Co-observation of germline pathogenic variants in breast cancer predisposition genes: Results from analysis of the BRIDGES sequencing dataset.

Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels.

The impact of coding germline variants on contralateral breast cancer risk and survival.

Evidence linking coding germline variants in breast cancer (BC)-susceptibility genes other than BRCA1, BRCA2, and CHEK2 with contralateral breast cancer (CBC) risk and breast cancer-specific survival (BCSS) is scarce. The aim of this study was to assess the association of protein-truncating variants (PTVs) and rare missense variants (MSVs) in nine known (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53) and 25 suspected BC-susceptibility genes with CBC risk and BCSS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox regression models. Analyses included 34,401 women of European ancestry diagnosed with BC, including 676 CBCs and 3,449 BC deaths; the median follow-up was 10.9 years. Subtype analyses were based on estrogen receptor (ER) status of the first BC. Combined PTVs and pathogenic/likely pathogenic MSVs in BRCA1, BRCA2, and TP53 and PTVs in CHEK2 and PALB2 were associated with increased CBC risk [HRs (95% CIs): 2.88 (1.70-4.87), 2.31 (1.39-3.85), 8.29 (2.53-27.21), 2.25 (1.55-3.27), and 2.67 (1.33-5.35), respectively]. The strongest evidence of association with BCSS was for PTVs and pathogenic/likely pathogenic MSVs in BRCA2 (ER-positive BC) and TP53 and PTVs in CHEK2 [HRs (95% CIs): 1.53 (1.13-2.07), 2.08 (0.95-4.57), and 1.39 (1.13-1.72), respectively, after adjusting for tumor characteristics and treatment]. HRs were essentially unchanged when censoring for CBC, suggesting that these associations are not completely explained by increased CBC risk, tumor characteristics, or treatment. There was limited evidence of associations of PTVs and/or rare MSVs with CBC risk or BCSS for the 25 suspected BC genes. The CBC findings are relevant to treatment decisions, follow-up, and screening after BC diagnosis.

Cancer-related fatigue: Towards a more targeted approach based on classification by biomarkers and psychological factors.

Cancer-related fatigue is a frequent, burdensome and often insufficiently treated symptom. A more targeted treatment of fatigue is urgently needed. Therefore, we examined biomarkers and clinical factors to identify fatigue subtypes with potentially different pathophysiologies. The study population comprised disease-free breast cancer survivors of a German population-based case-control study who were re-assessed on average 6 (FU1, n = 1871) and 11 years (FU2, n = 1295) after diagnosis. At FU1 and FU2, we assessed fatigue with the 20-item multidimensional Fatigue Assessment Questionnaire and further factors by structured telephone-interviews. Serum samples collected at FU1 were analyzed for IL-1ß, IL-2, IL-4, IL-6, IL-10, TNF-a, GM-CSF, IL-5, VEGF-A, SAA, CRP, VCAM-1, ICAM-1, leptin, adiponectin and resistin. Exploratory cluster analyses among survivors with fatigue at FU1 and no history of depression yielded three clusters (CL1, CL2 and CL3). CL1 (n = 195) on average had high levels of TNF-α, IL1-ß, IL-6, resistin, VEGF-A and GM-CSF, and showed high BMI and pain levels. Fatigue in CL1 manifested rather in physical dimensions. Contrarily, CL2 (n = 78) was characterized by high leptin level and had highest cognitive fatigue. CL3 (n = 318) did not show any prominent characteristics. Fatigued survivors with a history of depression (n = 214) had significantly higher physical, emotional and cognitive fatigue and showed significantly less amelioration of fatigue from FU1 to FU2 than survivors without depression. In conclusion, from the broad phenotype "cancer-related fatigue" we were able to delineate subgroups characterized by biomarkers or history of depression. Future investigations may take these subtypes into account, ultimately enabling a better targeted therapy of fatigue.

The Healthy Participant Effect: insights and results from a population-based case-control study on breast cancer.

Agreement to participate in case-control studies has become low. Healthy participant bias resulting from differential response proportions in cases and controls can distort results; however, the magnitude of bias is difficult to assess. We investigated the effect in a large population-based case-control study on breast cancer, with a participation rate of 43.4% and 64.1% for controls and cases. We performed a mortality follow-up in 2020 for 3,813 cases and 7,335 controls recruited between 2002-2005. Standardized mortality ratios (SMR) for overall mortality and selected causes of death were estimated. The mean age at recruitment was 63.1 years. The overall mortality for controls was 0.66 times lower (95%CI 0.62-0.69) than for the reference population. For causes of death other than breast cancer, SMRs were similar in cases and controls (0.70 and 0.64). Higher education was associated with lower SMRs in both cases and controls. Options for adjusting the healthy participant bias are limited if the true risk factor distribution in the underlying population is unknown. However, a relevant bias in this particular case-control study is considered unlikely since a similar healthy participant effect was observed for both controls and cases.

Social relationships and their impact on health-related quality of life in a long-term breast cancer survivor cohort.

BACKGROUND: Health-related quality of life (HRQOL) has become increasingly important for breast cancer survivors, but clinically relevant declines often persist for many years after treatment. This study aimed to investigate whether social relationships can mitigate or prevent this decline in HRQOL. METHODS: Data were used from the German population-based Mamma Carcinoma Risk Factor Investigation (MARIE) cohort of 2022 breast cancer cases with follow-up information for more than 15 years after diagnosis. Correlations between social integration, social support, and global health status (GHS) as an overall measure of HRQOL were analyzed, and linear regression analysis was performed with structural equation modeling. RESULTS: The majority of participants reported high levels of social integration and social support and moderate levels of GHS. Social integration 5 years after diagnosis was associated with GHS 5 years after diagnosis (ß = 1.12; 95% CI, 0.25-1.99), but no longitudinal effects were found. Social support 5 years after diagnosis was associated with better GHS 5 years (ß = 0.42; 95% CI, 0.36-0.48) and 10 years after diagnosis (ß = 0.12; 95% CI, 0.02-0.22), whereas social support 10 years after diagnosis was associated with GHS 10 years (ß = 0.29; 95% CI, 0.20-0.39) and 15 years after diagnosis (ß = 0.10; 95% CI, 0.01-0.21). CONCLUSIONS: These results confirm that social relationships positively influence HRQOL in long-term breast cancer survivors and that their association should receive more attention clinically and beyond routine care.

Does breast cancer modify the long-term relationship between lifestyle behaviors and mortality? A prospective analysis of breast cancer survivors and population-based controls.

BACKGROUND: Modifiable lifestyle factors are known to impact survival. It is less clear whether this differs between postmenopausal women ever diagnosed with breast cancer and unaffected women. METHODS: Women diagnosed with breast cancer and unaffected women of comparable age were recruited from 2002 to 2005 and followed up until 2020. Using baseline information, a lifestyle adherence score (range 0-8; categorized as low [0-3.74], moderate [3.75-4.74], and high [≥4.75]) was created based on the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations. Cox regression and competing risks analysis were used to analyze the association of adherence to WCRF/AICR lifestyle recommendations with overall mortality and with death due to cardiovascular diseases and cancer, respectively. RESULTS: A total of 8584 women were included (2785 with breast cancer and 5799 without). With a median follow-up of 16.1 years there were 2006 total deaths. Among the deaths of known causes (98.6%), 445 were cardiovascular-related and 1004 were cancer-related. The average lifestyle score was 4.2. There was no differential effect of lifestyle score by case-control status on mortality. After adjusting for covariates, moderate (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.57-0.76) and high (HR, 0.54; 95% CI, 0.47-0.63) adherence to WCRF/AICR lifestyle recommendations were significantly associated with a decrease in overall mortality. Similarly, in competing risks analysis, moderate and high adherence were associated with decreased mortality from cardiovascular diseases and from cancer. CONCLUSIONS: A healthy lifestyle can substantially reduce mortality risk in women. With low adherence to all WCRF/AICR guidelines in about a third of study participants, health interventions are warranted.

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel.

BACKGROUND: Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS: We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS: In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS: Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.

Postdiagnosis circulating osteoprotegerin and TRAIL concentrations and survival and recurrence after a breast cancer diagnosis: results from the MARIE patient cohort.

BACKGROUND: Experimental studies suggest a role for osteoprotegerin (OPG) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in mammary tumor development and progression. These biomarkers have been minimally investigated with respect to outcomes in breast cancer patients. METHODS: OPG and TRAIL were evaluated in blood samples collected from 2459 breast cancer patients enrolled in the MARIE study, a prospective population-based patient cohort, at median of 129 days after diagnosis. Participants were between ages 50 and 74 at diagnosis and recruited from 2002 to 2005 in two regions of Germany. Follow-up for recurrence and mortality was conducted through June 2015. Delayed-entry Cox proportional hazards regression was used to assess associations between OPG and TRAIL with all-cause and breast cancer-specific mortality, and recurrence, both overall and by tumor hormone receptor status. RESULTS: Median follow-up time was 11.7 years, with 485 deaths reported (277 breast cancer-specific). Higher OPG concentrations were associated with a higher risk of all-cause mortality (hazard ratio for 1-unit log2-transformed concentration (HRlog2) = 1.24 (95% confidence interval 1.03-1.49). Associations were observed in women diagnosed with ER-PR- tumors or discordant hormone receptor status (ER-PR-, HRlog2 = 1.93 (1.20-3.10); discordant ERPR, 1.70 (1.03-2.81)), but not for women with ER + PR + tumors (HRlog2 = 1.06 (0.83-1.35)). OPG was associated with a higher risk of recurrence among women with ER-PR- disease (HRlog2 = 2.18 (1.39-3.40)). We observed no associations between OPG and breast cancer-specific survival, or for TRAIL and any outcome. CONCLUSIONS: Higher circulating OPG may be a biomarker of a higher risk of poor outcome among women diagnosed with ER- breast cancer. Further mechanistic studies are warranted.

The impact of cardiovascular disease on all-cause and cancer mortality: results from a 16-year follow-up of a German breast cancer case-control study.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide. The aim of this study was to examine if CVD affects the mortality of women after a breast cancer diagnosis and population controls differently. METHODS: The analysis included a total of 3,555 women, diagnosed with primary stage 1-3 breast cancer or in situ carcinoma between 2002 and 2005 and 7,334 controls breast cancer-free at recruitment, all aged 50-74 years, who were followed-up in a German breast cancer case-control study until June, 30 2020. Kaplan-Meier and cumulative incidence function were calculated for all-cause mortality and mortality from any cancer, stratified for case-control status and CVD, separately for women aged < 65 and ≥ 65 years. Cox regression and Fine-Gray subdistribution hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) for the association between case-control-status, CVD and mortality from all causes/any cancer. RESULTS: The median follow-up was 16.1 years. In total, 1,172 cases (33.0%) and 1,401 initial controls (19.1%) died. CVD prevalence at recruitment was 15.2% in cases and controls. Cases with CVD had the highest and controls without CVD the lowest mortality during the entire observation period in both age groups (< 65 and ≥ 65 years). CVD was identified as a risk factor for all-cause mortality in both cases and controls aged < 65 years (HR 1.22, 95%CI 0.96-1.55 and HR 1.79, 95%CI 1.43-2.24) as well as at ages of ≥ 65 years (HR 1.44, 95%CI 1.20-1.73 and HR 1.59, 95%CI 1.37-1.83). A significant association of CVD and cancer mortality was found only for cases aged ≥ 65 years. CONCLUSION: CVD was significantly associated with all-cause mortality of both cases and controls and CVD was identified as a risk factor for cancer mortality of cases aged ≥ 65 years at recruitment. Therefore, attention should be paid on monitoring and preventing CVD in breast cancer patients, especially in those diagnosed at older ages.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry.

BACKGROUND: Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. METHODS: Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. RESULTS: Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). CONCLUSIONS: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Endogenous estrogen receptor modulating oxysterols and breast cancer prognosis: Results from the MARIE patient cohort.

BACKGROUND: 27-hydroxycholesterol (HC) and 25-HC were identified as endogenous selective estrogen receptor modulators (SERMs) and estrogen receptor (ER) modulators, respectively. They are hypothesized to play a role in multiple physiologic processes and pathologies, including breast cancer development and progression. METHODS: We evaluated circulating 27-HC and 25-HC, and outcomes following a breast cancer diagnosis in 2282 women from the MARIE study over median follow-up of 11.6 years. 27-HC and 25-HC were quantified by liquid chromatography-mass spectrometry. We calculated hazard ratios (HR) and 95% confidence intervals [CI] using multivariable Cox Proportional Hazards regression. RESULTS: We observed no associations between 27-HC and breast cancer prognosis overall. Associations between 27-HC and survival differed by circulating estradiol concentrations and endocrine therapy, but not by hormone receptor status. Among women with estradiol levels below the median (0.08 nM), 27-HC was associated with higher risk of all-cause mortality (HRlog2 = 1.80 [1.20-2.71]) and breast cancer-specific mortality (HRlog2 = 1.95 [1.14-3.31]). No associations were observed in women with estradiol levels above the median. Higher 25-HC levels were associated with lower risk of recurrence (HRlog2 = 0.87 [0.77-0.98]). CONCLUSION: Associations between 27-HC and breast cancer prognosis varied by circulating estradiol levels and endocrine therapy. Less consistent results were observed for 25-HC.

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk.

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.

Circulating oxysterols and prognosis among women with a breast cancer diagnosis: results from the MARIE patient cohort.

BACKGROUND: Breast cancer is the most commonly diagnosed cancer in women worldwide, and underlying mechanistic pathways associated with breast cancer-specific and non-breast cancer-related deaths are of importance. Emerging evidence suggests a role of oxysterols, derivates of cholesterol, in multiple chronic diseases including breast cancer and coronary artery diseases. However, associations between oxysterols and survival have been minimally studied in women diagnosed with breast cancer. In this large breast cancer patient cohort, we evaluated associations between a panel of circulating oxysterols and mortality and recurrence outcomes. METHODS: Concentrations of 13 circulating oxysterols representing different pathways of cholesterol metabolism were quantified using liquid-chromatography mass-spectrometry. Associations between baseline levels of oxysterols and cause-specific mortality outcomes and recurrence following a breast cancer diagnosis were assessed in 2282 women from the MARIE study over a median follow-up time of 11 years. We calculated hazard ratios (HR) and 95% confidence intervals (CI) using multivariable Cox proportional hazard models and competing risks models. RESULTS: We observed no associations for circulating oxysterols and breast cancer-specific outcomes. Higher levels of six oxysterols were associated with an increased risk of cardiovascular disease death, including 24S-hydroxycholesterol (alternative bile acid pathway, HRlog2 = 1.73 (1.02, 2.93)), lanosterol (cholesterol biosynthesis pathway, HRlog2 = 1.95 (1.34, 2.83)), 7-ketocholesterol (HRlog2 = 1.26 (1.03, 1.55)), 5α,6α-epoxycholesterol (HRlog2 = 1.34 (1.02-1.77)), and 5a,6ß-dihydroxycholestanol (HRlog2 = 1.34 (1.03, 1.76)). After adjusting for multiple comparisons, none of the associations were statistically significant. CONCLUSION: We provide first evidence on a range of circulating oxysterols and mortality following a breast cancer diagnosis, contributing to a better understanding of associations between different pathways of cholesterol metabolism and prognosis in women with a breast cancer diagnosis. The findings of this study suggest circulating oxysterols may be associated with cardiovascular mortality among women diagnosed with breast cancer. Further studies are needed to evaluate these oxysterols as potential markers of risk for cardiovascular mortality among women with a breast cancer diagnosis as well as their clinical potential.

Association of circulating free and total oxysterols in breast cancer patients.

OBJECTIVES: Oxysterols, a family of oxidized cholesterol derivates, are of increasing interest due to their role in cancer development and progression. Some oxysterols are estrogen receptor modulators and thus of particular interest in breast cancer research. In human studies, two forms of circulating oxysterols are commonly evaluated: "free" (unesterified) and "total" (esterified and unesterified). However, associations between free and total oxysterols are not well established. We addressed this knowledge gap in a pilot study by evaluating correlations between the free and the total form of each of the circulating oxysterols (free vs. total), and pairwise associations within the panel of total oxysterols (total vs. total) and the panel of free oxysterols (free vs. free). METHODS: Concentrations of oxysterols and other non-cholesterol sterols were quantified in blood samples of 27 breast cancer patients from the MARIE breast cancer patient cohort using liquid chromatography mass spectrometry. We used Spearman rank correlations to assess associations. Overall, 12 oxysterols (including 27-hydroxycholesterol (HC), 25-HC, 24S-HC, 7a-HC, 5a6a-epoxycholesterol) and five sterols (including lanosterol and desmosterol) were analyzed. RESULTS: Strong correlations (r≥0.82) were observed for seven circulating free and total oxysterols/sterols. The free and total form of 27-HC (r=0.63), 25-HC (r=0.54), and two more oxysterols were weaker correlated. Correlation patterns in the panel of total oxysterols/sterols and the panel of free oxysterols/sterols were similar. CONCLUSIONS: These findings demonstrate that concentrations of most free and total oxysterols/sterols are strongly correlated. We provide further insight into the interrelationships between oxysterols in breast cancer patients.

Association analysis identifies 65 new breast cancer risk loci.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Longitudinal changes of health-related quality of life over 10 years in breast cancer patients treated with radiotherapy following breast-conserving surgery.

PURPOSES: The study intended to (1) assess changes of health-related quality of life (HRQoL) between early treatment-related time points and 10 years post-treatment in a cohort of breast cancer (BC) patients who received radiotherapy (RT), (2) to evaluate differences in HRQoL between long-term BC survivors and unaffected women from the same geographical region and (3) to identify determinants of long-term HRQoL in the survivor cohort. METHODS: 292 BC patients were recruited prior to RT after breast-conserving surgery between 1998 and 2001 in Germany and prospectively followed up for a median of 11.4 years (range 10.3-12.8 years). HRQoL was assessed using EORTC QLQ-C30 at pre-RT (baseline), during RT, 6 weeks after RT, and at the 10-year follow-up. Changes in mean HRQoL scores over time were assessed using linear-mixed models. HRQoL in long-term survivors and controls was compared using Wilcoxon rank-sum test, stratified by age groups. Multivariable linear regression models were used to identify determinants for HRQoL in long-term BC survivors. RESULTS: Compared to baseline level (mean summary score of 64.9), global health status/quality of life (GHS/QoL) declined during RT (62.4) and improved 6 weeks after RT (69.9) before decreasing to baseline level at the 10-year follow-up (66.7). Most functional domains deteriorated or remained stable at 10 years post-diagnosis compared to post-RT scores, except for role functioning which improved, while dyspnea and diarrhea significantly deteriorated between those two time points. There were no significant differences in long-term GHS/QoL between BC survivors 10 years post-RT and controls for all age groups (p > 0.05). However, deficits in specific HRQoL domains such as emotional burden, sleep problems or fatigue were found to more strongly affect survivors, in particular those younger than 65 years, compared to controls. In the determinant analysis, being overweight was associated with lower GHS/QoL and physical functioning, while living with others was found to be associated with better physical functioning, and decreased dyspnea and pain levels. Certain comorbidities such as depression had a strong association with multiple HRQoL domains, including lower GHS/QoL and functioning as well as a higher level of fatigue, pain, sleep/intestinal problems, and financial difficulties. Side effects such as lymphedema/pain and fibrosis were associated with worse physical and social functioning, respectively. CONCLUSION: The long-term GHS/QoL remained comparable when compared with the control population while restrictions in certain functional and symptoms domains in long-term BC survivors persisted over 10 years, in particular among younger survivors. Targeted screening to identify cancer survivors at risk for psychosocial/other impairment accounting also for comorbidities and treatment side effects may be warranted in long-term aftercare to address unmet health needs.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes.

BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.