The eQTL analysis was carried out using the METABRIC dataset and analyses from GTEx and ncRNA eQTL databases. We found putative breast cancer risk variants (p < 1 × 10–5) targeting the lncRNA GABPB1-AS1 in INQUISIT and eQTL analysis. In addition, putative breast cancer risk associated SNPs (p < 1 × 10–5) in the region of two T-UCRs, uc.184 and uc.313, located in protein coding genes CPEB4 and TIAL1, respectively, targeted these genes in INQUISIT and in eQTL analysis. Other non-coding regions containing SNPs with the defined p-value and highly significant false discovery rate (FDR) for breast cancer risk association were discovered that may warrant further studies. These results suggest candidate lncRNA loci for further research on breast cancer risk and the molecular mechanisms.Long non-coding RNAs (lncRNAs) play crucial roles in human physiology, and have been found to be associated with various cancers. Transcribed ultraconserved regions (T-UCRs) are a subgroup of lncRNAs conserved in several species, and are often located in cancer-related regions. Breast cancer is the most common cancer in women worldwide and the leading cause of female cancer deaths. We investigated the association of genetic variants in lncRNA and T-UCR regions with breast cancer risk to uncover candidate loci for further analysis. Our focus was on low-penetrance variants that can be discovered in a large dataset. We selected 565 regions of lncRNAs and T-UCRs that are expressed in breast or breast cancer tissue, or show expression correlation to major breast cancer associated genes. We studied the association of single nucleotide polymorphisms (SNPs) in these regions with breast cancer risk in the 122970 case samples and 105974 controls of the Breast Cancer Association Consortium’s genome-wide data, and also by  About 70–90% of the human genome is transcribed . The proA curious subclass of lncRNAs are the ultraconserved regions (UCRs). These are stretches of DNA expanding over 200 nucleotides that are absolutely conserved between orthologous regions in human, mouse and rat . There eBRCA1 and BRCA2 genes carry pathogenic variants of high-penetrance that cover approximately 20% of the familial relative risk , were reported to have disease association based on SNP-association either with breast cancer or prostate cancer risk or survival  is an international multidisciplinary consortium with a focus on inherited risk of breast cancer dataset , 2017.p < 10–5 to uncover other candidate lncRNA loci for further analysis. The functionality of the SNPs of interest was studied with integrated expression quantitative trait and in silico prediction of GWAS targets , cytoplasmic polyadenylation element binging protein 4 (CPEB4) associated with uc.184, and TIA 1 cytotoxic granule associated RNA binding protein like 1 (TIAL1) associated with uc.313.In this study, we look into the breast cancer risk association of SNPs on lncRNAs expressed in mammary tissue or associated with known breast cancer risk genes, as well as SNPs located at the T-UCRs. We carried this out by analyzing the Breast Cancer Association Consortium’s (BCAC) GWAS, OncoArray, and iCOGs SNP array summary statistics to find SNPs in or near lncRNAs or T-UCRs that associate with breast cancer risk. The loci with GWAS-significant results have been published recently , and in The work flow of the study is presented in The analyses were based on summary results of the Breast Cancer Association Consortium (BCAC). The collaborative dataset of the BCAC contained 122970 female breast cancer case samples and 105974 controls of European ethnicity. Of these, 61282 cases and 45494 controls were genotyped using OncoArray , and 467BRCA1, three with BRCA2, two with ATM, one with CDH1, three with CHEK2, two with PALB2, thirteen with RAD51C, and one with TP53). Several lncRNAs showed positive correlation with multiple of these genes, but here only the strongest correlations are listed  were reported to have disease association based on SNP association either with breast cancer or prostate cancer risk or survival . Their genotyping and the genotyping of the eleven GWAS in the BCAC has been previously described in detail , 2017. Ain silico prediction of GWAS targets, INQUISIT) that combines genomic data from multiple sources, including chromatin interactions, computational enhancer–promoter correlations, transcription factor binding chromatin immunoprecipitation followed by sequencing, gene expression and topologically associated domain boundaries, and which is described in detail by The functionality of the putative breast cancer risk variants was assessed by annotating each variant with publicly available genomic data from breast cells and by using a heuristic scoring system .The Genotype-Tissue Expression (GTEx) project’s breast tissue eQTL results (version 7) were used to detect SNP associations with gene expression. The dataset included 251 normal breast tissue samples. The data used for the analyses in this study were downloaded from the GTEx Portal3. The genotype data was processed with Affymetrix Genotyping Console Software following the practices of the Affymetrix SNP 6.0 analysis workflow. The workflow including a quality control step has been previously described  and standard error to NES. The R-package Matrix eQTL used to carry out METABRIC eQTL analysis also provided FDR p-values. Those were viewed as additional information for the discussion. ncRNA eQTL statistical information included beta, r, and p-values.For the eQTL analysis results, a cut-off of nominal 7, version 4.7, accessed 4.5.2018, 8, 9, Linkage disequilibrium between SNPs was checked using Broad Institutes SNP annotation and proxy search  for five of the lncRNA regions and 18 of the T-UCR regions have previously been published by the BCAC and are listed in p-value of <10–5 and MAF <0.45 was used as the limit of interrogation, resulting in seven lncRNA regions and eight T-UCRs containing three genotyped and 248 imputed SNPs not previously reported by the BCAC . The regions of interest included 5401 genotyped and 349112 imputed SNPs. Results with genome-wide significance level . Nine SNPs were shared between the overall and ER-positive analyses  and no SNP gave a p-value under the threshold in ER-positive analysis only. None of the SNPs were shared by all three subgroup analyses.In addition to the results from the meta-analysis of breast cancer overall, we interrogated the meta-analysis results from ER-negative and ER-positive patient subgroups separately . FourteeA heuristic scoring system, INQUISIT , was usep < 10–5) with overall breast cancer, with FDR <0.005. Four SNPs in uc.313 were also associated with ER-positive breast cancer. It is to be noted that MCF7 is a breast cancer cell line which may cause alteration in its cellular processes and may affect these results.For 60 of the 251 SNPs, INQUISIT predicted one or more target genes . There wGABPB1-AS1, the subject of the lncRNA-75 region and targeted by three lncRNA-75 SNPs in INQUISIT predictions. Three T-UCRs were located within the gene that the SNPs in their regions targeted by INQUISIT: uc.147 in the intron of LRBA, uc.184 in the 3′UTR of CPEB4 and uc.313 in the intron of TIAL1.Overall, the INQUISIT-predicted target genes of the SNPs were not the lncRNA or T-UCR of the SNPs region, but mostly protein-coding genes. The only exception to this was GABPB1-AS1 , CPEB4 and TIAL1  . There were three such genes in our data: nalysis) . Only innalysis) . HoweverGABPB1-AS1 of lncRNA-75 region   . All thrCPEB4 was the predicted target of seventeen SNPs in the uc.184 region  and NGS2 (rs55946741).4 region . The majTIAL1 was targeted by ten SNPs .ten SNPs . The tarp < 0.05 was found for 171 of the 251 SNPs in this study  and rs28489579 . The two SNPs are linked with r2 = 0.8996. All SNPs that show association with GABPB1-AS1 expression are downstream of the gene starting from approximately 4.7kb. Rs71124350 lies 31kb and rs28489579 36kb from the gene.low 0.05 . Curiousp < 0.05 in METABRIC  and p = 3.66 × 10–64 (after FDR correction 3.75 × 10–58) with beta coefficients of −0.317 and 0.324, respectively . Both rs17695092 and rs1564823 as well as the T-UCR uc.184 are located within CPEB4 gene: rs17695092 lies in the intron 2, while rs1564823 and uc.184 are situated in the 3′UTR of the gene.Two SNPs, rs17695092 and rs1564823 in region uc.184, associated strongly in cis with ectively . These STIAL1 in METABRIC . The beta coefficient for rs4752331 and rs12569630 variants is 0.04, and for rs3009879 – 0.04.Three SNPS, rs4752331, rs3009879, and rs12569630 in uc.313, associated in cis with METABRIC . Only rsGABPB1-AS1 results from the GTEx eQTL analysis, we looked for other eQTL resources. Non-coding RNA eQTL database ncRNA eQTL was queried with the GABPB1-AS1 GTEx eQTL results. The data base did not include the SNPs rs71124350 and rs28489579. However, SNPs in strong linkage disequilibrium with these SNPs of interest  were found in the ncRNA eQTL database, and their results support the GTEx eQTL results: SNP rs35831049 linked to the SNP of interest rs71124350 (r2 = 0.822) was associated with GABPB1-AS1 with effect r = −0.35  and p = 9.29e-32, and SNP rs34565064 linked to rs28489579 (r2 = 0.883) was associated with GABPB1-AS1 with effect r = −0.35 (rs28489579 NES = −0.52 and p = 5.45e-32).To validate the In this study, we looked into the connection between lncRNAs and T-UCRs and breast cancer risk. The connection was investigated by identifying putative breast cancer risk SNPs in BCAC data located in or near lncRNAs and T-UCRs, assessing the SNPs’ functional effects using heuristic scoring method INQUISIT that predicts target genes for risk SNPs by combining genomic information from multiple sources, and performing eQTL analysis. These analysis methods are especially suitable for gaining insight into the role of SNPs located in the areas flanking the lncRNAs and T-UCRs and not directly affecting their sequence. All the SNPS found in this study to be associated with breast cancer were flanking SNPSs.GABPB1-AS1 as the target for two SNPs, rs71124350, and rs28489579, and the same SNP-gene association was seen in GTEx eQTL analysis of normal mammary tissue , and for 60 of these in two lncRNA regions and 4 T-UCR, INQUISIT predicted a target gene. For three of these genes, also an eQTL association was found in METABRIC or GTEx eQTL analysis . INQUISIy tissue . Resultsociation .GABPB1-AS1 targeting SNPs, rs71124350 and rs28489579, are linked (r2 = 0.8996) and located near each other. According to a database of human enhancers, between the two SNPs lies a GABPB1-AS1 enhancer site (GeneHancer ID GH15I050390). This site is not a direct enhancer of GABPB1, and concordantly rs71124350 and rs28489579 do not have an eQTL association with GABPB1. As the minor alleles of both rs71124350 and rs28489579 are also associated with a small decrease in breast cancer risk . Commonly, the role of antisense RNAs is to bind the sense-oriented mRNA, and thus block its translation. There are no reports on how GABPB1-AS1 affects the expression of GABPB1, but they share common promotor/enhancer loci according to GeneHancer: of the 18 promoter/enhancer regions associated with GABPB1-AS1, nine were also associated with GABPB1. GABPB1 is a transcription factor and an activator of BRCA1 expression . Of the twelve SNPs that target TIAL1 in INQUISIT prediction, or as METABRIC association, the majority are located downstream of the gene, three are in the TIAL1, all intronic, and one is located upstream of the gene , but as it does target TIAL1 in INQUISIT, a connection discovered by the CHiA-PET method, it suggests involvement in a chromatin interaction. It is worth noting that in METABRIC eQTL analysis, the significance of rs3009879 association withTIAL1 expression was p = 0.0013, but it did not survive FDR correction. Thus, it is also possible that the eQTL association of this variant withTIAL1 is an artefact.Uc.313 is located in the intron 5 or 6 of the the gene . The SNPTIAL1 , is a ubiquitously expressed RNA binding protein that contains three N-terminal RNA recognition motifs and a C-terminal glutamine-rich prion-like domain, which is found to aggregate during the formation of cytoplasmic stress granules  with breast cancer risk have been reported in several genomic regions containing lncRNAs , available online at: All participating BCAC studies were approved by their appropriate institutional ethics review boards for the initial BCAC study. This study uses only publicly available BCAC-summary data, no individual data.SK and HN designed the study. MS and SK carried out the data and eQTL analyses, wrote the main manuscript text and prepared the figures and the tables. CB provided clinical expertise and critically reviewed the manuscript. JB and GC-T provided the INQUISIT analysis. All authors contributed to and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


To explore how Chinese Canadian patients with breast cancer make dietary choices and to understand their nutritional information needs in order to inform oncology healthcare providers about provision of optimal supportive care for this population.Using interpretive description methodology, semi-structured interviews were conducted with first- and second-generation Chinese Canadian women aged 41–73 years living in Vancouver, Canada, who were diagnosed with breast cancer within the last 5 years. A follow-up focus group was held to validate emergent themes.Nineteen women were interviewed; 6 participated in the focus group. Their accounts of dietary experiences following diagnosis focused on three areas: dietary change , facilitators and barriers to dietary change, and information and resource needs. Dietary changes reported included avoiding or consuming greater amounts of certain foods, and taking traditional Chinese medicine (TCM) and natural health products. Barriers to desired dietary change included the interplay between food preferences and family and social life, work-life balance, and cost and availability of specialty foods. Support from family members, however, facilitated participants’ consumption of more whole and natural foods after their cancer diagnosis. Participants obtained food and nutrition information from a variety of sources but had difficulty determining the reliability and accuracy of information. They requested timely, credible, culturally-relevant, and easily accessible dietary information.Oncology healthcare providers would benefit from increased understanding of the dietary practices, including TCM, of Chinese women living with breast cancer. To facilitate communication and improve quality of care, healthcare professionals should provide credible and culturally relevant diet-related information in a variety of forms. Breast cancer is the most frequently diagnosed cancer in women in Canada . BetweenImmigrant Chinese women in Western countries who are diagnosed with breast cancer may face particular challenges when making food choices as they navigate between Western medical messaging about diet and cancer and Chinese cultural understandings of the complex influences of food on health and illness . The genStudies in Hong Kong, USA, and Canada have found that Chinese cancer patients integrate cultural beliefs about food and health to prevent cancer recurrence and promote health , 7, 9–11We, therefore, conducted a qualitative study to explore how Chinese Canadian women with breast cancer make dietary choices and to understand their nutritional information needs. Vancouver, Canada, was an appropriate setting for the study as it has a large Chinese population with diverse linguistic and cultural backgrounds.This study utilized interpretive description, a qualitative research approach that asks questions that explore human phenomenon within a specific context, analyzes data to identify meanings, characteristics, and patterns, and produces theoretically sound and clinically useful findings . The stuWe used purposive sampling to recruit first-generation (i.e. immigrant) and second-generation (i.e. born in Canada) Chinese Canadian women living in Vancouver who were Cantonese, Mandarin, or English speaking and diagnosed with breast cancer within the last 5 years. We deliberately sought a diverse sample in terms of immigration and language because this is characteristic of the Vancouver Chinese Canadian community and we wanted to understand any differences in experiences and needs within this group. Chinese and English language posters and recruitment cards were displayed at outpatient cancer care clinics at the cancer centre serving the Vancouver region, provided to patients by cancer centre oncologists, or circulated at the centre’s Chinese cancer support group sessions. Recruitment continued until saturation (or redundancy of information) was reached .Semi-structured interviews were conducted using an interview guide based on the interpretive description approach . ParticiNVivo 10 software was used to facilitate data analysis, which included (1) manually coding and decontextualizing the data; (2) sorting and categorizing the codes; and (3) developing topics and interpretive schema . BN was Following initial analysis of the interview data, all participants were invited to a follow-up focus group to validate the preliminary findings, enhance the depth of the inquiry, identify contextual and individual circumstances of the dietary decision-making process, and ensure the trustworthiness of the findings . Three mNineteen first- and second-generation Chinese Canadian women were recruited Table  and inteStudy participants’ accounts of their dietary experiences following their breast cancer diagnosis focused on three areas: dietary change , facilitators and barriers to dietary change, and information and resource needs. Focus group participants confirmed that their experiences in making dietary choices before and after cancer diagnosis were consistent with the 3 key themes identified in the preliminary analyses of interview data. They also provided additional examples in support of these themes. Interview and focus group data are integrated in the presentation of data below.Most participants stated that they had made significant changes to their diet following their breast cancer diagnosis. Women reported three main types of dietary changes: avoiding specific foods, consuming more of certain foods, and taking TCM and nutritional supplements.I like deep-fried pork chop, beef, beef noodle soup. I don’t eliminate them completely but I would go for… beef noodle soup maybe only once a month now. I love deep-fried food but staying away from them… deep-fried meats and tofu.Almost all participants indicated that they had reduced consumption of animal protein, including chicken, beef, and salmon. Some indicated they were concerned about antibiotics and growth hormone residue found in meat and dairy products, such as a 61-year-old woman who said “I used to have milk, soymilk, toast and sometimes oatmeal for breakfast but I am not drinking milk now as some people said that milk has hormones.” A number of Cantonese-speaking and second-generation participants mentioned that they avoided certain foods, such as duck and seafood, which they described as “duk,” which means poisonous in Cantonese. Some participants believed these foods might exert adverse effects on their cancer and aggravate inflammation. In contrast, Mandarin-speaking participants generally did not mention any food that they believed was “poisonous.” Some participants talked about avoiding meat because of acid-alkali concerns and wanting to balance the pH in their blood. Other types of food participants avoided included soy products, deep-fried and barbequed foods, processed foods, and sugar.Participants also described increasing consumption of specific types of foods, including fresh fruits, vegetables, beans, and lentils. About half of the group indicated that they preferred buying organic produce because of concerns about residues of chemical fertilizers and pesticides found in regular produce. Most participants stated that they preferred traditional Chinese foods after treatments, such as congee , rice noodles in fish soup, and, for Cantonese-speaking participants, traditional Chinese homemade soups. One first-generation participant, who spoke predominantly English and had moved to Vancouver when she was 8 years old, indicated that she usually had a mix of Asian and Western cuisines in her everyday diet. However, during treatment, she found herself avoiding Western food that made her feel sick and craving traditional “comfort” food, such as congee, which reduced her nausea. A second-generation woman also pointed out that she preferred traditional Chinese food like congee or traditional soups when she was sick because “It’s just soothing and comforting.”The third type of diet-related changes reported by participants was increased use of TCM and nutritional supplements. Several women were taking TCM in the form of capsules (e.g. Cordyceps or Reishi mushrooms) while those who had consulted TCM doctors consumed Chinese medicine in the form of decoction, which is a preparation of herbs, botanicals , and/or animal ingredients placed in water, boiled until the volume is markedly reduced, and the residues strained off. Cordyceps or Reishi mushrooms, consumed in either capsules or soups, were used to increase strength and energy after surgery and as an adjuvant to chemotherapy. A number of participants also started taking nutritional supplements, such as grapeseed extract, fish oil, calcium, and antioxidant drinks, after their diagnosis.Participants provided a variety of reasons for their dietary changes, including maintaining a healthy body weight, reducing risk of breast cancer recurrence, alleviating symptoms resulting from conventional treatments, helping family members adopt healthier diets, and wanting to live longer. For example, one woman said: “I gained weight during treatment and I know that maintaining a healthy BMI is important to help reduce recurrence so I am trying to be a little bit healthier.” Another woman shared: “I really don’t want any of my family members to have cancer… also I think by consuming a healthier diet, it’s also good for cardiovascular health.”Participants’ stories regarding their experiences with diet and dietary change following their cancer diagnosis revealed beliefs as well as uncertainties about traditional Chinese health concepts. First-generation participants often talked about practical aspects of food choice and preparation in ways that reflected traditional concepts of ying/yang and hot/cold. For example, one woman talked about preparing a traditional Lo For Tong soup and said: “I think these soups are good for our health as lamb soups warm us up, warm up our hands and legs. And so does chicken soup - this is a Chinese tradition.” Another woman said, “Some vegetables are of cold-nature, for example mustard greens. It is very cold (nature) so putting in some ginger can help balance the coldness.” These concepts were mostly mentioned by Cantonese-speaking women, though one Mandarin speaker from Mainland China talked about making soups to balance her “cold” body. One Taiwanese woman mentioned this concept but said she did not believe in it.Despite this practical knowledge, most women did not display in-depth theoretical knowledge of these concepts and indicated that they learned about TCM and dietary therapy from their family members and/or TCM practitioners. As well, many participants expressed uncertainty about the validity and rationale underlying these dietary beliefs and practices. These included a few second-generation participants, who consumed traditional soups prepared by their mothers out of appreciation for their concern and effort. Other participants received conflicting messages from healthcare professionals about the effects and/or benefits of drinking traditional soups after a cancer diagnosis: “I noticed that different doctors have different opinions, so for now I will still drink Lo For Tong but not drinking too much.”The participants experienced various obstacles when attempting to implement their post-diagnosis dietary changes. Specifically, this included (1) interplay between food preferences and family and social life; (2) work-life balance; and (3) cost and availability of specialty foods. Some of these obstacles, however, also acted as facilitators that promoted healthful eating for several participants.Participants’ dietary changes sometimes involved trying to eat less of the foods that they and their family members and friends enjoyed eating, and/or consuming a greater amount of foods that were less preferred. Adhering to dietary goals was easier when family and friends were supportive of those goals, especially when they tried to eat in the same way as the patient. For example, one woman reported that her husband supported her by preparing food with her and eating less meat together. Another woman discussed how her friends, who were also experiencing health issues, were trying to “eat more fish, more fruits and veggies, more steaming; less deep-frying, less drinking, less sweets…that kind of thing.” However, other women found family members were resistant and wanted to eat the foods that they were familiar with. One woman shared: “I am having a tough time convincing my family” to eat less red meat and more beans and lentils. Social and festive occasions were particularly challenging for the women, because food items were selected based on taste, traditions, and meanings rather than health effects: “It’s not just about feeling full or satisfying our appetite… eating with friends and family is for socializing… like for Chinese New Year, we would still eat turnip cake with preserved meats, Chinese sausages and dried shrimps… I still eat these with my family and friends and feel very happy… if I had to totally eliminate these foods from my diet, it would definitely affect my emotional well being.”Many participants indicated that they were consuming less packaged and processed food because of the perceived health benefits of having more homemade, whole foods in their diets. However, some found it challenging to allocate time for meal planning, grocery shopping, and cooking. One participant with a busy work schedule said, “I wish I had the time. If I could buy my food from somebody who will make everything healthy, I would eat healthy, but it really has to be convenient.”Finally, the cost of specialty foods such as organic produce, meat and poultry, and Cordyceps mushrooms was identified as a challenge by some women. While participants were generally able to find these foods in Vancouver, the higher price compared with conventional foods was sometimes prohibitive, “When it comes to buying organic, it’s half and half ‘cause sometimes it’s just too expensive. I can’t afford it. Sometimes Costco has a good deal on organic chicken so I will buy it; otherwise, I will just use regular chicken.”Participants sought and obtained food and nutrition information from a variety of sources, including family, friends, fellow cancer survivors, internet, social media, oncologists, dietitians, an integrative supportive cancer care clinic, library books, TCM practitioners, and family physicians. Some participants had received information and attended a nutrition class delivered by dietitians at their local cancer treatment centre. Given the range of information sources, not surprisingly, many women reported receiving conflicting information. This often related to traditional Chinese practices; while first-generation Chinese Canadian participants usually followed traditional practices without concern, second-generation participants found the advice they were receiving from their mothers contradicted their own, more Western, beliefs. When they proactively searched for information to verify the advice they were receiving, they had difficulty determining what information was reliable and accurate. As a result, participants expressed a need for timely, credible, culturally relevant, easily accessible information.Participants requested information specific for different stages of the cancer trajectory. Women receiving active treatment generally felt weak and some experienced difficulty eating, including nausea and vomiting. These women expressed the need for information to help plan their meals, cope with the symptoms associated with cancer treatments, and regain energy. In contrast, women in the recovery phase indicated they would like to learn about food and nutrition to help reduce the risk of cancer recurrence and promote overall health.This booklet was good but all the ingredients listed were based on Western diet, beans, hummus…not commonly consumed by Chinese and not usually found in our diet. It would be helpful to use this booklet as the basis and modify, to develop a booklet that talks about Chinese ethnic food, Chinese cooking methods and recipes, the seasonings, spices.While most second-generation women indicated that current nutrition resources were culturally adequate for them, first-generation women noted that information often did not address ingredients and preparation methods that they were familiar with:First-generation women also noted that they were interested in group education sessions presented by registered dietitians who were familiar with Chinese dietary practices and ideally conducted in Cantonese and/or Mandarin.This study explored dietary choices and information needs of Chinese Canadian women living with breast cancer in Vancouver, Canada. Findings showed that participants made dietary changes following diagnosis that were influenced by a number of factors, including Western and/or traditional Chinese principles, and that facilitators and barriers to making these changes included family and social/lifestyle factors. Participants were seeking credible and culturally relevant diet-related information to promote health as well as to prevent the recurrence of breast cancer.Some dietary changes that participants made were similar to those reported by women diagnosed with breast cancer in the general population , 4, 19. Where our findings differ is with the heterogeneity found among participants with difference linguistic and/or regional backgrounds. Specifically, the women in our sample who were from Taiwan did not practice and/or believe in TCM concepts, and mostly relied on media and medical professionals for diet-related information after cancer diagnosis. In contrast, the Mandarin-speaking participants from Mainland China did believe in TCM concepts and consumed traditional foods for health maintenance, and Cantonese speakers from Hong Kong and China were the participants who talked about consuming traditional homemade soups and herbal decoctions as a means to protecting and restoring their health.There were also differences between first- and second-generation participants. Second-generation participants, all of whom were born to Cantonese-speaking parents, generally did not hold traditional dietary beliefs but learned some TCM concepts and the practice of consuming traditional soups and herbal decoctions for health maintenance from their mothers. Despite their uncertainties, they consumed the soups as a token of appreciation for the effort their mothers put into preparing the soups. There were also differences in information-seeking behaviours and information needs, especially with regard to the use of TCM and dietary therapy after diagnosis, between first- and second-generation participants.Our study was limited by its small sample size and in that only 6 of the 19 interview participants returned for the focus group. Because of this, we cannot make strong claims about regional and generational differences. However, the findings suggest the need for further research to more fully explore heterogeneity in beliefs, practices, and information needs within immigrant Chinese communities. It is important for healthcare providers to be aware of this heterogeneity and not assume that all patients from a particular ethnic background will have similar needs or make similar choices.With regard to facilitators and barriers to dietary change, family support or resistance was a significant influence. Participants stated that it was easier to adhere to dietary changes if family and friends were supportive, particularly when they followed a similar diet. Other researchers have noted that food is often used to express love and care in Chinese culture, especially among family members . Cost waStudies conducted with Chinese patients in other countries, including China, have identified the need for culturally sensitive and linguistically appropriate resources about food and dietary guidelines , 24–26. Finally, in the present study, some participants indicated that they did not inform their oncologists or dietitians about their use of TCM as they felt these professionals did not understand TCM and might ask them to stop using it, similar to what was reported by Xu et al. . To faci


Breast cancer survivors suffer from disproportionate cardiovascular disease risk compared to age-matched controls. Beyond direct cardiotoxic effects due to treatments such as chemotherapy and radiation, breast-cancer-related reductions in skeletal muscle mass, quality and oxidative capacity may further contribute to cardiovascular disease risk in this population by limiting the ability to engage in aerobic exercise—a known promoter of cardiovascular health. Indeed, 20–30% decreases in peak oxygen consumption are commonly observed in breast cancer survivors, which are indicative of exercise intolerance. Thus, breast-cancer-related skeletal muscle damage may reduce exercise-based opportunities for cardiovascular disease risk reduction. Resistance training is a potential strategy to improve skeletal muscle health in this population, which in turn may enhance the capacity to engage in aerobic exercise and reduce cardiovascular disease risk.  Diagnostic and therapeutic advances have drastically improved breast cancer survival rates over the last half-century ,2, yet s2peak) [2peak is a global indicator of the function of the cardiovascular-muscular axis which facilitates the intake, transport, uptake, and utilization of oxygen, and is related to the capacity to perform aerobic exercise. Furthermore, VO2peak is linked to CVD, disability, and mortality in healthy and clinical populations, including breast cancer [2peak and CVD risk. It is also plausible that diminished VO2peak, an indicator of exercise intolerance, contributes to CVD risk by creating a barrier for engagement in cardio-protective behaviors such as aerobic exercise and physical activity. Of concern, breast cancer survivors typically have a VO2peak 20–30% less than healthy age-matched controls [2peak and promote exercise intolerance [The detrimental effects of breast cancer treatment and lifestyle factors on cardiovascular health have been evaluated using gold standard cardiopulmonary exercise testing (CPET) assessment of peak oxygen consumption (VO2peak) ,33,34. Vt cancer ,36,37. Dcontrols ,34,38, dcontrols ,39,40. Tolerance ,32,41. SIn this short review, we discuss how breast cancer-related treatment and lifestyle factors may negatively impact skeletal muscle health and oxygen consumption, thereby contributing to exercise intolerance and, in turn, elevated CVD risk. More specifically, we describe how exercise intolerance as a result of breast cancer-mediated skeletal muscle damage may impede the utilization of aerobic exercise as a therapeutic, cardioprotective tool. Future considerations for researchers and clinicians are also highlighted with a particular emphasis on resistance training as a feasible strategy to combat the deleterious effects of muscle damage on CVD risk in this population.The deleterious effects of breast cancer-related treatment and lifestyle factors can negatively affect skeletal muscle size, which can contribute to functional limitations, including exercise intolerance ,23,28. D2 in breast cancer survivors [2, but potential mechanisms include: (i) blood flow diversion to metabolically inactive intramuscular fat via vasodilation of adipose tissue vessels, (ii) increased distance for oxygen to travel from capillaries to muscle mitochondria, and (iii) decreased overall blood flow to tissue [Breast cancer-related treatment and lifestyle factors have been associated with impaired skeletal muscle quality, which, in turn, may contribute to exercise intolerance . The mosurvivors  and repourvivors . It is no tissue ,52,53,54o tissue ,52,53,542peak may experience diminished aerobic capacity due to peripheral issues such as reduced capillary-fiber ratio and number of oxidative fibers, despite having a preserved ejection fraction [In addition to reductions in skeletal muscle quality and mass, diminished muscular oxidative capacity has been reported among breast cancer survivors . Severalfraction ,55. Othefraction ,38,40,562peak and exercise intolerance [2peak and CVD risk. However, it is also possible that VO2peak reductions and exercise intolerance as a result of breast cancer-related skeletal muscle damage is further contributing to CVD risk by creating a barrier for engagement in cardioprotective strategies such as aerobic exercise and physical activity. For example, leg strength has been shown to be related to both 6-min walk test [2peak [2peak less than 15.4 mL/kg/min—the aerobic capacity needed for functional dependence [The adverse changes in skeletal muscle quality, mass, and oxidative capacity contribute to a range of functional consequences and negative outcomes, including decreased quality of life (QOL) , fatigueolerance , which molerance . Dysfuncalk test , and VO2t [2peak . Furtherpendence . As suchpendence .Various exercise modalities have been assessed as tools to promote physiological and psychological health during and following treatment in many cancers ,63. Aero2peak) [2peak . [Indeed, structured aerobic and resistance exercise during and following breast cancer treatment seems to be mostly feasible and safe ,69,70. P2peak) ,72,73, m2peak) , and bod2peak) . Aerobic2peak) ,76, and 2peak) ,78. Yet,essure). ,80,81 Thessure). ,82. HoweAs described previously, breast cancer treatment can cause damage to skeletal muscle, which has been measured by impairment of structure  ,48 and fGiven that skeletal muscle health supports exercise and movement known to prevent CVD risk in healthy and clinical populations , we posi2peak/max) and overall function associated with aging [2peak [2peak and force production in post-menopausal, sedentary females—the primary demographic of breast cancer survivors at high CVD risk [2peak, in clinical conditions including breast cancer [Resistance training can mitigate decreases in muscle mass, strength, aerobic capacity  direct cardiotoxic effects of breast cancer treatment, (ii) indirect effects of the treatment-mediated development of poor lifestyle factors , and (iii) effects of pre-existing poor lifestyle factors at the time of diagnosis.  Understa2peak, systolic blood pressure) following exercise-based therapies in clinical populations including cancer [Secondly, great heterogeneity exists in (i) CVD risk accrual (or lack thereof) following cancer treatment , and  resistance training to “prime” skeletal muscles for aerobic work, followed by combined aerobic exercise and resistance training after traditional treatment is more advantageous than, say, combined exercise before and after traditional treatments remains an intriguing question. While tempting to speculate, there is likely not a “right” answer, per se. Rather, baseline characteristics , prior exercise history, pre-existing risk factors, cancer stage, traditional treatment plan/stage/dose, and symptom presentation following traditional treatment should weigh into individualized, and, ideally, supervised, exercise prescriptions . For insIn conjunction with improved survival rates, breast cancer survivors are at increased risk of CVDs, including left ventricular dysfunction and heart failure ,3,9,10.


Since then, an overwhelming number of studies in human cohorts and animal models have provided support for that hypothesis. It is becoming clear, however, that exposure in the parent generation can lead to multigenerational and transgenerational inheritance of breast cancer. Importantly, recent data from our lab and others show that pre-conception paternal diets reprogram the male germline and modulate breast cancer development in offspring. This review explores the emerging evidence for transgenerational epigenetic inheritance of breast cancer focusing on studies associated with ancestral nutritional factors or related markers such as birth weight. We also explore paternal factors and the epigenetic mechanisms of inheritance through the male germline while also reviewing the existing literature on maternal exposures in pregnancy and its effects on subsequent generations. Finally, we discuss the importance of this mode of inheritance in the context of breast cancer prevention, the challenges, and outstanding research questions in the field.The past decade has made evident that in addition to passing their genetic material at conception, parents also transmit a molecular memory of past environmental experiences, including nutritional status, to their progeny through epigenetic mechanisms. In the 1990s, it was proposed that breast cancer originates  The genome is relatively stable throughout an organism's life span; however, the epigenome is malleable to ensure short-term adaptation to the environment . BecauseBRCA1 and BRCA2 explain only a small proportion of breast cancers. Despite intense search, no major genetic mutations have emerged  which will help it to survive after birth  induces epigenetic changes that can increase the risk of chronic diseases such as cancer. However, the disease phenotype might only manifest itself when an individual is exposed to certain environmental signals after birth  during pregnancy increased estradiol levels and subsequent risk of mammary cancer in the female offspring . Anotherin utero exposures can lead to breast cancer reduction in animal models. For instance, prenatal exposure to a lard-based high-fat diet during pregnancy or pregnancy and lactation significantly reduced the offspring susceptibility to mammary cancer  is likely due to fetal programming of the mammary tissue as many studies show morphological and molecular changes in that tissue induced by a number of prenatal exposures . Howeverneration , which cneration , 45]. Seneration . Whetherneration –49.in utero exposure to a N-6 PUFA diet. We also showed that maternal exposure to an ethinyl-estradiol (EE2)-supplemented diet  led to an increase in breast cancer predisposition not only in daughters (F1) and granddaughters (F2) but also in great-granddaughters (F3)  . DNA meters (F3) , 53. Durers (F3) , 54. To ers (F3) . The traers (F3) ]. A receers (F3) .Because of the intimate relationship between mother and the developing fetus during pregnancy, the evidence for developmental programming and epigenetic inheritance of disease comes overwhelmingly from studies investigating maternal environmental exposure during gestation and outcomes in the offspring and subsequent generations as described earlier in this review. However, a variety of pre-conception paternal experiences ranging from nutritional status, alcohol consumption, and stress to exposure to pollutants have been shown to alter the male germline epigenome and impact their children's and, sometimes, grandchildren's health [Using a carcinogen-induced mouse model of breast cancer, we showed that both paternal obesity and malnutrition programs development of breast cancer in offspring , 7, 40. While population studies investigating paternally induced programming of breast cancer are still scarce, a few reports can be found in the literature. For instance, both paternal age and ethnicity have been associated to the risk of breast cancer in daughters , 57. UsiThe role of environmentally induced epigenetic reprogramming of the germline has been actively investigated in recent years , 9, 68. The proposed mechanism by which paternal environmental exposures are linked to disease phenotypes in offspring is sperm epigenetic reprogramming . While DMore recent studies show that small non-coding RNAs, which are abundant in sperm , 76, plaThe sperm non-coding RNA load and the abundance of specific RNA subtypes changes as the sperm travels through the male reproductive tract . It is wA variety of nutritional and environmental exposures can program the sperm epigenome, particularly sperm non-coding RNAs , 59, 70.While it is increasingly evident that environmental and nutritional insults modulate the sperm epigenome in animal models and humans , 84, howIn eutherian mammals, such as human and rodents, the placenta connects the fetus to the mother and provides the nutrient and gas exchanges necessary for the proper fetal development . The plaPpara and Casp12 while female placentas did not show this difference in gene expression. However, paternal obesity significantly increased global DNA methylation levels in female placentas, which could explain differences in phenotypic changes faced by male and female offspring. Thus, the placenta effects could hold a potential answer into how poor paternal nutrition can modulate breast cancer risk and other diseases in offspring. We are currently exploring whether sperm non-coding RNAs play a role in placenta development and ultimately modulate disease phenotypes such as breast cancer in offspring.Paternal effects on the placenta are potentially important as its development is driven mostly by the paternal genome and epigenome , 89. In It has long been known that maternal experiences in pregnancy can modulate offspring's breast cancer risk in human populations and animal models. This is not surprising given that maternal environmental insults could directly affect the developing fetus' mammary gland. However, the past decade showed that history of exposure in the parental generation could lead to multigenerational and transgenerational predisposition for breast cancer. The evidence stems primarily from animal models and replication of those findings in human cohorts is urgently needed to determine whether transgenerational inheritance of breast cancer also occurs in humans.In recent years, animal models have also provided important experimental support for epigenetic inheritance and showed that pre-conception paternal factors can modulate breast cancer development in daughters through the germline. In humans, epidemiological studies have linked food supply in the grandparental generation to health outcomes in the grandchildren  and pateWhile a growing number of studies have shown that ancestral dietary and environmental factors can lead to intergenerational and transgenerational epigenetic predisposition to breast cancer, there is still a lot that we need to learn for how this happens mechanistically. Questions that still require answers in this emerging field include: How does paternal germline epigenetic programming alter embryonic mammary tissue development? How is epigenetically induced information transmitted between generations? Do the same mechanisms uncovered in animal models apply to humans? Can germline alterations be reversed in order to manipulate disease phenotypes in offspring? In addition to local mammary tissue alterations, do systemic metabolic changes in offspring play a role in environmentally induced breast cancer risk? These and other questions have important implications and need to be addressed with a multidisciplinary effort that will require knowledge from fields such as developmental and mammary gland biology, cancer biology, and epidemiology.It is also important to note that we have observed a striking overlap between phenotypes induced by paternal and maternal dietary exposures on both mammary gland morphology and breast cancer development, suggesting that a common mechanism may exist. We have also observed consistent systemic metabolic changes and mammary tissue-specific alterations in energy-sensing pathways in offspring induced by paternal diet paradigms. The consequences of those alterations for mammary cancer development also need to be further explored.The research summarized in this review challenges the current view of how breast cancer predisposition is transmitted between generations. If confirmed in humans, this research field could lead to a better understanding of non-genetic transmission of breast and other cancers and what drives tumor growth in a subset of women and how we can stop it. It could also lead to the development of population-based preventive strategies to reduce breast cancer incidence, including epigenetic markers to identify women at risk. This will be a daunting task though, as population studies to identify epigenetic markers of ancestral exposure will likely take decades, given the temporal distance between the parental exposure and breast cancer onset in daughters. Another challenge to overcome and confirm findings from animal models in humans is the difficulty in ascertaining exposures in parents retrospectively, although data from our lab and others , 61, 72 Another possible strategy to reduce epigenetically induced predisposition to breast and other cancers in offspring would require interventions in the pre-conception window. Preliminary data from our lab and others suggest that environmentally induced effects on the male germline are transitory and can be reversed if the environmental insult is removed , 84. ImpSA conceived and wrote the review. RC oversaw the literature research, and wrote and edited the manuscript. EC, MS, and JB contributed to the literature research, helped to write, and edit the review. All authors contributed to the article and approved the submitted version.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.


The objective of this article is to investigate through a review of the literature the role of nutrition in breast cancer prevention through three dimensions (D). Each D offers a different lens. The First D identifies windows/ages of exposures or conditions that convey vulnerability or protection from breast cancer. The Second D addresses the intensity and duration of the exposure; and the (Third D) examines the pace, i.e., how rapid or slow the young woman experiences her growth and development. Birthweight illustrative of the First D reveals a strong signal across the life course on BC risk, but the risk group varies from low to high birthweight. Stressful life events like being a pubertal aged girl living in a household with an unemployed father during the Great Depression or high levels of environmental contaminants exposure are representative of the Second D. Height velocity at specific ages and weight loss in postmenopausal years are illustrative of anthropometric trajectories that reveal an adaptive biosystem that provides a contextual state to interact with the other two Ds. This article presents a new paradigm of nutrition and breast cancer prevention through the lens of three very different dimensions. It is the premise of this article that all three dimensions are essential tasks to tease apart the life course and identify windows for preventive strategies.Breast cancer, the most common cancer in women worldwide, has recognized reproductive and anthropometric risk factors including age at menarche and adult height. Yet the age  The tempo of height velocity and the peak height velocity that end in a woman's adult height, and the age of first birth and pace of occurrence  are essential components to understanding the cumulative risk from adult height and parity on BC risk  levels in cord blood vary by birthweight and preeclampsia exposure; they may set the baseline concentrations of hormones for breast cancer  examines the pace i.e., how rapid or slow the young woman experiences her growth and development. Growth occurs with damage to DNA repair and other components like radical oxygen species in carcinogenesis. Examination of the growth trajectory may provide context for biosystemic aging and interact with the influence of an exposure through prolonging or shortening it or modifying its intensity of effect as evidenced in the other 2Ds. Pregnancy has commonalities to carcinogenesis, because growth factors, hormones, and molecular pathways are up- and down-regulated with gestation but in a “controlled sense.” Pregnancy is a hyperinsulinemic state, with hormones at the highest concentrations experienced by a women in her life. Therefore, growth and pregnancy have always been risk factors but not placed into the context of their trajectory in a life course approach. Encapsulating a life course approach to breast cancer through nutrition can offer a unique lens into prevention and provide strategies for intervention and further research.To achieve the goal of breast cancer prevention, we need to examine the arsenal of exposures (both preventive and adverse), the window of the life course for the exposure (or its proxy indicator like hunger or an economic depression), and the trajectory of growth and the hormonal tone in a woman. Nutrition is fundamental to BC prevention because a woman's body mass and height for example are the result of diet, physical activity, metabolism, hormones, and reproductive life events that are underlying her body mass index, linear growth and attained adult height. The four indicators of nutritional status– anthropometric, biochemical, clinical and diet- are typically measured at one point in time in research rather than repeated measures that capture trajectories and change over the life course. It is the intent of this article to focus on life course approaches to research in nutrition and BC. The objective of this article is to investigate the role of nutrition in breast cancer prevention through three dimensions (D). Each D offers a different lens. The First D identifies in utero offers a window of exposure for breast cancer. Hormone levels in pregnancy vary by race-ethnicity, birthweight and parity. Concentrations of free estradiol and percent free estradiol are higher in the first than subsequent pregnancies  by 9–10 years among girls in the U.S. . Higher infancy as a period of vulnerability for breast cancer arises in conjunction with the third D notably the trajectory of weight gain. Specifically, risk for breast development by 10.8 years in Norway varies by timing of peak weight gain in infancy and by maternal preeclampsia status. In a nested case-cohort study of preeclampsia, we report that peak weight gain during the third through 6th months of infancy in a daughter of a women with a normotensive pregnancy incurs a 1.87 risk for early breast development by 10.8 years. In contrast peak weight gain in the last 6 months of infancy in daughters of preeclamptic pregnancy has a 3.19-fold increased risk for early breast development (Thelus-Jean R 2009). Rapid weight gain in the first 4 months of infancy is associated with a 60% or higher risk for a diagnosis of benign breast disease  after adjustment for birthweight, preeclampsia, weight, and height and other covariates (earlier puberty assessed by age at menarche and age at peak height velocity (2 (95% CI: −13.9–0.63) smaller dense breast area, and 26.17 cm2 (95% CI: 9.42–43.58) larger non-dense area  and 5.14 (95% CI 1.70–17.1) fold increased risk for breast cancer, respectively, compared to women in the lowest tertile of exposure at the same age. Those women exposed at or after 14 years had no risk of BC by tertile of exposure to DDT  the daughter had a marginally reduced risk by 18% (95% CI 0.66–1.02) of breast cancer  Living iThe third D  examines the effects of how rapidly or slowly a girl/woman experiences her linear growth and weight trajectory and/or hormonal and pubertal development and their implications for BC risk. This D is revealed in a life stage-specific lens for BC risk with a strength that can be manifest across life stages (2 difference 0.77 95% CI 0.73–0.80) (e stages –29. The e stages . This lae stages . Li et ae stages . Rosner e stages . Weight 73–0.80) . Associa73–0.80) . Another73–0.80) .This paper presents a life course approach to nutrition and breast cancer in three dimensions. The evidence base for each D and the picture puzzle that appears by addressing all three Ds offers a unique lens into nutrition and BC. The first D focuses on windows of vulnerability for indicators of nutritional and hormonal status. Birthweight reveals a strong signal across the life course on BC risk, but the direction of the associations are not consistent. Specifically the signal for high birthweight on BC appeared in some , 16 but Weight gain (and the pace of weight gain) during specific months in infancy influences breast development, and the risk for benign breast disease. The turning point for weight and its direct influence on BC risk arises from the data on the independent effect of weight at age 18 and of weight gain over the adult years on BC risk. Stunning evidence now appears that BC can be prevented by weight loss over a 25 years period capturing peri-and postmenopausal intervals; these data are primarily based on NHW in the U.S. and need further research in other race-ethnic groups and countries. How much weight is sufficient to prevent BC and how long the weight loss needs to be sustained to reduce risk are other elements that need flushing out.Height in the absolute sense and in multiple manifestations of the linear growth trajectory has a strong signal for BC. Height velocity, age of peak height velocity, and attained height directly influence BC risk. Illuminating what these markers of BC risk mean is a challenge. The insulin-like growth factor 1 signaling pathway and genes are contributors to height but different ages have different patterns of linear growth. For example, infants typically gain weight before a linear growth spurt, however this pattern is not so evident in adolescence, when leptin and IGF-1 work in tandem during puberty. What are the underlying pathways at these stages lending themselves to different phenotypic hormonal precursors to linear growth? How do they relate to BC risk?The timing and intensity of exposure to pesticides and stressful life events influence BC risk. DDT exposure at a certain level and before 14 years, i.e., puberty exhibited a signal for BC risk; any exposure at 14 years or later let alone exposure to a lower level had no effect. Likewise being in a household with an unemployed father during the Great Depression or experiencing hunger in an urban area during World War II was sufficient to be an indicator of risk for BC. It appears that three parameters–age, the intensity of the exposure and the timing during development– are key to identifying the components in the life course that are related to BC risk later in life.This article presents a new paradigm of nutrition and breast cancer prevention through the lens of three very different dimensions. It is the premise of this article that all three dimensions are essential tasks to tease apart the life course and identify windows for preventive strategies. The picture puzzle has the potential for enrichment by examination of the gene-environment interactions in diverse populations and the examination of the epigenetic influences from diet, pesticides, and other environmental exposures.The datasets generated for this study are available on request to the corresponding author.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.The author confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Weight increase from early‐adulthood to ages 45–54 years is associated with a reduced premenopausal breast cancer risk independently of early‐adulthood weight. Biological explanations are needed to account for these two separate factors.Early‐adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual‐level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18–24 years and other breast cancer risk factors showed that weight gain from ages 18–24 to 35–44 or to 45–54 years was inversely associated with breast cancer overall  and with oestrogen‐receptor(ER)‐positive breast cancer . Weight gain from ages 25–34 was inversely associated with ER‐positive breast cancer only and weight gain from ages 35–44 was not associated with risk. None of these weight gains were associated with ER‐negative breast cancer. Weight  What's new?Body weight in childhood and early adulthood plays a key role in determining premenopausal breast cancer risk but little is conclusively known about how subsequent weight changes affect this risk. Here the authors pooled results from existing studies on weight changes and breast cancer risk including more than 600,000 premenopausal women. The results show that weight gain >10–15 kg from early adulthood on lowers the risk of developing premenopausal breast cancer, providing further evidence of body weight as an important determinant of breast cancer risk. The influence of obesity on breast cancer risk varies by life‐stage. Adiposity before menopause is inversely associated with risk, whereas adiposity during the postmenopausal years is positively associated with risk.It is not clear whether changes in weight after early adulthood further affect risk of premenopausal breast cancer. The role of weight gain in adulthood is of interest because increases in body weight during adulthood mostly reflect accumulation of adipose rather than lean tissue, and therefore any change might reflect body fatness better than adult weight itself, and because of its association with intra‐abdominal fat deposition, which is more metabolically active than peripheral adiposity.Due to the relatively low incidence of premenopausal breast cancer, past studies have had limited numbers of cases to investigate the association of weight change with risk by timing of weight change, to examine the effect of weight loss or to analyse these associations by participant or tumour characteristics. Additionally, past studies have often only used proxies for menopausal status, such as status at study entry or attained age, rather than time‐updated menopausal status.We pooled individual‐level data from prospective studies to investigate the association of weight change and its timing with premenopausal breast cancer risk, overall and by breast cancer characteristics.n = 9), Europe (n = 6), Asia (n = 1) and Australia (n = 1), with participants recruited between 1963 and 2013. Data from 1 to 16 questionnaire rounds per study were harmonised to a common protocol. Women provided historical information on their weight prior to study entry on the baseline questionnaire and their current body weight was provided or measured at baseline and on follow‐up questionnaires (if available). This work was approved by the relevant institutional review boards and women provided informed consent to partake.We used data from 17 of the 22 cohort studies in the Premenopausal Breast Cancer Collaborative GroupWomen were included in the analysis if they were breast cancer‐free and premenopausal at study entry, and had premenopausal weight available for at least two age categories (defined below). Premenopausal follow‐up time was determined from menopause information obtained from multiple questionnaire rounds, and, if missing, assumptions based on attained age using age 50 as cut‐off .in situ premenopausal breast cancer combined. We also conducted analyses of invasive and in situ outcomes separately, as well as outcomes by hormone‐receptor status and a clinicopathological surrogate definition of intrinsic breast cancer subtypes  and 95% confidence intervals (CI) representing estimates of relative risk of breast cancer were derived from Cox proportional hazards models with attained age as the underlying time scale.Tests for effect modification of weight change by cohort, starting weight, other available breast cancer risk factors and time since weight change were conducted using log‐likelihood ratio tests.i) excluding the first 2 years of follow‐up to reduce the chance of reverse causation by preclinical disease; (ii) restricting analyses to reported, rather than assumed, premenopausal follow‐up time; (iii) repeating the analyses excluding one study at a time; (iv) additionally adjusting for the number of years between weight assessments; (v) in analyses restricted to subjects with weight at ages 18–24 available, adjusting for weight at ages 18–24 rather than weight at the start of the age category; (vi) restricting analyses to the five cohorts contributing to analyses of weight change at all of the six age groups; (vii) repeating analyses for subjects with nonmissing covariate information; (viii) for subjects with available data, additionally adjusting one at a time for variables only available for some cohorts: ethnicity, cigarette smoking, alcohol consumption, physical activity level, polycystic ovary syndrome, childhood somatotype and mammographic screening history.We conducted sensitivity analyses by  breast cancer patients; ER, progesterone‐receptor (PR) and HER2‐status was available for 3,425  breast cancer patients.The analyses included 628,463 women, whose median age at recruitment was 39.4 (interquartile range 33.8–44.0) years and who were followed for a median of 10.1 (interquartile range 5.9–15.5) years from recruitment during which 10,886 breast cancer cases  were diagnosed. Oestrogen‐receptor (ER) status was known for 6,994 (72.5% of invasive and 43.5% of Most women were white (85.7%), from North America (56.6%), or Europe 41.1%) . The association of starting weight with risk remained statistically significant in these models (data not shown).Weight Patterns of risk with weight change from later ages (i.e. from 25 to 34 or 35–44 years) were less clear, with no association between weight loss and linear trends with weight gain not being statistically significantly associated with risk after adjustment for starting weight.in situ than for invasive breast cancer, but only significantly so for weight gain between ages 18–24 and 25–34 years (p‐interaction = 0.007) .In analyses by breast cancer invasiveness, the inverse associations of weight gain with breast cancer risk tended to be stronger for Associations of weight gain from young ages tended to be stronger for ER‐positive than ER‐negative Table  or for EIn analysis by breast cancer intrinsic subtype, weight gain from ages 18–24 onwards was inversely associated with Luminal A‐like (ER+ PR+ HER2−) breast cancer and weight gain from ages 18–24 to 35–44 and to 45–54 years additionally with luminal B‐like (other ER+/PR+) breast cancer risk  and 25–34 to 35–44 years (p‐interaction = 0.006), but in opposite directions and some of the results were based on small numbers of cases .It is of interest that we observed the strongest inverse associations with risk for weight change from early adulthood and no significant association of risk with absolute or rate of weight gain from ages 35–44 years onwards. Weight gain soon after age 18, if not followed by later weight loss, would lead to the greatest cumulative exposure to adiposity. It is possible that it is cumulative exposure to excess weight that is inversely associated with risk or that late weight gain is outside the susceptibility window for premenopausal breast cancer, for example, because there is a lag time between weight gain and an effect on risk. Our analyses by time since weight gain did not suggest the latter is the case. The lack of association with later (i.e. ≥35 years) weight gain appears discordant with the results from two previous studies. The EPIC‐PANACEA study reported a positive association of rate of weight gain over 4 years with breast cancer diagnosed at age ≤50 years, based on 283 cases.The strong inverse association of breast cancer risk with early adult body sizegain in Asian women have, so far, shown an inverse or null association with premenopausal breast cancer risk overall.Strengths of our study include its prospective design, its large number of cases, and therefore its ability to investigate associations according to breast cancer characteristics, multiple time‐points of weight assessments, and the use of time‐updated covariates. Limitations include that weight at ages 18–24 years was ascertained by recall for most participants, but recalled weight at age 18 years has been shown to correlate well with measured weight,Our results may contribute to the understanding of breast cancer causation and aid in risk stratification. However, weight gain would not provide a strategy for long‐term risk reduction because weight and weight gain are positively associated with risks of postmenopausal breast cancer, several other types of cancer, and other adverse health outcomes.In conclusion, we have observed that both body size in early adulthood and subsequent weight gain are independently associated with reductions in premenopausal breast cancer risk. There is a need to understand mechanisms underlying this finding, which may provide a means for breast cancer prevention.Michael Jones, Minouk Schoemaker, Anthony Swerdlow and Lauren Wright declared grant funding to the Institute of Cancer Research from the charity Breast Cancer Now. Dr Kataro Ozasa declared an institutional research contract with the US National Cancer Institute. None of the other authors declared a conflict of interest with regard to this paper.Since 1 January 2019, Elisabete Weiderpass has been a staff member of the International Agency for Research on Cancer. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization , the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer/World Health Organization.Appendix S1. Supporting Information.Click here for additional data file.


How can imaging facilities optimize the number of breast cancers detected during periods of reduced capacity using clinical indication and individual characteristics?In this cohort study including 898 415 individuals with 1 878 924 mammograms, 12% of mammograms with very high and high cancer detection rates accounted for 55% of detected cancers, while 44% of mammograms with very low cancer detection rate accounted for 13% of detected cancers.These findings suggest that triaging individuals most likely to have cancer detected during periods of reduced capacity could result in detecting the most cancers while performing the fewest examinations compared with a non–risk-based approach. This cohort study assesses strategies to triage patients for mammogram cancer screening during times of reduced capacity. Breast cancer screening, surveillance, and diagnostic imaging services were profoundly limited during the initial phase of the coronavirus disease 2019 (COVID-19) pandemic.To develop a risk-based strategy for triaging mammograms during periods of decreased capacity.This population-based cohort study used data collected prospectively from mammography examinations performed in 2014 to 2019 at 92 radiology facilities in the Breast Cancer Surveillance Consortium. Participants included individuals undergoing mammography. Data were analyzed from August 10 to November 3, 2020.Clinical indication for screening, breast symptoms, personal history of breast cancer, age, time since last mammogram/screening interval, family history of breast cancer, breast density, and history of high-risk breast lesion.Combinations of clinical indication, clinical history, and breast cancer risk factors that subdivided mammograms into risk groups according to their cancer detection rate were identified using classification and regression trees.The cohort included 898 415 individuals contributing 1 878 924 mammograms  interpreted by 448 radiologists, with 1 722 820 mammograms in individuals without a personal history of breast cancer and 156 104 mammograms in individuals with a history of breast cancer. Most individuals were aged 50 to 69 years at imaging (1 113 174 mammograms [59.2%]), and 204 305 (11.2%) were Black, 206 087 (11.3%) were Asian or Pacific Islander, 126 677 (7.0%) were Hispanic or Latina, and 40 021 (2.2%) were another race/ethnicity or mixed race/ethnicity. Cancer detection rates varied widely based on clinical indication, breast symptoms, personal history of breast cancer, and age. The 12% of mammograms with very high  or high  cancer detection rates accounted for 55% of all detected cancers and included mammograms to evaluate an abnormal mammogram or breast lump in individuals of all ages regardless of breast cancer history, to evaluate breast symptoms other than lump in individuals with a breast cancer history or without a history but aged 60 years or older, and for short-interval follow-up in individuals aged 60 years or older without a breast cancer history. The 44.2% of mammograms with very low cancer detection rates accounted for 13.1% of detected cancers and included annual screening mammograms in individuals aged 50 to 69 years  and all screening mammograms in individuals younger than 50 years regardless of screening interval .In this population-based cohort study, clinical indication and individual risk factors were associated with cancer detection and may be useful for prioritizing mammography in times and settings of decreased capacity. These recommendations do not specifically address how breast cancer risk factors should be considered nor address individuals with a personal history of breast cancer.During periods of reduced capacity or in settings with limited mammography availability, facilities, individuals and their physicians who are determining the urgency of mammography should consider the probability that breast cancer will be detected. Several professional associations have posted guidance for scheduling individuals for breast imaging services during the COVID-19 pandemic based on expert opinion.16 to develop an algorithm that radiology facilities could use to optimize triaging of individuals for mammography examinations during periods of decreased mammography capacity, such as during surge periods of the COVID-19 pandemic.We used data representative of the US population from the Breast Cancer Surveillance Consortium (BCSC)STROBE) reporting guideline for cohort studies.The BCSC registries and the Statistical Coordinating Center received institutional review board approval for active or passive consenting processes or waiver of consent to enroll participants, link and pool data, and perform analysis. All procedures adhered to the Health Insurance Portability and Accountability Act. Registries and the Statistical Coordinating Center received a Federal Certificate of Confidentiality and other protections for the identities of individuals, physicians, and facilities. This report follows the Strengthening the Reporting of Observational Studies in Epidemiology .19 Mammograms with a nonspecific diagnostic indication (66 382 mammograms [3.5%]) were classified as short-interval follow-up if the most recent prior mammogram was within 3 to 13 months, with a final Breast Imaging Reporting and Data System (BI-RADS)20 assessment of 3  after all imaging work-up was performed; as an additional evaluation of recent mammogram if the most recent prior mammogram occurred within 3 months and had an initial assessment of 0 , 3, 4 , or 5 , or occurred within 3 to 6 months and had an initial assessment of 0, 4, or 5; or otherwise as a diagnostic mammogram for clinical signs or symptoms. Radiologists categorized BI-RADS breast density20 at the time of clinical interpretation as almost entirely fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense.Clinical indication for the mammogram was assigned by the radiologist or technologist as screening, additional evaluation of a recent mammogram, short-interval follow-up, or diagnostic for clinical signs or symptoms. We further subdivided indications for clinical symptoms into presence of a lump, presence of other symptoms, and unknown. We classified surveillance mammograms  among individuals with a breast cancer history using a previously described algorithm with slight modifications.21 The final BI-RADS assessment was considered positive if it had an assessment of 4 or 5 and negative if the assessment was 1, 2, or 3.20 The cancer detection rate was calculated as number of mammograms with positive final assessment and invasive carcinoma or ductal carcinoma in situ diagnosed within 90 days divided by total number of mammograms.Breast cancer diagnoses were obtained by linking with pathology databases and state or regional cancer registries.22We summarized characteristics of the study population by breast cancer history. We estimated cancer detection rate by individual and mammographic characteristics, separately by breast cancer history, and estimated 95% CIs using generalized estimating equations with a working independence correlation structure to account for correlation among mammograms within the same facility.23 were used to identify factors most strongly associated with cancer detection rate. We fit 4 models: screening mammograms in individuals without a breast cancer history, surveillance mammograms in individuals with a breast cancer history, and diagnostic mammograms separately by breast cancer history. All models included age group , time since last mammogram , first-degree family history of breast cancer, and breast density as potential predictors. Models for diagnostic mammograms also included clinical indication as additional evaluation of a recent mammogram, short-interval follow-up, or clinical signs or symptoms subdivided by lump, other symptoms, and unknown symptoms. Models for individuals without a breast cancer history also included history of a high-risk lesion. Models for individuals with a breast cancer history also included years since diagnosis .Classification and regression trees (CART)We set a maximum tree depth  of 10 and a maximum number of leaves  of 10. We required at least 10% of the sample in each leaf. The maximum tree depth achieved was 5, the maximum number of leaves was 7, and pruning was not required. To internally validate the model, we split the study population into 2 random samples, fit the CART models to each sample, and compared the results to the overall model; we found no clinically meaningful differences.We grouped the final subgroups from the 4 models into 5 risk groups: very high (>50), high (22-50), moderate (10-22), low (5-10), and very low (<5) cancer detection rate per 1000 mammograms. Thresholds were chosen based on the observed cancer detection rates and clinical expertise. Given limitations of CART in identifying small subgroups with clinically important risk differences, we separated screening examinations of individuals with a history of a high-risk lesion into their own subgroup, because of their relatively high cancer detection rate. We plotted the cumulative percentage of cancers detected by the cumulative percentage of mammograms according to the cancer detection rates for the subgroups selected by the CART models, sorted from high to low. We created simplified flowcharts that facilities can use for scheduling under 2 scenarios of reduced capacity.Statistical analyses used SAS statistical software version 9.4 software (SAS Institute). Data were analyzed from August 10 to November 3, 2020.Among individuals with a personal history of breast cancer, the cancer detection rate was 18.6  cancers per 1000 mammograms overall and varied by clinical indication, from 10.0  cancers per 1000 short-interval follow-up mammograms to 138  cancers per 1000 mammograms for additional evaluation of a recent abnormal mammogram. The cancer detection rate for surveillance mammograms generally increased with increasing time since last mammogram, from 10.8  cancers per 1000 mammograms for 1 year to 36.8  cancers per 1000 mammograms among individuals whose last mammogram had been 3 or more years ago, except that mammograms performed less than 1 year since last mammogram had a cancer detection rate of 15.1  cancers per 1000 mammograms. The cancer detection rate for surveillance mammograms increased with age, from 9.2  cancers per 1000 mammograms in individuals younger than 40 years to 15.8  cancers per 1000 mammograms in individuals 70 years or older. The cancer detection rate for surveillance mammograms increased with time since diagnosis, from 7.7  cancers per 1000 mammograms in individuals diagnosed within 5 years to 17.5  cancers per 1000 mammograms for individuals diagnosed 10 or more years prior.The 12.0% of mammograms with very high  or high  cancer detection rates accounted for 55.0% of all detected cancers . The FigThe eFigure in the Using data from 92 US-based radiology facilities in the BCSC, this cohort study identified subgroups of individuals undergoing mammograms with combinations of clinical indications and individual characteristics associated with high, moderate, and low cancer detection rates. Radiology facilities could use this risk stratification model to triage individuals for mammography during periods of reduced capacity, such as that which occurred during the start of the COVID-19 pandemic. Clinicians could use our results to counsel individuals about how urgently they should seek breast imaging based on their breast symptoms, breast cancer history, age, and time since last mammogram. We demonstrate that triaging individuals at highest risk of having cancer detected could result in detecting the most cancers while performing the fewest examinations compared with a non–risk-based approach. For example, a non–risk-based approach resulted in 11.5 cancers detected per 1000 mammograms  while a risk-based approach limiting to the 12.1% of mammograms with high or very high risk of cancer detection detected 55.0% of cancers and resulted in at least a 3- to 10-fold greater cancer detection rate (36-122 cancers per 1000 mammograms). In contrast, the cancer detection rate for the 44.2% of mammograms with the lowest risk was 3.8 cancers or less per 1000 and accounted for 13.1% of detected cancers. The low cancer detection rate in these individuals should be considered, along with patient preferences, when deciding about the safety of postponing imaging owing to limited capacity, such as during pandemic surges when individuals may also experience risks and anxiety about contracting an infectious disease.24 encompassing general resources for facilities, including pamphlets and letter templates to reassure patients regarding COVID-19 safety measures. Our results and triaging flowcharts complement this resource by providing direct, detailed evidence that supports risk-based scheduling of individuals most likely to have a cancer detected based on recent data from more than 1.8 million mammograms interpreted by more than 400 radiologists from more than 90 imaging facilities. In contrast to Society of Breast Imaging guidance based on expert opinion,12 our data-driven analysis suggests a different triage order for certain groups. For instance, while the Society of Breast Imaging recommends prioritizing short-interval follow-up examinations over screening examinations, we found that woman with breast cancer diagnosed more than 10 years prior undergoing surveillance mammography and individuals with a history of high-risk lesions undergoing screening had higher cancer detection rates than most individuals requiring short-interval follow-up.The American College of Radiology posted a “Return to Mammography Care” toolkit,Infrastructure should be developed and resources should be allocated to facilitate risk-based algorithm implementation. Challenges include population-based risk factor ascertainment to triage those already scheduled, and software for real-time implementation when individuals call to schedule their examinations. Electronic health records could be adapted to automate prioritization, given they typically contain risk factor information. As part of our ongoing project, we are developing scripts that schedulers can use to encourage individuals with the highest risk to receive care as soon as possible despite the pandemic, and to reassure individuals whose care may be deferred owing to their low risk.26 Some centers had to greatly reduce clinical care until records were back online. The strategy of offering and promoting medical services based on risk is relevant for other cancer screening tests, including cervical cancer screening, low-dose computed tomography lung cancer screening, prostate cancer screening, and colonoscopy.32 Additionally, our approach may be applicable to other diseases, such as hypertension and diabetes, for which visits to clinicians may be limited by the pandemic or in regions where health care services and clinicians are in short supply. Using data-driven strategies to identify subgroups at highest risk of disease during times of limited capacity may lead to less downstream strain on an already taxed health care system. When capacity is limited, health care systems must ensure that the patients with the highest risk receive care.While our analysis was motivated by limited mammography capacity at the start of the COVID-19 pandemic, our results are applicable to other situations and clinical settings. For example, several medical centers have experienced cyberattacks that limited access to electronic health records.Our study has several limitations. Some facilities may only offer screening or diagnostic mammography or may not collect all the risk factors in our models. These facilities could remove nonapplicable subgroups or combine subgroups. Small subgroups may not have been identified by the CART models. We were unable to assess individuals at greater than 20% lifetime risk owing to a strong family history of cancer, genetic variation, or chest radiation before age 30 years. Our algorithms do not consider individual preferences or worries about breast cancer or about contracting COVID-19. We used cancer detection as a measure of potential benefit of mammography; however, benefits of detecting breast cancer may depend on other factors such as life expectancy  and characteristics of the cancer detected .This cohort study found that in situations of reduced clinical capacity, risk-based triaging of mammograms based on clinical indication, breast symptoms, breast cancer history, and age could maximize cancer detection. We found that the 12% of mammograms with the highest cancer detection rates accounted for 55% of detected cancers. The approach we propose may provide a model for prioritizing use of screening, diagnostic, or other medical services for other types of conditions during periods of reduced capacity or in resource-limited settings.