LEP (2548G>A) and LEPR (109 Lys>Arg and 223Gln>Arg) genes polymorphisms to the risk of breast cancer development. The study involved 209 women aged 59.6 ± 11 years diagnosed with breast cancer and 202 healthy women aged 57.8 ± 8.2 years, who were blood donors. Polymorphism were evaluated by PCR–RFLP reaction followed by the verification of part of the samples by sequencing. The results of the study confirmed obesity as a significant breast cancer development risk factor in Polish women. However, no significant association between the studied polymorphisms and breast cancer risk or severity of the neoplastic disease was found. Interestingly, it was shown that wild type 223Gln>Gln leptin receptor (LEPR) was statistically more common in women with human epidermal growth factor receptor 2 negative (HER2−) than human epidermal groth factor receptor 2 positive (HER2+) breast cancer and wild type form of 2548G>A LEP was more common in women with progesterone receptor positive (PR+) than progesterone receptor negative (PR−) breast cancer. Studied polymorphisms of the LEP and LEPR genes do not increase breast cancer risk in the population of Polish women. However, they can affect PR an HER receptors expression and thus the severity of the disease. Noteworthy, this interesting correlation is being reported for the first time and might constitute an essential contribution to the identification of molecular mechanisms of carcinogenesis.On a global scale, breast cancer is the most common type of cancer in women, and it is still a growing problem. Therefore, new prognostic or diagnostic markers are required that would facilitate the assessment of patients or provide more efficient therapy, respectively. In these studies, we analyzed the contribution of  LEP gene [LEPR gene [The increasing incidence of breast cancer in both women and men is significantly correlated with obesity . AdiposeLEP gene . BiologiEPR gene . The mosEPR gene . Leptin EPR gene . It is aEPR gene , 7.ERBB2) [Interestingly, a positive correlation was found between the leptin level and the incidence of breast cancer, which probably results from the proinflammatory, pro-angiogenic, and pro-carcinogenic activity of this protein. Both in vitro and in vivo studies have shown that leptin stimulates tumor growth and cell migration, thereby increasing the risk of distant metastasis , 9. LeptERBB2) . As a reERBB2) —to terazERBB2) . Leptin ERBB2) . An incrLEP and LEPR genes, which can be affected by polymorphisms [The increase in serum leptin concentration may be due to excess body fat or a decreased leptin receptor functioning/sensitivity. The production of leptin may also depend on the expression of the orphisms .LEP gene  and polymorphisms of the LEPR gene in position 326 (326A>G) which results in the conversion of lysine to arginine at position 109 of the leptin receptor  and position 668 (668A>G) resulting in the conversion of glutamine to arginine at position 223 , respectively [The most significant effect on the function of these proteins seems to be correlated with the polymorphisms in the position 2548G>A of the ectively .LEP polymorphic allele A (2548G>A) varies in different populations. This polymorphism is found in the gene promoter region, thus can regulate the binding of transcription factors and, consequently, contribute to the change in LEP gene expression and serum leptin levels [LEPR gene encoding the leptin receptor extracellular domain. Replacing amino acids in this part of the protein may interfere with the binding of leptin, which can lead to the lack of a biological effect and increased leptin concentration. The frequency of both polymorphic forms varies between populations [LEP and LEPR genes polymorphisms on the development of breast cancer in women from the Greater Poland region. Unfortunately, since these were just retrospective studies based on the assessment of already collected blood samples (with no plasma fraction), we could not evaluate the correlation between the leptin level and the LEP/LEPR genotypes.Noteworthy, the frequency of the n levels . The pren levels . The Lysulations –21. In sBased on the population data on the incidence of breast cancer among women from the Greater Poland region the sample size and power was calculated with calculator.net (α = 0.95).The control group consisted of 202 women in menopausal age (age 57.8 ± 8.2) who were blood donors at The Regional Center for Blood Donation and Blood Treatment in Poznań, Poland. Women were diagnosed as cancer-free.The health status of blood donors was assessed using: medical history including the age of the donor, past diseases, lifestyle, medicines and treatments; physical examination including body height and weight, body temperature measurement, blood pressure, and heart rate, and assessment of lymph nodes; laboratory blood tests including blood counts, total protein level, presence of HBs antigen, anti-HIV antibodies, anti-HCV antibodies, HCV RNA, HBV DNA, and HIV RNA.The study group consisted of 209 women aged 59.6 ± 11 hospitalized in the Department of Oncology, Poznan University of Medical Sciences. They were diagnosed with various types of breast cancer at various stages. The most common type of tumor (50.5%) was invasive ductal carcinoma (IDC).DNA was isolated from blood remaining after standard laboratory test. All women agreed to use their blood for research. The study obtained the permission of the Bioethics Committee of the Poznan University of Medical University, No. 568/18.LEP and LEPR genes fragments was performed using specific primers at the optimal annealing temperature and reaction conditions that were determined experimentally (Table LEP gene polymorphism with a length 242 bp were digested with a specific restriction enzyme (CfoI) . Amplification of ly Table . The comly Table . Then 1 s Tables . All priTo assess the specificity of restriction enzymes digestion, 10% of the samples were subjected to sequencing using the BigDye v3.1 kit  and separation by ethanol extraction using the ABI Prism 3130XL  in a 36 cm capillary in a POP7 polymer.t-test. The occurrence of genotypes in the study group with different tumor stage and grade was assessed using the Hardy–Weinberg equilibrium (χ2 test). Odds ratio (OR) and 95% confidence intervals (CIs) was also calculated. A p-value of < 0.05 was considered statistically significant (Statistica 6.0).We used Fisher’s exact test to examine the distinction in the genotypic and allelic frequencies between the cases and control. The continuous variables between the studied groups were com-pared with the Student’s The observed genotype frequency distribution did not show significant deviation from Hardy Weinberg equilibrium Table . The anaLEP (2548G>A) and the LEPR gene (109Lys>Arg) in the group of women with breast cancer and healthy women. Genotype distributions and allele frequencies of the leptin gene 2548G>A polymorphism in the group of women with breast cancer were 34% for WW, 47% for WV, 19% for VV, and in the group of healthy women it was 33% 43.5%, and 23.5% respectively.Analysis of the results did not show a statistically significant difference between the frequency of polymorphisms of the LEPR polymorphism 109 Lys>Arg occur in the group of women with breast cancer with frequency 47% for WW, 44% for WV, 9%for VV, and the group of control subjects 50.5%, 37%, and 12.5%. These differences are also not statistically significant. However, analysis of polymorphism 223Gln>Arg showed that the polymorphic allele occurred statistically more often in the control group than in the study group (p = 0.05)  Table .Table 6ILEP and LEPR genes polymorphisms on the body mass of women with breast cancer and control subjects was assessed. It was shown that the polymorphic allele 109Arg>Arg (LEPR) correlated with the increased body weight of healthy women . However, there was no association between LEP (2548G>A) and LEPR (223Gln>Arg) genes polymorphisms and the body mass index weight in both groups (data not shown).Leptin is produced by adipose tissue which amount directly affects plasma concentration of the protein. The influence of LEPR) were shown to significantly less frequently express HER2 (HER2+ 24.5% vs. HER2− 46.5%). Moreover, patients who were wild type homozygotes 2548 G>G (LEP) were statistically more likely to express PR receptors than women who were heterozygous and polymorphic homozygous. However, no association between the polymorphism and ER or PR expression was observed. There was also no relationship between LEPR 109Lys>Arg polymorphisms and the expression of ER, PR, and HER2 receptors . Additionally, women with different body weight and BMI were enrolled in the study. Consequently, we definitely lack a broader picture of the potential correlation between genetic and environmental factor which implies further detailed studies in the context of breast cancer risk.It is possible that lower plasma concentration of the hormone, resulting from the lower amount of adipose tissue, reduces the risk of breast cancer development. However, some women show high levels of leptin independent of the amount of adipose tissue, which may result from orphisms . Women worphisms . Howeverorphisms . TherefoImportantly, no differences were found in the incidence of 2548G>A polymorphism in healthy women with average and high body mass index (BMI>25) , and the results are comparable to the Mexican and Romanian populations , 29.LEPR gene among healthy women with normal and high (BMI > 25) body weight. The influence of 223Gln>Arg polymorphism on the body mass index of women with breast cancer also has not been demonstrated. However, it was shown that 109Arg>Arg polymorphisms occur significantly more often in individuals with breast cancer and normal weight than in overweight and obese women. Therefore, it is possible, that the presence of arginine in the leptin receptor results in a change of the structure of the leptin receptor and thus the binding of leptin [Furthermore, there were no statistically significant differences in the incidence of individual polymorphisms 223Gln>Arg and 109Lys>Arg of the f leptin . Eventuaf leptin , 32. Wilf leptin  as well f leptin , 32.LEP and LEPR gene polymorphisms and expression of ER, PR, and HER2 receptors in women with breast cancer was evaluated. It was shown, that wild type 223Gln>Gln LEPR is statistically more common in women with HER2 negative breast cancer (W vs. V p = 0.019) and wild type form of 2548G>A LEP is more common in women with PR positive breast cancer . . Table  None of ferences . These dLEPR gene polymorphism correlates with obesity in healthy women but does not increase the risk and stage of breast cancer. Moreover, the occurrence of LEPR gene polymorphisms (LEPR Gln>Arg) correlated with HER2 receptor expression in breast cancer cells of women from Greater Poland. However, the conducted analyzes did not show the relationship between the LEP and LEPR gene polymorphisms and the risk of breast cancer development and its stage. To the best of our knowledge, this is the first study to evaluate the correlation between LEP/LEPR polymorphisms status and breast cancer in the population of women from Greater Poland.Statistical analysis confirmed that obesity is a significant risk factor for breast cancer in Polish menopausal women from The Grater Poland region. This relationship positively correlates with data from other populations. 109Lys>Arg


Improved breast cancer risk assessment models are needed to enable personalized screening strategies that achieve better harm-to-benefit ratio based on earlier detection and better breast cancer outcomes than existing screening guidelines. Computational mammographic phenotypes have demonstrated a promising role in breast cancer risk prediction. With the recent exponential growth of computational efficiency, the artificial intelligence (AI) revolution, driven by the introduction of deep learning, has expanded the utility of imaging in predictive models. Consequently, AI-based imaging-derived data has led to some of the most promising tools for precision breast cancer screening.This review aims to synthesize the current state-of-the-art applications of AI in mammographic phenotyping of breast cancer risk. We discuss the fundamentals of AI and explore the computing advancements that have made AI-based image analysis essential in refining breast cancer risk assessment. Specifically, we discuss the use of data derived from digital mammography as well as digital breast tomosynthesis. Different aspects of breast cancer risk assessment are targeted including (a) robust and reproducible evaluations of breast density, a well-established breast cancer risk factor, (b) assessment of a woman’s inherent breast cancer risk, and (c) identification of women who are likely to be diagnosed with breast cancers after a negative or routine screen due to masking or the rapid and aggressive growth of a tumor. Lastly, we discuss AI challenges unique to the computational analysis of mammographic imaging as well as future directions for this promising research field.We provide a useful reference for AI researchers investigating image-based breast cancer risk assessment while indicating key priorities and challenges that, if properly addressed, could accelerate the implementation of AI-assisted risk stratification to future refine and individualize breast cancer screening strategies. Randomized trials and screening cohort studies have clearly demonstrated that routine, mammographic screening is associated with a reduction in breast cancer morbidity and mortality . InitialThis complex landscape of mammographic screening offers several opportunities for improvements including the incorporation of computational imaging phenotyping of breast tissue. Importantly, doing so comes at little additional cost in terms of patient engagement and imaging time. For instance, mammographically assessed breast density, which reflects the amount of radio-dense tissue within the breast, has been well established as a risk factor for breast cancer as well as a feature that can reduce the sensitivity of mammography, since dense tissue may obscure or, “mask” tumors . The recIn the last 6 years, the computational medical imaging community has taken notice of an AI revolution driven by the introduction of deep learning (DL)-based convolutional neural networks (CNNs), which, compared to radiomic AI, possesses the advantage of ingesting images directly without explicit feature conversion . These DThis narrative review synthesizes the current state-of-the-art applications of AI in mammographic phenotyping of breast cancer risk. For a more complete view of AI updates in breast cancer screening, we refer the reader to many excellent recent review papers on AI-enabled breast cancer detection  and broaAI is an umbrella term that encompasses various approaches to making machines mimic human decision-making Fig. . MachineIn general, the development of DL models requires a large amount of data for training, validation, and testing, with various imaging studies reporting logarithmic trends between model performance and data sample size . HoweverThe most commonly used method to assess breast density in the clinical setting is the visual and subjective grading of breast density by the interpreting radiologist into one of 4 categories outlined by the American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) . HoweverDespite the large inter- and intra-reader variation in BI-RADS density assessments, using them as the gold-standard in AI density models is a common approach, mainly due to the lack of large datasets with ground-truth density estimations. Actual ground-truth density estimations could be obtained only via breast excisions, while manual density segmentations are extremely time-consuming. Therefore, BI-RADS density assessments are usually the only ground-truth density information available for large mammographic datasets. Of note however is that despite the variability in subjective BI-RADS density assignments, they still remain highly predictive of future breast cancer risk .K) = 0.67). In the same paper, the DL model was evaluated in a reader study with five radiologists working in consensus on 500 FFDM exams randomly selected from the test set (four-class K = 0.78), and was also implemented in routine clinical practice, where eight radiologists reviewed 10,763 consecutive FFDM exams assessed with the DL model (four-class K = 0.85). Recently, the authors implemented their DL model at a partner community breast imaging practice and reported a high clinical acceptance rate among both academic (94.9%) and community (90.7%) radiologists as well as a reduction in the proportion of mammograms assessed as dense from 47 to 41% (P < 0.001) [To enhance reproducibility in breast density assessment, several studies have developed DL models of various architectures that learn to automatically classify mammographic images into BI-RADS density categories, using radiologists’ assessments –35 Tabl. For ins< 0.001) .Table 1RK = 0.67), this study explored the effects of different FFDM image formats , model architectures  and training approaches  on the DL model performance  [Most recently, in what could be an essential step towards AI-enabled BI-RADS breast density assessment, research has focused on leveraging domain adaptation approaches to create DL models that utilize 2D synthetic mammographic (SM) images reconstructed from DBT acquisitions. The feasibility of this approach was demonstrated in large, racially diverse datasets from two clinical sites, where the adapted model achieved good agreement with the BI-RADS density classification from SM images by radiologists (four-class 72–0.79) . Additio72–0.79) , 28, as 72–0.79) .Despite the substantial progress made in automating BI-RADS density classification, merely striving for agreement with radiologists’ BI-RADS density interpretations is rather limiting since the rigid BI-RADS density categories do not capture finer density variations that may be important when refining breast cancer risk . MoreoveAs of now, breast density evaluation from 3D reconstructed image volumes has only been explored via traditional radiomic AI techniques  and no DP < 0.05).Among the first to explore the potential of DL in breast cancer risk assessment, Kallenberg et al.  implemenbefore an actual cancer is diagnosed . Moreover, the “Digital Mammography DREAM Challenge”  and the Interpretability is also key to advance AI applications in breast cancer risk assessment. DL models can only be debugged, audited, and verified when they can be interpreted. As such, interpretability is key to understanding the cause of an erroneous error or ensuring that causal relationships are picked up in a correct decision. A DL model that can sufficiently explain its decisions will not only gain users’ trust but will also identify data that is mislabeled or contains inconsistencies across institutions. This transparency and interpretability will facilitate improvements in quality control over training data. Interpretability methods may even serve as valuable discovery tools that identify new patterns and interactions in data. While so far, AI interpretability has focused mostly on image regions that drive the model’s decisions , the set of available interpretability approaches is rapidly growing, offering unique opportunities for AI applications in mammographic images . Even soAnother challenging step in establishing the role of AI in breast cancer risk assessment is validating that DL models generalize well to heterogeneous datasets , 62. TheFinally, practical considerations related to clinical adoption of AI , cost-effectiveness, and various ethical and legal dilemmas must be addressed before AI becomes common place in breast cancer risk assessment , 63. In The rise and dissemination of AI in breast cancer screening is poised to improve breast cancer risk assessment and enable personalized screening recommendations. However, many technical challenges related to inherent properties of mammographic imaging are yet to be addressed, especially as AI developments transition to digital breast tomosynthesis. Furthermore, to accelerate the validation of AI breast cancer risk models and their transition into clinical implementation, it is paramount to enhance their reproducibility, interpretability, and robustness using large, heterogeneous datasets. With creative AI solutions to improve accuracy, validate performance, and cultivate trust in decision-making, AI will transform how breast cancer screening is performed.


Background: The prevalence rate of hypertension and breast cancer increases with advancing age. Renin-angiotensin system inhibitors (RASIs), β-blockers (BBs), calcium channel blockers (CCBs), and diuretics are widely used to treat patients with hypertension. Although, the association between the use of antihypertensive medication and breast cancer has been highly debated, recent evidence supporting this association remains controversial.Objective: To evaluate the association between the use of antihypertensive medication and the risk of breast cancer and its prognosis.Methods: This study was conducted using data from the PubMed, Embase, and Cochrane Library databases retrieved for the period from January 2000 to April 2021. Articles and their references were checked and summary effects were calculated using random- and fixed-effects models. Heterogeneity test and sensitivity analysis were also performed.Results: This meta-analysis included 57 articles, which were all related to breast cancer risk or prognosis. Assessment of breast cancer risk using the pooled data showed that the use of BBs or CCBs or diuretics was associated with increased cancer risk . Long-term use of diuretic increased the risk of breast cancer , whereas long-term RASIs treatment reduced the risk . In addition, we found that diuretic users may be related to elevated breast cancer-specific mortality , whereas using other antihypertensive medications was not associated with this prognosis in patients with breast cancer.Conclusion: Using CCBs, BBs, and diuretics increased the risk of breast cancer. In addition, diuretics may elevate the risk of breast cancer-specific mortality. The long-term use of RASIs was associated with a significantly lower breast cancer risk, compared with non-users. Thus, this analysis provides evidence to support the benefits of the routine use of RASIs in patients with hypertension, which has important public health implications. In 2017, hypertension was identified as a major risk factor for cardiovascular disease globally, accounting for 10.4 (9.39–11.5) million deaths and 218 (198–237) million disability-adjusted life-years . FortunaSeveral studies have found that breast cancer is associated with a variety of antihypertensive medications, including angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs), β-blockers (BBs), calcium channel blockers (CCBs), and diuretics. However, these results remain controversial. A recent systematic review of observational studies concluded that BB reduced the risk of breast cancer recurrence , whereasThis question remains controversial and, therefore, in this updated meta-analysis, we aimed to assess the association between the use of various classes of antihypertensive medication and breast cancer risk, prognosis .Studies fulfilling the following inclusion criteria were included: 1) the exposed group included individuals who had received antihypertensive medication; 2) the study had a comparative design: antihypertensive medication users vs. non-users; 3) the outcome was breast cancer risk, breast cancer-specific mortality, recurrence, or survival (DSS or OS); 4) the study reported the relative risk (RR), OR, or hazard ratio (HR) with corresponding 95% CIs or sufficient data to calculate these parameters. When the results of multiple studies were from the same database, the study including the largest number of participants was included. The following types of studies were excluded from this meta-analysis: meta-analyses, systematic or narrative reviews, case studies, experimental laboratory articles, conference abstracts, commentaries, randomized controlled trials, repeated publications, or if the reference group was administered another class of antihypertensive medication.Two of the authors (Yuxiu Xie and Men Wang) extracted data from the included studies and any disagreements between them were resolved by discussions with between the two other relevant co-authors. We extracted the following information from the selected articles: first author and year of publication, source of data, country, study design, duration of follow-up, study outcome, sample size of participants, and covariates used for the adjustment of confounders. The risk estimate adjusted for the largest number of confounding factors was extracted.The nine-star Newcastle–Ottawa Scale (NOS) was used to assess the methodological quality of cohort studies and case-control studies . A scoreI2 test was used to assess potential heterogeneity between individual studies, and an I2 > 50% indicated significant heterogeneity , as shown in Twenty-nine independent studies examined the association between antihypertensive medication use and breast cancer-specific mortality, with a pooled HR of 1.04 (95% CI 0.98–1.10). When HRs for the individual antihypertensive medication  were calculated in subgroup analyses, no significant results were observed . HoweverTwenty-one studies revealed no significant link between antihypertensive medication use and breast cancer OS , CCBs (P = 0.151), diuretics (P = 0.348), or RASIs (P = 0.397) in relation to the risk of breast cancer risk (P = 0.001), but not in other studies on prognosis   .A sensitivity analysis was performed as shown in Our meta-analysis showed that the use of BBs, CCBs, or diuretics was associated with a moderate increase in the risk of breast cancer. Diuretic therapy for ≥10 years could increase breast cancer risk by 10%. Long-term use of RASIs exerted a protective effect against breast cancer, especially when used for ≥10 years. In addition, this meta-analysis indicated that diuretics are related to elevated breast cancer-specific mortality, but antihypertensive medication use did not affect recurrence, OS, or DSS.Our conclusion that BBs were associated with increased breast cancer risk was consistent with this highly influential and large studies . The proOur meta-analysis showed a positive association between CCBs use and the risk of breast cancer, which was consistent with the results of previous studies . The elein vivo and in vitro studies on RASIs have demonstrated a protective anti-inflammatory, anti-proliferative, and pro-apoptotic effect on breast cancer , CCBs (dihydropyridines and non-dihydropyridines), and diuretics  were not conducted because of the lack of relevant studies. Thirdly, our current summary evidence did not support a clear relation between long-term use of CCBs or BBs and breast cancer risk. Finally, significant heterogeneity was observed among studies focused on antihypertensive medication use and breast cancer risk and this persisted even when the data were stratified into subgroups.The results of this meta-analysis demonstrated that BBs, CCBs, and diuretics were significantly associated with breast cancer risk. Unexpectedly, a beneficial effect of long-term use of RASI was observed against breast cancer risk. Additionally, according to the analysis of prognosis, no association was observed with any class of antihypertensive medication. Considering the limitations in this meta-analysis, further research is needed to fully clarify the association between antihypertensive medication use and breast cancer risk.


FANCM protein truncating variants (PTVs) are emerging as risk factors for ER-negative and triple negative breast cancer. Here, we discuss evidence that greatest risk associates with PTVs, such as p.Arg658*, that extensively truncate the 2048 amino acid FANCM protein. Moreover, risks associated with other less-truncating FANCM PTVs such as p.Gln1701* and p.Gly1906Alafs12* may be amplified by additional gene variants acting as modifiers. Further studies need to be conducted taking into considerations these aspects. BRCA1 and BRCA2 genes are associated with a high-risk of breast and ovarian cancers. These genes are now widely screened to assess the risk of developing these diseases in variant carriers and their relatives. Over the last 15 years, protein-truncating variants (PTVs) in several other genes have been described or proposed to cause moderate- to high-risk for breast cancer but insufficient data hamper a conclusive annotation. Early this year, two large case-control studies were published in the New England Journal of Medicine, which aimed to clarify which genes should be used clinically and to estimates the breast cancer risk magnitude associated with PTVs in each gene. These studies were based on the sequencing of 34 and 28 known or candidate breast cancer risk genes in 113,000 women from 25 countries, and 64,000 women from the US, respectively2. Both studies found that PTVs in the 8 genes BRCA1, BRCA2, PALB2, BARD1, RAD51C, RAD51D, ATM, and CHEK2 were significantly associated with breast cancer risk. In particular, PTVs of ATM and CHEK2 were associated with risk of estrogen receptor (ER) positive breast cancer, and PTVs of BARD1, RAD51C, and RAD51D with a risk of ER-negative breast cancer. Moreover, among the genes previously proposed to be associated with an increased risk of breast cancer, the majority including NBN and RECQL, were found not associated. The unparalleled statistical power of such a large dataset appears to make this a definitive designation4. But for one of the candidate genes, FANCM, the role in breast cancer predisposition appears more nuanced. In the Dorling et al. study, FANCM PTVs were not found to be associated with overall breast cancer risk nor to have an effect on age at diagnosis, but were statistically associated with risk in ER-negative breast cancer cases  disease subtypes  change expected according to the genetic code. Instead, as we showed in cell-based experiments, the variant creates a consensus sequence for a splicing silencer triggering the skipping of exon 22. This causes a frameshift starting at aa position 1906 forming a stop codon 12 codons later6. Therefore, while the c.5791 C >T variant is universally known as p.Arg1931*, the correct protein annotation of this variant would be p.Gly1906Alafs12*. FANCM:c.5101 C >T (p.Gln1701*) is another PTV identified in a Finnish population study, by exome sequencing of 11 breast cancer families. Further genotyping of this allele found it to be significantly associated with breast cancer risk with higher ORs detected in ER-negative and TNBC cases8. In addition to single PTVs genotyping studies, two burden analyses of all FANCM PTVs discovered by gene sequencing were published10. Altogether, these data indicate that, while the association with risk for breast cancer was inconclusive, FANCM PTVs might be risk factors for familial breast cancer or for ER-negative and TNBC disease subtypes , which is the third most common FANCM PTV found in Europeans, in a large study including breast cancer cases and controls from 19 European countries. Surprisingly, we only found p.Arg658* to be associated with risk of ER-negative and TNBC subtypes11. We also functionally tested these three PTVs for their capacity to rescue survival and chromosome fragility in a FANCM−/− patient-derived cell line exposed to the DNA damaging agent diepoxy butane. We observed that p.Arg658* was unable to rescue the cell survival and chromosome fragility while p.Gln1701* and p.Gly1906Alafs12* showed an intermediate effect11. This is consistent with the fact that the p.Gln1701* and p.Gly1906Alafs12*, located in the C-terminus of the protein, are both expected to just disrupt the binding domain of the partner protein FAAP24; while p.Arg658*, located much upstream in the gene, is expected to cause the loss of greater protein portions. Based on these genetic and functional data, it is possible to speculate that the effects on breast cancer risk of the different FANCM PTVs might be due to the extent of protein truncation of the PTV. In support of this hypothesis, two women with early-onset breast cancer (at age 29 and 32); were genotyped as homozygotes for p.Arg658*. In addition, one developed several cancers, and the other demonstrated chromosomal fragility12. In the same study, two women genotyped as homozygotes for p.Gln1701*, and one homozygous for p.Gly1906Alafs12*, developed breast cancer at age 52 or later, and their cells did not demonstrate chromosome fragility.More recently, we tested 13 which are lost in the Arg658* variant protein. Previous in vitro work has shown that the ability to recruit Fanconi and Bloom syndrome complexes is more important to the function of FANCM protein than the association with FAAP2413. Furthermore, although yet to be experimentally validated, Arg658* can be predicted to act in a dominant-negative fashion. Because the Arg658* protein variant retains the N-terminal DNA binding and ATPase domain, it could potentially block the recruitment of DNA repair complexes by the full-length protein in heterozygotes and reduce DNA repair capacity. In most other breast cancer genes, including BRCA1 and BRCA2, it is the loss of DNA repair capacity that associates with variant severity.As FANCM protein is a large, multi-domain anchor that binds both DNA and other protein complexes at DNA damage sites, different effects may arise relating to breast cancer predisposition, depending upon the protein domains deleted. For example, p.Gln1701* and p.Gly1906Alafs12* delete the C-terminal DNA binding domain and FAAP24 interaction site but retain interaction with two complexes necessary for DNA repair (the Fanconi Anemia core complex and the Bloom syndrome complex). These protein complexes associate at distinct regions located between aa 960–1210BRCA1, BRCA2, and other genes associated with breast cancer, there is also an impact of population ancestry and potential modifier alleles. Could this explain the differences between studies investigating FANCM variants and their impact on breast cancer? First, the Finnish studies were based on the p.Gln1701* and p.Gly1906Alafs12* genotyping in geographically, ethnically, and genetically matched cases and controls. In addition, the p.Gln1701* and p.Gly1906Alafs12* carrier frequencies are high in Finns being 1.62% and 0.92%, vs. 0.21% and 0.21% in non-Finnish Europeans (https://gnomad.broadinstitute.org/), respectively. This has allowed the authors of these studies to derive robust associations with ER-negative and TNBC risk in a relatively small sample size. Second, the multicentric study was based on greater case-control numbers allowing to reach a statistical power sufficiently large to show that p.Arg658*, despite a low carrier frequency of 0.033% in non-Finnish Europeans (https://gnomad.broadinstitute.org/), was associated with ER-negative and TNBC risks11. It is hence puzzling that in this study no association was found for p.Gln1701* and for p.Gly1906Alafs12* and risk for breast cancer or the ER-negative and TNBC disease subtypes. One potential explanation is the relative genetic isolation of the Finnish population. Finns have recurrent BRCA1/2 founder PVs and at least 12 other PVs in the moderate risk genes ATM, CHEK2, FANCM, PALB2, RAD51C, and RAD51D have known that account for the majority of Finnish breast cancer cases with a genetic component14. In addition, an excess of double heterozygosity for variants in the moderate penetrance genes has also been documented in Finns14. It can therefore be speculated that some other modifier allele exists within this population which amplifies the p.Gln1701* and p.Gly1906Alafs12* risk effects, although the studies to locate such a modifier have yet to be conducted.For FANCM PTVs could be moderate risk factors for ER-negative and TNBC. It is possible that deletions that remove more of the FANCM protein, such as p.Arg658*, are likely to have a stronger effect on both the DNA repair defect and the risk for ER-negative or TNBC. Conversely, the risk effects of FANCM:p.Gln1701* and p.Gly1906Alafs12* on these breast cancer subtypes are probably lower but may be amplified by additional variants acting as modifiers. Importantly, the two new very large studies from Dorling et al. and Hu et al. have not analyzed each FANCM PTVs singularly nor grouped based on their location within the gene. More clear results about which of the FANCM PTVs are moderate risk factors for ER-negative or TNBC and which are not may arise if this were to be done.In conclusion, all these observations indicate that certain


Following a vegetarian diet has become increasingly popular and some evidence suggests that being vegetarian may be associated with a lower risk of cancer overall. However, for specific cancer sites, the evidence is limited. Our aim was to assess the associations of vegetarian and non-vegetarian diets with risks of all cancer, colorectal cancer, postmenopausal breast cancer, and prostate cancer and to explore the role of potential mediators between these associations.We conducted a prospective analysis of 472,377 UK Biobank participants who were free from cancer at recruitment. Participants were categorised into regular meat-eaters , low meat-eaters , fish-eaters , and vegetarians (n = 8685) based on dietary questions completed at recruitment. Multivariable-adjusted Cox regressions were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for all cancer incidence and separate cancer sites across diet groups.p = 0.007), with an inverse association across diet groups in men, but not in women. Vegetarian postmenopausal women had a lower risk of breast cancer , which was attenuated and non-significant after adjusting for body mass index ; in mediation analyses, BMI was found to possibly mediate the observed association. In men, being a fish-eater or a vegetarian was associated with a lower risk of prostate cancer .After an average follow-up of 11.4 years, 54,961 incident cancers were identified, including 5882 colorectal, 7537 postmenopausal breast, and 9501 prostate cancers. Compared with regular meat-eaters, being a low meat-eater, fish-eater, or vegetarian were all associated with a lower risk of all cancer . Being a low meat-eater was associated with a lower risk of colorectal cancer in comparison to regular meat-eaters ; however, there was heterogeneity in this association by sex (The lower risk of colorectal cancer in low meat-eaters is consistent with previous evidence suggesting an adverse impact of meat intake. The lower risk of postmenopausal breast cancer in vegetarian women may be explained by their lower BMI. It is not clear whether the other differences observed for all cancers and for prostate cancer reflect any causal relationships or are due to other factors such as residual confounding or differences in cancer detection.The online version contains supplementary material available at 10.1186/s12916-022-02256-w. Cancer is a leading cause of death worldwide , and in It has been hypothesised that vegetarian diets, which exclude the consumption of all meat and fish, may be associated with a lower cancer risk. In addition to excluding red and processed meat, which are associated with an increased risk of colorectal cancer , vegetarAny difference in cancer risk between diet groups may be due to differences in physiological characteristics, including adiposity. In western populations, vegetarians and fish-eaters have been shown to have lower body mass indices in comparison with the body mass index (BMI) of meat-eaters –20 whichTo further understand these relationships, we assessed the associations of diet groups with risks of all, colorectal, postmenopausal breast, and prostate cancer in the UK Biobank, which includes approximately 10,000 fish-eaters, 8000 vegetarians, and nearly 55,000 total incident cancer cases. We additionally aimed to assess the roles of BMI, circulating IGF-I, and calculated free testosterone as potential mediators of the observed associations between diet groups and cancer risk.Potential participants were first identified for the UK Biobank study using National Health Service (NHS) records, and 9.2 million eligible individuals, aged 40–70 and living within 25 miles of one of the assessment centres in the UK, were invited to participate in the study. Over 500,000 participants (5.5% response rate) consented to participate between 2006 and 2010  and visiThe UK Biobank was approved by the NHS North West Multicentre Research Ethics Committee (21/NW/0157). All participants provided informed consent at recruitment, allowing for follow-up using data-linkage to health records. The study was performed in accordance to the Declaration of Helsinki.n = 871), had a prevalent cancer diagnosis at recruitment  code: C44; n = 29,504), their genetic sex was different from their reported sex (n = 321), or they did not contribute any follow-up time . This left a total of 472,337 participants, of whom 217,937 were males and 254,400 were females. For prostate cancer analyses, women were excluded, and for postmenopausal breast cancer analyses, women who were premenopausal at recruitment and did not reach the age of 55 over the follow-up time , and men, were excluded.Participants were excluded from this analysis if they withdrew consent over the study period n = 87, had a pn = 446).Diet groups were categorised using the touchscreen questionnaire completed at recruitment which asked participants about their frequency of consumption of processed meat, beef, lamb or mutton, pork, chicken, turkey or other poultry, and oily and non-oily fish. Participants chose a frequency of intake ranging from “Never” to “Once or more daily”. From these responses, participants were categorised into four diet groups . Regular meat-eaters were participants who said they consumed processed, red meat , or poultry > 5 times a week. Low meat-eaters were participants who reported consuming processed, red meat, or poultry ≤ 5 times a week. Fish-eaters were participants who reported that they never consumed red meat, processed meat, or poultry but ate oily and/or non-oily fish. Vegetarians were defined as participants who reported that they never consumed any meat or fish. The vegetarian group also included vegans who reported not consuming any meat, fish, dairy, or eggs  and testosterone, as well as sex hormone-binding globulin which we used to calculate an estimate of free testosterone . FurtherData on cancer diagnosis were ascertained using a combination of records from the NHS Digital (cancer registry) and Public Health England for participants from England and Wales, NHS Central Register for participants from Scotland  as well Baseline characteristics of UK Biobank participants were summarised across diet groups for all participants, and separately for men and women.Cox proportional hazards regressions were used, with age as the underlying time variable, to estimate hazard ratios (HR) and 95% confidence intervals (CI). Minimally adjusted models were stratified by sex  and age at recruitment  and adjusted for region at recruitment .Multivariable-adjusted Cox regression models for all analyses were further adjusted for height ), physical activity ), Townsend deprivation index ), education ), employment status ), smoking status ), alcohol consumption ), ethnicity ), and diabetes status ).For colorectal cancer and for all cancer sites, multivariable models were further adjusted for female specific covariates: menopausal hormone therapy (MHT) use ) and menopausal status at recruitment ). Moreover, for colorectal cancer, multivariable models were adjusted for non-steroidal anti-inflammatory drug use . For prostate cancer, models were additionally adjusted for marital status  . For pos2, or unknown/missing (0.57%)). Models assessing BMI as a mediator are explained below in the mediation analyses section.We considered BMI as a potential confounder as well as a mediator. When BMI was considered as a potential confounder, BMI measured at recruitment was added to multivariable models  comparing a model without the diet groups variable to the model with the diet groups variable.To determine if there was heterogeneity in the associations of diet groups with cancer risk, and to assess the influence of confounder adjustments , 34, χ2 2) and smoking status (ever and never) by using a LRT comparing the main model to a model including an interaction term between diet groups and the subgroup variable (BMI and smoking status). For colorectal cancer, we further assessed heterogeneity by sex. For all cancer sites combined, we additionally explored heterogeneity by smoking status, censoring participants at baseline who were diagnosed with lung cancer.For all analyses, we assessed heterogeneity by subgroups of BMI .In sensitivity analyses, we excluded cases and participants who had less than 2 years of follow-up and all participants with missing data on covariates. We also examined associations separately in white participants because a large proportion of the vegetarians in this cohort are of South Asian ethnicity (~ 17.5%). Furthermore, we additionally adjusted for fruit and vegetable intake in the multivariable adjusted model  to control for this component of dietary intake as a proxy for a healthy diet. For prostate cancer analyses, we included in the multivariable adjusted model prostate-specific antigen (PSA) testing  reported at baseline in all men and during follow-up from general practice records in a subsample  method , 37. ThiP-values were two-sided with p < 0.05 being considered statistically significant.All analyses were conducted using Stata version 17.0 . Of the participants included in the analysis, 247,571 (52.4%) were classified as regular meat-eaters, 205,385 (43.5%) were low meat-eaters, 10,696 (2.3%) were fish-eaters and 8685 (1.8%) were vegetarians. After an average of 11.4 years of follow-up, 54,961 incident cases of any type of cancer were diagnosed; 5882 participants were diagnosed with colorectal cancer, 7537 women were diagnosed with postmenopausal breast cancer, and 9501 men were diagnosed with prostate cancer.Table The minimally adjusted models and sequential adjustments for the associations between diet groups and cancer risks are presented in Additional file Phet = 0.007), with male low meat-eaters, fish-eaters, and vegetarians having a lower risk of colorectal cancer  in comparison to regular meat-eaters, whereas no significant association was observed across diet groups for females ; amongst ever smokers, the low meat-eaters, fish-eaters, and vegetarians had lower risks of all cancer sites than regular meat-eaters , whereas these associations were non-significant for non-smokers  implying that BMI may explain nearly 93% of the lower risk observed in vegetarian women although this was not statistically significant (Table NIE of 0.91 (95% CI: 0.73–1.15) was observed. For prostate cancer risk, IGF-I and free testosterone concentrations did not seem to mediate the observed difference in risk between vegetarians and regular meat-eaters, and free testosterone was not found to mediate the difference in risk between fish-eaters and regular meat-eaters  of BMI, IGF-I, and free testosterone concentrations measured at recruitment across diet groups. Fig. S1. Flow diagram of the study exclusion criteria. Fig. S2. Hazard ratios and 95% confidence intervals for sensitivity analyses including only participants of white ethnicity and complete cases analyses on associations between diet groups and risk of all cancer, prostate, postmenopausal breast, or colorectal cancer. Fig. S3. Hazard ratios and 95% confidence intervals for sensitivity analyses removing first two years of follow-up and adjusting for fruit and vegetable intake on associations between diet groups and risk of all cancer, prostate, postmenopausal breast, or colorectal cancer.


Similar to prostate cancer, male breast cancer (MBC) is a hormone-responsive neoplasm. Opposite to prostate cancer, MBC is extremely rare, with MBC cases accounting for <1% of all newly diagnosed malignancies and an incidence of approximately 1 in 100,000 men . In an aFinally, some genetic alterations may also play an important role as risk factors of MBC. In a retrospective case series of 27 MBC patients with available genetic test results, nine (33.3%) had a breast cancer gene (BRCA) 1 or 2 mutation . In factet al. who developed and published a nomogram capable of estimating the risk of contralateral breast cancer in male patients [Mastectomy, with or without radiotherapy, hormonal therapy and chemotherapy, represents the mainstay of treatment of MBC . Contralpatients . The respatients .In this Editorial, we have reviewed useful evidence to underline the potential role of CPM in patients with MBC and the uncertainties of the associated benefits, which generates a challenging situation for both the patient and the physician. While evaluation of known risk factors, such as presence of BRCA mutation or any of the other conditions reviewed above, is surely important, the possibility of providing the exact expected increase in the chances of survival associated with CPM is of great value in the context of common clinical practice. In practical terms, we propose that in men with a BRCA mutation, CPM should always be discussed with the patient, with benefits outweighing risks in the majority of cases. In those who do not harbor a BRCA mutation, the use of the cited nomogram appears to provide valuable information to be discussed with the patient on an individual basis. For instance, in a patient with a risk of breast cancer death at 8 years of 30%, CPM can yield a considerable risk reduction in absolute terms (≅10%), which becomes trivial in men who have a risk of 5% without CPM because of the favorable characteristics of the disease. Randomized Phase III trials are required, specifically designed to randomize men who have completed the standard course of treatment for breast cancer, to CPM versus observation. Men with wild-type BRCA and men with an estimated risk of breast cancer-related death at 5 years > = 20% could be included. Although a large sample size would be needed, which may be accomplished only with an international effort, such a trial would represent a unique opportunity to establish the optimal indication for CPM.


Comprehensive investigations of the associations between 21-gene recurrence assay and metabolic profiles in Chinese breast cancer patients are limited.We evaluated the relations of the 21-gene recurrence risk score (RS) and the expression of cancer-related genes with metabolic factors and biomarkers of insulin and the insulin-like growth factor (IGF) axis, and examined the interactions between the 21-gene RS and these metabolic profiles on breast cancer recurrence in Chinese women with HR-positive, HER2-negative early-stage breast cancer.2; P=0.040), the homeostasis model assessment of insulin resistance index , insulin , and C-peptide  and was positively associated with high-density lipoprotein cholesterol , which were driven by the relation patterns between specific cancer-related genes and these metabolic profiles. Each 10-unit increase in the 21-gene RS was associated with 28% (95% CI: 5–47%) higher risk of breast cancer recurrence; this association was also observed in patients with favorable metabolic profiles in relevant to an absence of obesity, insulin resistance, hyperglycemia, hypertension, or dyslipidemia (28–44% higher risk) and among women with a low level of insulin, C-peptide, or the IGF1/IGFBP3 ratio (41–155% higher risk).The 21-gene RS was inversely associated with body mass index ([BMI]β: −0.178 kg/mThe 21-gene RS was related to favorable metabolic profiles including lower BMI, HOMA-IR, insulin, and C-peptide, and higher HDL in Chinese breast cancer patients, and its prognostic impact on breast cancer recurrence was more likely to present among patients with relatively favorable metabolic profiles. Breast cancer is the leading cause of cancer death in women and has now surpassed lung cancer as the most commonly diagnosed cancer  worldwide in 2020, according to statistics released by the International Agency for Research on Cancer , 4. The In addition to the 21-gene RS assay, the complex metabolic profiles are closely related to the recurrence of breast cancer. Several metabolic risk factors, such as insulin resistance, hyperglycemia, and dyslipidemia, systemically occur in the setting of adipose inflammation and operate in concert with local mechanisms to maintain an inflamed microenvironment and promote adverse breast cancer prognosis –8. BesidIn an effort to address this knowledge gap, we aimed to study the associations of the 21-gene RS with metabolic risk factors and circulating biomarkers of insulin and the IGF axis, and characterize the prognosis prediction interaction between the 21-gene RS and metabolic profiles in Chinese women with hormone receptor (HR)-positive, HER2-negative early-stage breast cancer.This study included 1,038 patients who were enrolled from the Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between 2012 and 2017. Patients who met the inclusion criteria were included in the analysis: (1) female gender; (2) ER and/or PR-positive, HER2-negative invasive breast cancer; (3) tumor size T1-T3; (4) axillary lymph node involvement N0-N1; and (5) with complete data available on baseline demographic and clinical characteristics, metabolic factors, biomarkers of insulin and the IGF axis, and the 21-gene RS assay. The exclusion criteria were as follows: (1) pT4 or pN2-3 breast cancer; (2) metastatic breast cancer; or (3) previous neoadjuvant systemic therapy. Pathology diagnoses were given from the experienced pathologists by evaluating stored hematoxylin and eosin–stained sections from all patients in the Department of Pathology, Ruijin Hospital. Breast cancer was diagnosed by histopathologic examination according to the fourth edition of the World Health Organization Classification of Tumors of the Breast . The stuin situ hybridization. Ki-67 index was characterized as the proportion of positively nuclear staining cells among at least 1,000 tumor cells in the area counted  status, Ki-67 level, molecular subtype, and adjuvant therapies. Histological grade, TNM stage, tumor size, and lymph node status were defined according to American Joint Committee on Cancer (AJCC) stage of disease classification (Eighth Edition) . ER and  counted . Molecul counted . Adjuvan2. The homeostasis model assessment of insulin resistance (HOMA-IR) index was calculated as fasting insulin (μIU/ml) × fasting glucose (mmol/L)/22.5. Insulin resistance was defined as HOMA-IR ≥2.5. Hyperglycemia was defined as fasting glucose ≥5.6 mmol/L. Hypertension measured by blood pressure cuff was defined as systolic blood pressure (SBP) ≥140 mmHg or diastolic blood pressure (DBP) ≥90 mmHg. Dyslipidemia was defined as total cholesterol (TC) ≥6.22 mmol/L, high-density lipoprotein (HDL) <1.04 mmol/L, low-density lipoprotein (LDL) ≥4.14 mmol/L, or triglycerides ≥2.26 mmol/L.Metabolic risk factors included obesity, insulin resistance, hyperglycemia, hypertension, and dyslipidemia. The biomarkers of insulin and the IGF axis included insulin, C-peptide, IGF1, and IGF-binding protein 3 (IGFBP3). Weight was measured to the nearest 0.1 kg wearing light indoor clothing, and height was measured to the nearest 0.1 cm without shoes. BMI was calculated as weight in kilograms divided by height in meters squared. Obesity was defined as body mass index (BMI) ≥25 kg/mMeasurements of all metabolic profiles mentioned above were presented in details in our previous work , 19. AftThe 21-gene RS assay was performed in the Department of Clinical Laboratory, Ruijin Hospital. Detailed information about the 21-gene RS assay has been reported previously . Hematoxin situ (DCIS), and contralateral DCIS  for continuous variables or number (proportion) for categorical variables. Differences between baseline characteristics within low, intermediate, and high categories of the 21-gene RS were compared by general linear model for continuous variables or Chi-square test for categorical variables.General linear models were applied to examine the associations of the ΔCt value for cancer-related genes and the 21-gene RS with metabolic factors including BMI, HOMA-IR, fasting glucose, SBP, DBP, total cholesterol, HDL, LDL, and triglycerides, as well as the biomarkers of insulin and the IGF axis with, with adjustment for age and postmenopausal status. Levels of HOMA-IR, IGF1, IGFBP3, IGF1/IGFBP3 ratio, insulin, and C-peptide were log transformed in analysis to improve the normality of their distributions.In the time-to-event analysis for breast cancer recurrence, participants were censored at the date of recurrence or the end of follow-up, whichever occurred first. Person-time was calculated from the enrollment date to the censoring date for each participant. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer recurrence associated with each 10-unit increase in the 21-gene RS, according to status of obesity, insulin resistance, hyperglycemia, hypertension, and dyslipidemia, as well as levels of insulin, C-peptide, IGF1, IGFBP3, and IGF1/IGFBP3 ratio. Models were adjusted for age, BMI, postmenopausal status, tumor size, lymph node status, PR status, Ki-67 level, molecular subtype, chemotherapy, radiotherapy, and endocrine therapy. Interactions of the 21-gene RS with the stratifications of metabolic risk factors and biomarkers on the risk of recurrence were assessed by including the multiplicative interaction product term , as well as the main association in the models. All reported P values are nominal and 2-sided, and a P value of less than 0.05 was considered statistically significant. All statistical analyses were performed by using SAS software, version 9.2 (SAS Institute Inc).Baseline characteristics of 1,038 women with ER-positive, HER2-negative early-stage breast cancer are shown in The ΔCt values of 11 cancer-related genes  were positively associated with HDL , C-peptide (related to PR), and IGFBP3 (related to CEGP1)  and HOMA-IR  and was positively associated with HDL  after adjustment for age and postmenopausal status  and C-peptide  after adjustment for age and postmenopausal status (During a mean follow-up of 36.6 months (SD: 14.4 months), 36 participants with breast cancer recurrence were documented. The cases/1,000 person-years of recurrence was 8.01 for low RS category, 9.19 for intermediate RS category, and 21.00 for high 21-gene RS category (Multivariable-adjusted HR (95% CI) for breast cancer recurrence associated with each 10-unit increase in the 21-gene RS was 1.28 (1.04–1.57) in the overall participants , low C-peptide , and low IGF1/IGFBP3 ratio  exhibited increased risk of breast cancer recurrence , and such prognostic impact was more pronounced among women with relatively favorable metabolic profiles in relevant to an absence of obesity, insulin resistance, hyperglycemia, hypertension, or dyslipidemia (28–44% higher risk per 10-unit increase in the RS) and among women with a low level of insulin, C-peptide, or the IGF1/IGFBP3 ratio (41–155% higher risk per 10-unit increase in the RS).One noteworthy finding of this study was the significant association patterns of the 21-gene RS and the individual cancer-related genes with specific metabolic factors and biomarkers of insulin and the IGF1 axis. Our results were partly in line with recent studies that revealed an inverse relationship between BMI and the RS in postmenopausal women with hormone receptor-positive, HER2-negative breast cancer , and a h2; hypertension; impaired fasting glucose; HDL <50 mg/dl; hypertriglyceridemia) or any individual components  for the publication of any potentially identifiable images or data included in this article.Study concepts: YZ, TW, XC, and KS. Study design: YZ, TW, XC, and KS. Data acquisition: YZ, YT, XC, and KS. Quality control of data and algorithms: YZ, TW, XC, and KS. Data analysis and interpretation: YZ and TW. Statistical analysis: YZ and TW. All authors contributed to the article and approved the submitted version.This work was funded by the financial support from the National Natural Science Foundation of China ; Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Grant Support .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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


ABSTRACT IMPACT: This study will be the first to explore the relationship between preeclampsia and breast cancer risk using the largest cohort of Black women in the US, and it will guide future research and potentially inform clinical practice to reduce breast cancer disparities in this population. OBJECTIVES/GOALS: Black women are disproportionately impacted by preeclampsia. This disorder induces hormonal changes that may contribute to diseases such as breast cancer. However, there is a lack of clear data on the relationship between preeclampsia and breast cancer, and few previous studies included Black women. This study will work to fill this knowledge gap. METHODS/STUDY POPULATION: We prospectively assessed the association between preeclampsia during pregnancy and risk of breast cancer in 43,040 parous women in the Black Women’s Health Study, a nationwide cohort of Black women who were ages 21 -69 at enrollment in 1995. Through 2017, we confirmed 1,968 incident diagnoses of invasive breast cancer. Approximately 6% of parous women reported a diagnosis of preeclampsia; characteristics of the population at baseline are shown in Table 1. We used multivariable Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of breast cancer overall. We used age as the time scale and adjusted for breast cancer risk factors including parity, age at first birth, age at menarche, and body mass index (BMI) at age 18. RESULTS/ANTICIPATED RESULTS: : Compared to parous women without a history of preeclampsia, women with a history of preeclampsia in any pregnancy were not at an increased risk of breast cancer overall . These preliminary results suggest that history of preeclampsia is not an important risk factor for breast cancer overall in Black women. Our analyses are ongoing to evaluate whether the association may vary by estrogen receptor status or within subgroups of the population defined by age, menopausal status, BMI, and time since last pregnancy. DISCUSSION/SIGNIFICANCE OF FINDINGS: Findings from this study will provide unprecedented knowledge on the association between hypertensive diseases during pregnancy and incidence of breast cancer in the largest cohort of Black women in the U.S.


Gallstones affect women more frequently than men. Symptomatic gallstones are treated with surgical removal of the gallbladder. Overweight, obesity, and exposure to female hormones can cause gallstones and also breast, uterine, and ovarian cancer. We assessed if surgical removal of the gallbladder is associated with these cancers in women. We found risk of ovarian cancer is increased within the first 6 months after surgery. Women undergoing this operation also show an increased risk of breast and uterine cancer up to 30 years after surgery. It is important to screen women with this surgery indication for the three abovementioned cancers.Background: Gallstones affect women more frequently than men, and symptomatic gallstones are increasingly treated with surgical removal of the gallbladder (cholecystectomy). Breast, endometrial, and ovarian cancer share several risk factors with gallstones, including overweight, obesity, and exposure to female sex hormones. We intended to assess the association between cholecystectomy and female cancer risk, which has not been comprehensively investigated. Methods: We investigated the risk of female cancers after cholecystectomy leveraging the Swedish Cancer, Population, Patient, and Death registries. Standardized incidence ratios (SIRs) adjusted for age, calendar period, socioeconomic status, and residential area were used to compare cancer risk in cholecystectomized and non-cholecystectomized women. Results: During a median follow-up of 11 years, 325,106 cholecystectomized women developed 10,431 primary breast, 2888 endometrial, 1577 ovarian, and 705 cervical cancers. The risk of ovarian cancer was increased by 35%  2% to 77%) in the first 6 months after cholecystectomy. The exclusion of cancers diagnosed in the first 6 months still resulted in an increased risk of endometrial  and breast  cancer, especially in women cholecystectomized after age 50 years. By contrast, cholecystectomized women showed decreased risks of cervical  and ovarian  cancer. Conclusions: The risk of ovarian cancer increased by 35% in a just short period of time (6 months) following the surgery. Therefore, it is worth ruling out ovarian cancer before cholecystectomy. Women undergoing cholecystectomy showed an increased risk of breast and endometrial cancer up to 30 years after surgery. Further evaluation of the association between gallstones or gallbladder removal on female cancer risk would allow for the assessment of the need to intensify cancer screening in cholecystectomized women. Surgical removal of the gallbladder (cholecystectomy) is indicated mainly for the treatment of symptomatic gallstones (cholelithiasis) and its complications. Considering the high and increasing prevalence of gallstones, cholecystectomy is one of the most commonly performed surgeries ,2. SeverGallstone disease and breast, endometrial, and ovarian cancers share several important risk factors, including overweight, obesity, and exposure to female sex hormones ,14. CervIn the present large nationwide cohort study, we ascertained and accurately quantified the association between cholecystectomy and the risk of breast, endometrial, ovarian, and cervical cancer. We also considered the time since cholecystectomy, and the age at cholecystectomy for the identified associations. Our aim was to find new clues for the early detection and improved prevention of the investigated female cancers.For the current study, data from the Swedish National Patient Registers, the Swedish Cancer Registry, national censuses, and the Death Register were linked using the individually unique pseudonymized national registration number. These nationwide registered sources are updated every 1–3 years, and in our datasets, which were updated in 2017, the combined datasets included information for more than 15 million individuals up to the end of 2015 (there is a 2-year delay in the release of cancer registry data to ensure the completeness of the reported cases). The Swedish National Patient Registers include nationwide data on surgical procedures from all private and public hospitals and visits to specialized physicians in Sweden, as well as hospital (inpatient) records from 1964 to 2015 and day clinic (outpatient) records from 2001 to 2015. Information on cholecystectomy  code, 9th revision (ICD-9] 51.2 and its subcategories) and date of the surgery were extracted from this dataset. The Swedish Cancer Registry data provided information on date of cancer diagnosis, topography and morphology, and diagnostic reports from physicians for 1958–2015. All cancer records were reported using ICD-7. There were no missing data on the cancer status of individuals. The overall completeness of the registry was estimated to be 96%  [The final dataset contained up to 51 years of follow-up. The follow-up for patients with cholecystectomy started at the date of cholecystectomy (month and year) and for other individuals it was from the beginning of 1964, the birth date (month and year), or the immigration, whichever was the latest. The follow-up period for all individuals ended when they were diagnosed with cancer, emigrated, died, or at the end of study period (end of 2015), whichever came first.P-values were adjusted for multiplicity using the Bonferroni method . For cholecystectomized women, cancer incidence rates by year since surgery were also calculated. Incidence rates in non-cholecystectomized women were calculated for each 1-year interval age and shown in the same chart starting from the corresponding median age of surgery in cholecystectomized women.Standardized incidence ratios (SIRs) were calculated to compare the risks of first primary breast, endometrial, ovarian, and cervical cancer diagnoses for women with a history of cholecystectomy with the risks in their counterparts without such a history. SIRs were calculated as the ratio of observed to expected number of incident cancer cases. The expected numbers were calculated from the strata-specific cancer incidence rate in those with no history of cholecystectomy, multiplied by the corresponding person-years for subjects with history of cholecystectomy. All SIRs were adjusted for age, calendar period , socioeconomic status , and residential area . Confidence intervals (95% CI) were calculated assuming a Poisson distribution. Further stratified analyses were performed by age at cholecystectomy  and time since cholecystectomy . All analyses were performed using SAS software, version 9.4 . To avoid the risk of identification of participants, researchers only had access to pseudonymized secondary data. All linkages were performed by the individual national identification number, which is assigned to all residents staying in Sweden longer than 3 months (residence permit). To preserve confidentiality, this ID number was replaced by a serial number.Among the 325,106 cholecystectomized women, 10,431 primary breast, 2888 endometrial, 1577 ovarian, and 705 cervical cancers were diagnosed during a median follow-up of 11 years. Considering any time elapsed since gallbladder removal, cholecystectomized women showed an increased risk of endometrial  and breast cancer  in the first 6 months after cholecystectomy (95% CI did not include 1), but the risk increase did not reach statistical significance after multiplicity adjustment  and breast cancer , we were able to quantify the risk of breast and gynecological cancer after cholecystectomy in women by time since surgery, and age at surgery, with unprecedented precision. Overall, a 15% to 20% increased risk of endometrial cancer, and a 4% to 8% increased risk of breast cancer after cholecystectomy were observed. Ovarian cancer showed a 35% increased risk during the first half-year period after cholecystectomy, but the risk of ovarian cancer did not increase after 3 years from gallbladder removal. Cholecystectomies performed after the age of 50 years were associated with a lower risk of cervical cancer.Dietary habits , obesity, and the associated hormonal and metabolic changes may explain part of the observed association between cholecystectomy (most often indicated because of cholelithiasis) and breast cancer , endometrial cancer, and ovarian cancer ,22,23,24Surgical removal of the gallbladder can lead to changes in metabolic hormone levels and bacterial microbiota, which in turn can cause inflammation—this sequence has been hypothesized as a likely reason for the increased risk of cancer after cholecystectomy ,36,37,38The increased risk of ovarian cancer detected in the first half-year period after cholecystectomy could be related to existing undiagnosed ovarian cancer. Therefore, women with an indication for cholecystectomy, especially those with overweight or obesity, should be screened for ovarian, endometrial, and breast cancer, and should also take steps to improve their dietary habits, weight control, and exposure to exogenous estrogen after gallbladder surgery to avoid these cancers. Further studies on the exact mechanisms behind the identified associations and age/type/frequency of intensified cancer screening procedures are warranted, which may guide future cancer prevention measures.When cholecystectomy was performed at the age of 50 years or older, it was associated with a decreased risk of cervical cancer, whereas cholecystectomy at younger ages was not associated with a lower risk of cervical cancer. This observation needs to be confirmed in future studies, and the reason underlying the observed decrease in risk needs to be further clarified. Cervical cancer shares some risk factors with gallstone disease, such as low socioeconomic status, oral contraceptive use, and parity. However, the main cause of cervical cancer is human papilloma virus infection .Information on the subtypes of cancers  and the therapeutic response of patients were not available for our study data. Further studies are needed to find the association between surgical gallbladder removal and cancer stage, disease progression, and cancer sub-types, e.g., triple negative breast cancer, high grade serous ovarian carcinoma, and clear cell carcinoma. It is also warranted to find any differences in the survival or therapeutic response of the patients who had undergone cholecystectomy. It would be worth investigating in further studies whether such associations are significantly different in the presence or absence of a family history of the corresponding gynecological cancer.According to the results of our comprehensive analyses of a large nationwide cohort, which was based on highly accredited long-lasting register datasets, we provided accurate risk estimates according to the time since cholecystectomy and the age at cholecystectomy. We investigated the risk patterns considering these two important predictive factors, and reported novel, clinically relevant information that was lacking in previous studies.Our study benefitted from long-standing and large-scale nationwide data on diseases and surgical procedures in Sweden since 1964, with the possibility of record linkage to a high-quality nationwide cancer registry that was in operation since 1958 with a completeness of over 96%. This allowed us to comprehensively analyze the cancer risk after cholecystectomy by time since cholecystectomy and age at surgery with unprecedented detail. The surveillance bias was mitigated by the exclusion of cancer diagnoses within first 6 months after cholecystectomy.In recent years, numerous studies have reported that the detection rate of gynecological cancers, except ovarian cancer, has been improving, especially for those with existing recommended screening modalities. Therefore, in our long-term study (1964–2015), in addition to aging, the effect of the year of inspection on the detection rate of breast, endometrial, ovarian, and cervical cancer could have partially contributed to the overall increasing trend of incidence of these cancers by time after cholecystectomy in both cholecystectomized and reference groups. However, without using such a long-standing data, the long-term follow-up of cholecystectomy would not be possible. There were some random fluctuations at the end of the incidence curves, which were mainly due to small sample size at elderly ages (25–30 years after cholecystectomy). The chance of findings due to multiple testing was restricted by considering probability values smaller than 0.0125 as statistically significant. Similar to other register-based studies, detailed clinical information, such as the exact indication for cholecystectomy, was lacking, although the majority of patients globally undergo this surgery due to symptomatic cholelithiasis or its complications. The residual confounding factors, such as obesity, diet, ethnicity, cigarette smoking, education, and physical activity, may co-exist. We adjusted all SIRs for residential area and socioeconomic status that, to some extent, could take care of variation in lifestyle factors.In conclusion, the risk of ovarian cancer increased by 35% in just a short period of time (6 months) following the surgery. Therefore, it is worth ruling out ovarian cancer before cholecystectomy. Women undergoing cholecystectomy also showed an increased risk of breast and endometrial cancer up to 30 years after surgery. Further evaluation of the association between gallstones or gallbladder removal on female cancer risk would allow for the assessment of the need to intensify cancer screening in cholecystectomized women. In other words, women with an indication for cholecystectomy could benefit from screening for these cancers.


Advances in the early detection of cancer and its treatment have resulted in an increasing number of people living with and beyond breast cancer. Multimorbidity is also becoming more common in this population as more people live longer with breast cancer and experience late effects of cancer treatment. Breast cancer survivors have heightened risk of depression, but to what extent multimorbidity affects the mental health of this population is less clear. This study aims to investigate the association between multimorbidity and depression among women living with and beyond breast cancer in the UK Biobank cohort.Data from UK Biobank  were used to identify 8438 women with a previous diagnosis of breast cancer via linked cancer registries in England, Scotland and Wales. The lifetime number of chronic conditions was self-reported and multimorbidity defined as 0, 1, 2, 3, 4 or 5+. The Patient Health Questionnaire (PHQ-2) was used to define participants that were likely to have depression based on their symptom reporting at baseline. Logistic regression models were used to analyse the associations between multimorbidity and depression, accounting for a number of potential sociodemographic confounding variables  and characteristics related to the cancer (number of years since diagnosis and recurrence/secondary cancer).Multimorbidity was common among breast cancer survivors, with 32.9% of women experiencing one and 30.1% experiencing two or more chronic health conditions. Hypertension (25.8%), painful conditions (18.3%), and asthma (11.6%) were the three most common co-morbid conditions. 5.3% of participants had current depression. A strong, dose-response relationship was found between multimorbidity and the likelihood of depression .Multimorbidity and depression were strongly associated among female UK Biobank participants with a previous breast cancer diagnosis. This association became increasingly pronounced as the number of chronic comorbid conditions increased. As more people survive cancer for longer, increasing recognition and support for multimorbidity and its impact on mental health is needed.The online version contains supplementary material available at 10.1186/s12885-021-08409-z. Breast cancer is one of the most frequently diagnosed cancers around the world, representing 11.6% of all cancer cases . AdvanceMultimorbidity, defined as the presence of two or more chronic health conditions , is an aBoth breast cancer and multimorbidity are factors associated with an increased risk of depression . DepressThe individual links between multimorbidity, depression, and breast cancer have been relatively well researched, but the interplay between the combination of the three has a much more limited representation in the current literature . This stUK Biobank contains data from over 500,000 volunteers, recruited in the period between 2006 and 2010 from across England, Scotland, and Wales. The volunteers were aged between 40 and 70 at the time of recruitment, and provided data from touchscreen questionnaires, physical measurements, genotyping and longitudinal follow-up, with further data continuing to be added . The datIncluded in this study were women with a primary diagnosis of a malignant neoplasm of the breast  code C50 and ICD-9 code 174). 9364 women matching this criterion were identified.UK Biobank received ethical approval from the NHS National Research Ethics Service North West (16/NW/0274) and was performed in accordance with the Declaration of Helsinki. Informed consent was obtained for all UK Biobank participants. The analyses in this study were performed under UK Biobank application number 41686.Current depression was the primary outcome variable, which was assessed using the validated two-item Patient Health Questionnaire (PHQ-2) at baseline . The PHQMultimorbidity was measured by a count of the number of self-reported doctor diagnosed lifetime chronic health conditions recorded during the baseline nurse-led interview (data fields 20001 and 20002) and informed by previous literature on multimorbidity , 20, 21.We included a number of potential confounding variables: age (5-year bands), education level , socioeconomic deprivation  from the analysis, with most missing data being found for PHQ-2 (N = 675). A small amount of missing data was also observed for multimorbidity (N = 66), ethnicity (N = 34), education level (N = 168), marital/cohabitation status (N = 51), and socioeconomic deprivation (N = 12). After the exclusion of missing data 90.1% of participants were included in the final analysis sample (N = 8438). Analyses were completed in R version 4.0.2 and Stata/MP 16.0.Descriptive statistics were used to summarise the sample and the most commonly reported chronic health conditions. Logistic regression models were calculated to analyse the association between multimorbidity and the odds of depression. Model 1 included the number of chronic conditions and patient age as predictors. Model 2 additionally included ethnicity, education level, socioeconomic deprivation, marital/cohabitation status, more than one cancer diagnosis and number of years since the primary breast cancer diagnosis as predictors. These models were used to calculate odds ratios with 95% confidence intervals and predicted probabilities (using Stata’s margins command with the atmeans option) to determine the effect sizes. A significance level of 63% of participants had at least one other chronic condition, with 30.1% having two or more co-morbid conditions Table .Table 1Women with one co-morbid chronic condition had higher odds of experiencing depression, compared to those with no such condition  in Model 1 which adjusted for age), corresponding to a predicted probability for depression of 4.3% compared to a predicted probability of 2.9% in participants without any comorbidity .A comparison to people without breast cancer would have been beneficial to this study, as would a comparison to people with other cancers. As a smaller subset of the breast cancer population, men are underrepresented in this area of research, and regretfully were not included in our analysis. Finally, the exclusion of participants with missing data has a risk of introducing bias, but only a small proportion of people were excluded for this reason (This study finds clear evidence of an association between multimorbidity and depression among breast cancer survivors in UK Biobank. A dose-response relationship was observed in which the risk of depression increased alongside the increased number of comorbid conditions experienced. These results are of importance at this current time, when breast cancer patients are surviving for greater periods of time and thus experiencing the impact of multimorbidity to a greater extent. Increased awareness and effort to prevent depression and multimorbidity in cancer survivors is needed as they both contribute to decreased adherence to treatment, decreased cancer survival, increased suicidal behaviour, and greater health expenditure –34.Additional file 1: Table S1. Self-reported chronic health conditions included in the multimorbidity count.