Heritable rare high- and moderate-risk mutations in breast cancer susceptibility genes are known of, alongside 170 common genetic low risk variants with a minor increase in risk. However, based on genetic studies, we know that over half of the breast cancer heritability is still unexplained. By analyzing combinations of chromosomal nearby variants, so-called haplotypes, and their association to breast cancer we could identify a novel genetic breast cancer risk locus on chromosome 8 and confirm three well known low risk loci on Chr 10, 11 and 16.p 3.92 × 10−8), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2–25 and 113 risk haplotypes of window size 50 at p < 5 × 10−8 on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68. (4) Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.(1) Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility. (2) Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1–25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls. (3) Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08;  The inherited genetic background of breast cancer is only partly understood. Epidemiological studies have shown breast cancer to be approximately twice as common in first degree relatives of breast cancer patients compared to the general population . There aThe majority of known low risk loci have been identified through large Genome Wide Association Studies (GWAS), based on Single Nucleotide Polymorphism (SNP) association, conducted within the Breast Cancer Association Consortium (BCAC) ,9,10. SNThe aim of this study was to identify breast cancer risk haplotypes in the Swedish population. Therefore, we were prompted to reanalyze two Swedish breast cancer cohorts—KARMA and KARBAC—consisting of 3200 invasive breast cancer cases and 5021 controls previously analyzed within the BCAC consortium ,17,18,19n = 2712) and KARBAC (n = 503), and controls without family history of breast cancer from KARMA (n = 5032) in the analysis. The cohorts are thoroughly described elsewhere and previously analyzed in several BCAC studies [n = 394) is a hospital cohort of consecutive breast cancer cases recruited from October 1998 until May 2000 [n = 109) is a BRCA1- and BRCA2 negative breast cancer cohort recruited from a clinical genetic counselling department from February 2000 until January 2012 [We included 3215 invasive breast cancer cases from two Swedish cohorts, KARMA . Familial breast cancer cases were defined as individuals affected by breast cancer with a first degree relative diagnosed with breast cancer. The same KARMA controls, as in the overall breast cancer study, were used.p < 0.001 (634 markers removed). No individual was removed due to missing genotype data. In the last step of QC a Multi-Dimensional Scaling (MDS) analysis was conducted to identify ethnic outliers [DNA was extracted from peripheral blood samples using standard procedures. DNA from 8247 individuals were genotyped with an Illumina Infinum OncoArray-500K B BeadChip ,24. A tooutliers . The MDSp value criteria for genome-wide statistical significance was applied, i.e., p < 5 × 10−8 was considered statistically significant [p-values along the chromosomes (https://github.com/patrickbryant1/CMM/blob/master/hap_vis.py) (accessed on 24 February 2022) after which the haplotypes were sorted on OR and illustrated in We performed a sliding window haplotype GWAS using PLINK 1.07 from a window size of (wdw) 1 to 25 SNPs using a logistic regression model to examine the effect of a SNP or a haplotype of various length on the risk of breast cancer ,28. In tnificant . No corromosomes . The QQ p-value for each locus on Chr 8, 10, 11 and 16. All significant breast cancer risk SNPs and haplotypes of various lengths on Chr 10, 11 and 16 were sorted based on OR and are illustrated in p-value is indicated with a star, which chromosomal position is outlined in red, and the haplotype with the lowest p-value is indicated with a black rectangle. The position of previous published SNPs from the BCAC collaboration, in this study called “BCAC SNPs”, are outlined in yellow. In the plots, the x-axes are compressed for the loci including many haplotypes to be able to illustrate them all. All overlapping significant SNPs and haplotypes have identic alleles on a given position. The subloci  in 11q13.3 . Similarp-value  within t within the CASC16 gene.We identified 49 significant risk SNPs and 2553 significant risk haplotypes  in 16q12.1-16q12.2 . Similarp-value ; sublocup-value  and subl p-value  includes pattern b. Again, pattern , compareIn order to increase power only invasive cases and controls without a family history of breast cancer were used in our study. To test the hypothesis that removing cancer in situ and familial controls would increase power the full data set, including cancer in situ and familial controls, was reanalyzed for Chr 8, 10, 11 and 16 with similar results for Chr 10, 11 and 16, whereas the locus on Chr 8 was not identified.BNIP3L is located in the region of the novel locus and encodes a proapoptotic protein [BNIP3L as a breast cancer gene, why nearby genes or transcripts are suggested to be the target for LOH at 8p21 in breast cancer [BNIP3L gene is still of interest and a recent publication suggested a BNIP3L dependent pathway to be a target for cancer therapy in a subgroup of triple negative breast cancer [FGFR2, CCND1 and TOX3—have been thoroughly discussed in relation to breast cancer [TOX3, in the area of the CASC16 gene, but considered to be causative through a TOX3 gene effect, whereas three of our novel subloci on Chr 16 are located within the TOX3 gene itself [FGFR2 on 10q26.13 and CCND1 on 11q13.3, while the relation to the gene TOX3 on 16q12.1-16q12.2 was less clear. This could possibly relate to our finding of two loci at this target, TOX3 and CASC16. The genes FGFR2, CCND1 and TOX3 are still not studied much in relation to the roles in breast cancer although genetic studies have suggested their involvement in cancer risk. FGFR2 has been suggested to be implicated in breast cancer as a target for therapeutic strategies [CCND1 is frequently mutated by copy number variation and suggested as a prognostic biomarker [TOX3 in relation to breast cancer is less clear. However, TOX3 has been shown to stimulate estrogen in ovarian granulosa cells, suggesting a role in breast cancer pathogenesis [CASC16 to correlate to breast cancer susceptibility [In the search for founder haplotypes, we reanalyzed genotype data from Swedish samples included in the BCAC by performing both a haplotype and SNP GWAS of 3200 Swedish invasive breast cancer cases and 5021 controls. We identified a novel locus on Chr 8 and confirmed and fine-mapped three of the known breast cancer risk loci on Chr 10, 11 and 16 with haplotype analysis. Within the three known loci, novel subloci were identified. Top risk haplotypes presented higher ORs than top risk SNPs at the same locus. The novel breast cancer susceptibility locus 8p21.2 has been discussed before in a cancer perspective. Zeegers et al. presented strong evidence for 8p21.1-8p21.3 to harbor prostate cancer susceptibility genes, which confirmed previous prostate cancer GWAS findings . The gen protein . Loss of protein ,36. Lai t cancer . Howevert cancer . The gent cancer ,40,41,42t cancer . Interese itself . The resrategies , CCND1 iiomarker . The rologenesis . Moreovetibility .p-value on Chr 16 was similar to the OR of the significant single SNP with the lowest p-value. The haplotype effect is suggested to depend on whether nearby SNPs act together in a risk generating or protective mode. You could therefore hypothesize that protective subloci could be involved as well at the locus on Chr 16. The risk SNPs were consistent with previous BCAC results (Haplotype analysis could identify a novel breast cancer susceptibility locus in 8p21.2, whereas SNP analysis could not. The haplotype in 8p21.2 is rarer than the haplotypes in the known loci and could be a founder haplotype that happens to have reached a frequency that makes it detectable. When unfiltered cases and controls were used for analysis, the region was not identified, which could be explained by the increased power of the filtered analysis where only invasive cases and controls without a family history of breast cancer were used. Replication of this locus is required for confirmation, but previous findings in other tumor types in the Swedish population support the use of haplotype analysis, in addition to SNP analysis ,13,14,15 results . Enrichm results . This coThis study has a smaller sample size compared to previous published breast cancer GWASs within the BCAC collaboration including our samples ,17,18,19The level chosen for statistical significance could be discussed. Haplotype analysis include multiple testing, but numerous overlapping haplotypes are generated. We assume that all haplotypes in each sublocus reflect the same genetic risk locus, and therefore no correction for multiple testing was performed.In conclusion, this haplotype GWAS, using Swedish breast cancer cases and controls, demonstrated that haplotype analysis could give novel and more detailed information on risk variants in addition to single SNP analysis. However, haplotype analysis most often requires a fairly homogenous population. Genetic risk is enriched in familial cases and thus haplotype analysis in homogenous populations of familial cases could potentially identify novel risk loci even in small study populations. We identified a novel breast cancer risk locus in 8p21. Further replication of this locus is required. Most importantly, there is clear support of founder variants at the three known loci on Chr 10, 11 and 16, but our study did not support any other previously reported loci. Future studies in haplotype regions could define causative variants to be used in genetic testing and risk prediction.


The significance of exogenous hormone manipulation as part of fertility treatment and its relationship to the development of breast cancer remains uncertain. Several historical reviews have been performed with conflicting results. This study is an updated meta-analysis to determine whether there is a causal relationship between different fertility treatments and breast cancer.in vitro fertilization (IVF) practice. This study was prospectively registered on PROSPERO on 07/04/2021, registration identification CRD42021247706. The primary outcome of the study was to determine whether there is an increased incidence of breast cancer in women treated with hormonal fertility treatment. The secondary outcomes were to determine whether fertility treatments were individually associated with excess breast-cancer risk.The study report is based on the guidelines of PRISMA and Meta-Analysis of Observational Studies in Epidemiology. Studies published within the last 20 years were included to reflect up to date Overall, 25 studies, including 617 479 participants, were eligible for inclusion. There was no significant breast-cancer risk association with fertility treatment . Summary odds ratio of all included studies was 0.97 (95 per cent c.i. 0.90 to 1.04). Women who received six or more IVF cycles did not have an increased risk of breast cancer. Similarly, there was no excess breast-cancer risk associated with clomiphene, human chorionic gonadotropin, gonadotropin analogues and progesterone when examined individually. Comparably, there was no significant association between fertility treatment and excess breast-cancer risk in patients with more than 10 years’ follow-up. Summary odds ratio was 0.97 (95 per cent c.i. 0.85 to 1.12).This meta-analysis did not find a significant association between fertility treatments and excess breast-cancer risk. Women considering IVF should be informed that it does not appear to increase breast-cancer risk. This meta-analysis of 25 studies published within the last 20 years did not find a significant association between fertility treatments and excess breast-cancer risk. Women considering IVF should be informed that IVF does not appear to increase breast-cancer risk. Prolonged oestrogen exposure is an established risk factor for developing oestrogen-positive breast cancer2. Since the first in vitro fertilization (IVF) baby was born in 1978, the use of IVF has increased exponentially3. It is estimated that at least 9 per cent of couples experience some form of infertility and 56 per cent of these couples will seek medical treatment for this4. In 2010, 1 per cent of all children born in the USA, 2 per cent of children in the UK and almost 4 per cent in Denmark and Finland were conceived through IVF5. The steady increase in IVF use can be attributed to the significant postponement of child-bearing in the western world6. The mean maternal age at first birth is trending upwards with the mean age approaching 30 years in several European countries and many women are delivering their first child aged 35 years or older7. As nulliparity and delayed childbearing are risk factors for developing breast cancer due to excess endogenous oestrogen exposure, there is significant anxiety surrounding the potential confounding risk of IVF9.Breast cancer is the most common malignancy amongst reproductive women worldwide10. Such therapies include ovarian-stimulating agents such as clomiphene, human chorionic gonadotropin (HcG) and gonadotropin analogues. They are administered during the follicular phase of the menstrual cycle to increase the serum concentration of gonadotropins, targeting follicle maturation and ovulation11. Ovulation induction is just one aspect of fertility treatment. To prevent spontaneous ovulation and hyperstimulation, continuous gonadotropin-releasing hormone (GnRH) analogue therapy is sometimes administered to suppress pituitary gonadotropin release. Progesterone therapy is also supplemented to support the luteal phase of ovulation in the presence of GnRH analogues13. Several reviews have been performed to determine whether there is a causal association between breast cancer and fertility treatment. In 2013, Sergentanis and colleagues did not find a correlation between overall breast-cancer risk and IVF, however they reported that women who received IVF aged less than 30 years had marginally adverse outcomes (pooled effect estimate 1.64 (95 per cent c.i. 0.96 to 2.80))14. In the same year, another meta-analysis conducted by Li and co-workers reported a protective effect of fertility treatment in the subgroup of breast-cancer patients (risk ratio 0.79 (95 per cent c.i. 0.65 to 0.95))15. A more recent review by Gennari and co-workers in 2015 reported an increased risk of breast cancer with longer follow-up (less than 10 versus greater than 10 years) in patients who had fertility treatment10.The significance of exogenous hormone manipulation for fertility treatment is a conflicting area. In contrast to hormone replacement therapy (HRT), fertility treatment induces transient high levels of circulating oestrogen to initiate ovulation in women with anovulatory disorders and control hyperstimulation in women receiving assisted reproductive technology (ART)16. Similarly, a recent study conducted in the UK of over 250 000 women did not report any excess overall breast-cancer risk with IVF but suggested an increased incidence of breast carcinoma in situ with increasing number of cycles17. In contrast Reigstad and colleagues studied a cohort of women from the Medical Birth Register in Norway and found that women exposed to ART had an elevated risk of breast cancer, which became more apparent with greater than 10 years’ follow-up18. As a result of the current conflicting literature, an updated meta-analysis has been performed to determine whether there is a causal association between different fertility therapies and breast cancer.Since publication of these reviews, several large population-based studies have been conducted. Van den Belt-Dusebout and colleagues studied a population of 25 108 women and reported that breast-cancer risk amongst IVF-treated women was not significantly different from that of women with subfertility who did not receive IVF, with a median follow-up of 21 years19 . Analysis and results were extracted from previous ethically approved studies therefore patient consent and ethical approval were not required. This study was registered prospectively on PROSPERO on 7 April 2021, registration identification CRD42021247706.The study report is based on the guidelines of PRISMA and Meta-Analysis of Observational Studies in Epidemiologyin-vitro fertilisation OR in vitro fertilisation OR fertility treatment OR assisted reproductive technology OR clomiphene) AND (Breastcancer (Mesh) OR breast cancer OR breast tumour OR breast carcinoma) AND (Incidence (Mesh) OR risk). All titles were initially screened, and appropriate abstracts were reviewed. Each of the publications’ bibliographies and Google Scholar were manually searched for relevant articles. The last date of search was 31 March 2021.An electronic search was conducted using the Cochrane library, Sciencedirect, PubMed and Embase. All studies from January 2000 to January 2021 were included. The following search terms/MESH terms were used: (IVF (Mesh) OR in situ and more than five cycles of IVF17. Subgroup analysis of studies that used subfertility cohorts as reference groups was also performed to reduce potential confounding. The quality of the studies included was assessed using the Newcastle–Ottawa scale20. The risk of bias was assessed using the Risk of Bias in Non-Randomized Studies of Intervention Tool21. Publication bias was assessed using visual inspection of the forest plots.The primary outcome was to determine whether there is an increased incidence of breast cancer in women treated with hormonal fertility treatment. The secondary outcomes were to determine whether individual fertility treatments such as clomiphene, HcG, gonadotropins and progesterone were associated with excess breast-cancer risk. Subgroup analysis was performed to elucidate whether increasing number of IVF cycles (six or more cycles) and longer duration of follow-up were associated with an increased incidence of breast cancer. Six cycles or more was the arbitrary cut-off point due to previous data suggesting an association between breast carcinoma To be included in the analysis, the studies had to meet the following criteria: subjects received fertility treatment and breast-cancer incidence expressed and publication date within the last 20 years to reflect more up-to-date IVF practice.BRCA mutation carrier) were included, and if they did not present standardized incidence ratio, odds ratios, risk ratios or hazard ratios estimates , or number of events necessary to calculate these for the outcomes of interest. Studies that included patients with a previous personal history of breast cancer, and those that included non-hormonal ART only  were also excluded.Studies were excluded from the analysis if published in languages other than English (for English proficiency reasons), if patients with genetic mutations increasing individuals’ risk of developing breast cancer  independently reviewed the available literature according to the above predefined strategy and criteria. Each reviewer extracted the following variables: title and study details , study population characteristics .Statistical analysis was performed using Review Manager 5 . Binary outcome data were reported as risk ratios with 95 per cent confidence intervals using the Mantel–Haenszel method. Risk ratios or odds ratios reported in the study publication were used when available; otherwise, they were extrapolated from the available data. Weighted mean differences were calculated for the effect size on continuous variables. Odds ratio greater than 1.00 indicated higher breast-cancer risk with fertility treatment.I2 statistics, with greater than 50 per cent being considered significant heterogeneity. A fixed-effects model was preferred to a random-effects model when there was no significant heterogeneity and vice versa when there was significant heterogeneity (I2 greater than 50 per cent). Pooled estimates of differences were calculated using random-effects models, accounting for potential interstudy heterogeneity. P <0.050 was considered significant.Heterogeneity was assessed by 22–42 . Two studies were prospective cohort studies39 and two studies were case–control studies38. The other 21 studies were historical cohort studies40–42. Studies from Asia, Europe, Australia and North America were included. Twenty-one studies reported the incidence of breast cancer amongst women who received fertility treatment40–42, whilst the other four studies examined the number of patients with breast cancer who received fertility treatment using a reverse causation approach39. Study follow-up periods ranged from 3.6–30 years with seven studies including data with over 10 years of follow-up40. All 25 studies included multiple regimens of IVF22–42. Ten studies used women with infertility as a reference group41, 12 studies used the general population as a comparison42 and the remaining three studies examined a cohort of women with breast cancer who did or did not have a history of IVF use38.Overall, 25 studies, including 617 479 participants, were eligible for inclusion for analysis31–42. Studies including the general population and infertile cohorts as reference groups were pooled together. Date of publication ranged from 2001 to 2020. The odds ratios for each of these studies and the summary odds ratio are shown in Fig. 2. There was no significant breast-cancer risk association with fertility treatment. Summary odds ratio was 0.97 (95 per cent c.i. 0.90 to 1.04). Heterogeneity testing demonstrated significant heterogeneity between the studies  .Twenty-four studies were eligible for inclusion for analysis of overall breast-cancer risk associated with all fertility treatment38. The odds ratios for each of these studies and the summary odds ratio are shown in Fig. 2. There was no significant association between breast cancer risk and clomiphene administration, odds ratio 1.07 (95 per cent c.i. 0.98 to 1.16). There was no significant heterogeneity between the studies  .Nine studies reported the incidence of breast cancer in women who received the ovulation induction agent clomiphene28–30. Similarly, there was no significant association between breast-cancer risk and HcG fertility treatment (odds ratio 0.91 (95 per cent c.i. 0.81 to 1.03)) with no heterogeneity between the studies . However, one study constituted 48.5 per cent of the weighted mean.Five studies were eligible for inclusion in the analysis of breast-cancer risk associated with HcG fertility treatment30. Breast-cancer risk was not significantly associated with progesterone treatment (odds ratio 1.11 (95 per cent c.i. 0.76 to 1.61)). Significant heterogeneity was observed between the studies  .Four studies examined the association between breast-cancer incidence and progesterone fertility treatment38. There was no significant association between gonadotropin analogues and breast-cancer incidence (odds ratio 1.03 (95 per cent c.i. 0.95 to 1.13)) .The associated risk between breast-cancer incidence and gonadotropin fertility treatment was examined in seven studies, with one study contributing 82.7 per cent to the overall weight mean38. An increased incidence of breast cancer in women who received six or more cycles of fertility treatment was not observed (odds ratio 0.92 (95 per cent c.i. 0.73 to 1.16)). There was significant heterogeneity between the studies  .To determine whether an increasing number of cycles of IVF were associated with excess breast-cancer risk, an analysis of six eligible studies was performed40. There was no significant association between fertility treatment and excess breast-cancer risk in patients with greater than 10 years’ follow-up (OR 0.97 (95 per cent c.i. 0.85 to 1.12)) with significant heterogeneity between the studies  .Seven studies included patients with greater than 10 years’ follow-up41. As Jensen and colleagues did not report overall breast-cancer risk associated with all fertility treatment, the most commonly used regime described (clomiphene and gonadotropins) was included in this analysis30. There was no excess breast-cancer risk observed in this subgroup (odds ratio 0.99 (95 per cent c.i. 0.92 to 1.08); I2 = 64%, P = 0.003) .Ten studies included women with subfertility as a reference group when analysing breast cancer riskThis is the largest meta-analysis in the past 20 years on the incidence of breast cancer associated with fertility treatment. There was no significant association demonstrated between fertility treatments and excess breast-cancer risk. The null hypothesis remained consistent when fertility treatment options such as clomiphene, gonadotropins, HcG and progesterone were examined individually.43. If follicular development has occurred, HcG is administered 36 h prior to oocyte retrieval and progestogens or HcG are administered as luteal phase support for embryo implantation16. Clomiphene is the most commonly used agent to induce ovulation induction for women with anovulatory infertility and is often administered alone in the minimal ovarian-stimulation protocol for IVF45. Clomiphene is similar to tamoxifen as they are both selective oestrogen-receptor modulators. Selective oestrogen-receptor modulators are thought to act primarily by binding with oestrogen receptors in the hypothalamus and this competitive inhibition results in a perceived drop in endogenous oestrogen levels, eventually leading to increased gonadotrophin secretion and subsequent induction of ovulation45.IVF is a complex process involving several phases, treatment schedules and multiple drug regimens. Typically, in the first phase of controlled ovarian stimulation, a woman’s natural menstrual cycle is downregulated via administration of GnRH, followed by ovarian stimulation with gonadotropins causing a surge of oestrogen and progesterone levels40. However, after adjusting for important confounding reproductive factors of age at first birth and total parity, the excess risk was only observed in women referred for infertility due to non-ovulatory factors who received four or more cycles of clomiphene )40. Findings from the present meta-analysis, however, did not find a significant association between clomiphene use and excess breast-cancer risk.In contrast to the effects of tamoxifen, an elevated incidence of breast cancer treated with clomiphene was reported by Orgeas and colleagues in a cohort of 824 patients30, however this was not reproducible in other studies29. Progesterone is mainly used as a routine treatment in most IVF/intracytoplasmic sperm injection protocols to enhance implantation of the fertilized eggs since it increases thickening of the endometrial lining30. As progesterone is often included as part of a regimen of multiple fertility drugs, the independent effect of progesterone on excess breast-cancer risk is difficult to establish. Jensen and co-workers also reported on the confounding potential of multiple administration of fertility drugs and concluded that the excess breast-cancer risk associated with progesterone use could be attributed to other types of fertility drugs and their combined effects30. The combined effects of progesterone with other fertility drugs did not appear to convey an increased risk of breast cancer in the present analysis.In 2007, Jensen and co-workers reported a four-fold increased risk of ductal breast cancer after use of progesterone46. Schüler-Toprak and colleagues suggest that mimicking pregnancy by treatment with HcG is a potential strategy for breast-cancer prevention46. There was no such protective association between breast-cancer risk and HcG noted in subgroup analyses of the included studies. Similarly, an adverse effect of gonadotropins on breast-cancer risk was reported by Burkman and co-workers23 and Taheripanah and colleagues38. Whilst gonadotropins do not directly affect breast tissue, they may increase circulating oestrogen levels during the follicular phase of ovulation-induction cycles and have an indirect influence on breast tissue30. Both Jensen and co-workers30 and Brinton and colleagues47 reported a higher breast-cancer risk associated with use of gonadotropin analogues among women who remain nulliparous but the lack of parity could be attributing to this excess risk.HcG exerts its effect by triggering ovulation after induction of follicular growth and development with administration of gonadotropins. The role of HcG in breast cancer is paradoxical. Placental HcG acts as a protective agent of the mammary gland by determining a refractory condition to malignant transformation which is characterized by cellular differentiation, apoptosis and growth inhibition. Conversely, ectopic expression of β-HcG in various cancer entities is associated with a poor prognosis due to its tumour-promoting function48. Subgroup analysis of the 10 studies that used women with infertility problems as a reference group was performed to combat confounding from infertility and there was no excess risk observed. All studies used a retrospective study design to collect data and are therefore subject to information bias, as patients with infertility may have been exposed to alternative hormonal treatments outside of the remit of conventional IVF. The impact of such treatments on breast-cancer risk cannot be estimated due to study methodology limitations.One of the major challenges with studying the influence of fertility treatment on breast-cancer risk is the confounding associated with underlying causes of fertility. Nulliparity and infertility are associated with an increased risk of breast cancer, therefore comparisons with the general population may lead to inaccurate effect estimates46. Katz and colleagues studied a cohort of women who received a similar IVF regimen and compared breast-cancer incidence between those that did and did not develop breast cancer to identify women who are at increased risk of developing breast cancer after IVF31. Being aged over 30 at first IVF cycle was associated with a significantly elevated risk of developing breast cancer even after controlling for age at first pregnancy. Similarly Pappo and co-workers reported an increased incidence of breast cancer among women with hormonal infertility who were 40 or older and who underwent four or more IVF cycles35. They did not adjust for age at first pregnancy or address the fact that women over 40 having multiple cycles of IVF are likely to be nulliparous which could be contributing to their increased cancer risk. To determine whether there is a significant increased risk of cancer in women treated with IVF at an advanced age, Tsafrir and colleagues studied a cohort of 501 patients with a mean age at first IVF cycle of 42.3 years and greater than 10 years’ follow-up40. The incidence of breast cancer in women who received IVF was not associated with an excess risk at long-term follow-up. In contrast Stewart and colleagues compared breast-cancer incidence in a cohort of women undergoing treatment for infertility, comparing the rate in women who had IVF and those who did not and reported an increased rate of breast cancer in women who commenced IVF at a young age41. The authors highlighted the fact that information on other important risk factors for developing breast cancer, such as family history, germline mutation status and age of menarche, were not available and could have resulted in confounding of the results.Breast-cancer incidence and associated death increase proportionally with age. Throughout the world, this disease peaks around age 60 years, with a sharp incline beginning at age 4023 and Taheripanah and co-workers38 both reported an increased incidence of breast cancer with multiple IVF cycles (more than six cycles) and/or greater than 6 months of IVF treatment. However, it is worth noting that both studies collated data using non-specific patient questionnaires without medical record verification, which raises the possibility of recall bias. In the present meta-analysis, to elucidate whether there is a causative relationship between multiple IVF cycles and breast-cancer incidence, a subgroup analysis was performed which did not show a significant association between breast-cancer risk and six or more IVF cycles. Due to the growing evidence base in reproductive medicine, seven out of the 25 studies had greater than 10 years’ follow-up. Subgroup analyses of the studies with long-term follow-up did not demonstrate an association between excess breast-cancer risk and IVF use.Burkmann and colleaguesBRCA1 and BRCA2), was not analysed, however the evidence suggests that IVF is safe in patients with such mutations. A recent study performed by Derks-Smeets and colleagues on a cohort of 2514 women with BRCA mutations reported that no evidence was found for an association between ovarian stimulation for IVF and breast-cancer risk in BRCA1/2-mutation carriers49. Similarly, Kotsopoulos and colleagues performed a matched case–control study on 1380 pairs of women with BRCA mutations to determine if IVF was associated with an increased risk of breast cancer; no such association was found50. Provisional data from these studies suggest ovarian stimulation and IVF for fertility preservation due to BRCA-mutation status is safe. Similarly, studies which included patients with a previous history of breast cancer were not included in the present meta-analysis. Fertility preservation prior to commencement of chemotherapy is an option for women who wish to consider future pregnancies. Oocyte/embryo cryopreservation is the most well established and successful option for fertility preservation; it is, therefore, the recommended option for women with sufficient ovarian reserve who are medically stable to undergo controlled ovarian stimulation51. Ovarian stimulation causes an increase in the level of circulating oestrogen, and accordingly, many fertility-preservation programmes administer an aromatase inhibitor concurrently51. Due to the variability in regimes administered to women with a previous history of breast cancer, this cohort was omitted from the present meta-analysis.The potential risk of IVF treatment in the setting of germline mutations, such as breast cancer gene (16. More recent IVF strategies largely consist of protocols with antagonists and shorter periods of downregulation, and improved success rates and therefore it is uncertain whether the results of this study can be generalizable to newer regimens.There are several limitations to this study. Many of the studies included were retrospective cohort studies derived from national databases and therefore subject to recall and information bias. Data collated from the databases were often deficient of important information such as family history, HRT exposure, BMI, smoking, alcohol use and age of menarche, all of which are important risk factors for developing breast cancer and potential confounders. Twelve of the studies used the general population as a reference group. Women treated with IVF are likely to differ from the general population due to parity, age of first birth, age of menarche and age of menopause and these factors should be adjusted for when considering excess breast-cancer risk. Several large population-based studies with greater than 10 years’ follow-up were included in the analyses. One of the challenges with these studies is that during the study period, IVF regimens and strategies changed significantly as the number of ampoules of gonadotropins used increased until 1990 and decreased thereafterThis meta-analysis of 25 studies published in the past 20 years did not find a significant association between fertility treatments and excess breast-cancer risk. The same remained consistent when fertility treatment options such as clomiphene, gonadotropins, HcG and progesterone were examined individually. Women considering IVF should be informed that IVF does not appear to increase breast-cancer risk.zrab149_Supplementary_DataClick here for additional data file.


A decreased level of serum adiponectin is associated with obesity and an increased risk of breast cancer among postmenopausal women. Yet, the interplay between genetic variants associated with adiponectin phenotype, obesity, and breast cancer risk is unclear in African American (AA) women.We examined 32 single-nucleotide polymorphisms (SNPs) previously identified in genome-wide association and replication studies of serum adiponectin levels using data from 7,991 AA postmenopausal women in the Women’s Health Initiative SNP Health Association Resource.2, the minor TT genotype of FER rs10447248 had an elevated breast cancer risk. Interaction was observed between obesity and the CT genotype of ADIPOQ rs6773957 on the additive scale for breast cancer risk . The joint effect of BMI ≥ 30 kg/m2 and the TC genotype of OR8S1 rs11168618 was larger than the sum of the independent effects on breast cancer risk.Stratifying by obesity status, we identified 18 adiponectin-related SNPs that were associated with breast cancer risk. Among women with BMI ≥ 30 kg/mWe demonstrated that obesity plays a significant role as an effect modifier in an increased effect of the SNPs on breast cancer risk using one of the most extensive data on postmenopausal AA women.The results suggest the potential use of adiponectin genetic variants as obesity-associated biomarkers for informing AA women who are at greater risk for breast cancer and also for promoting behavioral interventions, such as weight control, to those with risk genotypes. It ccer risk –6. This cer risk –9. Durincer risk . The conADIPOR1 and ADIPOR2) in breast cancer cells  was associated with an increased risk of breast cancer in some studies  that were associated with functional and structural regulation of adiponectin and their association with breast cancer risk; but the findings were inconsistent and conducted mostly in population with European or Asian ancestry –25. In p studies , 23, but studies . No cons studies –24. Of te  , 29–35. The study included postmenopausal women aged 50 to 79 years enrolled in the WHI Clinical Trial and Observational Study that was conducted from 1993 to 2005. The details of its study design and method are described elsewhere , 37. BriFor the purpose of our study, subjects must meet the following inclusion criteria to be included in the study analysis: the subjects (i) were AA postmenopausal women aged 50 to 79 years; (ii) without a diagnosis of cancer at the time of study enrollment (except non-melanoma skin cancer); and (iii) reported at least one of four physical measurements . Assuming that those who ended participation early are more likely to have incomplete outcome information leading to potential follow-up bias, the study excluded those who had been followed up for less than 1 year. In addition, individuals who had developed invasive breast cancer within the 1-year follow-up period were excluded to avoid the potential effects of reverse causation between obesity and invasive breast cancer risk.Of 50,256 participants, a total of 8,380 identified their race or ethnicity as AA. We excluded 372 subjects who reported a diagnosis of any type of cancer at the time of enrollment, and two subjects who were missing information on all four physical measurements. Further, we excluded 15 participants who had developed invasive breast cancer within the 1-year follow-up period. There was no withdrawal or cessation of participation within the 1-year follow-up period. After applying the eligibility criteria, a total of 7,991 subjects were included in the analysis. Of 7,991 participants, 402 (5.0%) of the eligible women, greater than the breast cancer incidence of AA postmenopausal women in the US Figure 1Self-reported invasive breast cancer cases were verified by adjudication of medical records in all participants of all phases of the WHI studies . As a re2), normal (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), and obesity (≥ 30 kg/m2) , and waist circumference (WC). Each index was considered as a potential effect modifier to estimate its effect on the association between adiponectin-related SNPs and breast cancer among AA women. Also, these indices were each separately considered as a confounder of the relationship. Trained research personnel measured anthropometric measurements as continuous variables at the baseline . We used0 kg/m2) . WHR use0 kg/m2) , and WC 0 kg/m2) .ADIPOQ  that were in high linkage disequilibrium at a pairwise r2 threshold of 0.80. Of the 32 candidate SNPs, 8 SNPs were located within or nearby ADIPOQ or adiponectin receptor genes  and its 95% confidence intervals (CIs) for an effect of each SNP in predicting breast cancer development using a Cox proportional hazards regression model. Prior to fitting the model, the proportional hazard assumption was verified using the Schoenfeld residuals.vs. no), depressive symptom , smoking status (ever smoke vs. no), age at menopause (year), number of pregnancies , exogenous estrogen use ever (yes vs. no), exogenous estrogen and progesterone use ever (yes vs. no), diabetic status (yes vs. no), dietary alcohol per day (gram), dietary total fat (gram), and physical activity . We performed a complete case analysis excluding study participants with missing data in covariates. All 7,991 participants had data on age at baseline for fitting model 1, and a total of 6,121 participants (77%) were eligible for fitting model 2.For each SNP, two sets of adjusted models were used, with the first adjusting for only age at baseline (Model 1) and the second adjusting for all covariates (Model 2). Covariates included in the analysis as potential confounding factors were measured at the baseline: age at baseline (year), family income , employment status , the mean WHR was 0.82 , and the mean WC was 91.3 cm . Characteristics of participants were generally balanced between those with and without breast cancer.Of 7,991 subjects, 402 (5.0%) reported developing breast cancer Table 1.OR8S1 rs11168618  was correlated with a lower risk of breast cancer compared to the major CC genotype  in model 1. The heterozygous TC genotype of EIF4A2 rs266719 (T/C) decreased breast cancer risk compared with the major CC genotype in model 2 . The heterozygous CA genotype of KCNK9 rs2468677 (C/A) had increased breast cancer risk compared with the major AA genotype; however, it was found to be statistically significant only in model 2 with an additional adjustment for BMI . After adjustments for multiple testing, those SNPs did not reach the significance level. Further, the assessment of confounding by BMI, WHR, and WC on the SNP-breast cancer relationship revealed that a confounding effect is unlikely to be a concern.Among 32 adiponectin-related SNPs Table 2.vs. ≥0.85), and WC (<88 cm vs. ≥88 cm), respectively. The effects of obesity status on the relationship between several SNPs and breast cancer differed between strata. In model 1, the heterozygous TC genotype in OR8S1 rs11168618 (T/C) was inversely associated with breast cancer risk among individuals with under/normal weight, overweight, WHR <0.85, and WC <88 cm. However, the significance was no longer observed in model 2. There was also a possible interaction of BMI ≥30 kg/m2 with the heterozygous TC genotype in OR8S1 rs11168618 (T/C) .ADIPOQ gene, the heterozygous CT genotype in rs6773957 (C/T) was negatively associated with breast cancer risk among individuals with under/normal weight by roughly 60% in model 2. An interaction between BMI ≥30 kg/m2 and the heterozygous CT genotype was observed with a RERI of 0.62 with 95% CI of 0.32 to 0.92. Among those with WC <88 cm, the heterozygous CT genotype in rs6773957 (C/T) appeared to have a lower risk of breast cancer compared with the major CC genotype . WC ≥88 cm showed an RERI of 0.47 with 95% CI of 0.33 to 0.62, suggesting super-additivity for the interaction between ADIPOQ rs6773957 (C/T) and WC. In addition, whereas effect alleles in ADIPOR1 rs2232853 (T/C) were associated with an increased risk of breast cancer among White women , women with BMI ≥30 kg/m2 and the minor TT genotype had increased breast cancer risk in comparison to those with major CC genotype by approximately 2-fold in both model 1  and model 2 . When we stratified the analysis by WHR status, different patterns were observed for the association between FER rs10447248 (T/C) and breast cancer risk. Carriers of the heterozygous TC genotype had an elevated risk of breast cancer among WHR <0.85 compared with those with the major CC genotype , whereas the reduced risk among WHR >0.85  in model 1.For OR8S1 rs11168618 (T/C) and EIF4A2 rs266719 (T/C) were negatively associated with breast cancer risk, whereas the heterozygote of KCNK9 rs2468677 (C/A) had an elevated risk. The crude estimates of breast cancer risk did not differ from the adjusted estimates, thus confounding by obesity is unlikely. The findings suggest that low circulating levels of adiponectin may serve as a risk factor for breast cancer, independent of obesity. Indeed, in vivo and in vitro studies have demonstrated a direct effect of adiponectin on breast cancer development with and without obesity environment  were associated with increased risk of breast cancer in a case-control study that consists of predominantly White women aged 20 to 87 years  and having BMI ≥30 kg/m2 had an elevated risk of postmenopausal breast cancer. FER tyrosine kinase increases NF-κβ activation and signals interleukin-6 (IL-6) to regulate STAT3 phosphorylation  that belongs to G protein-coupled receptors influencing tumorigenesis (OR8S1 rs11168618 (T/C), which decreases adiponectin levels (Olfr544) increased adiponectin secretion in 3T3-L1 mouse adipocytes  at University of California, Los Angeles. Part of the data for this project was provided by the WHI program, which is funded by the National Heart, Lung, and Blood Institute, the National Institutes of Health, and the U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


CHEK2 variants have about a 3-fold increased risk of developing breast cancer. CHEK2 is now commonly included in genetic tests for breast cancer predisposition and increasingly used to inform the clinical management of women who are identified to carry pathogenic variants. Important information for counselling these women includes knowing how breast cancer risk, due to having a pathogenic variant in CHEK2, changes over a woman’s lifetime. This information is currently not well established. By conducting a population-based case-control-family study of pathogenic CHEK2 variants we aimed to provide this information and estimated the penetrance (age-specific cumulative risk) of breast cancer to be 18% (95% CI 11–30%) to age 60 years and 33% (95% CI 21–48%) to age 80 years. These findings provide new and important information for the clinical management of breast cancer risk for women carrying pathogenic variants in CHEK2.It is well established that women who carry pathogenic CHEK2 are associated with about a 3-fold increased risk of breast cancer. Information about the recurrent protein-truncating variant CHEK2 c.1100delC dominates this estimate. There have been no formal estimates of age-specific cumulative risk of breast cancer for all CHEK2 pathogenic (including likely pathogenic) variants combined. We conducted a population-based case-control-family study of pathogenic CHEK2 variants  and estimated the age-specific cumulative risk of breast cancer using segregation analysis. The estimated hazard ratio for carriers of pathogenic CHEK2 variants (combined) was 4.9 (95% CI 2.5–9.5) relative to non-carriers. The HR for carriers of the CHEK2 c.1100delC variant was estimated to be 3.5 (95% CI 1.02–11.6) and the HR for carriers of all other CHEK2 variants combined was estimated to be 5.7 (95% CI 2.5–12.9). The age-specific cumulative risk of breast cancer was estimated to be 18% (95% CI 11–30%) and 33% (95% CI 21–48%) to age 60 and 80 years, respectively. These findings provide important information for the clinical management of breast cancer risk for women carrying pathogenic variants in CHEK2.Case-control studies of breast cancer have consistently shown that pathogenic variants in  CHEK2) is an established breast cancer predisposition gene whose protein plays an important role in cell-cycle checkpoint regulation and DNA damage repair [CHEK2 c.1100delC is the most common protein-truncating variant in European populations and has been the focus of work that has estimated the magnitude of breast cancer risk associated with CHEK2 pathogenic variants [CHEK2 c.1100delC estimated an odds ratio (OR) of 2.7  for unselected breast cancer cases and OR 4.8  for women with a family history of breast cancer [CHEK2 c.1100delC carriers have shorter breast cancer-specific survival compared with non-carriers [CHEK2 c.1100delC was 20% to age 80 years [Cell-cycle checkpoint kinase 2  associated with increased breast cancer risk and a substantial proportion of these were missense variants [CHEK2 missense variants identified by Le Calvez-Kelm et al. were incorporated in a custom Illumina Infinium array (iCOGS) as part of a multiconsortia collaboration [CHEK2 c.349A>G and c.538C>T were associated with increased breast cancer risk; OR 2.26  and OR 1.33  respectively [Although stimates ,6,8. Mucm et al.  performevariants . Six of boration ,18. Genoectively .CHEK2 is now included in routine gene panel tests for breast cancer susceptibility which has substantially increased the need to more precisely understand the breast cancer risks associated with rare genetic variants in this gene. As described above, previous work has predominantly estimated breast cancer risk in terms of average relative risks and has been either exclusive to, or dominated by, risks associated with CHEK2 c.1100delC. For the purposes of genetic counseling, in the era of gene panel testing, age-specific cumulative risks (penetrance) are more useful. Often, absolute risk estimates are derived from relative risk estimates, which are likely to be biased due to oversampling by many studies of cases with a family history [ history .CHEK2 in an Australian population-based case-control-family study of breast cancer. This study is focused on disease at an early age and participants were unselected for family history. We estimated the prevalence and penetrance of CHEK2 pathogenic variants in this study sample and discuss the capacity of these findings to further inform risk management strategies for families carrying these pathogenic variants.To address this knowledge gap, we conducted a genetic screen of CHEK2 was identified in 20/1476 (1.4%) case-probands and 7/861 (0.8%) control-probands. There were two carriers of a stop-gain variant, 17 carriers of a frameshifting variant, two carriers of a consensus splice site variant and six carriers of a missense variant (CHEK2 c.1100delC (nine case-probands and three control-probands).Targeted-sequencing was successfully performed on the germline DNA of 1476/1480 (99.7%) case-probands and 861/864 (99.7%) control-probands. A pathogenic (including likely pathogenic) variant in  variant . Of the CHEK2 variant identified in the proband  also carried a pathogenic variant in BRCA1, so this family was excluded from the risk analyses. There were, therefore, 26 eligible families, which included 1071 relatives of the proband, 72 of which had DNA for testing (described above). The risk estimates were effectively based on the 1071 relatives of the remaining 26 probands. These 1071 relatives included 43 female breast cancer cases and one male breast cancer case, though the male case did not affect our estimates because male hazard ratio (HRs) were fixed to be 1. In addition to the 44 relatives with breast cancer, a number of relatives had cancers of other anatomical sites: 16 prostate, 16 bone marrow, 11 intestine, 10 stomach, 9 skin, 8 colorectum, 7 lung, 6 brain and 49 at all other sites combined . The relatives included 28 known carriers and 44 known non-carriers, though ungenotyped people also contributed to our estimates via their phenotypes and their relationships to genotyped people.One of the 27 CHEK2 variants was 4.9 , meaning that carriers are estimated to have breast cancer incidences that are 4.9 times those for non-carriers. There was no evidence that the HR depended on age (p = 1). The HR for carriers of the CHEK2 c.1100delC variant was estimated to be 3.5 (95% CI 1.02–11.6) and the HR for carriers of all other CHEK2 variants combined was estimated to be 5.7 (95% CI 2.5–12.9), though our data were consistent with carriers of the c.1100delC variant having the same risks as carriers of the other CHEK2 variants (p = 0.5).The estimated breast cancer HR for carriers of pathogenic CHEK2 variants combined, cumulative risks for these carriers to various ages were calculated , 4.85 (2.5–9.5) and 4.79 (2.4–9.4) when the combined allele frequency was taken to be 0.001, 0.005 and 0.01, respectively.Sensitivity analyses showed that our main results were robust to changes in the assumed allele frequency within a plausible range. The HR (95% CI) for all pathogenic CHEK2.This important new information supports gene panel testing and clinical management, including genetic counselling, for women who carry pathogenic variants in CHEK2 is consistently found to have a high number of pathogenic variants, usually only surpassed by the number of pathogenic variants identified in BRCA1 and BRCA2 in most settings not involving selection by breast cancer subtype [CHEK2 variants in this population-based study (1.4% of case probands) is consistent with reports from other studies in which panel testing was applied.In gene panel sequencing for breast cancer predisposition,  subtype ,22. The CHEK2 variants [CHEK2 as a bona fide breast cancer predisposition gene but information suitable for estimating age-specific cumulative risk (penetrance) has been lacking. Our population-based case-control-family study provides such information and estimated penetrance of CHEK2 pathogenic variants to be 26%  and 33%  to 70 and 80 years respectively. There is no directly comparable data (generated with similar study design and methodology) from previous literature. The most relevant is the estimate of cumulative risk of breast cancer for carriers of CHEK2 c.1100delc (only) reported by Schmidt et al (2016) who estimated 22% by age 80 [CHEK2 c.1100delC.Case-control studies have estimated a 3-4-fold increased risk of breast cancer associated with pathogenic variants ,24,25,26y age 80 . This esBRCA2  [PALB2  [BRCA1  [CHEK2 on standard cancer predisposition gene panel tests means that many clinical genetics services are already using data related to CHEK2 pathogenic variants to advise women and their families about breast cancer risk management. Appropriate risk management strategies are predicated on robust risk estimates; these include surveillance, but also irreversible clinical decisions such as risk reducing mastectomy.Other breast cancer susceptibility genes that have equivalent information include  31–56%) , PALB2 ( 37–52%)  and BRCA 44–78%) . The met 44–78%) ,30,31. F 44–78%) ,28). TheBRCA1, BRCA2 and CHEK2 and the amplicon-based approaches used in this study only enable the detection of single nucleotide substitutions and small insertion and deletions. The probands participating in the ABCFR resources have previously been systematically screened for large genomic rearrangements in BRCA1 and BRCA2 [CHEK2 and thus unidentified carriers of large rearrangement events in CHEK2 may exist in the study resources. Our analyses were limited to variants that were classified as pathogenic in ClinVar. An expert panel oversees BRCA1 and BRCA2 variant classification reported in ClinVar but the equivalent ClinVar expert panel (and rules) for classification of variants in CHEK2 is still under development. Furthermore, CHEK2 missense variants have not been investigated as extensively by functional assays compared to missense variants BRCA1 and BRCA2. With our capability for clinical classification of CHEK2 variants still emerging, many studies have focused on CHEK2 c.1100delC. The rarity of other variants greatly limit our ability to provide precise estimates of risk on a variant by variant basis. The estimated HRs are instead provided for pathogenic variants as a group. Lastly, the parametric survival analysis built into our segregation analysis models assumed the age at breast cancer diagnosis was independent of the age of death from other causes , which could very slightly bias our penetrance estimates at older ages.There are limitations to our study. Genetic testing was limited to the coding regions of nd BRCA2 ,33, but PALB2 [BRCA1 and BRCA2 pathogenic variant carriers, recently been demonstrated to modify the risk of breast cancer for CHEK2 pathogenic variant carriers [Further international collaboration is required to confirm and refine the breast cancer risk estimates and further understand breast cancer risk modifying factors. Important factors include family history, which still remains an important additional clinical consideration for families that carry pathogenic variants in PALB2  and the carriers .CHEK2 that include cancers in the Li-Fraumeni syndrome spectrum [CHEK2 pathogenic variants for these cancers. Furthermore, it is likely that the presence of pathogenic variants in the CHEK2 gene will impact management options for those in whom detection coincides with the diagnosis of breast cancer, in consideration of targeted chemotherapy and the safety of radiotherapy.It is also important to further understand the risk of other cancers (in addition to breast cancer) that are associated with pathogenic variants in spectrum  and prosspectrum  and the The Australian Breast Cancer Family Registry (ABCFR) is a population-based, case-control-family study of breast cancer, carried out in Australia (Melbourne and Sydney) as part of the international Breast Cancer Family Registry (BCFR). Case probands were over-sampled for those with early-onset breast cancer.The BCFR is an infrastructure for cooperative multinational, interdisciplinary and translational studies of the genetic epidemiology of breast cancer supported by the National Cancer Institute (USA) since 1995 ,38. The Cases were identified via the Victorian and New South Wales cancer registries, to which notification of all cancer diagnoses is a legislative requirement. Cancers in relatives were verified by cancer registry reports, medical records or death certificates. Control subjects were adult women living in the metropolitan areas of Melbourne and Sydney who were selected from the electoral roll , and approached with a letter similar to that used for case probands .All participants provided written informed consent for participation in the study. This study was approved by The University of Melbourne Human Research Ethics Committee .Blood-derived germline DNA from 1480 case probands and 864 control probands were screened by targeted-sequencing of the coding regions and proximal intron–exon junctions of BRCA1 (NM_007294.3), BRCA2 (NM_000059.3) and CHEK2 (NM_007194.3). Libraries were prepared using one of two amplicon-based methodologies, Hi-Plex2  or Halo-Paired-end reads were aligned to the human reference genome GRCh37 using BWA-mem 0.7.17. . HaloPleThis study focused on rare pathogenic or predicted protein-truncating variants. Rare variants were defined as those identified in the Exome Aggregation Consortium (ExAC) with a minor allele frequency (MAF) ≤ 0.01 in the non-Finnish European population (NFE-non TCGA). Genetic variants in CHEK2 were considered pathogenic if they were annotated as “Pathogenic” or “Likely Pathogenic” in ClinVar (accessed 30 July 2020). Predicted protein-truncating variants in CHEK2 that were absent from ClinVar were included in this analysis, except if they were located in the last coding exon. For BRCA1 and BRCA2 variants, pathogenicity was strictly determined using the ENIGMA expert panel classification available from ClinVar.DNA was extracted from blood samples provided by family members of case-probands and control-probands that were identified to carry pathogenic variants in CHEK2. Targeted-sequencing of CHEK2, BRCA1 and BRCA2 using the Hi-Plex panel and variant annotation and classification were conducted as described in CHEK2 variants, where the HR is defined to be the age-specific breast cancer incidences for female carriers divided by those for non-carriers. Segregation analysis is a classical method for analysing family data [Segregation analysis ,44,45 waily data ,44,45 thily data . All estily data , in whicily data  for the Cancer Incidence in Five Continents [CHEK2 variants combined was taken to be 0.005, which is approximately half the carrier frequency in controls [The age at breast cancer diagnosis was modelled as a random variable whose hazard is the relevant HR multiplied by the incidence of breast cancer for non-carriers. Non-carrier incidences were chosen so that the average incidence for carriers and non-carriers (weighted by the carrier frequency) was the age-specific population incidence rates for Australia in the period 1998–2002, as obtained from ntinents . Particicontrols ,51,52, tCHEK2) [Major gene models, which attribute all familial aggregation of disease to the gene being studied, can often give biased estimates of risk . TherefoCHEK2) ,53, was CHEK2) ). The poCHEK2) ,53. UndeCHEK2) . The meaCHEK2) .The age-specific cumulative risk (penetrance) to age No ages at diagnosis were missing for the breast cancer cases, though ages at death or last follow-up were missing for 219 (21.2%) of the 1032 controls. The missing ages for these people (who were mostly second-degree relatives of the proband) were set to 0, which censored them at birth and effectively removed them from the analysis. Non-missing ages were truncated at 80 years.p-values were 2-sided, and all p-values for the segregation analyses were based on the likelihood ratio test. A p-value threshold of 0.05 was used to define statistical significance.All CHEK2 in a population-based case-control-family study. As gene panel testing is now becoming routine and implementation of population screening is increasingly discussed, these risk estimates are highly relevant and urgently needed for the clinical management of the women and families found to carry a pathogenic variant in CHEK2.We estimated the age-specific cumulative risk of breast cancer for carriers of pathogenic variants in


Slightly higher odds ratios were observed in post-menopausal women, particularly those with body mass index > 25 kg/m2 , and among ever smokers . The analyses by breast cancer subtype showed that the DII was associated with breast tumors that expressed either the estrogen (ER) or progesterone (PR) hormone receptors or the Human Epidermal Growth Factor Receptor-2 (HER2), but no association was seen for the triple negative breast tumor subtype. Our results add further evidence that a pro-inflammatory diet is associated with breast cancer risk with possible effect variation according to tumor subtype.Dietary regimens promoting inflammatory conditions have been implicated in breast cancer development, but studies on the association between pro-inflammatory diet and breast cancer risk have reported inconsistent results. We investigated the association between the inflammatory potential of diet and breast cancer risk in a case–control study in France including 872 breast cancer cases and 966 population controls. All women completed a food frequency questionnaire that was used to compute a Dietary Inflammatory Index (DII) based on the inflammatory weight of 33 dietary components. The DII ranged from a median of − 3.22 in the lowest quartile (anti-inflammatory) to + 2.96 in the highest quartile (pro-inflammatory). The odds ratio contrasting quartile 4 to quartile 1 was 1.31 (95% CI 1.00, 1.73;  While hormonal and lifestyle factors are known to contribute to the occurrence of breast cancer, considerable evidence suggests that chronic inflammation plays a crucial role in the pathogenesis of breast cancer and other cancers3. Diet is one of the main lifestyle-related factors that can modulate the inflammatory process8. Dietary components may have pro- or anti-inflammatory properties via modulation of inflammatory biomarker levels10. It has been shown that a high intake of fruits, vegetables and whole grain are associated with lower levels of inflammatory biomarkers9, while a high intake of red and processed meat resulted in an increased level of inflammatory biomarkers11.Breast cancer is the most common cancer in women and the leading cause of cancer death among women, accounting for 2 million new cases and 0.6 million deaths worldwide in 202012 have developed the Dietary Inflammatory Index (DII), a score based on the compilation of inflammatory weights of 45 food parameters combined with data of dietary intakes obtained from food frequency questionnaires. In the Shivappa approach12, the dietary intake is standardized on the mean and standard deviation of dietary intakes of 45 food parameters available in a composite dietary database from eleven countries to facilitate international comparisons. Using a slightly different approach, an adapted DII was developed by van Woudenbergh et al.13 where the intake of dietary components is standardized on the means and standard deviations of dietary intakes in the population under study without reference to an external database. Recently, other authors used this adapted DII16 in combination with the inflammatory weights of dietary components proposed by Shivappa12.In order to assess the inflammatory potential of the diet, Shivappa et al.24, others found no such association31. It is also unclear whether a pro-inflammatory diet may affect breast cancer risk differently according to menopausal status, body weight or other risk factors that may modify the association between DII and breast cancer. Moreover, it is possible that the association of inflammatory diet with breast cancer differs by tumor subtype defined by expression of ER, PR and HER2 receptors in tumor tissue, but inconsistent findings have been reported in a limited number of studies29.The DII has been used in epidemiological studies on breast cancer with mixed and inconsistent results. While several studies reported a positive association between a pro-inflammatory diet and breast cancerIn the present study, we investigated the role of dietary inflammation in relation to breast cancer risk among women in two regions of France, using the adapted DII score. We will also examine whether the association between DII and breast cancer is modified according to selected breast cancer risk factors and by breast tumor subtype.départements) in the western and eastern part of France, respectively.We conducted a population-based case–control study (CECILE study) in Ille-et-Vilaine and Côte d’Or, two administrative areas  were recruited for the study and were contacted for an in-person interview.Cases were patients aged 25 to 75 years old with incident invasive or in situ breast cancer diagnosed between April 2005 and March 2007 in the two study areas. Cases were actively searched in the main cancer treatment hospital of each Controls were women frequency-matched to the cases by 10-year age group selected from the general population of each study area. To form the control group, women living in a random sample of private homes were contacted by phone and invited to participate in the study if they had no previous history of breast cancer. To account for possible differential participation rate across categories of socio-economic status (SES), quotas by SES were used to obtain a distribution by SES in the control group similar to that of the female general population, but socioeconomic status was not used as a criterion for matching cases and controls in our study. Among the 1731 controls identified by phone fulfilling eligibility criteria for SES, 1317 (76%) agreed to participate.An in-person interview of the cases and the selected controls was conducted with trained interviewers by means of a standardized questionnaire. We collected information on socio-demographic characteristics, family history of cancer, personal medical history, reproduction, lifestyle-related factors, as well as occupational and residential history. At the end of the interview, women were asked to complete a food frequency questionnaire (FFQ) and to return it to the research team in a prepaid envelope.32 and on the NutriNet-Santé composition table33. The polyphenol intake was estimated using the Phenol-Explorer database34 and the EPIC Nutrient Database35. From the 153 food items available from the FFQ, we used 33 dietary components with inflammatory weight available in Shivappa12 to calculate the DII  using food photographs. Total energy and nutrient intakes were estimated using a food composition table specifically developed for the study based on the CIQUAL-2013 French food composition databaseIn the present analysis, we excluded women who did not complete the dietary questionnaire . In addition, women with a ratio of dietary energy intake to energy requirement below the 1st or above the 99th percentile  were also excluded. In total, the present analysis included 872 cases (70.8%) and 966 controls (73.3%).The study was approved by a French Ethics Committee , and was conducted in accordance with the French regulations for medical research. A signed informed consent was obtained from all study subjects.14 that combines the calculation of the adapted DII proposed by van Woudenbergh et al.13 and the inflammatory weight of the dietary components proposed by Shivappa et al.12. First, the dietary intake of each 33 dietary components was adjusted for total energy intake using the residual method36; second, the energy-adjusted intake was standardized by subtracting the mean and dividing by the standard deviation of the dietary intake calculated over the whole study sample; third, the standardized energy-adjusted intake of the dietary component was multiplied by its corresponding inflammatory weight; fourth, the weighted standardized energy-adjusted intakes of the 33 dietary components were summed to obtain the overall DII for each subject. A high DII indicates a pro-inflammatory diet and a low DII indicates an anti-inflammatory diet.In order to obtain the DII score for each subject, we used the approach described by Laouali et al.2). For all covariates missing values were < 1.5% and therefore were imputed by the corresponding mode value. Additional adjustments for socioeconomic status and education were also made, but these had only marginal influence on the odds ratios (results not shown).The DII score was analyzed as a categorical variable in quartiles based on the distribution among controls. Odds ratio (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression models adjusting for age (continuous variable), department , history of benign breast disease (yes/no), family history of breast cancer in first-degree relatives (yes/no), age at menarche , parity , age at first full-term pregnancy , duration of breast feeding , menopausal status , menopausal hormone therapy (yes/no), oral contraceptive use (never/ever), and body mass index (BMI), BMI, physical activity, smoking status and alcohol consumption. Further analysis was performed by breast cancer subtype based on estrogen-receptor (ER), progesterone receptor (PR) and Human Epidermal Growth Factor Receptor-2 (HER2). Breast cancer tumors were classified as hormone-receptor positive , HER2-positive , and triple negative tumors . All analyses were carried out using SAS .The protocol of the CECILE study was approved by the Ethic Committee Kremlin-Bicêtre (CCPPRB Jan 2005) and by the National Data Protection Commission (CNIL Dec 2004).All participants signed informed consent before inclusion.The distribution of cases and controls by age, study area and breast cancer risk factors are shown in Table The median DII and the median intake of the dietary components in each DII quartile are shown in Table Table 2), while among post-menopausal the odds ratios increased with DII in overweighed women (p-trend = 0.02) but not in leaner women (p-trend = 0.46). The stratification according to smoking status showed a significant trend among ever smokers (p-trend = 0.01), but not among never smokers (p-trend = 0.45). However, none of the interaction tests between DII and breast cancer risk factors shown in Table Table The odds ratios for DII associated with breast cancer subtypes are shown in Table Our results suggest that a pro-inflammatory diet is associated with an increased risk of breast cancer in French women. This association appeared to be slightly stronger in post-menopausal than in pre-menopausal women, particularly those who were overweighed. It was also slightly stronger in ever smokers as compared to never smokers. Our results also show that a pro-inflammatory diet increases the risk of the most frequent breast tumor subtypes, i.e. tumors that are positive for either ER, PR or HER2-positive tumors, but no association was found for the triple negative  breast cancers.38, and several prospective studies have shown that circulating C-reactive protein (CRP), a systemic inflammation biomarker, is associated with an increased risk of breast cancer39. Besides, the inflammatory potential of the diet has been demonstrated by studies showing that a high intake of refined carbohydrates, saturated fatty acids and low intake of dietary fiber are associated with increased levels of circulating pro-inflammatory markers, while nutrients like β-carotene, magnesium and flavonoids may inhibit and suppress the activation of certain pro-inflammatory markers10. Based on these results, several prospective cohorts27 or case–control studies29 have sought to demonstrate that a pro-inflammatory diet is associated with breast cancer risk, using the dietary inflammatory index developed by Shivappa et al.12. Case–control studies generally reported that a pro-inflammatory diet was associated with an increased risk of breast cancer,with one exception29, but considerable heterogeneity between studies was observed41. Conversely, cohort studies reported no27 or only marginally increased risks17. Further scrutiny of dietary patterns and of covariate distributions between study populations would be useful to understand these discrepancies.There is strong evidence that chronic inflammation plays a major role in breast carcinogenesis40, others in post-menopausal women23, and others reported no clear difference between groups18.Although the association of the DII with breast cancer was slightly higher in post- than in pre-menopausal women in our data, the differences were very small. Among studies that examined women separately by menopausal status, some reported stronger associations in pre-menopausal women30, yet this was not evaluated according to menopausal status. Obesity is associated with chronic inflammation due to the release of pro-inflammatory mediators by adipose tissue43. It has also been shown that the release of pro-inflammatory markers by the adipose tissue is stimulated by excessive intake of macronutrients44. It is thus possible that the pro-inflammatory condition conferred by overweight combines with that of a pro-inflammatory diet to enhance the risk of cancer. The estrogen production in adipose tissue of menopausal women is another possible explanation for a synergistic effect of obesity and pro-inflammatory diet on breast cancer risk45.Among post-menopausal women, we found that the association between DII and breast cancer was more pronounced in overweighed than in leaner women. Previous studies also reported slightly stronger associations of DII with breast cancer in overweighed than in leaner women28, a similar effect was reported in studies examining the association between DII and head and neck46 or thyroid cancer47. Complex immune modulatory effects occur among smokers including induction of a chronic inflammatory process48. When concurrent with other inflammatory conditions, high inflammatory potential of the diet might therefore increase the body inflammatory load and the risk of developing breast cancer. The combined effects of smoking and dietary inflammation on breast cancer risk should may be worthy of further investigation.We found that the DII was more strongly associated with breast cancer in ever than in never smokers. Although no effect modification by smoking status was observed in the Spanish case–control study on DII and breast cancerp-trend 0.03), or those that are positive for HER2 (p-trend 0.03), corresponding to the molecular subtypes Luminal A, Luminal B and HER2-enriched tumors. Conversely, we found no evidence of an association between DII and Triple Negative breast tumors defined by the absence of ER, PR and HER2 receptors, although the relatively small number of cases with this subtype may explain this negative finding. Triple negative tumors stand out for their aggressive behavior, and it is possible that they do not share the same etiological pathways as other breast cancer subtypes49.We found that a pro-inflammatory diet was associated with tumors subtypes that express the hormone receptors ER or PR  for ER-positive/PR-positive tumors, 1.56  for HER2-positive tumors, and 0.99  for triple negative tumors. In the Women’s Health Initiative cohort study, Tabung reported null results for all tumor subtypes26. Other studies which evaluated the association of DII with breast cancer subtypes based only on the ER/PR receptor status found no clear difference between tumor subtypes29. Investigating the links between the inflammatory potential of the diet and tumorigenesis driven by hormonal or HER2 pathway might be helpful to see whether breast cancer subtypes are affected differently by pro-inflammatory diet.To our knowledge, results for breast cancer subtypes based on the ER, PR and HER2 receptor status have been reported by only two studies12 to classify dietary habits into pro- or anti-inflammatory. In our study, we computed an adapted DII following an approach that was used previously in studies on gastric cancer50, diabetes14, or hypertension15. This procedure slightly differs from that of Shivappa. First, we did not use the inflammatory weight for total fat to compute the DII because the 3 components of dietary fat  were also included separately. Second, the weight used for alcohol was different because alcohol was considered to be anti-inflammatory for intake below 40 g/day, and was assumed to have no inflammatory effect for intake above 40 g/day52. Third, the intake of food components in our study subjects was standardized by using the mean and standard deviation of each component in our study population, while the DII of Shivappa was standardized using a regional world-wide database taken as a referent population. The adapted DII was chosen in our study because this approach allowed us to perform the analyses without having to rely on a worldwide food consumption database, and because the objective was not to compare the inflammatory potential of the diet across populations, but to assess whether the inflammatory potential of the diet was associated with breast cancer risk in our population of French women. In addition, in a study on type 2 diabetes among French women comparing different approaches, similar results were observed regardless of the DII14.Previous studies examining the role of dietary inflammation in breast cancer have used the DII score of Shivappa et al.53. Finally, unmeasured dietary factors that are potentially associated with the DII may have led to residual confounding.Our study has some limitations. First, selection and recall bias cannot be excluded as in any study using a case–control study design. In our study, selection bias was minimized as we aimed to include all incident cases that occurred during the study period among women living in two well-defined geographical areas, and by including controls who were representative of the population from which the cases arose, using quotas by socioeconomic status to avoid differential participation rates. Possible recall bias was also reduced by the use of standardized questionnaires. Exposure misclassification on dietary intake was also controlled, at least in part, by excluding subjects with implausible dietary recall. To calculate the DII, we relied on the 33 food parameters that were available out of the 45 pre-defined parameters. However, it was shown that the predictive ability of DII score does not change with the decrease of the number of dietary parametersIn conclusion, our findings add to the evidence that a pro-inflammatory diet increases the risk of breast cancer, especially among overweight post-menopausal women. Our data also suggest that a pro-inflammatory diet affects the most frequent breast cancer subtypes, with the exception of triple negative breast cancer that may not share the same etiological pathways. Dietary anti-inflammatory regimens are beneficial for disease prevention at large and might be considered as a means for preventing breast cancer.


COX and ALOX genes are involved in inflammatory processes and that may be related to breast cancer risk differentially between White and Black women. We evaluated distributions of genetic variants involved in COX2 and ALOX-related pathways and examined their associations with breast cancer risk among 1,275 White and 1,299 Black cases and controls who participated in the Women’s Circle of Health Study. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable-adjusted logistic regression models. Our results showed differential associations of certain genetic variants with breast cancer according to menopausal and ER status in either White or Black women. In White women, an increased risk of breast cancer was observed for COX2-rs689470  in the dominant model, and was strongest among postmenopausal women  and for estrogen receptor positive (ER+) breast cancers . A reduced risk was observed for ALOX5-rs7099874  in the dominant model, and was stronger among postmenopausal women  and for ER+ cancer . Four SNPs  in the ALOX12 gene were found in high LD (r2 >0.98) in White women and were similarly associated with reduced risk of breast cancer, with a stronger association among postmenopausal women and for ER− cancer. Among Black women, increased risk was observed for ALOX5-rs1369214  in the recessive model and was stronger among premenopausal women  and for ER+ cancer . Our study suggests that genetic variants of COX2 and ALOX genes are associated with breast cancer, and that these associations and genotype distributions differ in subgroups defined by menopausal and ER status between White and Black women. Findings may provide insights into the etiology of breast cancer and areas for further research into reasons for breast cancer differences between races. COX2 and ALOX are associated with breast cancer. These associations and genotype distributions differ in subgroups defined by menopausal and estrogen receptor status between White and Black women.Genetic variants of Among women in the United States, breast cancer is the most common cancer and the second leading cause of cancer death . It is wOne hypothesis is that there may be variation in the molecular and cellular mechanisms in response to chronic inflammation, a process involving the immune system and various inflammatory regulators , 7. The COX2 gene have been associated with susceptibility to breast cancer , also known as prostaglandin-endoperoxide synthase 2 (PTGS2), a key enzyme in prostaglandin synthesis, is known to play a role in carcinogenesis and tumor progression, including breast cancer , 13. COXt cancer , 20. In ogenesis , 22. HowCOX2 and three ALOX genes and risk of breast cancer among White and Black women. We further considered if associations varied according to menopausal and ER status. We hypothesized that deviations from the standard distribution of “at-risk” alleles for specific single nucleotide polymorphisms (SNPs) could be associated with risk of breast cancer and may vary between races.In this large case-control study, we examined associations between genetic variants of The Women’s Circle of Health Study (WCHS) was a case–control study designed to assess risk factors associated with early onset and aggressive breast cancer among White and Black women. Further details on the study design, enrollment criteria, biospecimen and questionnaire data collection have been previously described , 23, 24.Detailed data on demographic characteristics, medical history, family history of cancer, lifestyle factors, and anthropometric measures were collected in-person by trained interviewers. Blood samples, as a source of DNA, were initially collected from approximately 850 participants until we transitioned to collection of saliva samples using Oragene™ kits  as a source of DNA. Pathology data including ER status, grade, and stage were collected and abstracted from patient records by trained staff.Genomic DNA was extracted from blood samples using FlexiGene™ DNA isolation kits  and from saliva samples using Oragene™ kits. DNA was then evaluated and quantified by Nanodrop UV-spectrometer  and PicoGreen-based fluorometric assay . Samples were stored at −80°C until analysis.COX-2 and ALOX inflammation-related pathways to identify SNPs that were previously associated with risk of any cancer or cancer outcome, with a focus on SNPs that were previously shown to be functional (COX2-rs20417) was removed due to the violation of Hardy–Weinberg Equilibrium, all other SNPs were included in the analysis.We surveyed the Human Genome Epidemiology (HuGE) Navigator for the four genes involved in nctional . A panelnctional . Proportnctional . As a quDescriptive analysis was done using chi-square tests for categorical variables and t-tests for continuous variables between 1,275 White and 1,299 Black cases and controls. Odds ratios (ORs) and 95% confidence intervals (CIs) for each SNP were derived from multivariable logistic regression models with adjustment for age (continuous), proportion of European ancestry (continuous), and family history of breast cancer . Other covariates did not significantly affect the risk estimates and thus were not included in the multivariable-adjusted analysis. Participants with the most common homozygous genotype among White controls were treated as the referent group. Genotypic (co-dominant) models were assumed for SNP effects. Based on the risk estimates, heterozygotes were combined with either homozygous rare or homozygous common genotypes to explore dominant and recessive models, respectively. Additive genotype coding on the number of rare alleles was analyzed as an ordinal variable in tests for linear trend. Analysis was performed separately for White and Black women, and interactions by race were tested by including an interaction term SNP*race in multivariable logistic models and performing the likelihood ratio test. Additional stratified analyses were conducted to examine whether SNP associations with breast cancer risk differed by menopausal or ER status.2 values between SNP pairs using Haploview  considered statistically significant.All analyses were conducted using SAS V 9.4 . Linkage disequilibrium (LD) was determined by calculating raploview . Statistvs. 18.8%).Characteristics of White and Black cases and controls are shown in COX2-rs689470  in the dominant model and ALOX5-rs1487562  in the recessive model, while the association among Black women was essentially null. A reduced risk among White women was also observed for ALOX5-rs7099874  in the dominant model. Four SNPs  in the ALOX12 gene were in high LD (r2 >0.98) and were similarly associated with reduced risk in White women. These SNPs, however, were not in LD (r2 <0.43) in the Black population and were not associated with overall breast cancer risk. Among Black women, significant associations were observed for ALOX5-rs1369214  and rs1051713  in the recessive models. Although these genotype-breast cancer associations differed in strength according to race, significant SNP-race interactions were observed only for COX2-rs689470 and ALOX5-rs1487562 , as shown above, both SNPs were associated with increased risk of breast cancer among White women.Genotype distributions of each SNP and their associations with overall breast cancer risk in White and Black women are shown in ALOX5AP-rs9315048 was associated with increased risk of breast cancer  in the recessive model. Among postmenopausal White women, COX2-rs689470 and ALOX12-rs2292350 were associated with increased risk  in the dominant models, while ALOX5-rs7099874 was associated with reduced risk  in the dominant model. Further, for the four ALOX12-SNPs in LD that showed similar significant associations with overall breast cancer risk among White women, the reduced risk was stronger among post-menopausal women, as shown for rs3840880 . Among pre-menopausal Black women, an increased risk was observed for ALOX5-rs1369214  and ALOX5AP-rs9315045  in the dominant models, whereas a reduced risk was observed for ALOX5-rs1051713  in the recessive model. In post-menopausal Black women, a reduced risk was observed for COX2-rs2745557  and ALOX5AP-rs4293222  in the dominant models.In stratified analyses, associations between each SNP and breast cancer risk were examined separately in pre- and post-menopausal women  in the dominant model, whereas a reduced risk was observed for ALOX5-rs7099874  in a dominant model. ALOX5AP-rs9315048 was associated with increased risk of ER− breast cancer  in the recessive model. Among Black women, an increased risk of ER+ cancer was observed for ALOX5-rs1369214  and ALOX5AP-rs9579648  in the recessive models. A reduced risk was also observed for COX2-rs2745557  with risk of ER− breast cancer in the dominant model. In addition, although there was no significant association observed in either White or Black women, COX2-rs5275 was associated with increased risk among post-menopausal Black women and specifically a significant increased risk for ER− breast cancer  in a recessive model. In contrast, there was an indication of inverse association for this SNP among post-menopausal White women  .Associations of each SNP and risk of ER positive (ER+) and ER negative (ER−) breast cancer were examined separately Table 4.COX-2 and ALOX inflammation-related pathways and risk of breast cancer. Allele frequencies of some of the SNPs in these genes varied significantly between White and Black populations. A number of these SNPs in COX2, ALOX5, ALOX5AP, and ALOX12 genes were found to be associated with overall breast cancer risk, as well as breast cancer risk in subgroups defined by menopausal and ER status, in either White or Black women. To our knowledge, this is among the first study to examine associations of genetic variants of these genes with breast cancer within and across White and Black populations, specifically in a large number of Black women.In this large case-control study of White and Black women, we examined candidate genetic variants in four genes involved in COX2–prostaglandin pathway links inflammation and tumorigenesis by providing a tumor-promoting microenvironment  and the ALOX5AP-rs9315045 in premenopausal Black women, and ALOX5AP-rs4293222 in postmenopausal Black women. The ALOX5-rs7099874 and ALOX5AP-rs9579648 were specifically associated risk of ER+ breast cancer, while ALOX5AP-rs9315048 were associated with risk of ER− cancer, in either White or Black women. These SNPs in relation to breast cancer were not well studied or reported in the literature, our findings provide some evidence of their potential role in breast cancer susceptibility and potential differences by menopausal and ER status.Like the COX pathway, studies have shown that 5-lipoxygenase (5LOX) and its metabolites are upregulated in multiple cancers and play a potential role in carcinogenesis . In thisALOX12 and its metabolite, 12S-hydroxyeicosatetraenoic acid, have been implicated in influencing tumor transformation and progression , 50. A rCOX and LOX genetic variants in a large number of Black women, which addresses the unmet need to improve representation of Black populations in genomic breast cancer studies. Furthermore, SNP associations with breast cancer risk were found to differ between White and Black populations, especially when menopausal and ER statuses were considered. These findings may provide insights into the etiology of breast cancer, indicating areas for further research into reasons for breast cancer racial differences.Several limitations warrant consideration. First, we selected a panel of candidate SNPs based on their potential functions from previous studies, other potentially important genetic variants may not be included in the current study. However, analysis of these common genetic variants in candidate pathways is a more focused method for increasing our knowledge of potentially important biological pathways in the etiology of breast cancer . Second,In conclusion, this study is among the first to examine genetic variants in genes involved in the COX- and LOX-related inflammatory pathways with breast cancer risk among both White and Black women. Our study suggests that genetic variants of these inflammation-related genes are associated with breast cancer, and that these associations and genotype distributions differ in subgroups defined by menopausal and ER status between White and Black women. As current research remains limited, additional studies are necessary to confirm these findings and explore the underlying molecular mechanisms.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/This study was approved by institutional review boards at the Roswell Park Comprehensive Cancer Center, the Rutgers Cancer Institute of New Jersey, Mount Sinai School of Medicine (now the Icahn School of Medicine at Mount Sinai), and participating hospitals in New York City. Signed informed consent was obtained from each participant prior to interview and biospecimen collection. The patients/participants provided their written informed consent to participate in this study.JM made substantial contributions to the interpretation of the data, drafted the manuscript, and revised it critically for important intellectual content. CA, EB, CCH, AO, GZ, TK and SY were essential to data collection and genotyping, interpretation of the data and manuscript writing. ZG made substantial contributions to the conception, design, analysis, and writing the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by grants from the National Cancer Institute , the Breast Cancer Research Foundation and a gift from the Philip L. Hubbell Family. The New Jersey State Cancer Registry (NJSCR) is a participant in the Centers for Disease Control and Prevention’s National Program of Cancer Registries and is a National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Expansion Registry. The NJSCR is supported by the Centers for Disease Control and Prevention under cooperative agreement DP07-703 awarded to the New Jersey Department of Health & Senior Services. The collection of New Jersey cancer incidence data is also supported by the National Cancer Institute’s SEER Program under contract N01-PC-95001-20 and the State of New Jersey. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.