Associations between adjuvant radiotherapy and different causes of death in a German breast cancer cohort

BACKGROUND

Studies of cohorts of breast cancer (BC) patients diagnosed before 1990 showed radiotherapy (RT) to be associated with increased cardiovascular (CVD) and lung cancer mortality many years after diagnosis. In the late 1990s, improvements in RT planning techniques reduced radiation doses to normal tissues. Recent studies did not consistently report higher RT-related mortality for CVD and second cancers. Aim of the study was to analyze specific causes of death after 3D-conformal RT in a recent BC cohort.

METHODS

Stage I-III BC patients diagnosed 2001-2005 and enrolled in the population based MARIEplus study were followed-up for 11.9 years (median). Associations between adjuvant RT and cause-specific mortality were analyzed by using competing risks models, yielding subdistribution hazard ratios (SHR) for RT directly related to cumulative incidences. Models were adjusted for differences in baseline characteristics applying inverse-probability-of-treatment-weighting (IPTW).

RESULTS

Of the 2951 patients, 2439 (83.0%) received RT. No significant association of RT with lung cancer mortality (SHR_IPTW 0.88, 0.35-2.12), other cancer mortality (SHR_IPTW 1.04, 95% CI 0.62-1.73) or cardiac mortality was observed (SHR_IPTW 1.57, 0.75-3.29). Mortality from lung and other diseases were significantly lower in irradiated women (SHR_IPTW 0.39, 95% CI 0.17-0.90 and SHR_IPTW 0.58, 95% CI 0.34-0.97, respectively).

CONCLUSION

In line with recent studies, 3D-conformal RT did not significantly increase mortality from non-BC causes in the German MARIEplus cohort. Since long-term data are still sparse and event rates low in BC-cohorts, who received modern RT, investigation of possible late RT effects on mortality beyond 14 years of follow-up is warranted.

Body mass index and breast cancer survival: a Mendelian randomization analysis

Background

There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer.

Methods

We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis.

Results

BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P = 0.95).

Conclusions

Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.

Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients

PURPOSE

Several small studies have indicated that the ATM rs1801516 SNP is associated with risk of normal tissue toxicity after radiotherapy. However, the findings have not been consistent. In order to test this SNP in a well-powered study, an individual patient data meta-analysis was carried out by the International Radiogenomics Consortium.

MATERIALS AND METHODS

The analysis included 5456 patients from 17 different cohorts. 2759 patients were given radiotherapy for breast cancer and 2697 for prostate cancer. Eight toxicity scores (overall toxicity, acute toxicity, late toxicity, acute skin toxicity, acute rectal toxicity, telangiectasia, fibrosis and late rectal toxicity) were analyzed. Adjustments were made for treatment and patient related factors with potential impact on the risk of toxicity.

RESULTS

For all endpoints except late rectal toxicity, a significantly increased risk of toxicity was found for carriers of the minor (Asn) allele with odds ratios of approximately 1.5 for acute toxicity and 1.2 for late toxicity. The results were consistent with a co-dominant pattern of inheritance.

CONCLUSION

This study convincingly showed a significant association between the ATM rs1801516 Asn allele and increased risk of radiation-induced normal tissue toxicity.

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

BACKGROUND

The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.

METHODS

We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.

RESULTS

For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10-5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10-8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.

CONCLUSIONS

This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts

PURPOSE

To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate.

METHODS AND MATERIALS

Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas under the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs).

RESULTS

Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely.

CONCLUSIONS

Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.

SNPs in transporter and metabolizing genes as predictive markers for oxaliplatin treatment in colorectal cancer patients

Oxaliplatin is frequently used as part of a chemotherapeutic regimen with 5-fluorouracil in the treatment of colorectal cancer (CRC). The cellular availability of oxaliplatin is dependent on metabolic and transporter enzymes. Variants in genes encoding these enzymes may cause variation in response to oxaliplatin and could be potential predictive markers. Therefore, we used a two-step procedure to comprehensively investigate 1,444 single nucleotide polymorphisms (SNPs) from these pathways for their potential as predictive markers for oxaliplatin treatment, using 623 stage II-IV CRC patients (of whom 201 patients received oxaliplatin) from a German prospective patient cohort treated with adjuvant or palliative chemotherapy. First, all genes were screened using the global test that evaluated SNP*oxaliplatin interaction terms per gene. Second, one model was created by backward elimination on all SNP*oxaliplatin interactions of the selected genes. The statistical procedure was evaluated using bootstrap analyses. Nine genes differentially associated with overall survival according to oxaliplatin treatment (unadjusted p values < 0.05) were selected. Model selection resulted in the inclusion of 14 SNPs from eight genes (six transporter genes, ABCA9, ABCB11, ABCC10, ATP1A1, ATP1B2, ATP8B3, and two metabolism genes GSTM5, GRHPR), which significantly improved model fit. Using bootstrap analysis we show an improvement of the prediction error of 3.7% in patients treated with oxaliplatin. Several variants in genes involved in metabolism and transport could thus be potential predictive markers for oxaliplatin treatment in CRC patients. If confirmed, inclusion of these variants in a predictive test could identify patients who are more likely to benefit from treatment with oxaliplatin.

A Comprehensive Multistate Model Analyzing Associations of Various Risk Factors With the Course of Breast Cancer in a Population-Based Cohort of Breast Cancer Cases

We employed a semi-Markov multistate model for the simultaneous analysis of various endpoints describing the course of breast cancer. Results were compared with those from standard analyses using a Cox proportional hazards model. We included 3,012 patients with invasive breast cancer newly diagnosed between 2001 and 2005 who were recruited in Germany for a population-based study, the Mamma Carcinoma Risk Factor Investigation (MARIE Study), and prospectively followed up until the end of 2009. Locoregional recurrence and distant metastasis were included as intermediate states, and deaths from breast cancer, secondary cancer, and other causes were included as competing absorbing states. Tumor characteristics were significantly associated with all breast cancer-related endpoints. Nodal involvement was significantly related to local recurrence but more strongly related to distant metastases. Smoking was significantly associated with mortality from second cancers and other causes, whereas menopausal hormone use was significantly associated with reduced distant metastasis and death from causes other than cancer. The presence of cardiovascular disease at diagnosis was solely associated with mortality from other causes. Compared with separate Cox models, multistate models allow for dissection of prognostic factors and intermediate events in the analysis of cause-specific mortality and can yield new insights into disease progression and associated pathways.

Relationship between menopausal hormone therapy and mortality after breast cancer The MARIEplus study, a prospective case cohort

Cohort studies of breast cancer (BC) patients, but not of disease-free women at inclusion, have found menopausal hormone therapy (MHT) to be associated with decreased BC specific mortality (BCM). Here, the German population-based MARIEplus BC cohort was analyzed to further elucidate associations of prediagnostic MHT with BCM (and modification by tumor characteristics), recurrence, and secondarily with other cause and overall mortality. Enrolled 2002-2005, incident invasive BC cases (N = 3,321) were followed up for a median of 6.1 years. Cox proportional hazards models adjusted for tumor characteristics, mammography and lifestyle were applied. Compared with never users of MHT, current users at date of diagnosis had significantly lower BCM (Hazard ratio (HR) 0.72, 95% CI 0.53-0.97) and risk of recurrence (HR 0.61, 95% CI 0.46-0.82). The MHT related reduced BCM was confined to patients with low grade tumors (HR 0.44, 95% CI 0.28-0.70; phet  = 0.01) and not modified by estrogen receptor or nodal status. BCM decreased with MHT duration in current and increased in past users (phet  = 0.015). Mortality due to causes other than BC and overall mortality were also reduced in current MHT users (HR 0.51, 95% CI 0.32-0.81, HR 0.66, 95% CI 0.52-0.86, respectively). Favorable tumor characteristics and mammographic surveillance could not fully explain associations of current MHT use with BCM and recurrence risk. Thus, the study contributes to the evidence that prediagnostic MHT does not have a negative impact on prognosis after BC. The restriction of a reduced BCM to low grade tumors should be confirmed in independent studies.

A polymorphism in the base excision repair gene PARP2 is associated with differential prognosis by chemotherapy among postmenopausal breast cancer patients

BACKGROUND

Personalized therapy considering clinical and genetic patient characteristics will further improve breast cancer survival. Two widely used treatments, chemotherapy and radiotherapy, can induce oxidative DNA damage and, if not repaired, cell death. Since base excision repair (BER) activity is specific for oxidative DNA damage, we hypothesized that germline genetic variation in this pathway will affect breast cancer-specific survival depending on treatment.

METHODS

We assessed in 1,408 postmenopausal breast cancer patients from the German MARIE study whether cancer specific survival after adjuvant chemotherapy, anthracycline chemotherapy, and radiotherapy is modulated by 127 Single Nucleotide Polymorphisms (SNPs) in 21 BER genes. For SNPs with interaction terms showing p<0.1 (likelihood ratio test) using multivariable Cox proportional hazard analyses, replication in 6,392 patients from nine studies of the Breast Cancer Association Consortium (BCAC) was performed.

RESULTS

rs878156 in PARP2 showed a differential effect by chemotherapy (p=0.093) and was replicated in BCAC studies (p=0.009; combined analysis p=0.002). Compared to non-carriers, carriers of the variant G allele (minor allele frequency=0.07) showed better survival after chemotherapy (combined allelic hazard ratio (HR)=0.75, 95% 0.53-1.07) and poorer survival when not treated with chemotherapy (HR=1.42, 95% 1.08-1.85). A similar effect modification by rs878156 was observed for anthracycline-based chemotherapy in both MARIE and BCAC, with improved survival in carriers (combined allelic HR=0.73, 95% CI 0.40-1.32). None of the SNPs showed significant differential effects by radiotherapy.

CONCLUSIONS

Our data suggest for the first time that a SNP in PARP2, rs878156, may together with other genetic variants modulate cancer specific survival in breast cancer patients depending on chemotherapy. These germline SNPs could contribute towards the design of predictive tests for breast cancer patients.

Height and Breast Cancer Risk: Evidence From Prospective Studies and Mendelian Randomization

BACKGROUND

Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear.

METHODS

We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients.

RESULTS

The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8).

CONCLUSIONS

Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer.

Abstract 3445: Diacylglycerol kinase alpha as a novel epigenetically regulated risk marker for radiotherapy-induced fibrosis

Ionizing radiation is a common treatment option for cancer but its use is limited by the unpredictable and highly heterogeneous onset of late side effects, especially radiation-induced fibrosis. Clinically applicable biomarkers and effective treatments for radiation fibrosis are currently unavailable. In order to identify novel markers we ran a genome-wide DNA methylation screen in primary dermal fibroblasts obtained from breast cancer patients before intraoperative radiotherapy. Cells from patients developing fibrosis within a three-year follow up were compared to those without fibrosis (12 individuals per group). Illumina Infinium HumanMethylation450 BeadChip analysis revealed differentially methylated sites which are associated with fibrosis. Notably, we identified a differentially methylated region (DMR) at the diacylglycerol kinase alpha (DGKA) locus as a potential fibrosis marker. This DGKA DMR was confirmed using quantitative MassARRAY technology in 75 patient fibroblast samples. We first investigated whether high or low DNA methylation at this DGKA DMR affects cellular radiation response. Functional in vitro analysis showed that the methylation status of the DGKA DMR inversely correlated with its radiation-induced mRNA and protein expression as well as with its enzymatic activity. We next examined the DMR for its role as a regulatory site. The intragenically located DMR was identified as a potential enhancer sequence using chromatin immunoprecipitation (ChIP) for H3K4me1 and H3K27ac as well as luciferase reporter assays. Chromatin conformation capture (3C) analysis revealed interaction of this enhancer with the DGKA promoter in fibroblasts with low DNA methylation, and further ChIP experiments showed a DNA methylation-dependent recruitment of the profibrotic transcription factor Early Growth Response 1 (EGR1) to this site. We finally asked how epigenetically altered DGKA expression could impact on cellular processes relevant to fibrosis such as fibroblast transactivation or stress response. Results in primary fibroblasts showed that, in response to ionizing radiation and other stress factors, DGKA affects global levels of its substrate diacylglycerol, as well as expression of the fibroblast activation markers Alpha Smooth Muscle Actin (ACTA2) and collagen 1 (COL1A1). Upon overexpression of DGKA in HEK293T cells, a luciferase-based screening of 15 stress-responsive signaling reporters revealed functional consequences on several response pathways. In summary, DGKA has emerged as a novel, epigenetically regulated signaling protein that has a role in radiation fibrosis and may serve as a new biomarker and therapeutic target.

Citation Format: Christoph Weigel, Marlon R. Veldwijk, Christopher C. Oakes, Petra Seibold, Alla Slynko, David B. Liesenfeld, Carsten Herskind, Elena Sperk, Axel Benner, Christoph Plass, Frederik Wenz, Jenny Chang-Claude, Peter Schmezer, Odilia Popanda. Diacylglycerol kinase alpha as a novel epigenetically regulated risk marker for radiotherapy-induced fibrosis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3445. doi:10.1158/1538-7445.AM2015-3445

XRCC1 Polymorphism Associated With Late Toxicity After Radiation Therapy in Breast Cancer Patients

PURPOSE

To identify single-nucleotide polymorphisms (SNPs) in oxidative stress-related genes associated with risk of late toxicities in breast cancer patients receiving radiation therapy.

METHODS AND MATERIALS

Using a 2-stage design, 305 SNPs in 59 candidate genes were investigated in the discovery phase in 753 breast cancer patients from 2 prospective cohorts from Germany. The 10 most promising SNPs in 4 genes were evaluated in the replication phase in up to 1883 breast cancer patients from 6 cohorts identified through the Radiogenomics Consortium. Outcomes of interest were late skin toxicity and fibrosis of the breast, as well as an overall toxicity score (Standardized Total Average Toxicity). Multivariable logistic and linear regression models were used to assess associations between SNPs and late toxicity. A meta-analysis approach was used to summarize evidence.

RESULTS

The association of a genetic variant in the base excision repair gene XRCC1, rs2682585, with normal tissue late radiation toxicity was replicated in all tested studies. In the combined analysis of discovery and replication cohorts, carrying the rare allele was associated with a significantly lower risk of skin toxicities (multivariate odds ratio 0.77, 95% confidence interval 0.61-0.96, P=.02) and a decrease in Standardized Total Average Toxicity scores (-0.08, 95% confidence interval -0.15 to -0.02, P=.016).

CONCLUSIONS

Using a stage design with replication, we identified a variant allele in the base excision repair gene XRCC1 that could be used in combination with additional variants for developing a test to predict late toxicities after radiation therapy in breast cancer patients.

Abstract 4585: Folate-mediated one-carbon metabolism polymorphisms associated with risk and survival of colorectal cancer

Introduction

Folate-mediated one-carbon metabolism (FOCM) is a key pathway necessary for nucleotide synthesis, DNA methylation, replication and repair. Genetic variants in FOCM genes, especially the MTHFR-C677T polymorphism, have been associated with colorectal neoplasia. Moreover, FOCM is an important target for chemotherapeutic drugs for the treatment of colorectal cancer (CRC), such as 5-fluorouracil (5-FU). We performed a comprehensive assessment of FOCM-related genetic variation in relation to CRC risk and survival in an unfortified population.

Methods

Associations of 457 tagging and candidate SNPs in 47 FOCM-related genes with CRC risk and survival were investigated within a German population-based case-control study (the DACHS- study). Using multivariate adjusted logistic (n = 1754 incident cases and 1781 matched controls) and Cox regression (5 years follow-up of CRC cases only; 585 deceased), we evaluated co-dominant, dominant, and log-additive modes of inheritance. SNPs were genotyped using the Illumina GoldenGate Assay. Correction for multiple testing was performed using false discovery rates (FDR).

Results

Individuals having both variant alleles of a candidate SNP in the ADH1C gene (rs1693482) had a significantly decreased risk of developing CRC (ORhet = 0.94 [95% CI = 0.81-1.10]; ORhzv = 0.74 [95% CI = 0.59-0.92]; p-trend = 0.013). Before correction for multiple testing, 19 nominally significant genetic main effects on CRC risk were observed. None of the studied tagging SNPs was significantly associated with risk after multiple test correction. One polymorphism in the PON1 gene (rs3917538) was significantly associated with overall survival (HRhet = 1.22 [95% CI = 1.03-1.45]; HRhzv = 2.00 [95% CI = 1.48-2.71]; p-trend = 0.01), after correction for multiple testing. Effect modification by 5-FU chemotherapy was observed between two polymorphisms (MTHFR-rs4846047 [Int-pFDR = 0.02] and TK1-rs1811086 [Int-pFDR = 0.02]) for the endpoint overall survival. Cases with variant alleles of these SNPs had a reduced effect of 5-FU on overall survival.

Conclusion

Genetic variation in FOCM appears to be associated with CRC risk and survival. Furthermore, 5-FU might interact with FOCM polymorphisms. Further large investigations are required to replicate our findings.

Citation Format: Akke Botma, Katharina Buck, Yesilda Balavarca, Dominique Scherer, Nina Habermann, Reka Toth, Lina Jansen, Michael Hoffmeister, Hermann Brenner, Elisabeth J. Kap, Petra Seibold, Axel Benner, Alexis Ulrich, Barbara Burwinkel, Jenny Chang-Claude, Cornelia M. Ulrich. Folate-mediated one-carbon metabolism polymorphisms associated with risk and survival of colorectal cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4585. doi:10.1158/1538-7445.AM2015-4585

Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.

Identification of novel genetic markers of breast cancer survival

BACKGROUND

Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival.

METHODS

We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided.

RESULTS

We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust.

CONCLUSIONS

This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND

Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.

METHODS

We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.

RESULTS

There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.

CONCLUSIONS

The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Common germline polymorphisms associated with breast cancer-specific survival

INTRODUCTION

Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium.

METHODS

A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect.

RESULTS

Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease.

CONCLUSIONS

Although no variants reached genome-wide significance (P <5 x 10(-8)), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels.

The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients

We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.

Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) <1.1 × 10(-3) . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER-negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10(-4) ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.