information was documented for 857 breast cancer cases and 892 controls. Gene-gene and gene-shiftwork interactions were analyzed using model-based multifactor dimensionality reduction (mbMDR).

RESULTS

For combined heterozygotes and rare homozygotes a slightly elevated breast cancer risk was found for rs8150 in gene AANAT (OR 1.17; 95% CI 1.01-1.36), and a reduced risk for rs3816358 in gene ARNTL (OR 0.82; 95% CI 0.69-0.97) in the complete study population. In the subgroup of shift workers, rare homozygotes for rs10462028 in the CLOCK gene had an elevated risk of breast cancer (OR for AA vs. GG: 3.53; 95% CI 1.09-11.42). Shift work and CLOCK gene interactions were observed in the two-way interaction analysis. In addition, gene-shiftwork interactions were detected for MTNR1B with NPAS2 and ARNTL.

CONCLUSIONS

In conclusion, the results of our population-based case-control study support a putative role of the CLOCK gene in the development of breast cancer in shift workers. In addition, higher order interaction analyses suggest a potential relevance of MTNR1B with the key transcriptional factor NPAS2 with ARNTL. Hence, in the context of circadian disruption, multivariable models should be preferred that consider a wide range of polymorphisms, e.g. that may influence chronotype or light sensitivity. The investigation of these interactions in larger studies is needed.

The potential application of personalized preventive research

With increases in life expectancy, the focus has shifted to living a healthier, longer life. By concentrating on preventing diseases before occurrence, researchers aim to diminish the increasing gap in medical costs and health inequalities prevalent across many nations. Although we have entered an era of post-genomics, we are still in infancy in terms of personalized preventive research. Personalized preventive research has and will continue to improve with advancements in the use of biomarkers and risk assessment. More evidence based on well-designed epidemiologic studies is required to provide comprehensive preventive medical care based on genetic and non-genetic profile data. The realization of personalized preventive research requires building of evidence through appropriate methodology, verification of results through translational studies as well as development and application of prediction models.

TGFβ induces "BRCAness" and sensitivity to PARP inhibition in breast cancer by regulating DNA-repair genes

Transforming growth factor beta (TGFβ) proteins are multitasking cytokines, in which high levels at tumor sites generally correlate with poor prognosis in human patients with cancer. Previously, it was reported that TGFβ downregulates the expression of ataxia telangiectasia-mutated (ATM) and mutS homolog 2 (MSH2) in breast cancer cells through an miRNA-mediated mechanism. In this study, expression of a panel of DNA-repair genes was examined, identifying breast cancer 1, early onset (BRCA1) as a target downregulated by TGFβ through the miR181 family. Correlations between the expression levels of TGFβ1 and the miR181/BRCA1 axis were observed in primary breast tumor specimens. By downregulating BRCA1, ATM, and MSH2, TGFβ orchestrates DNA damage response in certain breast cancer cells to induce a "BRCAness" phenotype, including impaired DNA-repair efficiency and synthetic lethality to the inhibition of poly (ADP-ribose) polymerase (PARP). Xenograft tumors with active TGFβ signaling exhibited resistance to the DNA-damaging agent doxorubicin but increased sensitivity to the PARP inhibitor ABT-888. Combination of doxorubicin with ABT-888 significantly improved the treatment efficacy in TGFβ-active tumors. Thus, TGFβ can induce "BRCAness" in certain breast cancers carrying wild-type BRCA genes and enhance the responsiveness to PARP inhibition, and the molecular mechanism behind this is characterized.

IMPLICATIONS

These findings enable better selection of patients with sporadic breast cancer for PARP interventions, which have exhibited beneficial effects in patients carrying BRCA mutations.

Breast cancer susceptibility variants and mammographic density phenotypes in norwegian postmenopausal women

BACKGROUND

Mammographic density (MD) is one of the strongest known breast cancer risk factors. Twin studies have suggested that a large part of the variation in MD is genetically determined. We hypothesized that breast cancer susceptibility variants may affect MD, and that their effects may be modified by nongenetic factors.

METHODS

We assessed MD, using a computer-assisted method, on 2,348 postmenopausal Caucasian women (50-69 years) who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004 or 2006-07. We used linear regression (additive models) to determine the association between each SNP and MD, adjusting for age, body mass index (BMI), and study. We evaluated MD associations with 17 established breast cancer SNPs, overall, and by strata defined by non-genetic factors.

RESULTS

Two variants, 6q25.1-rs9383938 and TXNRD2-rs8141691, were statistically significantly associated with percent MD (P = 0.019 and 0.03, respectively), with the 6q25.1-rs9383938 association being consistent with the SNP effect on breast cancer risk. The effect of 6q25.1-rs3734805 on percent MD varied between parous and nulliparous women (Pinteraction = 0.02), whereas the effects of 9q31.2-rs865686 and MRPS30:FGF10-rs4415084 differed across strata of BMI (Pinteraction = 0.01 and 0.005, respectively). There was no evidence of effect modification by estrogen and progestin therapy use or alcohol consumption.

CONCLUSION

This study provides novel evidence of shared genetic risk factors between MD and breast cancer and of possible MD genetic-environmental interactions.

IMPACT

Although the results may be chance findings, they nevertheless highlight the need to investigate interactions with nongenetic factors in studies on the genetics of MD.

Two decades after BRCA: setting paradigms in personalized cancer care and prevention

The cloning of the breast cancer susceptibility genes BRCA1 and BRCA2 nearly two decades ago helped set in motion an avalanche of research exploring how genomic information can be optimally applied to identify and clinically care for individuals with a high risk of developing cancer. Genetic testing for mutations in BRCA1, BRCA2, and other breast cancer susceptibility genes has since proved to be a valuable tool for determining eligibility for enhanced screening and prevention strategies, as well as for identifying patients most likely to benefit from a targeted therapy. Here, we discuss the landscape of inherited mutations and sequence variants in BRCA1 and BRCA2, the complexities of determining disease risk when the pathogenicity of sequence variants is uncertain, and current strategies for clinical management of women who carry BRCA1/2 mutations.

Opportunities and challenges of next-generation DNA sequencing for breast units

BACKGROUND

The aim of this review is to introduce the topic of next-generation DNA sequencing, a new technology that is being introduced into clinical practice, and to explain the potential impact for breast cancer surgeons and the wider breast cancer multidisciplinary team.

METHODS

The PubMed database was used to identify relevant studies relating to breast cancer genetics. This evidence was then used to provide context and background information to demonstrate how next-generation sequencing (NGS) might change breast cancer practice.

RESULTS

With NGS, breast cancer clinicians will know whether their patients carry high-risk mutations in genes, such as BRCA1 or BRCA2, before the start of treatment. This could alter treatment decisions; for instance, more women might opt for mastectomy instead of breast-conserving surgery, or for bilateral rather than unilateral surgery.

CONCLUSION

The introduction of NGS will have a significant impact on breast cancer services in the near future. Speed of testing will improve in regions of the world where NGS is adopted in place of conventional sequencing, and, as costs decrease, genetic testing will also become accessible and realistic in less well funded health economies. This will create opportunities to improve patient treatment and challenges for the breast cancer multidisciplinary team.