Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer

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.

Update Breast Cancer 2018 (Part 4) - Genomics, Individualized Medicine and Immune Therapies - in the Middle of a New Era: Treatment Strategies for Advanced Breast Cancer

New therapeutic developments aimed at treating women with advanced breast cancer currently focus both on identifying patients eligible for targeted therapeutic concepts and on the continuing development of immune therapies. The data on CDK4/6 inhibitors are now complete and consistent in this class of substances (palbociclib, ribociclib and abemaciclib). Further pathways under investigation are PI3K and AKT signalling pathways along with diverse approaches to their inhibition. Initial study results were also presented recently on both mechanisms of action. Insights into the PARP inhibitors, moreover, are increasing; studies in this respect are also examining in which population they can be used most effectively. This review offers a summary of the recent studies and an outline of the latest developments.

Epidemiology of Moderate Alcohol Consumption and Breast Cancer: Association or Causation?

Epidemiological studies have been used to show associations between modifiable lifestyle habits and the incidence of breast cancer. Among such factors, a history of alcohol use has been reported in multiple studies and meta-analyses over the past decades. However, associative epidemiological studies that were interpreted as evidence that even moderate alcohol consumption increases breast cancer incidence have been controversial. In this review, we consider the literature on the relationship between moderate or heavy alcohol use, both in possible biological mechanisms and in variations in susceptibility due to genetic or epigenetic factors. We argue that there is a need to incorporate additional approaches to move beyond the associations that are reported in traditional epidemiological analyses and incorporate information on molecular pathologic signatures as a requirement to posit causal inferences. In particular, we point to the efforts of the transdisciplinary field of molecular pathological epidemiology (MPE) to evaluate possible causal relationships, if any, of alcohol consumption and breast cancer. A wider application of the principles of MPE to this field would constitute a giant step that could enhance our understanding of breast cancer and multiple modifiable risk factors, a step that would be particularly suited to the era of "personalized medicine".

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.

Clinical significance of ADAM29 promoting the invasion and growth of gastric cancer cells in vitro

ADAM metallopeptidase domain 29 (ADAM29) belongs to the ADAM family, is a type I integral membrane protein and secrets a glycoprotein that mediates cell-cell and cell-matrix interaction. Aberrant expression of ADAM29 is involved in a number of physiological processes diversification. The purpose of the present study was to investigate the expression and biological effect of ADAM29 in human gastric cancer (GC) specimens and cell lines in vitro. The expression of ADAM29 was examined in 83 GC samples and 25 adjacent normal gastric tissues using quantitative reverse transcriptase-quantitative polymerase chain reaction and immunohistochemistry. The association between ADAM29 expression and cellular function of GC cells was assessed in vitro. The ADAM29 mRNA levels were significantly elevated in GC tissues compared with paracancerous tissues. Increased levels of ADAM29 were associated with high-grade staging and high Tumor-Node-Metastasis stages. Kaplan-Meier survival curves demonstrated that patients with GC and low ADAM29 transcript levels exhibited longer overall survival (OS) (P<0.01) and progression-free survival (PFS) time (P<0.01) compared with patients with high ADAM29 expression levels. ADAM29 significantly promoted the proliferation, migration and invasion of GC cells in vitro when overexpressed in MGC803 cells and knocked down in AGS cells. ADAM29 was increased in GC and the elevated expression of ADAM29 was associated with a poor survival rate of patients. ADAM29 may become a prognostic factor and therapeutic candidate for human GC.

A Comprehensive cis-eQTL Analysis Revealed Target Genes in Breast Cancer Susceptibility Loci Identified in Genome-wide Association Studies

Genome-wide association studies (GWASs) have identified more than 150 common genetic loci for breast cancer risk. However, the target genes and underlying mechanisms remain largely unknown. We conducted a cis-expression quantitative trait loci (cis-eQTL) analysis using normal or tumor breast transcriptome data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project. We identified a total of 101 genes for 51 lead variants after combing the results of a meta-analysis of METABRIC and TCGA, and the results from GTEx at a Benjamini-Hochberg (BH)-adjusted p < 0.05. Using luciferase reporter assays in both estrogen-receptor positive (ER⁺) and negative (ER^-) cell lines, we showed that alternative alleles of potential functional single-nucleotide polymorphisms (SNPs), rs11552449 (DCLRE1B), rs7257932 (SSBP4), rs3747479 (MRPS30), rs2236007 (PAX9), and rs73134739 (ATG10), could significantly change promoter activities of their target genes compared to reference alleles. Furthermore, we performed in vitro assays in breast cancer cell lines, and our results indicated that DCLRE1B, MRPS30, and ATG10 played a vital role in breast tumorigenesis via certain disruption of cell behaviors. Our findings revealed potential target genes for associations of genetic susceptibility risk loci and provided underlying mechanisms for a better understanding of the pathogenesis of breast cancer.

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.

Breast cancer family history and allele-specific DNA methylation in the legacy girls study

Family history, a well-established risk factor for breast cancer, can have both genetic and environmental contributions. Shared environment in families as well as epigenetic changes that also may be influenced by shared genetics and environment may also explain familial clustering of cancers. Epigenetic regulation, such as DNA methylation, can change the activity of a DNA segment without a change in the sequence; environmental exposures experienced across the life course can induce such changes. However, genetic-epigenetic interactions, detected as methylation quantitative trait loci (mQTLs; a.k.a. meQTLs) and haplotype-dependent allele-specific methylation (hap-ASM), can also contribute to inter-individual differences in DNA methylation patterns. To identify differentially methylated regions (DMRs) associated with breast cancer susceptibility, we examined differences in white blood cell DNA methylation in 29 candidate genes in 426 girls (ages 6-13 years) from the LEGACY Girls Study, 239 with and 187 without a breast cancer family history (BCFH). We measured methylation by targeted massively parallel bisulfite sequencing (bis-seq) and observed BCFH DMRs in two genes: ESR1 (Δ4.9%, P = 0.003) and SEC16B (Δ3.6%, P = 0.026), each of which has been previously implicated in breast cancer susceptibility and pubertal development. These DMRs showed high inter-individual variability in methylation, suggesting the presence of mQTLs/hap-ASM. Using single nucleotide polymorphisms data in the bis-seq amplicon, we found strong hap-ASM in SEC16B (with allele specific-differences ranging from 42% to 74%). These findings suggest that differential methylation in genes relevant to breast cancer susceptibility may be present early in life, and that inherited genetic factors underlie some of these epigenetic differences.

Common Genetic Variation and Breast Cancer Risk-Past, Present, and Future

Breast cancer is the most common cancer among women in the United States, with up to 30% of those diagnosed displaying a family history of breast cancer. To date, 18% of the familial risk of breast cancer can be explained by SNPs. This review summarizes the discovery of risk-associated SNPs using candidate gene and genome-wide association studies (GWAS), including discovery and replication in large collaborative efforts such as The Collaborative Oncologic Gene-environment Study and OncoArray. We discuss the evolution of GWAS studies, efforts to discover additional SNPs, and methods for identifying causal variants. We summarize findings associated with overall breast cancer, pathologic subtypes, and mutation carriers (BRCA1, BRCA2, and CHEK2). In addition, we summarize the development of polygenic risk scores (PRS) using the risk-associated SNPs and show how PRS can contribute to estimation of individual risks for developing breast cancer. Cancer Epidemiol Biomarkers Prev; 27(4); 380-94. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Update Breast Cancer 2018 (Part 2) - Advanced Breast Cancer, Quality of Life and Prevention

The treatment of metastatic breast cancer has become more complicated due to increasing numbers of new therapies which need to be tested. Therapies are now being developed to treat special clinical or molecular subgroups. Even though intrinsic molecular subtypes play a major role, more and more new therapies for subgroups and histological subtypes are being developed, such as the use of PARP inhibitors to treat patients with BRCA mutations (breast and ovarian cancer). Supportive therapies are also evolving, allowing problems such as alopecia or nausea and vomiting to be treated more effectively. Treatment-related side effects have a direct impact on the prognosis of patients with metastatic breast cancer, and supportive therapy can improve compliance. Digital tools could be useful to establish better patient management systems. This overview provides an insight into recent trials and how the findings could affect routine treatment. Current aspects of breast cancer prevention are also presented.

GWAS in the SIGNAL/PHARE clinical cohort restricts the association between the FGFR2 locus and estrogen receptor status to HER2-negative breast cancer patients

Genetic polymorphisms are associated with breast cancer risk. Clinical and epidemiological observations suggest that clinical characteristics of breast cancer, such as estrogen receptor or HER2 status, are also influenced by hereditary factors. To identify genetic variants associated with pathological characteristics of breast cancer patients, a Genome Wide Association Study was performed in a cohort of 9365 women from the French nationwide SIGNAL/PHARE studies (NCT00381901/RECF1098). Strong association between the FGFR2 locus and ER status of breast cancer patients was observed (ER-positive n=6211, ER-negative n=2516; rs3135718 OR=1.34 p=5.46×10-12). This association was limited to patients with HER2-negative tumors (ER-positive n=4267, ER-negative n=1185; rs3135724 OR=1.85 p=1.16×10-11). The FGFR2 locus is known to be associated with breast cancer risk. This study provides sound evidence for an association between variants in the FGFR2 locus and ER status among breast cancer patients, particularly among patients with HER2-negative disease. This refinement of the association between FGFR2 variants and ER-status to HER2-negative disease provides novel insight to potential biological and clinical influence of genetic polymorphisms on breast tumors.

The breast cancer susceptibility-related polymorphisms at the TOX3/LOC643714 locus associated with lung cancer risk in a Han Chinese population

It has been well established that besides environmental factors, genetic factors are also associated with lung cancer risk. However, to date, the prior identified genetic variants and loci only explain a small fraction of the familial risk of lung cancer. Hence it is vital to investigate the remaining missing heritability to understand the development and process of lung cancer. In the study, to test our hypothesis that the previously identified breast cancer risk-associated genetic polymorphisms at the TOX3/LOC643714 locus might contribute to lung cancer risk, 16 SNPs at the TOX3/LOC643714 locus were evaluated in a Han Chinese population based on a case-control study. Pearson's chi-square test or Fisher's exact test revealed that rs9933638, rs12443621, and rs3104746 were significantly associated with lung cancer risk (P < 0.001, P < 0.001, and P = 0.005, respectively). Logistic regression analyses displayed that lung cancer risk of individuals with rs9933638(GG+GA) were 1.89 times higher than that of rs9933638AA carriers (OR = 1.893, 95% CI = 1.308-2.741, P = 0.001). Similar findings were manifested for rs12443621 (OR = 1.824, 95% CI = 1.272-2.616, P = 0.001, rs12443621(GG+GA) carriers vs. rs12443621AA carriers) and rs3104746 (OR = 1.665, 95% CI = 1.243-2.230, P = 0.001, rs3104746TT carriers vs. rs3104746(TA+AA) carriers). The study discovered for the first time that three SNPs (rs9933638, rs12443621, and rs3104746) at the TOX3/LOC643714 locus contributed to lung cancer risk, providing new evidences that lung cancer and breast cancer are linked at the molecular and genetic level to a certain extent.

The associations between MDM4 gene polymorphisms and cancer risk

Considerable studies have investigated the associations between MDM4 gene polymorphisms and cancer risk recently, but with contradictory results. The aim of this meta-analysis was to evaluate the associations between MDM4 gene polymorphisms and cancer risk. Relevant studies were identified by a systematic search of PubMed, Embase, and CNKI databases. Crude odds ratios (ORs) and 95% confidence intervals (CIs) were used to describe the strength of the associations. Fifty-six studies published in 11 publications involving 18,910 cases and 51,609 controls were included in this meta-analysis. Five MDM4 gene polymorphisms were evaluated: rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576. Our analyses suggested that the rs4245739 polymorphism was significantly associated with overall cancer risk. Furthermore, stratification analyses of ethnicity indicated that rs4245739 decreased the risk of cancer among the Asian population, and stratification analyses of smoking status indicated that rs4245739 decreased the risk of cancer among nonsmokers. However, stratification analyses of cancer type and sex suggested that rs4245739 was not related to cancer risk. There were no associations of rs1563828, rs11801299, rs10900598, or rs1380576 with overall cancer risk. In conclusion, our analyses indicated that rs4245739 polymorphism in the MDM4 gene may play an important role in the etiology of cancer.

Women's preferences, willingness-to-pay, and predicted uptake for single-nucleotide polymorphism gene testing to guide personalized breast cancer screening strategies: a discrete choice experiment

BACKGROUND

Single-nucleotide polymorphism (SNP) gene test is a potential tool for improving the accuracy of breast cancer risk prediction. We seek to measure women's preferences and marginal willingness-to-pay (mWTP) for this new technology.

MATERIALS AND METHODS

We administered a discrete choice experiment (DCE) to English-speaking Singaporean women aged 40-69 years without any history of breast cancer, enrolled via door-to-door recruitment with quota sampling by age and ethnicity. DCE attributes comprise: 1) sample type (buccal swab and dried blood spot), 2) person conducting pretest discussion (specialist doctor, non-specialist doctor, and nurse educator), 3) test location (private family clinic, public primary-care clinic, and hospital), and 4) out-of-pocket cost (S$50, S$175, and S$300). Mixed logit model was used to estimate the effect of attribute levels on women's preferences and mWTP. Interactions between significant attributes and respondent characteristics were investigated. Predicted uptake rates for various gene testing scenarios were studied.

RESULTS

A total of 300 women aged 52.6±7.6 years completed the survey (100 Chinese, Malay, and Indian women, respectively). Sample type (P=0.046), person conducting pretest discussion, and out-of-pocket cost (P<0.001) are significantly associated with going for SNP gene testing. Women with higher income and education levels are more willing to pay higher prices for the test. Preferences in terms of mWTP across ethnic groups appear similar, but Chinese women have greater preference heterogeneity for the attributes. Predicted uptake for a feasible scenario consisting of buccal swab, pretest discussion with nurse educator at the hospital costing S$50 is 60.5%. Only 3.3% of women always opted out of the SNP gene test in real life. Reasons include high cost, poor awareness, and indifference toward test results.

CONCLUSION

SNP gene testing may be tailored according to individual preferences to encourage uptake. Future research should focus on outcomes and cost-effectiveness of personalized breast cancer screening using SNP gene testing.

Update Breast Cancer 2017 - Implementation of Novel Therapies

In recent years, numerous new therapy options for patients with breast cancer have been developed in clinical studies, with some options already approved for routine treatment. As the speed at which innovations are introduced increases, the importance of conferences also increases, as conferences are where the data underpinning new therapies are usually presented for the first time. This review looks at publications of the ASCO (American Society of Clinical Oncology) and ESMO (European Society of Medical Oncology) conferences in 2017, summarizes them and evaluates them in the context of existing data. The focus is on new insights for neoadjuvant therapy and new treatment options in the metastatic setting, such as the use of CDK4/6 inhibitors or PARP inhibitors. The first results of treatments with checkpoint inhibitors are presented. With the patent expiry of trastuzumab, a number of study results for trastuzumab biosimilars have also been published. The digitization of patient care provides the first results on quality of life and prognosis of patients with advanced cancer. Digital communications between patients and physicians are being evaluated in several studies in Germany. As the discussion about patient-relevant endpoints for patients in the metastatic setting continues, overall survival rates from studies of big endocrine-based therapies are urgently needed. Preliminary analyses of small study cohorts offer initial insights. In the context of improving patient care, in the coming years, questions will center on which patients particularly benefit from certain therapies and which patients need particular protection from specific side effects. Questions about these predictors are raised in many scientific projects as attention increasingly focuses on this topic.

Analysis of Tumor Biology to Advance Cancer Health Disparity Research

Cancer mortality rates in the United States continue to decline. Reductions in tobacco use, uptake of preventive measures, adoption of early detection methods, and better treatments have resulted in improved cancer outcomes for men and women. Despite this progress, some population groups continue to experience an excessive cancer burden when compared with other population groups. One of the most prominent cancer health disparities exists in prostate cancer. Prostate cancer mortality rates are highest among men of African ancestry when compared with other men, both in the United States and globally. This disparity and other cancer health disparities are largely explained by differences in access to health care, diet, lifestyle, cultural barriers, and disparate exposures to carcinogens and pathogens. Dietary and lifestyle factors, pathogens, and ancestry-related factors can modify tumor biology and induce a more aggressive disease. There are numerous examples of how environmental exposures, like tobacco, chronic stress, or dietary factors, induce an adverse tumor biology, leading to a more aggressive disease and decreased patient survival. Because of population differences in the exposure to these risk factors, they can be the cause of cancer disparities. In this review, we will summarize recent advances in our understanding of prostate and breast cancer disparities in the United States and discuss how the analysis of tumor biology can advance health disparity research.

Lowly methylated region analysis identifies EBF1 as a potential epigenetic modifier in breast cancer

Breast cancer (BC) encompasses heterogeneous pathologies with different subtypes exhibiting distinct molecular changes, including those related to DNA methylation. However, the role of these changes in mediating BC heterogeneity is poorly understood. Lowly methylated regions (LMRs), non-CpG island loci that usually contain transcription factor (TF) binding sites, have been suggested to act as regulatory elements that define cellular identity. In this study, we aimed to identify the key subtype-specific TFs that may lead to LMR generation and shape the BC methylome and transcription program. We initially used whole-genome bisulfite sequencing (WGBS) data available at The Cancer Genome Atlas (TCGA) portal to identify subtype-specific LMRs. Differentially methylated regions (DMRs) within the BC PAM50 subtype-specific LMRs were selected by comparing tumors and normal tissues in a larger TCGA cohort assessed by HumanMethylation450 BeadChip (450K) arrays and TF enrichment analyses were performed. To assess the impact of LMRs on gene expression, TCGA RNA sequencing data were downloaded and Pearson correlations between methylation levels of loci presenting subtype-specific TF motifs and expression of the nearest genes were calculated. WGBS methylome data revealed a large number of LMRs for each of the BC subtypes. Analysis of these LMRs in the 450K datasets available for a larger sample set identified 7,765, 5,657, and 19 differentially methylated positions (DMPs) between normal adjacent tissues and tumor tissues from basal, luminal, and HER2-enriched subtypes, respectively. Unsupervised clustering showed that the discriminatory power of the top DMPs was remarkably strong for basal BC. Interestingly, in this particular subtype, we found 4,409 differentially hypomethylated positions grouped into 1,185 DMRs with a strong enrichment for the early B-cell factor 1 (EBF1) motifs. The methylation levels of the DMRs containing EBF1 motifs showed a strong negative correlation with the expression of 719 nearby genes, including BTS2 and CD74, two oncogenes known to be specific for basal BC subtype and for poor outcome. This study identifies LMRs specific to the three main BC subtypes and reveals EBF1 as a potentially important regulator of BC subtype-specific methylation and gene expression program.

Contribution of germline deleterious variants in the RAD51 paralogs to breast and ovarian cancers

RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) have recently been involved in breast and ovarian cancer predisposition: RAD51B, RAD51C, and RAD51D in ovarian cancer, RAD51B and XRCC2 in breast cancer. The aim of this study was to estimate the contribution of deleterious variants in the five RAD51 paralogs to breast and ovarian cancers. The five RAD51 paralog genes were analyzed by next-generation sequencing technologies in germline DNA from 2649 consecutive patients diagnosed with breast and/or ovarian cancer. Twenty-one different deleterious variants were identified in the RAD51 paralogs in 30 patients: RAD51B (n = 4), RAD51C (n = 12), RAD51D (n = 7), XRCC2 (n = 2), and XRCC3 (n = 5). The overall deleterious variant rate was 1.13% (95% confidence interval (CI): 0.72-1.55%) (30/2649), including 15 variants in breast cancer only cases (15/2063; 0.73% (95% CI: 0.34-1.11%)) and 15 variants in cases with at least one ovarian cancer (15/570; 2.63% (95% CI: 1.24-4.02%)). This study is the first evaluation of the five RAD51 paralogs in breast and ovarian cancer predisposition and it demonstrates that deleterious variants can be present in breast cancer only cases. Moreover, this is the first time that XRCC3 deleterious variants have been identified in breast and ovarian cancer cases.

Cumulative evidence for relationships between multiple variants in the VTI1A and TCF7L2 genes and cancer incidence

Genetic studies have linked the VTI1A-TCF7L2 region with risk of multiple cancers. However, findings from these studies were generally inconclusive. We aimed to provide a synopsis of current understanding of associations between variants in the VTI1A-TCF7L2 region and cancer susceptibility. We conducted a comprehensive research synopsis and meta-analysis to evaluate associations between 17 variants in this region and risk of seven cancers using data from 32 eligible articles totaling 224,656 cancer cases and 324,845 controls. We graded cumulative evidence of significant associations using Venice criteria and false-positive report probability tests. We also conducted analyses to evaluate potential function of these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project. Eight variants showed a nominally significant association with risk of individual cancer (p < 0.05). Cumulative epidemiological evidence of an association was graded as strong for rs7903146 [odds ratio (OR) = 1.05, p = 4.13 × 10^-5 ] and rs7904519 (OR = 1.07, p = 2.02 × 10^-14 ) in breast cancer, rs11196172 (OR = 1.11, p = 2.22 × 10^-16 ), rs12241008 (OR = 1.13, p = 1.36 × 10^-10 ) and rs10506868 (OR = 1.10, p = 3.98 × 10^-9 ) in colorectal cancer, rs7086803 in lung cancer (OR = 1.30, p = 3.54 × 10^-18 ) and rs11196067 (OR = 1.18, p = 3.59 × 10^-13 ) in glioma, moderate for rs12255372 (OR = 1.12, p = 2.52 × 10^-4 ) in breast cancer and weak for rs7903146 (OR = 1.11, p = 0.007) in colorectal cancer. Data from ENCODE suggested that seven variants with strong evidence and other correlated variants might fall within putative functional regions. Collectively, our study provides summary evidence that common variants in the VTI1A and TCF7L2 genes are associated with risk of breast, colorectal, lung cancer and glioma and highlights the significant role of the VTI1A-TCF7L2 region in the pathogenesis of human cancers.

Rethinking ovarian cancer genomics: where genome-wide association studies stand?

Genome-wide association studies (GWAS) allow the finding of genetic variants associated with several traits. Regarding ovarian cancer (OC), 15 GWAS have been conducted since 2009, with the discovery of 49 SNPs associated with disease susceptibility and 46 with impact in the clinical outcome of patients (p < 5.00 × 10-2). Among them, 14 variants reached the genome-wide significance (p < 5.00 × 10−8). Despite the results obtained, they should be validated in independent sets. So far, five validation studies have been conducted which could confirm the association of 12 OC susceptibility SNPs. Consequently, post-GWAS studies are crucial unravel the biological plausibility of GWAS’ findings and the allelic spectrum of OC.

An unbiased in vivo functional genomics screening approach in mice identifies novel tumor cell-based regulators of immune rejection

The clinical successes of immune checkpoint therapies for cancer make it important to identify mechanisms of resistance to anti-tumor immune responses. Numerous resistance mechanisms have been identified employing studies of single genes or pathways, thereby parsing the tumor microenvironment complexity into tractable pieces. However, this limits the potential for novel gene discovery to in vivo immune attack. To address this challenge, we developed an unbiased in vivo genome-wide RNAi screening platform that leverages host immune selection in strains of immune-competent and immunodeficient mice to select for tumor cell-based genes that regulate in vivo sensitivity to immune attack. Utilizing this approach in a syngeneic triple-negative breast cancer (TNBC) model, we identified 709 genes that selectively regulated adaptive anti-tumor immunity and focused on five genes (CD47, TGFβ1, Sgpl1, Tex9 and Pex14) with the greatest impact. We validated the mechanisms that underlie the immune-related effects of expression of these genes in different TNBC lines, as well as tandem synergistic interactions. Furthermore, we demonstrate the impact of different genes with previously unknown immune functions (Tex9 and Pex14) on anti-tumor immunity. Thus, this innovative approach has utility in identifying unknown tumor-specific regulators of immune recognition in multiple settings to reveal novel targets for future immunotherapies.

RNA binding protein RALY promotes Protein Arginine Methyltransferase 1 alternatively spliced isoform v2 relative expression and metastatic potential in breast cancer cells

Aberrant expression of Protein Arginine Methyltransferases (PRMTs) has been observed in several cancer types, including breast cancer. We previously reported that the PRMT1v2 isoform, which is generated through inclusion of alternative exon 2, is overexpressed in breast cancer cells and promotes their invasiveness. However, the precise mechanism by which expression of this isoform is controlled and how it is dysregulated in breast cancer remains unknown. Using a custom RNA interference-based screen, we identified several RNA binding proteins (RBP) which, when knocked down, altered the relative abundance of the alternatively spliced PRMT1v2 isoform. Amongst the top hits were SNW Domain containing 1 (SNW1) and RBP-associated with lethal yellow mutation (RALY), which both associated with the PRMT1 pre-mRNA and upon depletion caused an increase or decrease in the relative abundance of PRMT1v2 isoform mRNA and protein. Most importantly, a significant decrease in invasion was observed upon RALY knockdown in aggressive breast cancer cells, consistent with targeting PRMT1v2 directly, and this effect was rescued by the exogenous re-expression of PRMT1v2. We show that SNW1 expression is decreased, while RALY expression is increased in breast cancer cells and tumours, which correlates with decreased patient survival. This work revealed crucial insight into the mechanisms regulating the expression of the PRMT1 alternatively spliced isoform v2 and its dysregulation in breast cancer. It also provides proof-of-concept support for the development of therapeutic strategies where regulators of PRMT1 exon 2 alternative splicing are targeted as an approach to selectively reduce PRMT1v2 levels and metastasis in breast cancer.

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods

INTRODUCTION

Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients.

METHODS

This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation.

RESULTS

The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics.

CONCLUSION

Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

Common genetic variation drives molecular heterogeneity in human iPSCs

Technology utilizing human induced pluripotent stem cells (iPS cells) has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterization of many existing iPS cell lines limits their potential use for research and therapy. Here we describe the systematic generation, genotyping and phenotyping of 711 iPS cell lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative. Our study outlines the major sources of genetic and phenotypic variation in iPS cells and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPS cell phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of genomic copy-number alterations that are repeatedly observed in iPS cells. In addition, we present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells.

Assessment of Breast Cancer Risk Factors Reveals Subtype Heterogeneity

Subtype heterogeneity for breast cancer risk factors has been suspected, potentially reflecting etiologic differences and implicating risk prediction. However, reports are conflicting regarding the presence of heterogeneity for many exposures. To examine subtype heterogeneity across known breast cancer risk factors, we conducted a case-control analysis of 2,632 breast cancers and 15,945 controls in Sweden. Molecular subtype was predicted from pathology record-derived IHC markers by a classifier trained on PAM50 subtyping. Multinomial logistic regression estimated separate ORs for each subtype by the exposures parity, age at first birth, breastfeeding, menarche, hormone replacement therapy use, somatotype at age 18, benign breast disease, mammographic density, polygenic risk score, family history of breast cancer, and BRCA mutations. We found clear subtype heterogeneity for genetic factors and breastfeeding. Polygenic risk score was associated with all subtypes except for the basal-like (P_{heterogeneity} < 0.0001). "Never breastfeeding" was associated with increased risk of basal-like subtype [OR 4.17; 95% confidence interval (CI) 1.89-9.21] compared with both nulliparity (reference) and breastfeeding. Breastfeeding was not associated with risk of HER2-overexpressing type, but protective for all other subtypes. The observed heterogeneity in risk of distinct breast cancer subtypes for germline variants supports heterogeneity in etiology and has implications for their use in risk prediction. The association between basal-like subtype and breastfeeding merits more research into potential causal mechanisms and confounders. Cancer Res; 77(13); 3708-17. ©2017 AACR.

Cis-eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk

Breast cancer is the most common solid organ malignancy and the most frequent cause of cancer death among women worldwide. Previous research has yielded insights into its genetic etiology, but there remains a gap in the understanding of genetic factors that contribute to risk, and particularly in the biological mechanisms by which genetic variation modulates risk. The National Cancer Institute's "Up for a Challenge" (U4C) competition provided an opportunity to further elucidate the genetic basis of the disease. Our group leveraged the seven datasets made available by the U4C organizers and data from the publicly available UK Biobank cohort to examine associations between imputed gene expression and breast cancer risk. In particular, we used reference datasets describing the breast tissue and whole blood transcriptomes to impute expression levels in breast cancer cases and controls. In trans-ethnic meta-analyses of U4C and UK Biobank data, we found significant associations between breast cancer risk and the expression of RCCD1 (joint p-value: 3.6x10-06) and DHODH (p-value: 7.1x10-06) in breast tissue, as well as a suggestive association for ANKLE1 (p-value: 9.3x10-05). Expression of RCCD1 in whole blood was also suggestively associated with disease risk (p-value: 1.2x10-05), as were expression of ACAP1 (p-value: 1.9x10-05) and LRRC25 (p-value: 5.2x10-05). While genome-wide association studies (GWAS) have implicated RCCD1 and ANKLE1 in breast cancer risk, they have not identified the remaining three genes. Among the genetic variants that contributed to the predicted expression of the five genes, we found 23 nominally (p-value < 0.05) associated with breast cancer risk, among which 15 are not in high linkage disequilibrium with risk variants previously identified by GWAS. In summary, we used a transcriptome-based approach to investigate the genetic underpinnings of breast carcinogenesis. This approach provided an avenue for deciphering the functional relevance of genes and genetic variants involved in breast cancer.

The most important questions in cancer research and clinical oncology : Question 1. Could the vertical transmission of human papilloma virus (HPV) infection account for the cause, characteristics, and epidemiology of HPV-positive oropharyngeal carcinoma, non-smoking East Asian female lung adenocarcinoma, and/or East Asian triple-negative breast carcinoma?

Specific research foci: (1) Mouse models of gamma-herpes virus-68 (γHV-68) and polyomavirus (PyV) infections during neonatal versus adult life. (2) For human papilloma virus (HPV)-positive oropharyngeal carcinoma (OPC)—(a) Asking the question: Is oral sex a powerful carcinogen? (b) Examining the evidence for the vertical transmission of HPV infection. (c) Examining the relationship between HPV and Epstein–Barr virus (EBV) infections and nasopharyngeal cancer (NPC) in West European, East European, and East Asian countries. (d) Examining the association between HPV-positive OPC and human leukocyte antigen (HLA). (3) For non-smoking East Asian female lung adenocarcinoma—(a) Examining the incidence trends of HPV-positive OPC and female lung adenocarcinoma according to birth cohorts. (b) Examining the association between female lung adenocarcinoma and HPV. (c) Examining the associations of lung adenocarcinoma with immune modulating factors. (4) For triple-negative breast carcinoma (TNBC) in East Asians—(a) Examining the association between TNBC and HPV. (b) Examining the unique epidemiological characteristics of patients with TNBC. A summary “epidemiological” model tying some of these findings together.

Previous GWAS hits in relation to young-onset breast cancer

PURPOSE

Genome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered.

METHODS

Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects.

RESULTS

Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR = 1.39; p = 7.0 × 10-6), rs12662670-G (ESR1, RR = 1.56; p = 5.7 × 10-4), rs2981579-A (FGFR2, RR = 1.24; p = 0.002), and rs999737-G (RAD51B, RR = 1.37; p = 0.003). No maternally mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p = 2.2 × 10-7) and consistent with a multiplicative joint effect (multiplicative-fit p = 0.27). With the multiplicative formulation, the case sister's genetic risk score exceeded that of her unaffected sister in 59% of families.

CONCLUSIONS

The results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.

Trans-ethnic follow-up of breast cancer GWAS hits using the preferential linkage disequilibrium approach

Leveraging population-distinct linkage equilibrium (LD) patterns, trans-ethnic follow-up of variants discovered from genome-wide association studies (GWAS) has proved to be useful in facilitating the identification of bona fide causal variants. We previously developed the preferential LD approach, a novel method that successfully identified causal variants driving the GWAS signals within European-descent populations even when the causal variants were only weakly linked with the GWAS-discovered variants. To evaluate the performance of our approach in a trans-ethnic setting, we applied it to follow up breast cancer GWAS hits identified mostly from populations of European ancestry in African Americans (AA). We evaluated 74 breast cancer GWAS variants in 8,315 AA women from the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Only 27% of them were associated with breast cancer risk at significance level α=0.05, suggesting race-specificity of the identified breast cancer risk loci. We followed up on those replicated GWAS hits in the AMBER consortium utilizing the preferential LD approach, to search for causal variants or better breast cancer markers from the 1000 Genomes variant catalog. Our approach identified stronger breast cancer markers for 80% of the GWAS hits with at least nominal breast cancer association, and in 81% of these cases, the marker identified was among the top 10 of all 1000 Genomes variants in the corresponding locus. The results support trans-ethnic application of the preferential LD approach in search for candidate causal variants, and may have implications for future genetic research of breast cancer in AA women.

Association between breast cancer genetic susceptibility variants and terminal duct lobular unit involution of the breast

Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome-wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.

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.

Breast cancer risk prediction using a clinical risk model and polygenic risk score

Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome-wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95 % CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95 % CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95 % CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18 % of cases as high-risk (5-year risk ≥3 %), compared with 7 % using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.

Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.

Breast Cancer: A Molecular and Redox Snapshot

SIGNIFICANCE

Breast cancer is a unique disease characterized by heterogeneous cell populations causing roadblocks in therapeutic medicine, owing to its complex etiology and primeval understanding of the biology behind its genesis, progression, and sustenance. Globocan statistics indicate over 1.7 million new breast cancer diagnoses in 2012, accounting for 25% of all cancer morbidities.

RECENT ADVANCES

Despite these dismal statistics, the introduction of molecular gene signature platforms, progressive therapeutic approaches in diagnosis, and management of breast cancer has led to more effective treatment strategies and control measures concurrent with an equally reassuring decline in the mortality rate.

CRITICAL ISSUES

However, an enormous body of research in this area is requisite as high mortality associated with metastatic and/or drug refractory tumors continues to present a therapeutic challenge. Despite advances in systemic chemotherapy, the median survival of patients harboring metastatic breast cancers continues to be below 2 years.

FUTURE DIRECTIONS

Hence, a massive effort to scrutinize and evaluate chemotherapeutics on the basis of the molecular classification of these cancers is undertaken with the objective to devise more attractive and feasible approaches to treat breast cancers and improve patients' quality of life. This review aims to summarize the current understanding of the biology of breast cancer as well as challenges faced in combating breast cancer, with special emphasis on the current battery of treatment strategies. We will also try and gain perspective from recent encounters on novel findings responsible for the progression and metastatic transformation of breast cancer cells in an endeavor to develop more targeted treatment options. Antioxid. Redox Signal. 25, 337-370.

Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics

Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

Replication of Early B-cell Factor 1 (EBF1) Gene-by-psychosocial Stress Interaction Effects on Central Adiposity in a Korean Population

Objectives

Central obesity plays a major role in the development of many chronic diseases, including cardiovascular disease and cancer. Chronic stress may be involved in the pathophysiology of central obesity. Although several large-scale genome-wide association studies have reported susceptibility genes for central adiposity, the effects of interactions between genes and psychosocial stress on central adiposity have rarely been examined. A recent study focusing on Caucasians discovered the novel gene early B-cell factor 1 (EBF1), which was associated with central obesity-related traits via interactions with stress levels. We aimed to evaluate EBF1 gene-by-stress interaction effects on central adiposity traits, including visceral adipose tissue (VAT), in Korean adults.

Methods

A total of 1467 Korean adults were included in this study. We selected 22 single-nucleotide polymorphisms (SNPs) in the EBF1 gene and analyzed their interactions with stress on central adiposity using additive, dominant, and recessive genetic modeling.

Results

The four SNPs that had strong linkage disequilibrium relationships (rs10061900, rs10070743, rs4704967, and rs10056564) demonstrated significant interactions with the waist-hip ratio in the dominant model (p_int<0.007). In addition, two other SNPs (rs6556377 and rs13180086) were associated with VAT by interactions with stress levels, especially in the recessive genetic model (p_int<0.007). As stress levels increased, the mean values of central adiposity traits according to SNP genotypes exhibited gradual but significant changes (p<0.05).

Conclusions

These results suggest that the common genetic variants for EBF1 are associated with central adiposity through interactions with stress levels, emphasizing the importance of managing stress in the prevention of central obesity.

Genome-wide association study in East Asians identifies two novel breast cancer susceptibility loci

Breast cancer is one of the most common malignancies among women worldwide. Genetic factors have been shown to play an important role in breast cancer aetiology. We conducted a two-stage genome-wide association study (GWAS) including 14 224 cases and 14 829 controls of East Asian women to search for novel genetic susceptibility loci for breast cancer. Single nucleotide polymorphisms (SNPs) in two loci were found to be associated with breast cancer risk at the genome-wide significance level. The first locus, represented by rs12118297 at 1p22.3 (near the LMO4 gene), was associated with breast cancer risk with odds ratio (OR) and (95% confidence interval (CI)) of 0.91 (0.88-0.94) and a P-value of 4.48 × 10^{-  8} This association was replicated in another study, DRIVE GAME-ON Consortium, including 16 003 cases and 41 335 controls of European ancestry (OR = 0.95, 95% CI = 0.91-0.99, P-value = 0.019). The second locus, rs16992204 at 21q22.12 (near the LINC00160 gene), was associated with breast cancer risk with OR (95% CI) of 1.13 (1.07-1.18) and a P-value of 4.63 × 10 ^{-  8} The risk allele frequency for this SNP is zero in European-ancestry populations in 1000 Genomes Project and thus its association with breast cancer risk cannot be assessed in DRIVE GAME-ON Consortium. Functional annotation using the ENCODE data indicates that rs12118297 might be located in a repressed element and locus 21q22.12 may affect breast cancer risk through regulating LINC00160 expressions and interaction with oestrogen receptor signalling. Our findings provide additional insights into the genetics of breast cancer.

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.

A unified analytic framework for prioritization of non-coding variants of uncertain significance in heritable breast and ovarian cancer

BACKGROUND

Sequencing of both healthy and disease singletons yields many novel and low frequency variants of uncertain significance (VUS). Complete gene and genome sequencing by next generation sequencing (NGS) significantly increases the number of VUS detected. While prior studies have emphasized protein coding variants, non-coding sequence variants have also been proven to significantly contribute to high penetrance disorders, such as hereditary breast and ovarian cancer (HBOC). We present a strategy for analyzing different functional classes of non-coding variants based on information theory (IT) and prioritizing patients with large intragenic deletions.

METHODS

We captured and enriched for coding and non-coding variants in genes known to harbor mutations that increase HBOC risk. Custom oligonucleotide baits spanning the complete coding, non-coding, and intergenic regions 10 kb up- and downstream of ATM, BRCA1, BRCA2, CDH1, CHEK2, PALB2, and TP53 were synthesized for solution hybridization enrichment. Unique and divergent repetitive sequences were sequenced in 102 high-risk, anonymized patients without identified mutations in BRCA1/2. Aside from protein coding and copy number changes, IT-based sequence analysis was used to identify and prioritize pathogenic non-coding variants that occurred within sequence elements predicted to be recognized by proteins or protein complexes involved in mRNA splicing, transcription, and untranslated region (UTR) binding and structure. This approach was supplemented by in silico and laboratory analysis of UTR structure.

RESULTS

15,311 unique variants were identified, of which 245 occurred in coding regions. With the unified IT-framework, 132 variants were identified and 87 functionally significant VUS were further prioritized. An intragenic 32.1 kb interval in BRCA2 that was likely hemizygous was detected in one patient. We also identified 4 stop-gain variants and 3 reading-frame altering exonic insertions/deletions (indels).

CONCLUSIONS

We have presented a strategy for complete gene sequence analysis followed by a unified framework for interpreting non-coding variants that may affect gene expression. This approach distills large numbers of variants detected by NGS to a limited set of variants prioritized as potential deleterious changes.

Genetic predisposition to ductal carcinoma in situ of the breast

BACKGROUND

Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer. It is often associated with invasive ductal carcinoma (IDC), and is considered to be a non-obligate precursor of IDC. It is not clear to what extent these two forms of cancer share low-risk susceptibility loci, or whether there are differences in the strength of association for shared loci.

METHODS

To identify genetic polymorphisms that predispose to DCIS, we pooled data from 38 studies comprising 5,067 cases of DCIS, 24,584 cases of IDC and 37,467 controls, all genotyped using the iCOGS chip.

RESULTS

Most (67 %) of the 76 known breast cancer predisposition loci showed an association with DCIS in the same direction as previously reported for invasive breast cancer. Case-only analysis showed no evidence for differences between associations for IDC and DCIS after considering multiple testing. Analysis by estrogen receptor (ER) status confirmed that loci associated with ER positive IDC were also associated with ER positive DCIS. Analysis of DCIS by grade suggested that two independent SNPs at 11q13.3 near CCND1 were specific to low/intermediate grade DCIS (rs75915166, rs554219). These associations with grade remained after adjusting for ER status and were also found in IDC. We found no novel DCIS-specific loci at a genome wide significance level of P < 5.0x10(-8).

CONCLUSION

In conclusion, this study provides the strongest evidence to date of a shared genetic susceptibility for IDC and DCIS. Studies with larger numbers of DCIS are needed to determine if IDC or DCIS specific loci exist.

The MDM4 SNP34091 (rs4245739) C-allele is associated with increased risk of ovarian-but not endometrial cancer

The MDM4 protein (also known as MDMX or HDMX) is a negative regulator of p53, not only by direct interaction but also through its interaction with MDM2. Further, MDM4 overexpression and amplification have been observed in several cancer forms. Recently, a single nucleotide polymorphism (SNP) in the 3’ untranslated region of the MDM4 gene, SNP34091A > C (rs4245739) was reported to alter MDM4 messenger RNA (mRNA) stability by modulating a microRNA binding site, thereby leading to decreased MDM4 levels. In this case-control study, we aimed to evaluate the possible association between MDM4 SNP34091 status and cancer risk by comparing the genotype frequencies in large hospital-based cohorts of endometrial- (n = 1404) and ovarian (n = 1385) cancer patients with healthy female controls (n = 1870). Genotype frequencies were compared by odds ratio (OR) estimates and Fisher exact tests. We found that individuals harboring the MDM4 SNP34091AC/CC genotypes had a significantly elevated risk for serous ovarian cancer (SOC) in general and high-grade serous ovarian cancer (HGSOC) in particular (SOC: OR = 1.18., 95 % CI = 1.01–1.39; HGSOC: OR = 1.25, CI = 1.02–1.53). No association between SNP34091 genotypes and endometrial cancer risk was observed. Our data indicate the MDM4 SNP34091AC/CC genotypes to be associated with an elevated risk for SOC and in particular the HGSOC type.

Associations of Breast Cancer Risk Prediction Tools With Tumor Characteristics and Metastasis

Purpose

The association between established risk factors for breast cancer and subtypes or prognosis of the disease is not well known. We analyzed whether the Tyrer-Cuzick–predicted 10-year breast cancer risk score (TCRS), mammographic density (MD), and a 77-single nucleotide polymorphism polygenic risk score (PRS) were associated with breast cancer tumor prognosticators and risk of distant metastasis.

Patients and Methods

We used a case-only design in a population-based cohort of 5,500 Swedish patients with breast cancer. Logistic and multinomial logistic regression of outcomes, estrogen receptor (ER) status, lymph node involvement, tumor size, and grade was performed with TCRS, PRS, and percent MD as exposures. Cox proportional hazard models were used to estimate hazard ratios (HRs) of distant metastasis.

Results

Women at high risk for breast cancer based on PRS and/or TCRS were significantly more likely to be diagnosed with favorable prognosticators, such as ER-positive and low-grade tumors. In contrast, PRS weighted on ER-negative disease was associated with ER-negative tumors. When stratifying by age, the associations of TCRS with favorable prognosticators were restricted to women younger than age 50. Women scoring high in both TCRS and PRS had a lower risk of distant metastasis (HR, 0.69; 95% CI, 0.49 to 0.98). MD was not associated with any of the examined prognosticators.

Conclusion

Women at high risk for breast cancer based on genetic and lifestyle factors were significantly more likely to be diagnosed with breast cancers with a favorable prognosis. Better knowledge of subtype-specific risk factors could be vital for the success of prevention programs aimed at lowering mortality.

A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer

BACKGROUND

DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility.

METHODS

We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling.

RESULTS

We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10(-6)), MSH5 (P < 5.09 × 10(-6)), and BRCA2 (P = 5.70 × 10(-6)). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways.

CONCLUSIONS

Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways.

IMPACT

Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria.

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 .

Altered Gene Expression Associated with microRNA Binding Site Polymorphisms

Allele-specific gene expression associated with genetic variation in regulatory regions can play an important role in the development of complex traits. We hypothesized that polymorphisms in microRNA (miRNA) response elements (MRE-SNPs) that either disrupt a miRNA binding site or create a new miRNA binding site can affect the allele-specific expression of target genes. By integrating public expression quantitative trait locus (eQTL) data, miRNA binding site predictions, small RNA sequencing, and Argonaute crosslinking immunoprecipitation (AGO-CLIP) datasets, we identified genetic variants that can affect gene expression by modulating miRNA binding efficiency. We also identified MRE-SNPs located in regions associated with complex traits, indicating possible causative mechanisms associated with these loci. The results of this study expand the current understanding of gene expression regulation and help to interpret the mechanisms underlying eQTL effects.

MDM4 SNP34091 (rs4245739) and its effect on breast-, colon-, lung-, and prostate cancer risk

The MDM4 protein plays an important part in the negative regulation of the tumor suppressor p53 through its interaction with MDM2. In line with this, MDM4 amplification has been observed in several tumor forms. A polymorphism (rs4245739 A>C; SNP34091) in the MDM4 3′ untranslated region has been reported to create a target site for hsa‐miR‐191, resulting in decreased MDM4 mRNA levels. In this population‐based case–control study, we examined the potential association between MDM4 SNP34091, alone and in combination with the MDM2 SNP309T>G (rs2279744), and the risk of breast‐, colon‐, lung‐, and prostate cancer in Norway. SNP34091 was genotyped in 7,079 cancer patients as well as in 3,747 gender‐ and age‐matched healthy controls. MDM4 SNP34091C was not associated with risk for any of the tumor forms examined, except for a marginally significant association with reduced risk for breast cancer in a recessive model (OR = 0.77: 95% CI = 0.59–0.99). Stratifying according to MDM2 SNP309 status, we observed a reduced risk for breast cancer related to MDM4 SNP34091CC among individuals harboring the MDM2 SNP309GG genotype (OR = 0.41; 95% CI = 0.21–0.82). We conclude, MDM4 SNP34091 status to be associated with reduced risk of breast cancer, in particular in individuals carrying the MDM2 SNP309GG genotype, but not to be associated with either lung‐, colon‐ or prostate cancer.

Reevaluation of the BRCA2 truncating allele c.9976A > T (p.Lys3326Ter) in a familial breast cancer context

The breast cancer predisposition gene, BRCA2, has a large number of genetic variants of unknown effect. The variant rs11571833, an A > T transversion in the final exon of the gene that leads to the creation of a stop codon 93 amino acids early (K3326*), is reported as a neutral polymorphism but there is some evidence to suggest an association with an increased risk of breast cancer. We assessed whether this variant was enriched in a cohort of breast cancer cases ascertained through familial cancer clinics compared to population-based non-cancer controls using a targeted sequencing approach. We identified the variant in 66/2634 (2.5%) cases and 33/1996 (1.65%) controls, indicating an enrichment in the breast cancer cases (p = 0.047, OR 1.53, 95% CI 1.00-2.34). This data is consistent with recent iCOGs data suggesting that this variant is not neutral with respect to breast cancer risk. rs11571833 may need to be included in SNP panels for evaluating breast cancer risk.

An overview of triple-negative breast cancer

PURPOSE

Triple-negative breast cancer (TNBC) is a heterogeneous group of tumors comprising various breast cancers simply defined by the absence of estrogen receptor, progesterone receptor and overexpression of human epidermal growth factor receptor 2 gene. In this review, we discuss the epidemiology, risk factors, clinical characteristics and prognostic variables of TNBC, and present the summary of recommended treatment strategies and all other available treatment options.

METHODS

We performed a systematic literature search using Medline and selected those articles which seemed relevant for this review. In addition, the ClinicalTrials.gov was also scanned for ongoing trials.

RESULTS

TNBC accounts for 10-20 % of all invasive breast cancers and has been found to be associated with African-American race, younger age, higher grade and mitotic index, and more advanced stage at diagnosis. Locoregional treatment is similar to other invasive breast cancer subtypes and involves surgery-mastectomy with or without adjuvant radiotherapy or breast conservation followed by adjuvant radiotherapy. Due to lack of drug-targetable receptors, chemotherapy is the only recommended systemic treatment to improve disease outcome. TNBC is sensitive to chemotherapy as demonstrated by high pathological complete response rates achieved after neoadjuvant chemotherapy, and this approach also allows for breast-conserving surgery. The peak risk of relapse is at 3 years after surgery, thereafter recurrence risk rapidly decreases. Survival after metastatic relapse is shorter as compared to other breast cancer subtypes, treatment options are few and response rates are poor and lack durability. Important molecular characteristics have now been identified that can subdivide this group of breast cancers further and can provide alternative systemic therapies.

CONCLUSIONS

To improve therapeutic outcome of TNBC, reliable predictive biomarkers and newer drugs against the known molecular pathways are required.