CLOCK rs11133373 was associated with breast cancer risk even after false discovery rate (FDR) correction (Odd Ratios (OR) = 1.38  1.14–1.69) in CG and CC compared to GG genotype. Analysis of MTNR1A rs2119882 demonstrated a decreased risk of breast cancer in CC compared to TT (p-FDR = 0.043). A correlation between NSW and breast cancer interaction was found in two loci. NSW increased risk of breast cancer in women who carried the heterozygote genotype of CRY2 rs2292912  or carried at least one minor allele of RORA rs1482057 . Our study results support a putative role for several loci of circadian genes and genes of melatonin biosynthesis and their interaction, and the gene interactions with NSW in the development of breast cancer.Our purpose is to investigate the impact of circadian and melatonin pathway genes as well as their interactions with night-shift work (NSW) on breast cancer risk in Korean women. Information about NSW and other covariates was collected using a structured questionnaire and twenty-two polymorphisms in 11 genes were analyzed in a hospital-based case-control study with 941 cases of breast cancer and 959 controls. In analysis of the main effects of each single nucleotide polymorphisms(SNPs), variants in  Among them, light at night exposure in countries with a high level of light at night may contribute up to 30–50% of the increased risk for breast cancer2. In 2007, the International Agency for Research on Cancer (IARC) evaluated the carcinogenicity of night shift work (NSW) and classified it as a probable carcinogen to humans. The biological plausibility for increased risk of cancer with NSW is possibly related to the suppression of nocturnal melatonin secretion, the modification of estrogen utilization, or changes in the expression of clock genes3. Shift work suppresses the expression levels of core clock genes and also changes the behavior of melatonin pathway genes, leading to adverse effects on health status including an increased risk of breast cancer associated with circadian dysrhythmias4.Breast cancer is the leading cause of cancer related burden among women worldwide. Higher incidence of breast cancer in industrialized areas and increased trends observed elsewhere in the world5. In addition, all of the studies regarding NSW and breast cancer conducted in Asia failed to show an association, suggesting that a different resistance to the exposure to light at night or a differing genetic distribution in an Asian population compared to other populations might account for the non-association observed in Asia7. Furthermore, circadian rhythms that substantially affect an individual’s shift work tolerance could be altered by factors such as gene-environment interactions8. Genetic polymorphisms related to the circadian genes or melatonin pathway genes have been considered as candidates for increased disease risk because of their relationships with circadian disruption and gene expression alterations. Clock genes have been found in breast epithelium, and clock gene expression has been shown to be influenced by both the breast cellular microenvironment and the nearby breast tissues. Disruption of the clock genes changes their expression and might increase risk of breast cancer9. Also, the increased incidence of breast cancer associated with the melatonin pathway genes is thought to be due to melatonin binding to and activation of MT1 and MT2, the melatonin receptors encoded by the MTNR1A and MTNR1B genes, triggering anti-oncostatic actions in human breast cancer cells10. Some previous epidemiological studies have investigated NSW and variations of circadian rhythm gene interactions on breast cancer risk; however, the results are controversial. Several studies have indicated an association between NSW, the single nucleotide polymorphisms (SNPs) in circadian genes, and breast cancer risk, but the results from some studies could not be replicated in other studies15. Epidemiological findings looking at the melatonin pathway genes have associated some loci in MTNR1A with a decreased breast cancer risk, however, all the loci in AANAT that encode enzymes involved in melatonin synthesis and in the control of day/night rhythm of melatonin production, did not demonstrate any association with breast cancer risk16.In contrast to this previous work, a recent meta-analysis of prospective epidemiological studies failed to show any effect of NSW on breast cancer development17, the effects of SNPs and their interactions with NSW on breast cancer may be unique in Asian countries. Therefore, we aim to investigate the impact of variants in circadian and melatonin pathway genes and their interactions with NSW on breast cancer risk in a population of East-Asian women.Although several epidemiological studies have been conducted worldwide, up until now, no study focused in an Asian population has been conducted to elucidate the linkage of melatonin path genes, circadian genes and NSW with breast cancer. Considering that the frequency of variants in clock genes is reported to be significantly different between ethnicitiesth version. The information on NSW experience, demographic characteristics, reproductive factors, and lifestyle behaviors were obtained using a structured questionnaire administered through face-to-face interviews. NSW was defined as ever having worked for night shifts regularly between 9:00 pm and 8:00am for at least 2 months in their lifetime. Among 2,058 cases and 1,938 controls with NSW information, after matching by 1:1 ratio according to the age groups of 10 year intervals and checking the availability of blood samples, 941 cases and 959 controls with both NSW information and blood samples were included  of Korea to identify the factors associated with breast cancer risk. Cases were recruited from a population of women diagnosed with histologically confirmed breast cancer from 2012 to 2017 in the NCC. Controls were recruited from women who visited the NCC for health check-ups in the same period. Informed consent was collected for all cases and controls. The study protocol was reviewed and approved by the National Cancer Center Institutional Review Board (IRB number: NCCNCS13717). All procedures were performed in accordance with the Declaration of Helsinki 718. Among them, the SNPs with minor allele frequencies (MAFs) in East-Asian populations >0.1519 were included in this study. Information on 22 SNPs that are targeted during DNA sequencing, was obtained using high-throughput multiplex genotyping and Fluidigm BioMark™ System. The selected SNPs, chromosome locations and the protein function of each respective SNP are shown in Supplementary Table Genomic DNA was extracted using peripheral blood leukocytes isolated from whole-blood samples obtained from the participants. We considered genetic variants in circadian and melatonin pathway genes based on articles published prior to January 2017 regarding the relationship of NSW, circadian genes or melatonin genes and risk of breast cancer. The SNPs which had been shown significantly associated with breast cancer in five studies were taken into account2 for each of SNP pair and one SNP in high-correlated pairs was excluded. The frequency of genotypes and MAF for each SNP was checked in cases and controls separately. Chi-square test was computed using the permutation procedures to determine the difference among genotypes in case and control groups.The distribution of demographic characteristics and other covariates was described and tested by t-test and chi-square. For the 22 SNPs, the Hardy Weinberg equilibrium (HWE) was checked by performing an analysis which used 10,000 permutations in the controls groups to approximate P-values in the exact tests and SNPs with p value > 0.05 were included. We checked pairwise linkage equilibrium by calculating ret al. and has been applied by many authors20.The association between each SNP and breast cancer risk was derived from unconditional multiple logistic regression models and presented as odd ratios (ORs) with 95% confidence intervals (CIs). When the number of cases or controls with minor allele was small (<5), exact logistic regression was used. All of the four models including codominant, dominant, recessive, and log-addictive were used to measure the strength of the association. The multiple correction adjusted P-values were obtained by 10,000 permutation testing and further checked by false discovery rate (FDR). This test is appropriate as recommended by Clarke 21. SNPs with significant interactions were included in stratified analysis to illustrate the heterogeneity among genotypes of each SNP marker.The gene-gene interaction was tested by adding each SNP pair term in the logistic regression model with the main effect. P-values for interaction were calculated by the log-likelihood ratio (LRT) test. These P-values were adjusted using FDR. The initial cut-off point of P-values was chosen at 0.20 as was done in a previous studyWe tested the interaction between NSW and all of the SNPs in the circadian and melatonin pathway genes using the likelihood ratio test. The FDR adjusted method was also applied for p interaction values correction. We consider the initial cut-off point for P-value as 0.20. For the stratified analyses with NSW, NSW was divided into two classes (having ever/never exposed).23.All analyses were adjusted for age at time of diagnosis or interview (as continuous variable), educational level, number of pregnancies, age at birth of first child, body mass index (BMI), age at menarche, alcohol consumption, smoking, use of female hormone treatment, and family history of breast cancer in first degree relatives. These variables were also included in the final logistic regression model to obtain adjusted odds ratios (ORs) for developing breast cancer associated with the distribution of polymorphisms alone , and the polymorphisms and night work (stratified by presence or absence of night shifts). All statistical analyses were conducted by both SAS software version 9.4 and R version 3.5.0Informed consent was collected for all cases and controls. The study protocol was reviewed and approved by the National Cancer Center Institutional Review Board (IRB number: NCCNCS13717).The demographic characteristics of the study population are described in Table AANAT, ARNTL, ARNTL1/BMAL1, ARNTL2/BMAL2, CLOCK, CRY2, CUL1, MTNR1A, NPAS2, RORA, TIMELESS) from the circadian and melatonin signaling pathway with corresponding genotypes, frequencies of SNPs, less frequent alleles (LFA), MAF in study population, global LFA, global MAF, Hardy-Weinberg-derived P-values and P-value of chi-square test of genotypes are given in Supplementary Table Twenty-two SNPs in eleven genes  in the dominant model remained statistically significant . The OR of rs11133373 CG/CC genotype was 1.38 (95% CI = 1.14–1.69) compared with GG and that of rs2119882 CT/CC genotype was 0.75 (95% CI = 0.61–0.91) compared with TT. When the effect of the interaction between individual SNPs and menopausal status on breast cancer was assessed, we found no significant association between SNPs and menopausal status.All P-values from permutation test and FDR correction of four genetic models  are presented in Supplementary Table NPAS2 rs3820787 and RORA rs1482057, CUL1 rs758880 and RORA rs1482057, CLOCK rs11133373 and CUL1 rs758880. The significantly increased risk of breast cancer according to the increasing number of RORA rs1482057 A allele was found in women who carry the GG genotype of NPAS2 rs3820787 or the AA genotype of CUL1 rs758880 , but in GG genotype, it showed decreased associations significantly.All of the permutation P-values and FDR correction P-values between pair of SNPs are plotted in Supplementary Fig. CRY2 , however for women who carried the GG or CC, ever engaging in NSW rather decreased the risk. For rs1482057 in RORA, women with at least an A allele who engaged ever in NSW had a higher risk of breast cancer  but in women with the CC homozygote, ever engaging in NSW was not associated with breast cancer, and instead decreased the risk.The permutation P-values and FDR correction P-values of NSW-gene interaction are plotted in Supplementary Fig. CLOCK, TIMELESS) and genes of melatonin biosynthesis (MTNR1A) in the development of breast cancer. In addition, putative gene interactions between NPAS2, CUL1 and RORA, CLOCK and CUL1 is observed to have correlation in the development of breast cancer. The effect of NSW appears to be modified by variants of CRY2 and RORA genes.In this study, we investigated the associations between genes of circadian regulation, melatonin pathway and breast cancer risk. Our study results support a putative role of several loci in circadian genes  which was comparable with our results but no association between rs11133373 and breast cancer risk was found13. However, in this study an association between CLOCK rs11133373 and breast cancer risk in log-additive models when C allele were considered as a reference  is observed and it is similar with another previous result15. CLOCK rs2035691 is found to have no association with breast cancer risk in both Asian and European women20 and rs10462028 has no association with breast cancer risk18. Another finding indicated that breast cancer risk in postmenopausal women is associated with rs11932595 in CLOCK11. A possible explanation for the association between variants in the CLOCK gene and breast cancer risk would be that hypermethylation of the CLOCK promoter reduces the risk of breast cancer24. We checked and compared less frequent alleles and MAF of these significant SNPs in our study, MAF in Chinese and Japanese populations and confirmed no difference, as may be predicted in comparing results with other East-Asian populations25.Among twenty SNPs in circadian and melatonin pathway genesTIMELESS rs2291738 and breast cancer was observed with effect modification of hormone receptor status of breast cancer. The GG genotype of rs2291738 decreased hormone receptor positive breast cancer but not overall breast cancer26. Comparable with previous results, our study shows the CC genotype of rs2291738 decreased overall breast cancer risk. For other SNPs in TIMELESS genes, rs774036 was not associated with breast cancer risk in both European and Asian women20. In terms of melatonin pathway genes, MTNR1B rs10765576 showed inconsistent results in previous studies – reduced risk of breast cancer among those who carried AA allele16 or no association18, and MTNR1A rs7665392 showed different effects on breast cancer by menopausal status16. Other SNPs in MTNR1A or MTNR1B did not show association with breast cancer16. However, our study demonstrates that MTNR1A rs2119882 CT and TT genotype decreased breast cancer risk. One study considered rs2119882 but then excluded it due to HWE14.Other genes were also indicated in published studies for the association with breast cancer risk. A significant association between ARNTL/MTNR1B, MTNR1B/NPAS2 and three-way interactions with MTNR1B/NPAS2/ARNTL was observed in a previous study18. In our study, interactions between combinations of RORA and NPAS2, RORA and CUL1, and CUL1 and CLOCK are observed. Based on our findings, the potential role of CLOCK in breast cancer etiology seems plausible referring to both a main effect of individual SNP and gene-gene effects on breast cancer. Furthermore, loci in RORA play an important part in the interaction with other SNPs.In terms of gene-gene interactions of circadian and melatonin pathway genes on the relationship with breast cancer, two-way interactions between CRY2 and rs1482057 in RORA are observed to have possible interactions with shift work. A previous study showed interaction effects of NSW and various genes including CLOCK, CRY2, RORB, AANAT, MTNR1A on breast cancer14. In addition, women with the NPAS2 Ala394Thr (rs23051560) Thr/Thr variation showed increased breast cancer risk by about three times when they engaged in NSW for 24 months or more but did not show association in other genotypes13. However, two other previous studies did not find interaction effects between any of the examined genes and NSW on breast cancer risk20. Each SNP which showed interaction with NSW in only one study was not replicated in other previous studies. The interaction between CRY2 and NSW is observed in this study and in Zienolddiny et al. despite of different SNP in CRY2 gene14. Despite differences in SNP, according to Zienolddiny et al., genotype of SNPs in CRY2, the effect of NSW was different, especially heterozygote of rs11038689 as our study results14. The variants in CRY2 may affect breast cancer through the hormone signaling pathway27. Considering the effect of NSW in the modification of estrogen utilization3, the effect of interaction between polymorphisms of CRY2 and NSW on breast cancer can be explained. In addition, Zienolddiny et al. reported that not only CRY2, but also rs3903529 in RORB interacts with NSW and effects breast cancer risk with different direction of effect of NSW in those carrying heterozygote genotype14. Our results as an interaction between exactly same SNP and NSW have not been replicated in previously published results from Western countries. Differences in the genetic structure between the Asian and the Western population might could be the reason behind this variation29. Thus, investigation of these interactions in larger populations is needed, especially in the Asian population. Due to the small number of the subjects who had experience of NSW and each genotype, the most results for the interaction effect between night shift work and each SNP on breast cancer risk showed wide CIs, yielding inconclusive results, possibly caused by limited statistical power. However, our study is the first study conducted using an Asian population to examine the association of circadian genes, melatonin pathway genes and breast cancer, as well as genes-NSW interaction in relationship to the etiology of breast cancer. This is a carefully designed case–control study with detailed information in covariates. The sample size of our study is round 2,000, which is similar with previous studies20.In our study, SNPs having significant main effects on breast cancer in this study Table  did not 30, which is comparable to the percentage of night shift workers in our study. In addition, the number of women with experience of NSW in this study was comparable to that of previous population based case-control studies, which included approximately 100 patients and 100 controls with experience of NSW18. We selected a limited number of variants in circadian and melatonin pathway genes used in the previous studies, and, to cover all the SNPs in these genes to determine relevant makers in an East-Asian population, a much larger study is warranted. The breast cancer patients and controls were recruited from a single cancer center. Therefore, the external validity may be limited although whether the variants met HWE is considered in the analysis. Recall-bias could affect the result in the measurement of NSW and other covariates. In addition, although the sample size was adequate to identify the SNPs with a frequency of MAF of around 0.15 and OR of 1.4, for SNPs with smaller frequency or smaller ORs, the statistical power would not be enough. In addition, considering the small number of subjects who had engaged NSW, the power to detect interaction effect between NSW and relevant SNPs on breast cancer risk was reduced.The study may have a number of limitations. In defining NSW, we did not take into account the detailed night-shift characteristics such as shift duration or rotation cycles. We just considered the experience of NSW due to the limited number of subjects who were night-shift workers . Thus, stratification analysis according to detailed NSW information such as duration of NSW or the number of consecutive NSW shifts could not be conducted. The Korean 3rd Working Condition Survey reported that 7.5% of female workers were involved in night-shift workCRY2 and RORA genes were denoted for the effect on breast cancer though the interaction with other genes or with an environmental factor (NSW). Further study should be conducted in large populations to replicate this finding and investigate this association in a stratified analysis based on menopausal status and varying levels of shift work exposure.Our hospital based case-control data supported the possible role of several variants in genes of circadian regulation and the melatonin pathway associated with breast cancer risk, both with an individual effect and an interaction of genes effect. In addition, Supplementary information


Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Research Perspective, we highlight commonly used clinical risk assessment models and recent scientific advances to individualize risk assessment using precision biomarkers. Genome-wide association studies have identified >100 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, and polygenic risk scores (PRS) have been developed by several groups using this information. The ability of a PRS to improve risk assessment is promising; however, validation in both genetically and ethnically diverse populations is needed. Additionally, novel classes of biomarkers, such as microRNAs, may capture clinically relevant information based on epigenetic regulation of gene expression. Our group has recently identified a circulating-microRNA signature predictive of long-term breast cancer in a prospective cohort of high-risk women. While progress has been made, the importance of accurate risk assessment cannot be understated. Precision risk assessment will identify those women at greatest risk of developing breast cancer, thus avoiding overtreatment of women at average risk and identifying the most appropriate candidates for chemoprevention or surgical prevention. BRCA1, BRCA2, TP53, and PTEN) [Individual risk for developing breast cancer varies between 11.6% for women without specific clinical risk factors  and 85% for women with pathogenic germline mutations in highly penetrant genes  ,8. Womennd PTEN) . Women and PTEN) –13.e.g., hereditary, etc.) see the 2017 Cintolo-Gonzalez review [https://bcrisktool.cancer.gov. The Claus model uses first- and second-degree family history to calculate risk but does not consider additional family history and other risk factors . This model has an estimated AUC of 0.72 [https://cagene.com/) [http://www.ems-trials.org/riskevaluator/. See A number of models are available for estimation of individual breast cancer risk based on clinical factors such as family history, reproductive profile, history of prior breast biopsy, and breast density . The mosz review ,19. The z review ,20–22. Fne.com/) . The IBIne.com/) –28. For Newer clinical models such as the Breast Cancer Surveillance Consortium (BCSC) model and updated/revised versions of the IBIS model (version 8) have incorporated mammographic density (MD) into assessment of risk. Mammographic density is a strong, independent risk factor for breast cancer development with studies showing a 4-6-fold increased risk for breast cancer for women with the highest breast density category compared with women in the lowest breast density category –38. The Given that an AUC of 0.5 suggests that the test (or model in this case) performs no better than chance, the fact that none of the above models have an AUC greater than 0.76 leaves room for improvement ,42,43. TNovel classes of biomarkers, such as circulating microRNA (C-miRNA) have emerged as promising cancer biomarkers –65 and mIn breast cancer patients, the presence of miRNA in circulation correlates with expression of that miRNA in primary breast tumors –82. Addie.g., strong family history of breast cancer or benign breast disease), and follow-up time. The median age at blood draw was 55.4 (range 33.9-77.5) for affected cases and 55.1 (range 32.8-78.4) for cancer-free controls (see https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE98181) and the R scripts used for data analysis accompany our open access 2017 Oncotarget manuscript as a supplement [Our group recently identified a C-miRNA-based risk signature predictive of long-term risk in a prospective cohort of women at increased risk for developing breast cancer. This IRB-approved prospective cohort includes over 600 high-risk women (who have signed informed consent) with a median follow-up of 8.9 years. From this cohort we selected 24 invasive breast cancer cases, to whom we matched controls on age, reason for high-risk status (pplement . We idenpplement . RefinemPersonalized and precise risk assessment can identify those women at greatest risk to develop breast cancer, thus avoiding overtreatment of women at lower/average risk and identifying women at high risk who would be candidates for high risk screening, chemoprevention or surgical prevention. Progress has been made towards personalized risk assessment and some promising new markers have been identified. However, rigorous validation of the most promising markers, and the predictive models they contribute to, in relevant populations is necessary before deployment for clinical use.


FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases  and 26 controls . There was no evidence of an association with the risk of breast cancer, neither overall  nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C,  At least seven of them  are involved in different stages of homology-directed recombinational DNA repair (HRR), a pathway for error-free maintenance of the genome during replication and after DNA damage. A number of FA genes  have been shown to be breast cancer susceptibility genes3. The products of BRCA1, BRCA2, and PALB2 are central to early stages of HRR. Further interactors in this pathway, in particular BRIP1/FANCJ, mainly have been linked to ovarian cancer risk5. It is less known to what extent other FA gene products may play a role in the inherited component of breast cancer susceptibility. Few of these other FA genes have been tested for mutations in relatively small breast cancer case-control studies, thus far9.Fanconi Anemia (FA) is a rare recessively inherited disorder characterized by congenital malformations, progressive bone marrow failure and predisposition to cancer. Twenty-two different FA causative genes have now been identified whose products act in concert to mediate DNA interstrand crosslink repair13. After FA was stratified into subsets defined by complementation assays, an increased risk of breast cancer was attributed to heterozygous carriers of FANCC mutations13. Historically, this was the first of the FA genes to be identified and accounts for 8–15% of FA cases16. More recently, FANCC has been suggested as a candidate breast cancer susceptibility gene in an exome sequencing study of 33 familial breast cancer cases and extension to another 438 cases17. However, the evidence for an association between FANCC and breast cancer risk is limited by the low prevalence of mutations18, and much larger numbers of individuals are needed to provide sufficient power to detect associations of plausible magnitude19.Early studies suggested that blood relatives of FA patients show an increased risk of breast cancer, although these findings have not been corroborated in a replication study and could not assess distinct FA complementation groups due to lack of genetic information at that timeFANCC (p.R185X and p.R548X) using the Oncoarray (see Methods) in 64,760 female breast cancer cases and 49,793 female population controls of European descent. Both mutations are disease-causing in European FA patients and are recurrent in the FA mutation database20.In the present study, we genotyped two truncating variants of FANCC variants p.R185X (rs121917783) and p.R548X (rs104886457) in 40 of 153,899 individuals and 20 of 153,904 individuals, respectively. All mutation carriers were heterozygotes. Carrier distributions per study and intensity cluster plots for Europeans (which included the majority of mutation carriers) are shown in Supplementary Table 21.We identified the truncating FANCC variants were observed in 25/64,760 cases  and in 26/49,793 controls . There was no evidence of association between the FANCC variants and breast cancer risk, either for carriers of both variants combined , or for either variant individually . The variant carriers were markedly enriched among cases with ER-negative tumours  and specifically triple-negative breast tumours . The p.R414X truncating variant was also associated with ductal morphology, a positive first-degree family history of breast cancer, early age at diagnosis (<50 years), and low-differentiated tumours (grade 3)  have now been confirmed to predispose to breast or ovarian cancer while biallelic mutations in these genes cause FA3. However, the role of the FA genes most commonly mutated, FANCA and FANCC, in the risk of developing breast cancer has remained uncertain. Epidemiological and segregation studies have provided some evidence of an increased breast cancer risk for grandmothers of FA patients, particularly those who carry the FANCC mutation13.Functional defects of DNA repair are a hallmark of genomic instability syndromes as well as of carcinogenesis. FA is a genome instability and cancer prone disorder that has been investigated for breast cancer predisposition in homozygotes and heterozygotes for more than three decadesFANCC in 3 of 438 multiple-case breast cancer families but in none of 464 healthy controls, suggestive of a predisposing role for FANCC variants in breast cancer17. One of these variants, p.R185X, was also screened in our study. p.R185X was first reported shortly after the identification of the FANCC gene, and thus is one of the earliest recognized FA-causing mutations. Although representing an apparent nonsense mutation in exon 6, it also results in exon 6 being spliced out of a proportion of transcripts, suggesting this variant may alter splice site selection, with the aberrant transcript retaining the reading frame22. p.R548X, also an early-detected FANCC truncating variant23, is an authentic stop mutation in exon 14, and although in the last exon, it proved to be clearly pathogenic for FA24.A previous sequencing study of Australian multiple-case breast cancer families had identified truncating variants in 20 prompted us to investigate their association with breast cancer in a large case-control study. However, we did not observe a significant difference between their frequency among breast cancer cases and controls. The upper 95% confidence limit was 1.33, thus excluding a two-fold or greater increase in risk found for moderate- or high-penetrance alleles in predisposition genes such as CHEK2 and ATM. Moreover, we found no evidence of association in subgroups defined by earlier age at onset, a positive family history of breast cancer, bilateral occurrence, or defined tumor parameters . However, confidence intervals for those estimates for subsets were wider as numbers were small – in particular we could not rule out a 2-fold increased risk for ER-negative or triple-negative breast cancer.The fact that these two disease-causing variants have been frequently observed in European patients with FAPALB2/FANCN variant p.R414X and breast cancer risk. PALB2 is an established breast cancer susceptibility gene, and the investigated mutation p.R414X25 occurred at a similar frequency to the tested FANCC mutations. The observed six-fold enrichment of p.R414X in breast cancer patients is in line with previous findings for other PALB2 founder mutations28 and in the upper range of the overall mutational effect size in PALB2 case-control sequencing studies30. We confirmed stronger associations with ER-negative breast cancer, with familial breast cancer and with a high tumor grade31. While genotyping arrays such as the Oncoarray are primarily used for evaluating common variants, these data confirm that the array provides a robust platform for evaluating even very rare alleles.In contrast, we observed a clear association between the PALB2 and FANCC are both FA genes, their products exert different roles in the recognition and repair of DNA damage. FANCC is a component of the FA core complex which is thought to recognize an inter-strand crosslink. FANCL, an E3 ubiquitin ligase in the core complex, ubiquitinates FANCI and FANCD2. After many nuclease and translesion polymerase steps, a DNA double stranded intermediate is formed and its repair requires proteins from the homology-directed repair pathway, including FANCD1/BRCA2 and FANCN/PALB2. While truncating variants in BRCA2 and PALB2 confer a substantial risk of breast cancer, our study suggests that truncating FANCC variants do not confer a comparable risk. It is possible that members of the FA core complex that act upstream of HRR are less relevant for breast cancer due to their more specialized function in the repair of crosslinks while BRCA1, BRCA2, and PALB2 function more globally at DNA double-strand breaks. On the other hand, there is some evidence that truncating mutations in another gene involved in the early detection of intra-strand crosslinks, FANCM, are associated with both breast and ovarian cancer risk34, though FANCM is part of an anchor complex rather than the FA core complex and is not considered a classical FA gene36. It is also possible that the two prototype FANCC truncating variants analysed here, despite being FA-causing, have reduced penetrance for breast cancer due to some residual function, and other particular FANCC variants may confer a more substantial risk. More work will be required to clarify the role of each FA core complex member for breast cancer susceptibility.Although FANCC do not confer a high overall risk of breast cancer unlike PALB2, BRCA1 and BRCA2. Our study does not exclude a role of monoallelic FANCC variants as low-penetrance alleles for breast cancer or as a genetic risk factor for certain breast cancer subgroups. Very large datasets, such as those generated through the BCAC, are critical to evaluate such rare mutations.In conclusion, our study findings suggest important differences between FA genes, indicating that truncating variants in A total of 87 studies from the Breast Cancer Association Consortium (BCAC), of which 78 were case-control studies (some nested within prospective cohort studies) and 9 were case-only studies, contributed data as summarized in Supplementary Table 37. In brief, approximately 72,000 variants were selected, among others, for inclusion on the array specifically for their potential relevance to breast cancer, based on prior evidence of association with overall or subtype-specific disease, with breast density or with breast tissue specific gene expression. After genotype calling and quality control of the cluster file, variants with a call rate <95% in any consortium, not in Hardy-Weinberg equilibrium (P < 10−7 in controls or P < 10−12 in cases) or with concordance <98% among 5,280 duplicate pairs were excluded. We also excluded samples with extreme heterozygosity (>4.89 standard deviations [SD] from the mean for the respective ethnicity). The final dataset, before restriction based on ethnicity, consisted of 153,673 samples of which 89,733 were cases and 63,940 were controls.The Illumina OncoArray design and genotyping procedure have been described previouslyhttp://ccge.medschl.cam.ac.uk/software/pccalc/).Per-allele odds ratios and 95% confidence intervals were generated using logistic regression with adjustment for principal components and study. Principal component analysis was performed using data for 33,661 uncorrelated SNPs  with a MAF ≥ 0.05 and maximum correlation of 0.1, using purpose-written PCcalc software , and by first-degree family history of breast cancer, using available BCAC data for the cases. Since we analysed 3 variants across 10 subgroups, a two-sided p-value ≤ 0.016 for the overall analyses and a two-sided p-value ≤ 0.0016 for the subgroup analyses were considered nominally significant.All experimental protocols were approved by the respective ethical institutions of participating BCAC centers. The study was carried out in accordance with the Declaration of Helsinki, and informed consent was obtained from all study participants.Supplemental Info


Women with dense breasts face a double risk for breast cancer; they are at a higher risk for development of breast cancer than those with less dense breasts, and there is a greater chance that mammography will miss detection of a cancer in dense breasts due to the masking effect of surrounding fibroglandular tissue. These women may be candidates for supplemental screening. In this study, a masking risk model that was previously developed is tested on a cohort of cancer-free women to assess potential efficiency of stratification.Three masking risk models based on (1) BI-RADS density, (2) volumetric breast density (VBD), and (3) a combination of VBD and detectability were applied to stratify the mammograms of 1897 cancer-free women. The fraction of cancer-free women whose mammograms were deemed by the algorithm to be masked and who would be considered for supplemental imaging was computed as was the corresponding fraction in a screened population of interval (masked) cancers that would be potentially detected by supplemental imaging.Of the models tested, the combined VBD/detectability model offered the highest efficiency for stratification to supplemental imaging. It predicted that 725 supplemental screens would be performed per interval cancer potentially detected, at an operating point that allowed detection of 64% of the interval cancers. In comparison, stratification based on the upper two BI-RADS density categories required 1117 supplemental screenings per interval cancer detected to capture 64% of interval cancers.The combined VBD/detectability models perform better than BI-RADS and offer a continuum of operating points, suggesting that this model may be effective in guiding a stratified screening environment. High mammographic density is associated with increased risk of developing breast cancer –5 and alA stratification method must be both effective (identifying women where the risk of missed detection of breast cancer is high due to masking) and efficient in referring as few women as possible who do not have breast cancer for supplementary screening. Breast density is typically assessed using the Breast Imaging Reporting and Data System (BI-RADS) scale , 11, in There are two types of risk associated with elevated density, the underlying breast cancer risk and the risk of masking. Here, we attempt to isolate the masking risk and create a model that can be used to identify women for whom mammography screening will likely be compromised due to masking. The two types of risk can then be evaluated and used separately in the optimization of strategies for screening.We have reported previously on the development of a “masking risk” model , derivedThe mammograms used in this study came from an earlier study where breast density was incorporated in a risk stratification model for breast cancer . This stIn the original study , all womThe calculations were performed on the index unprocessed, i.e., “DICOM For Processing” mammograms, which included at least one standard view . Tiled views of large breasts were excluded. Arbitrarily, the measurements were performed on the left breast by default, except when the left views were not available. When multiple views were obtained for one projection, the values were averaged. Initially, there were images from 2047 cancer-free women: 4 were excluded because of tiled views; 31 and 11 were excluded due to failure of the Volpara calculation or our detectability algorithm (described below), respectively; 104 were excluded due to missing BI-RADS data, resulting in the images of 1897 women available for analysis.The development of the masking risk algorithm was previously described in detail , but is In the modeling , the assTo predict how many women without breast cancer would be recommended for supplementary screening with each of the masking prediction models, it is necessary to run the algorithms on sets of normal cases. The three models: “BI-RADS Density,” “Adjusted Volpara,” and “DETECT+,” under consideration for use for stratification are summarized in Table Our approach to stratification is to try to maximize the number of women for whom there is the potential for cancer masking who will be identified for supplemental screening while minimizing the number whose cancers (if present) are expected to be detectable on mammography. These two competing factors are computed to determine the efficiency of a simulated stratified screening environment.RF), which is the fraction of cancer-free women whose mammograms would be rated above the masking threshold, and (2) the capture fraction (CF), the fraction of women from NSD cases whose mammograms are above the same masking threshold. We examine the relationship between RF and CF at different settings of the threshold. In this analysis, the cancer-free women are used as a proxy for a screening population.The masking risk is computed on each of the images using the models described above. Each model is tested over a range of candidate thresholds of masking risk. The threshold (or operating point) distinguishes between images that are deemed to be “masked” or “non-masked.” Women identified as “masked” are the ones who would be considered as potential candidates for supplemental imaging. For those women, two fractions are determined: (1) The recruitment fraction . This ratio represents the “cost” of the supplemental screening program, in that as more women receive the additional screen (with the benefit of detecting missed cancers), more inconvenience to women and financial costs are imposed on the health care system. The most efficient (or lowest cost) supplemental screening program will have the lowest RF:CF ratio. See the CF and RF for the models discussed here. To evaluate performance, the C-statistic or discrimination accuracy of the masking risk models was computed. This is the probability that a model will score a randomly selected NSD exam at a higher masking risk than a randomly selected cancer-free exam.Given an underlying NSD cancer rate  in a population of N was set to 100,000. Error estimates on the values of the cost function were estimated by bootstrapping, for 1000 bootstrap replicas, using the “bootci” function in Matlab 2016b .For simulating a screening program, an ICR of 0.60 per 1000 screens was estimated using data from the Breast Cancer Surveillance Consortium (BCSC) as reported by Kerlikowske et al. . Here, Np value of the difference between the two groups was computed using a two-sample t test or chi-square test for the continuous or categorical data, respectively.Table CF vs. RF for the three stratification models.Table CF = 64%), supplemental screening would be performed for RF = 43%, 40%, and 28% of screening participants when supplemental screening is triggered on the basis of BI-RADS 3 or 4 density category, Adjusted Volpara, or DETECT+, respectively. This corresponds to 1117, 1051, and 725 supplemental screens per interval cancer detected. Figure Table CF values of approximately 50%, 30%, and 20% respectively for the DETECT+ model.Figure Table RF = 12.6%) to potentially detect 24 interval cancers (CF = 40%), representing a costs of 523 supplemental screens per interval cancer. When inverted, this costs represent 1.9 interval cancers potentially detected per 1000 supplemental screens. The Adjusted Volpara model requires, at the same operating point, 39% additional supplemental screens to potentially detect the same amount of interval cancers in 100,000 women. The discriminatory accuracy (C-statistic) between interval cancer cases and cancer-free women of the DETECT+ model was the largest at 0.72 [0.65–0.79]. Based on confidence intervals, the DETECT+ model was statistically better than the BI-RADS model, and just short of a statistical difference to the Adjusted Volpara model.The DETECT+ model offers the lowest cost over a wide range of capture fraction (CF = 14 to 98%) of interval cancers. The cost for the Adjusted Volpara model is lower only at the relatively low capture fraction of 10% . For example, the DETECT+ model requires 12,588 supplemental screens (RF = 9.3%) would be required, with 8 of the interval cancers potentially detected (CF = 13.6%). This corresponds to a cost of 1140 supplemental screens per interval cancer detected. Interestingly, at the same CF, the DETECT+ model would label only approximately 18% of the BI-RADS 4 examinations as masked, yet has a cost of only 374 supplemental screens per interval cancer (RF = 3.1%).The BI-RADS-based model was considered, primarily because this system is widely used by breast radiologists; however, its major limitations are that it has higher costs and has only three operating points. For example, if the threshold for suggesting supplemental screening was for women with extremely dense breasts (BI-RADS 4) only, 9331 supplemental screens  that is based on Volpara VBD as well as lesion size and location. The performance of the DETECT+ metric in a supplemental screening environment is similar but marginally better than their results. They also present results using Volpara VBD alone, which outperforms the Adjusted Volpara model shown in this analysis. This finding may be due to the fact that the models of Holland et al. ; however, there were a relatively small number of Hologic NSD cases in the set. In ongoing work with a broader data set, we will determine if a system-dependent covariate will improve the model. It is noted that the GE system was introduced to the clinic earlier when experience with digital mammography was quite limited and the majority of the NSD cases come from this time period.This study has several limitations. In the dataset, there were a small number of cancers with extremely dense BI-RADS category, very high VBD or very low detectability, resulting in the fairly wide confidence intervals seen for low numbers of interval cancers detected. These women, who have the highest masking risk, would likely be offered supplementary screening according to any of the models used.These models are currently being tested in a larger population for further validation and to predict the costs of supplemental screening. The simplifying assumption was also made that all interval cancers would be detected by supplemental screening tests. While supplemental screening will increase cancer detection , some caThe masking risk estimator presented in this investigations shows good potential for guiding stratification of breast cancer screening. This estimator is more efficient than using BI-RADS density and provides a continuous scale, allowing for optimizing the balance between the number of women receiving supplemental screening versus the number of interval cancers potentially detected.


Background and Objectives: Breast cancer is the most prevalent cancer in women worldwide. Lebanon is a developing country in the Middle East with a prominent breast cancer incidence. The aim of our study was to explore the incidence rates of breast cancer in Lebanon from 2005 to 2015, and compare them to the rates of other countries. Materials and Methods: Breast cancer data for the years 2005–2015 was collected from the National Cancer Registry of Lebanon and stratified by gender and age group. Age-specific and age-standardized incidence rates were calculated and analyzed using joinpoint regression. Age-standardized incidence rates in the world population (ASR(w)) were obtained for other countries, from two online databases. Results: Breast cancer was found to be the most prevalent cancer in Lebanon, accounting for 20% of all cancer cases. The average ASR(w) was 96.5 per 100,000. Over the studied period, breast cancer ASR(w) in Lebanon showed a significantly increasing trend with an annual percent change (APC) of +4.6. Moreover, the APC of breast cancer age-specific rates significantly increased for the age groups 45–49 (p = 0.013), 50–54 (p < 0.001), 55–59 (p = 0.001), 60–64 (p = 0.002), 65–69 (p = 0.003), 70–74 (p < 0.001), and 75+ years (p < 0.001). Lebanon had the highest breast cancer ASR(w), when compared to other regional countries, and trailed only behind Denmark, when compared to selected countries from different parts of the world. Conclusions: Breast cancer incidence in Lebanon is among the highest in the world. Future studies should focus on exploring the genetic profile of the Lebanese population in an aim to extrapolate proper prevention guidelines. Breast cancer is the most prevalent cancer in women worldwide, and as a result, constitutes a major public health issue . AnnuallBreast cancer is considered highly heterogenous in etiology, pathology, and outcomes with some cases showing great prognosis and others showing aggressive clinical results ,7,8,9,10Lebanon is a small developing country in the Middle East, with a prominent breast cancer incidence ,13. NumeOur study aimed to analyze the 11-year incidence rates of breast cancer in Lebanon from 2005, up to 2015. This study will also compare the incidence rates in Lebanon to the rates of other regional countries on the one hand, and selected countries from around the world on the other, and discuss the possible risk factors of this disease.The Lebanese NCR was screened for the time period 2005–2015, to compute the age-specific incidence rates and the age-standardized rates (ASR(w)), expressed per 100,000 population. The age-specific incidence rate constituted the number of new cancer cases that occurred during a specific time-period, in a population of a specific age and sex group, divided by the number of midyear population of that age and sex group. The ASR(w) were the incidence rates that would have been observed in our studied population if they have had the same age composition as a reference population. Standardization is pivotal when comparing between different populations and age structures. In our study, we used Ferlay’s modified world population as the reference to compare the results of our population to those of different countries .The computed age-specific rates and ASR(w) were analyzed using the joinpoint regression analysis with a significance level of 0.05. The joinpoint model provides information on the trends of breast cancer development, specifically the annual percent changes (APC) of breast cancer incidence, over the years studied. The computed age-specific rates and ASR(w) were then compared to those of the regional countries and other selected countries from different parts of the world. The selected countries were randomly chosen, using a random name picker, available on a website that allows the generation of country names, using the method of simple randomization . These chttps://www.moph.gov.lb/en). As such, it did not require an IRB approval.With regards to the need for an Institutional Review Board (IRB) approval, our study is a descriptive epidemiological study with public data available online and published by the Lebanese Ministry of Public Health (During the studied period (2005–2015), breast cancer was found to be the most prevalent cancer in Lebanon with a total of 22,357 cases reported, accounting for almost 37% of cancer cases among females, and 20% of all cancer cases. Lung cancer and colorectal cancer followed, with 10,459 and 9162 cases, respectively. An average of 2033 cases were reported every year. In general, the majority of patients were 35 years and older (90.3%).p = 0.013, CI ), 50–54 , 55–59 , 60–64 , 65–69 , 70–74 , and 75+ years  (2 = 0.85) and reached a peak of 317.1 per 100,000, for the 50–54 years age group (The breast cancer ASR(w) among Lebanese females averaged 91.7 per 100,000 between 2005 and 2015. The rates ranged between 71 and 115.6 per 100,000. The annual percent change (APC) of breast cancer incidence rate, calculated using the joinpoint regression analysis, was found to be +4.6, indicating a significant increase along the years of our study . The APC4, 8.6]) . The incge group .Lebanon ranked first with respect to breast cancer ASR(w), followed by Malta and Kuwait with ASR(w)s of 79 per 100,000 and 56.1 per 100,000, respectively. In contrast, the Batna province of Algeria had the lowest ASR(w) of 25.9 per 100,000. When compared with breast cancer ASR(w)s of the randomly selected countries, Lebanon ranked among the highest, trailing only behind Denmark, which had an ASR(w) of 97.3 per 100,000; and surpassing both Germany and Italy which had ASR(w)s of 90.9 per 100,000 and 90.1 per 100,000 respectively . The lowBreast cancer was found to be the cancer with the greatest number of cases in the Lebanese population. ASR(w) among Lebanese females were found to be the highest in Middle-Eastern countries, and among the highest in the world .Several social and health factors entail a variation in breast cancer incidence between different countries. The disparity in the implementation of screening procedures and awareness campaigns across different populations leads to a difference in reporting of breast cancer incidence ,31,32. LMany reproductive features present in Lebanese women predispose them to breast cancer more so than other countries . The meaSmoking has been known to increase the risk of breast cancer as well, and it has been found to be high among the Lebanese population ,37. Its Breast cancer incidence rates among Lebanese women increased significantly during the studied period. This might be attributed to the rise of the mean marital age, the drop in fertility rates, the high prevalence of obesity and smoking, the increased efficiency and improvement of NCR, and the rising use of mammography in the Lebanese population ,35. In aMany studies in Lebanon report that peak incidence of breast cancer occur at younger ages, as compared to other countries ,44. The BRCA mutations ranging between 5.6% to 12.5% of breast cancer cases, lower than those found in other populations. Given the genetic heterogeneity of this disease, this suggests the involvement of other genetic mutations in the pathogenesis of breast cancer in Lebanese women [In addition, several studies in the literature explored the genetic susceptibility of the Lebanese population to breast cancer ,46,47. Tse women . One stuse women . Anotherse women . Estrogese women . Such inse women ,49,50.It is worth mentioning that despite the high incidence of breast cancer among Lebanese women, breast cancer prognosis in the Lebanese population has been improving substantially. This is due to the improvement of the NCR, and the elevated drive towards earlier screening . As a reBreast cancer rates among Lebanese women have been increasing for years and are amongst the highest in the region and worldwide. Many risk factors predispose Lebanese women to breast cancer and these include high mean marital age, low fertility rate, and the prevalence of obesity and smoking. Increased efficiency of the NCR in reporting breast cancer cases, higher awareness levels among the population, and the wider implementation of screening procedures contribute to the greater incidence of this disease as well. Future studies should aim at exploring the genomic profile of the Lebanese population, to propose better screening guidelines and prevention modalities.


Previous studies on the link between macronutrients and breast cancer have mostly focused on individual macronutrients rather than their combination. This study investigates the association between adherence to a low carbohydrate diet and odds of breast cancer among women.This hospital-based case-control study was carried out on 412 women with pathologically confirmed breast cancer within the past year and 456 apparently healthy controls that were matched in terms of age and residential place. Dietary data was collected using a 168-item validated FFQ. Participants were classified in terms of quintiles of percentages of energy intake from carbohydrates, proteins, and fats. Then, individuals in the highest quintile of fat and protein intake were given a score of 5 and those in the lowest quintile of these macronutrients were given a score of 1. Participants in the other quintiles of these macronutrients were given the corresponding score. In terms of carbohydrate intake, those in the highest quintile received a score of 1 and those in the lowest quintile received 5. The scores were then summed up to calculate the total low carbohydrate diet (LCD) score, which varied from 3 to 15. A higher score meant greater adherence to a low carbohydrate diet.2. Mean LCD score of participants was 8.9 ± 2.5 (8.9 ± 2.6 in cases and 9.0 ± 2.5 in controls). Although no significant association was observed between adherence to the LCD score and odds of breast cancer in the study population, a trend toward significant positive association was seen between consumption of LCD and odds of breast cancer in postmenopausal women; after controlling for several potential confounders, individuals in the third quartile of LCD score were 1.94 times more likely to have breast cancer than those in the lowest quartile . This association strengthened after controlling for dietary variables . Even after further adjustment for BMI, this association remained significant . No significant relationship was observed in premenopausal women, either before or after controlling for confounders.The mean age of study participants was 45.2 y and mean BMI was 28.4 kg/mAdherence to LCD may be associated with increased odds of breast cancer in postmenopausal women. Prospective cohort studies are needed to confirm these findings. Low- carbohydrate diets (LCD) are popular diets, and studies have reported beneficial effects on several chronic diseases, including obesity , diabeteAn inverse association was reported between adherence to LCD and risk of mortality from all causes, and also from cancer and cardiovascular disease –17. DespThe dietary intake of people in the Middle-East, due to its heterogeneity as well as other general characteristics, provides a unique opportunity to examine the relation between diet and disease. Most people in this region consume refined grains (refined bread and white rice) as their staple food . In addin = 486) were breast cancer patients that referred to surgery, chemotherapy or radiotherapy departments of Iran Cancer Institute that is located at a major teaching and general hospital, Imam Khomeini complex in Tehran. All patients had pathologically confirmed breast cancer within the past year. They had no history of any other cancers and long term dietary restrictions. Controls were 523 apparently healthy subjects [frequency-matched to cases by age (±10 years) and place of residence] admitted to the same hospital as healthy visitors, relatives and friends of non-cancer patients. They had no long term dietary restrictions. Individuals with a total energy intake of > 4500 or < 800 kcal/d (n = 116) as well as those who had no response to more than 70 items of FFQ (n = 25) were excluded from the study. Eventually, 412 cases and 456 controls remained for the current analysis. The study was approved by the Bioethics Committee of Iran Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran, and all participants gave written informed consent at the beginning of the study.We conducted a hospital-based, case-control study between 2014 and 2016 among Iranian women aged 19–80 years old. Cases  score. The score for each participant ranged from 3 to 15. A higher score meant greater adherence to a low carbohydrate diet.Weight was measured using digital scales to the nearest 100 g. Study participants were minimally clothed and without shoes during weighing. Height was measured while the women were standing and without shoes, using a tape meter. Body mass index (BMI) was calculated using measured weight and height. Data on physical activity was collected via a validated questionnaire, the Global Physical Activity Questionnaire (GPAQ) . PatientP values < 0.05 were considered statistically significant. The analysis was performed by STATA version 14 .Analyses were done in the total study population as well as stratified by pre- and postmenopausal status. Individuals were categorized based on quartiles of LCD scores. We used one-way ANOVA and chi-square tests to compare continuous and categorical variables, respectively, across quartiles of LCD score. Multivariable logistic regression models were used to assess the association between adherence to LCD and risk of breast cancer. The analyses were first adjusted for age (continuous) and additionally for physical activity (continuous), family history of breast cancer (yes vs. no), educational level , parity , oral contraceptive use (yes vs. no), menopausal hormone use (yes vs. no), tobacco use (yes vs. no), alcohol use (yes vs. no), infertility treatment (yes vs. no), marital status . We further controlled for dietary intake of vitamin B6, iron, folic acid, vitamin A and vitamin E . Finally, we made adjustments for body mass index (continuous). The trend of odds ratios across quartiles of LCD score was examined by considering the median value of LCD score in each category as a continuous variable. P = 0.003), had lower BMI , and were more likely to have a family history of breast cancer  compared to controls (Table P = 0.001), married , use oral contraceptives , use postmenopausal hormones  and drink alcohol  than controls  across quartile categories of LCD score are provided in Table Table Multivariable-adjusted odds ratios and 95% CIs for breast cancer across categories of LCD score are provided in Table In this case-control study, we found that adherence to a low-carbohydrate diet was not significantly associated with increased odds of breast cancer in the study population, a trend toward significant positive association was seen between consumption of LCD and odds of breast cancer in postmenopausal women. To our knowledge, this is the first study examining the relationship between low-carbohydrate diet score and risk of breast cancer in a Middle- Eastern country.Earlier studies on the association between dietary carbohydrate intake and several outcomes have mostly examined total carbohydrate intake alone or in the context of low-carbohydrate, high-protein (LCHP) or low-carbohydrate, high-fat diets , 33–35. When we analyzed the results by menopausal status, a trend toward significant association was observed between adherence to LCD and risk of breast cancer among post-menopausal women. Despite lack of a significant association between dietary GI and risk of breast cancer in the population, Canadian researchers found a positive association between high GI diets and increased risk of breast cancer among postmenopausal women . In a caAlthough there are no clear mechanisms on the link between low carbohydrate dietary patterns and risk of breast cancer, some studies suggest some potential mechanisms. High carbohydrate intake was associated with elevated blood glucose and insulin levels, which can promote glucose intolerance, insulin resistance and hyperinsulinemia. Warburg et al. expressed that cancer cells depend on glucose as a fuel . InsulinThe strengths of the current study include considering several potential confounders, recruiting participants from a referral hospital, in which subjects are from all across the country. Stratified analysis by menopausal status is a strength of this study. However, several limitations need to be considered. First, due to the case-control design of the study with its inherent recall and selection bias, one cannot infer causality. Second, as with all epidemiologic studies that apply FFQ, misclassification of participants in terms of dietary intake cannot be excluded. Third, prominence in the third quartile may be due to chance as the sample size is limited in each quartile. Therefore further studies with larger sample sizes are needed to confirm this finding. Fourth, we did not gather information on the hormone receptor status of participants. This may affect our findings.Based on the present findings, we found no evidence on association between consumption of a low carbohydrate diet (LCD), and odds of breast cancer risk in the study population; however, adherence to LCD might be associated with increased odds of breast cancer in postmenopausal women. Further research, especially cohort studies are needed to confirm these findings.


There have been many original and review articles summarizing the impact of nutrition and diet on breast cancer risk. However, very few consider the implication of genetic background and the effect of personalised nutrition on the risk and prognosis of breast cancer. A literature search was performed using the following databases: MEDLINE (Ovid), PubMed, Scopus and EMBASE (Ovid). The ensuing search terms were selected: genomics, nutrigenomics, breast cancer, breast neoplasms, cancer, nutrigenetics, diet–gene interaction, and Mediterranean, nutrition, polyphenols and diet. In this review, we discuss the Mediterranean-style diet and associated nutrients, evidence of benefit, impact on gene expression and evidence of interactions with genotype and how this interaction can modify breast cancer risk and progression. In addition, the impact of nutrients commonly associated with a Mediterranean-style diet, on breast cancer treatment, and synergistic effects are mentioned when modified by genotype. Some evidence exists around the benefit of a gene-based personalised diet based on a Mediterranean-style dietary pattern, but further evidence in the form of clinical trials is required before such an approach can be comprehensively implemented. The incidence of non-communicable diseases such as cancers, cardiovascular diseases and diabetes has increased with an aging population. However, aging is not the only risk factor for non-communicable diseases. Lack of physical exercise, excess calorie intake and a diet low in unprocessed foods, fruit and vegetables, and high in meat, fats, salt and sugars have contributed to the rise in non-communicable diseases . Based oThe excitement surrounding a personalised approach to diet comes from a growing awareness of the potential for modifications of food or diet to reduce the risk of non-communicable diseases. This is as a result of the increasing knowledge of the importance of the individuals’ genetic response to diet . It is aThis review focuses on the effect of the Mediterranean-style diet (MD), and relevant food-related bioactive compounds, on the risk and progression of breast cancer. It encompasses a general overview of nutrigenomics, the role of single nucleotide polymorphisms (SNPs) in diet–gene interactions and how components of the MD may influence epigenetics and thus modify gene expression and impact breast cancer risk.Breast cancer ranks as the second most frequent type of cancer globally, and the fifth leading cause of cancer-related deaths overall . In womeDiet is an important pillar of any lifestyle, and can be used as a beneficial factor to help prevent cancer in general, and breast cancer in particular . In addiGenetic variants are relevant not only to breast cancer risk, but genotype may influence an individual’s nutritional behaviour as well as response to specific nutrients. For example, some genetic variations related to adiposity could affect energy intake by influencing satiety/appetite . In addiBreast cancer is a disease that may develop and/or progress due to several possible reasons, including non-modifiable factors such as increasing age and genotype, as well as modifiable factors such as smoking, alcohol consumption, lack of physical activity, poor diet and obesity. Obesity and being over-weight play a critical role in increasing the risk of breast cancer recurrence and arises due to an energy imbalance. In a meta-analysis of 43 studies carried out by Rock et al., the risk of recurrence was markedly higher amongst obese breast cancer survivors than those who were not obese . A recenp53, were decreased due to a high intake of linoleic acid (commonly found in plant oils) [p53 was up-regulated by docosahexaenoic acid (DHA) [retinoic acid receptor beta (RARB) or breast cancer one (BRCA1) genes. This interaction was demonstrated amongst 146 Iranian women with breast cancer in an age-dependent manner [In addition to an energy imbalance, the interaction between several dietary nutrients and gene expression is of interest in the field of tumorigenesis. For example, the protein levels of the tumour suppressor gene, nt oils) ,21. Howeid (DHA) ,21, whict manner . The afoThe MD diet is one of the most popular dietary patterns currently being examined in the field of cancer prevention and treatment outcomes. The Mediterranean-style dietary pattern is a dietary style followed by populations living around the Mediterranean Sea . The dieWe are well aware that high alcohol consumption is associated with harmful effects on health, some of which include the increased incidence of cancers , liver dInterestingly, implementing a healthy dietary intervention could not only decrease incidence, but also indirectly improve outcome in breast cancer survivors by promoting weight loss and reducing obesity ,30,31,32This review explores evidence to convey that the Mediterranean-style diet might be a beneficial dietary pattern to influence breast cancer outcomes, as well as the influence of the diet on biomarkers associated with the risk of recurrence. In addition, evidence of the beneficial role of nutrigenomics has been emphasized in terms of breast cancer outcomes in this review. A literature search of the interaction between diet, genetic influence and breast cancer was conducted by using various databases, namely MEDLINE (Ovid), PubMed, Scopus and EMBASE (Ovid). The following search terms were selected: genomics, nutrigenomics, breast cancer, breast neoplasms, cancer, nutrigenetics, diet–gene interaction, and Mediterranean, nutrition, polyphenols and diet. We also applied pearl growing to identify other suitable citations. Our strategy employed the use of medical subject headings (MeSH terms) where possible, but in circumstances when a MeSH term was invalid in a particular database, an equivalent term was substituted. Other than nutrigenomics we have also reviewed some of the works performed in the areas of diet supplementation, diet–gene interaction and dietary guidelines.Publications were selected if they included genotype or gene expression testing and diet-related outcome or intervention in breast cancer risk and/or progression. Studies on non-breast cancer patients, or patients not at risk of breast cancer, were included if deemed relevant to the discussion. Diet is considered one of the most important modifiable factors contributing to cancer prevention . AdherenAlthough adequate hydration is considered essential for life, water intake is seldom considered along with nutrient intake . HoweverDietary fatty acids in general are thought to be linked with cancer risk, development, and survival , despiteIn contrast, a recent in vitro study revealed that the exposure of MCF-7 breast cancer cells (oestrogen and progesterone receptor positive) to phenolic extracts from Brava extra virgin olive oil showed a positive role in minimizing cell viability and promoting the production of ROS and the induction of cell death . In addition to MUFAs, DHA, eicosapentaenoic acid (EPA), and other long-chain polyunsaturated fatty acids (PUFAs) are important fatty acids associated with a Mediterranean-style diet. The consumption of these fats has a promising effect on breast cancer prognosis. A cohort study performed on 3080 breast cancer survivors revealed a decrease in the mortality rate of those who consumed the highest quantity of DHA and EPA from foods . No beneThe role of fats commonly found in a Mediterranean-style diet can be demonstrated by investigating the effect of these fats on biomarkers of inflammation implicated in breast cancer development. Several studies have helped clarify this role, and these studies are presented in this review. The consumption of fish oil and some plant-based oils can play a protective role by reducing chronic inflammation and oxidative stress , both ofp53, were decreased due to a high intake of linoleic acid, in a rat mammary tumour cell lines [p53 was up-regulated by DHA [BRCA1 and BRCA2 [Her-2/neu, an important oncogene in breast carcinoma aetiology and development, has been seen in BT-474 and SKBr-3 breast cancer cells after treatment with oleic acid supplement [Moreover, fatty acid intake may have an effect on cancer risk, initiation, and development through its role in the expression of genes (particularly oncogenes and tumour suppressor genes), and the mediation of cell signalling pathways ,48. Thisll lines . Howeverd by DHA ,21. In and BRCA2 . In contpplement .After finding a protective effect of marine fatty acid intake on breast cancer risk in postmenopausal women, Gago-Dominguez et al. investigated the relationship of their findings with the genotypes associated with glutathione-S-transferase (GST) enzyme activity . They hyIn the same cohort, the genotype of cyclin D1 (CCND1) was investigated for an association between genotype, breast cancer risk and interaction between risk and ω3 fatty acid consumption . AlthougIn addition to the abovementioned genes, the arachidonyl lipoxygenase-12 (ALOX12) A835G genotype is associated with breast cancer risk . The ALOIn general, it is premature to recommend the personalised consumption of olive oils and fish oils based on tumour type or genotype and, at this stage, it would be advisable to recommend the consumption of these oils to all women with breast cancer, or a predisposition to breast cancer.Polyphenols have antioxidant activities and can be found in a wide variety of foods such as fruits, vegetables, cereals, chocolate, dry legumes, green tea, coffee, soy, and red wine . There aThe role of polyphenols in breast cancer has been widely investigated. Evidence revealed via several in vitro and in vivo observations will be explored below. Many observational studies have explained the important role of regular green tea intake on decreasing the risk of developing different types of cancer involving the breast ,64. GreeThe treatment of MCF-7 breast cancer cell lines with EGCG prompted a reduction in cell proliferation and promoted apoptosis by reducing telomerase reverse transcriptase (hTERT) promoter methylation and suppressing histone H3 Lys9 acetylation. This induced a down regulation of hTERT expression  (which gp53 (a tumour-suppressor gene) [Data from an animal study was used to elucidate the role of green tea polyphenols as well as black tea polyphenols in suppressing tumour growth in rats through a variety of mechanisms . These ior gene) . Furtheror gene) . Also, lor gene) . EGCG dior gene) .It is possible that EGCG may influence risk of breast cancer depending on the hormone receptor status of the tumour. In animal models, EGCG inhibited aromatase, which is involved in the conversion of androgen to oestrogen . HoweverGiven the mixed evidence of the benefit of EGCG on reducing breast cancer risk and recurrence, as well as the evidence garnered from in vitro and in vivo studies on gene expression associated with mechanisms of breast cancer, it is highly likely that there is an interplay between EGCG and genotype on breast cancer risk. However, to date, the evidence is lacking.Resveratrol is found in numerous plant-based products, including grapes, blueberries and some nut varieties. Also, it is abundant in red wine and dark chocolate , hence tBRCA1 and BRCA2 mRNA. These genes are known as major breast cancer-promoting genes, but the protein expression of these genes remained constant [BRCA1 promoter and enhancing MCF-7 breast cancer cell silencing [One of the abnormal events implicated in breast tumour development is silencing tumour suppressor genes through chromosome instability and DNA hypermethylation ,77. DNA constant . Moreoveilencing . In addiilencing .Resveratrol has been under investigation in term of its effect on inflammation and oxidative stress for some time. Treating female Sprague–Dawley rats with 100 µg of resveratrol led to an inhibition of 7, 12-Dimethylbenz(a) anthracene-induced tumorigenesis in rat mammary glands as well as suppressing subsequent effects including the activation of COX2, NF-κB and the expression of MMP-9. In the same article, the authors reported that the administration of resveratrol in MCF-7 breast cancer cells resulted in the suppression of NF-κB activity . Additio2 [In human trials, the role of circulating levels of resveratrol was evaluated in women at a high risk of developing breast cancer. The resveratrol-supplemented group revealed decreased Ras association domain family 1 isoform alpha (RASSF-1α) methylation, which is associated with enhancing cancer-promoting prostaglandin (PG)E2 . Despite the fact that red wine contains beneficial polyphenols, including resveratrol, the effect of alcohol consumption on breast cancer risk is controversial. This controversy may be due to the fact that not all studies differentiate between the sources of alcohol intake, while others specify their interest in red wine intake only. In addition, accurate information on red wine intake over the life cycle is difficult to collect. Ethnicity, folate deficiency and genotype may all influence the impact of red wine intake and breast cancer susceptibility and recurrence, and not all researchers have taken this into consideration when designing their studies and analysing results.BRCA1 mutation carriers [Some studies have demonstrated the possible protective effects of red wine consumption in carriers ,86, whilcarriers ,88. BRCA1 and BRCA2 protein transcription [The benefit of red wine intake to some women with breast cancer was evident in observational studies and was attributed to the binding of resveratrol to the oestrogen receptor, which promotes cription ,89. Subscription ,89. In ccription .In the context of cancers and alcohol consumption, it is important to consider folate blood concentrations. Although not proven in breast cancer, folate deficiency, together with high alcohol consumption is known to be a risk factor for colorectal, oesophageal and liver cancers together with genetic variants of the one-carbon metabolism pathway . The genDespite the evidence presented thus far, although the polyphenolic content of red wine could have a positive impact, the alcoholic content of red wine could have a negative impact on the epigenetic process with regards to breast cancer risk. A plausible mechanism of the effect of alcohol in epigenetic alteration is the increase in DNA methylation . Meng anIn response to previous findings of the strong correlation between elevated insulin-like growth factor-I (IGF-I)/insulin resistance (IR) axis and increasing risk of breast cancer ,94, a reIn conclusion, in addition to alcohol intake, nutrient intake may modify breast cancer risk. High folate intake is suggested to decrease the risk of breast cancer resulting from alcohol consumption in some genotypes . The mecThese compounds include the sulforaphane group, which are dietary isothiocyanates that can be acquired from cruciferous vegetables such as sprouts and broccoli. The exposure of an oestrogen receptor-negative breast cancer cell line to a combination of sulforaphane, green tea polyphenols, and Tamoxifen, increased cell death and suppressed proliferation compared to Tamoxifen exposure alone . This reAs a source of sulforaphane, 200 g/day of broccoli protected both smokers and non-smokers against DNA damage , and smoAlthough data regarding gene–nutrient interventions is not readily available, women at risk of DNA damage from smoking or with a low antioxidant capacity (due to genotype) would be encouraged to consume diets high in organosulfur compounds.This flavonoid compound is found in fruits, such as apples and grapes, and in specific vegetables such as onions, kale, broccoli, lettuce, and tomatoes. Quercetin has been shown to have a protective effect on anti-cancer activity  by supprMore and more research is being carried out on the synergistic effects of quercetin and anticancer drugs, for example Doxorubicin, which is a drug used to treat a number of cancer types, including breast cancer, shows enhanced activity when administered with quercetin in in vitro assays . It is aKaempferol is a phytoestrogen and a flavonoid that is found in a variety of fruits and vegetables, for example in grapefruit and grapes, as well as broccoli and beans. Kowalski et al. have shown that the treatment of J774.2 macrophages with kaempferol, in combination with apigenin and resveratrol, plays a significant role in suppressing the expression of TNF-α and interleukin-1β (IL-1β). Treatment with kaempferol also blocked the transcription of these two cytokines by reducing the level of mRNA . Additiop53 [Kaempferol inhibits the progression of a number of cancer types and in breast cancer, it is believed to inhibit cancer cell proliferation via cell cycle arrest and the upregulation of p53 , and alsp53 . In tripp53 . The mecp53 , and thip53 .Similar to the situation with quercetin, the bioavailability of kaempferol needs to be enhanced, and synergistic effects need to be elucidated. Plant-based foods such as parsley, chamomile tea, oranges, and grapefruit are sources of this flavonoid compound. Treating breast cancer cells with apigenin played a role in inhibiting cell proliferation, promoting cell cycle arrest and ROS generation . This poCDKN2A and p53, and decreased the expression of mdm2 [CDKN2A and p53 are important genes for inducing apoptosis and promoting survival, whereas mdm2 acts as a promoter for p53 gene degradation [Zinc contributes to the regulation of many intra- and extra-cellular pathways involved in cell proliferation, differentiation, development, apoptosis, and transformation ,123,124. of mdm2 . CDKN2A radation .The deficiency of this micronutrient plays an important role in DNA replication and repair by disrupting proteins and molecular actions involved in this process ,124. ZinBRCA1 carriers and non-carriers and a positive impact was found such that both groups with high serum levels of zinc had a lower incidence of breast cancer [BRCA1 gene carriers [Although there is limited evidence on the direct effect of zinc intake on breast cancer, in some studies, the effect of zinc intake has been explored. For instance, Kelleher et al., 2009  examinedt cancer . The procarriers . More clSe is a micronutrient essential for human health and associated with multiple diseases including cancers . Se is nIn vitro studies were used to evaluate the effects of Se-yeast and methylseleninic acid intake on oxidative stress, growth inhibitory activity and apoptosis in ER-positive MCF-7 and triple-negative MDA-MB-231 cells . Lower lBRCA1 gene carriers. Adequate serum Se concentrations have also been shown to be beneficial. However, both high and low levels may be harmful. To date, there is no evidence to support the personalisation of Se based on genotype.In conclusion, an adequate intake of zinc is essential, as zinc deficiency can impair DNA replication and promote abnormal cell growth. On the other hand, adequate levels can lower the risk of breast cancer in In multiple studies, the focus of dietary impact was on breast cancer outcomes. However, strong evidence to support the benefit of various dietary patterns is still lacking . One posA common means of assessing adherence to a Mediterranean-style dietary pattern is via the calculation of a dietary adherence score. No single scoring system has been used across all relevant studies, and hence variations in scoring, and therefore correlations between scores and biomarkers of disease risk and molecular pathways, may be inconsistent.A Mediterranean-style dietary pattern, from a medical/health research perspective, is often assessed on dietary intake only. However, such a dietary pattern incorporates a particular lifestyle that includes physical activity, culinary activities that involve friends and family, and conviviality  . GeneralAdherence to a Mediterranean-style dietary pattern is often assessed through the application of scoring system. These scoring systems differ, and therefore results/correlations may not be directly comparable. In addition, a high score on a MD adherence questionnaire does not necessarily imply adequate nutrient intake , althougA Mediterranean-style dietary pattern constitutes a moderate intake of alcohol , but theFrom the numerous studies presented in this review, it can be clearly seen that following a MD diet could be beneficial to health in general and help protect against breast cancer risk and recurrence in particular. To further support this notion, nutrients contained in a typical MD diet displayed a positive impact on biomarkers of inflammation, DNA damage, oxidative stress, and genetic alterations, all of which may influence breast cancer outcomes.Clearly, the host genotype also plays a role, not only in susceptibility to breast cancer, but also with regards to benefits obtained from typical foods and nutrients that make up the MD diet. In order to maximize the effect of nutrients on genotype, further research is required to discover additional diet–gene interactions. In addition, it is necessary to define the concentrations of nutrients, and synergistic effects between nutrients, as well as between nutrients and anticancer drugs in relation to genotype.