BRCA1, BRCA2, PALB2, ATM, and CHEK2 act as high- to moderate-penetrance cancer susceptibility genes. Genotyping of these genes informs genetic risk assessment and counseling, as well as treatment and management decisions in the case of high-penetrance genes. TGFBR1*6A (rs11466445) is a common variant of the TGF-β receptor type I (TGFBR1) that has a global minor allelic frequency (MAF) of 0.051 according to the 1000 Genomes Project Consortium. It is emerging as a high frequency, low penetrance tumor susceptibility allele associated with increased cancer risk among several cancer types. The TGFBR1*6A allele has been associated with increased breast cancer risk in women, OR 1.15 (95% CI 1.01–1.31). Functionally, TGFBR1*6A promotes breast cancer cell proliferation, migration, and invasion through the regulation of the ERK pathway and Rho-GTP activation. This review discusses current findings on the genetic, functional, and mechanistic associations between TGFBR1*6A and breast cancer risk and proposes future directions as it relates to genetic association studies and mechanisms of action for tumor growth, metastasis, and immune suppression.There is growing evidence that germline mutations in certain genes influence cancer susceptibility, tumor evolution, as well as clinical outcomes. Identification of a disease-causing genetic variant enables testing and diagnosis of at-risk individuals. For breast cancer, several genes such as  Pathogenic variants of high-risk predisposition genes such as BRCA1 and BCRA2 are the most widely known and are used in genetic testing and counseling to predict breast cancer risk and clinical outcomes5. However, these variants are uncommon , and account for less than 1.5% of all breast cancer cases6. Like other complex genetic traits such as diabetes, obesity, and autoimmune diseases, recent advances in genome-wide association studies reveal that the vast majority of hereditary breast cancer cases are genetically multifactorial10, involving numerous other polymorphisms of varying penetrance acting as tumor modifier genes13. Thus, several lower penetrance risk variants are now included in breast cancer susceptibility gene screening panels for testing and counseling. Inclusion of these polymorphisms into screening panels results in a 40 to 50% increase in breast cancer risk detection among women, and a 5 to 15% increase in detection among BRCA1/2-negative females14.Heritable predisposition genes are important risk factors for breast cancer susceptibility, accounting for 5.03% of all breast cancer cases17. Variants of the TGF-β pathway genes, particularly TGFBR1*6A, have been studied in a large number of females, and have been associated with low penetrance risk for breast cancer18  signaling pathway plays a critical role during cancer development and progression17. During TGF-β signaling, the TGF-β receptor 1 (TGFBR1) plays a critical role of binding and activating downstream receptor-regulated (R-) SMADs (SMAD2 and SMAD3), co-SMADs (SMAD4)20, and non-SMAD 21 intermediary proteins. In 1998, Pasche et al. identified TGFBR1*6A (rs11466445) as a polymorphic variant of TGFBR1 with an in-frame deletion of three GCG codons encoding alanine within exon 1 of the human TGFBR1 signal peptide sequence23  is a common variant of the TGF-β receptor type I (TGFBR1) with a study-wide minor allelic frequency (MAF) of 0.051 in the 1000 Genomes Project Consortium, ranging from 0.0079 among East Asians to 0.0975 among Europeans31. Nineteen case-control studies that included 14,837 participants  have investigated the association of TGFBR1*6A with breast cancer risk (Table TGFBR1*6A genotype frequencies were in Hardy–Weinberg equilibrium (HWE). HWE is a useful genotyping quality control metric that relates allele frequencies to genotype frequencies with an expected assumption that genotype frequencies will remain constant in a randomly mating population. The afore-mentioned TGFBR1*6A case/control studies consisted predominantly of Caucasian individuals of European ancestry (>80%), but also included modest numbers of individuals from other self-reported races/ethnicities . Early studies examined a mixed sample of Caucasians, African Americans, Hispanics, and Asians from the US, and Northern Italy, and found an allelic frequency of 7.9% in breast cancer patients compared to 5.3% in healthy controls23. Several other studies from the US consisting of >80% Caucasians and <20% non-Caucasians reported similar TGFBR1*6A allelic frequency of 5.6–10.0% among breast cancer patients35. The TGFBR1*6A allelic frequency also ranged from 6.1 to 12.8% among breast cancer patients from northern and southwestern Europe, including samples from the UK36, Spain32, Sweden37, Finland38, Poland39, and Ireland40 36. Cases and controls were residents of Southampton, UK. Controls were healthy females. Breast cancer cases were selected based on age at onset under 40 years, family history of breast cancer irrespective of age at onset, or bilateral breast cancer irrespective of family history or age at onset. The study noted that TGFBR1*6A allelic frequency among Caucasians from the UK does not differ by age of onset (<40 years), bilateral breast cancer, family history, and germline mutations of BRCA1 and BRCA236. In 2004, Caldes investigated breast cancer patients of Caucasian descent only from Madrid, Spain. The study found a significant association between TGFBR1*6A and breast cancer risk 32. In the Kaklamani 200526 study that included >80% Caucasians from New York, NY, TGFBR1*6A association with breast cancer risk was significant under both dominant  and additive  models. Breast cancer risk for women aged >50 years was higher , than for women aged ≤50 years . However, further subgroup analyses show no association between TGFBR1*6A and ER/PR status or cancer stage at diagnosis. In this study, both breast cancer patients and healthy controls were matched for age, gender, and location26. Other studies that included participants of similarly mixed ethnicities but from other states in the United States did not confirm an association between TGFBR1*6A and breast cancer risk35  and these studies were not powered to account for the effects of other confounding/modifying factors apart from ethnicity and geographical location that modify the magnitude of the risk attributable to the TGFBR1*6A polymorphism.Published case-control studies examining the association of k35 Fig. . This in40. In a case-control study among Swedish Caucasians37, the study further enriched its population sampling for genetic susceptibility by recruiting patients with family history of bilateral breast cancer cases. Overall, TGFBR1*6A carriership was not associated with breast cancer risk . However, subgroup analyses showed that TGFBR1*6A was associated with increased risk among low-risk familial breast cancer patients with one first- or second-degree breast cancer relative . In that study, TGFBR1*6A also correlated with higher tumor grade (OR 2.27 (95% CI 1.01–5.11) but had no association with tumor stage or ER/PR status37. For women of Asian and Middle Eastern descent, TGFBR1*6A association with breast cancer risk was neither significant nor protective42. Among Asians from India, Joshi 201141 found no association among Western Indians  and those from the Parsi community 41. Although these are important studies, the sample sizes are modest, and the lower allelic frequency in this population43 results in very low a priori statistical power to detect an association of the size previously reported. To date, TGFBR1*6A appears to be associated with decreased breast cancer risk only in Middle Eastern women, particularly in Iran 42. However, it is worth noting that the genotype frequencies in this sample of 280 cases and 280 controls show strong deviations from Hardy–Weinberg equilibrium expectations , an important measure of genotyping quality. Specifically, there were an excess of both TGFBR1*6A and TGFBR1 homozygotes, with a corresponding deficit of heterozygotes, when compared to HWE expectations.Intriguingly, other studies have investigated participants of similar Caucasian backgrounds from other European countries  and found no significant associations Fig. 37–40. InTGFBR1*6A is a common breast cancer susceptibility allele in diverse ethnic backgrounds and its influence may vary by ancestry, geographical location, and other risk modifying factors. Large case/control studies, with important related phenotypes, paralleling the magnitude of other complex genetic traits, and meta-analyses that incorporate strict genotype quality control assessment will be necessary to clarify its population-specific subgroup risk associations.In summary, it appears that TGFBR1*6A association with breast cancer risk, several meta-analyses have investigated its risk association in up to 14,837 participants (6787 cases/8050 controls) from 19 case-control studies. In all, eight meta-analyses have studied the association of TGFBR1*6A with breast cancer risk  found an association of TGFBR1*6A with breast cancer risk with odds ratios of 1.48 (95% CI 1.11–1.96) and 1.38 (95% CI 1.14–1.67), respectively. Subsequent studies examined ten case/control studies and did not find a significant risk association , albeit in a concordant direction. The heterogeneity in the reported results may be partly due to meaningful differences in the genotyping methods employed across these studies for this GCG repeat polymorphism, and increased variation in estimates due to lower sample sizes included in the case/control studies35.To derive a more precise estimate of isk Fig. . Five ofTGFBR1*6A and breast cancer risk. Liao et al. 2010 reported an odds ratio of 1.16 (95% CI 1.01–1.34) among 11,220 case/controls45. Wang et al. 2012 investigated 14,068 participants and showed a nearly identical OR of 1.15 (95% CI 1.01–1.31) 27. Additionally, Ou et al. 2015 found 14.8 and 9.6% TGFBR1*6A allelic distribution among 6275 cases and controls, respectively. There was a significant association of the TGFBR1*6A allele with breast cancer risk (OR 1.33 95% CI 1.02–1.73)46. The study also noted that the homozygous TGFBR1*6A/6A is not significantly associated with breast cancer risk. Colleran 201040 and Krishna 202047 found no significant associations between TGFBR1*6A and breast cancer risk  found an association between isk Fig. . It is i25. In MCF-7 breast cancer cells stably transfected with either TGFBR1 or TGFBR1*6A, TGF-β/SMAD signaling was comparable28. However, the stably transfected TGFBR1*6A MCF-7 breast cancer cells exhibited enhanced cell growth, migration, and invasion28. Importantly, TGFBR1*6A switched TGF-β anti-proliferative effects into growth stimulatory effects in the MCF-7 breast cancer cells. The TGFBR1*6A-mediated switch to growth stimulation was independent of TGFBR1*6A kinase domain, indicating a mechanism likely due to TGFBR1*6A signal peptide25. A similar conclusion was also reached following the investigation of TGFBR1*6A induction of migration and invasion. There was a 1.2-fold and 1.7-fold increase in migration and invasion, respectively, in TGFBR1*6A MCF-7 cells when compared to TGFBR1 transfected cells28. In the MCF-7 cells expressing low TGFBR1*6A levels, there were 1.3 and 1.9 times increase in migration and invasion respectively, when compared to the vector controls. Cells expressing higher and intermediate TGFBR1*6A levels showed 1.8 and 2.2 times increase in migration and invasion, respectively. The induction of migration and invasion observed in the TGFBR1*6A cells were not affected by TGF-β stimulation, suggesting an underlying migration mechanism that is TGF-β independent28. Similar observations of increased growth and invasion were reported in colorectal cancer cells that endogenously harbor TGFBR1*6A. Using SW48 (TGFBR1/TGFBR1) and DLD1 (TGFBR1/TGFBR1*6A) cells, TGF-β treatment resulted in growth inhibition in the TGFBR1/TGFBR1 SW48 cells while it resulted in growth stimulation in the TGFBR1/TGFBR1*6A DLD1 cells25. Stable transfection of the colorectal cancer cells with TGFBR1*6A also exhibited enhanced proliferation when compared with the vector-transfected cells48, indicating that TGFBR1*6A has similar functional outcomes in breast and colorectal cancer.Physicochemical studies using R1B/L17 and HEK 293 cells revealed that the mature TGFBR1*6A and the wild-type TGFBR1 receptors have similar half-life, receptor turnover, and binding affinity to TGF-β ligandTGFBR1*6A function in breast cancer cells is postulated to be mediated by its cleaved signal peptide, which is 3-alanine shorter than the wild-type TGFBR1 signal peptide  response elements (TREs) and a portion of the plasminogen inhibitor-1 (PAI-1) promoter region50. In a study that assessed the proliferation of MCF-7 cells expressing intermediate and high levels of TGFBR1*6A with kinase-inactivated domains, TGFBR1*6A enhanced cell proliferation in both clones similar to the kinase-activated TGFBR1*6A MCF-7 clones. Inactivation of the kinase domain did not influence TGFBR1*6A growth stimulation, indicating a cell proliferation enhancing mechanism that is not affected by the TGFBR1*6A kinase domain. Analyses of the TGF-β/SMAD signal transduction system using SBE4-lux and 3TP-lux transcription reporters, and phosphorylated-SMAD2 and SMAD3 levels showed comparable TGF-β/SMAD signaling levels for TGFBR1*6A and TGFBR1 cells28. The absence of TGFBR1*6A influence on TGF-β signaling is consistent with the observed TGF-β independent effect on migration and invasion in MCF-7 cells. Investigations into TGF-β/non-SMAD pathways revealed that TGFBR1*6A increases ERK1/2 phosphorylation but shows no significant influence on p38 and JNK activation28. The upregulation of ERK1/2 phosphorylation is suggestive of MAP-kinase-mediated migration and invasion  of the rat sarcoma (Ras) superfamily that function as molecular switches for cytoskeletal remodeling during cell division, cell-cell adhesion, cell contractility, migration, and invasion. ARHGAP5 (P190B) and ARHGAP35 (P190A) are the main regulators of the Ras homolog (Rho) family of actin-based regulators and are implicated in cellular adhesion, migration, and invasion52. ARHGAP5 silencing inhibits migration and invasion of AGS and MGC-803 gastric adenocarcinoma cells53. In colorectal cancer, however, ARHGAP5 is markedly overexpressed in the liver of metastatic tissues compared to matched primary tumor tissues54. ARHGAP5 suppression leads to decreased wound healing, migration, and invasion in DLD1 and SW480 colorectal cancer cells54. Similarly, amplification of ARHGAP5 on the 14q12 chromosomal locus promotes the spreading and migration of Huh-7 hepatocellular carcinoma cells55. FN1 encodes fibronectin, a soluble glycoprotein that binds to the cell surface and extracellular matrix. It is involved in cell-cell adhesion, cell motility, and maintenance of cell shape. Positive stromal fibronectin expression is significantly associated with low metastatic spread among patients with invasive breast carcinoma56. On the other hand, relatively low expression of stromal fibronectin correlates with lymph node metastasis, TNM stage, recurrence, and mortality57. Studies have also shown that tamoxifen-induced TGF-β expression regulates fibronectin levels in a feedback loop. TGF-β treatment reduced the levels of tamoxifen-induced FN1 in MCF-7 cells58. Overall, the unbiased gene expression analysis revealed that TGFBR1*6A alters the expression of known pro- and anti-metastatic effectors, which may contribute to its effect on breast cancer progression.Further investigations into the signaling network of TGFBR1*6A association with breast cancer risk suggest an association between TGFBR1*6A and risk for breast cancer, albeit with demonstrable heterogeneity in odds ratios41. They also suggest that TGFBR1*6A-associated breast cancer risk may depend on ancestry, geographical location, and other confounding factors. In genetic association studies, there are primarily four possible explanations that account for a statistical association between a genetic polymorphism  and risk for a disease . They include (i) the allele directly affects the actual disease phenotype/expression, (ii) the allele is in linkage disequilibrium (correlated) with the true disease allelic locus, (iii) there is a spurious association due to population stratification or other confounders60, and (iv) type II error. To assert a direct allelic effect on disease phenotype/expression, the study design must control for confounding factors such as population stratification that could lead to false-positive/spurious associations. In general, ancestral population substructure is the main confounding concern contributing to spurious genetic associations62. Other sources include age, other mutations, and disease-specific contributory factors65. By design, population-based case/control studies such as those used in most of the TGFBR1*6A case/control studies are susceptible to spurious risk associations due to their random or convenient selection of cases and controls from participants that may not belong to the same ancestral population69. On the other hand, family-based case/control studies can help control for confounding population stratification because of shared family pedigrees;70 albeit these designs can be more difficult to recruit. Thus, in a bid to conclusively establish the risk association between TGFBR1*6A and breast cancer, future case/control studies should consider multicenter family-based population studies.The case/control studies and meta-analyses assessing 73. Additionally, the effect sizes reported for nearly all complex genetic traits require large sample sizes for robust power and precise estimation. Thus, future studies should be designed with the range of magnitude of the effect, and allele frequencies observed in the published studies, and recruit cases and controls accordingly to enable well-designed and well-powered subgroup analyses of the contribution of the homozygous and heterozygous TGFBR1*6A genotypes. This will allow assessment of TGFBR1*6A risk association by age, ethnicity, family history, tumor subtypes, tumor grade/histology, other mutation (BRCA1/2) status, response to cancer treatment, and survival/mortality outcomes. When compared to high (BRCA1 and BRCA2: odds ratios ranging from 5.0 to 10.6) and moderate (CHEK2 and ATM: odds ratios ranging from 2.1 to 2.5) penetrance gene variants75, TGFBR1*6A has been described as low penetrance (<odds ratios <2.0) tumor susceptibility allele36. Although low penetrance gene variants and SNPs are common, their genetic risk to complex diseases such as cancer are comparatively small; carriers of low penetrance breast cancer gene variants are estimated to have less than 20% lifetime risk of developing breast cancers75. As such, low penetrance gene variants are postulated to exert their oncogenic influence through additive or multiplicative covariance interactions with other residual gene variants, whose presence or absence can determine disease trait77. Thus, the coupling of the TGFBR1*6A family-based case/control studies with the participants’ GWAS data will allow an additional estimation of the genome-wide composite association of TGFBR1*6A with breast cancer risk, as it relates to other gene variants and gene loci that are in linkage disequilibrium, polygenic association or epistatic interaction. Altogether, the estimation of the genetic risk and polygenic risk score of TGFBR1*6A from a robust family-based study will inform clinical guidelines for early detection and adoption of preventive measures.For multicenter population-based case/control studies that draw subjects from different self-reported races/ethnicities, careful consideration should be given to methods such as (i) structured association tests, (ii) principal components analyses (PCA), and (iii) multidimensional scaling (MDS) from GWAS ancestry to control genetic admixture and confounding effects78  in patients with advanced solid tumors including breast carcinomas, there were associated infusion-related reactions such as cytokine release syndrome. Also, the TGF-β small molecule inhibitor galunisertib (LY2157299) and several others acting as neutralizing monoclonal antibodies80 for TGFB1 and TGFB2, and protein traps81 for TGFBR1 and TGFBR282 invariably yielded promising but minimal clinical benefits. In all, a key weakness is a difficulty to identify precise biomarkers that would tailor TGF-β inhibitors to a specific patient population. Recent studies have proposed and developed a TGF-β gene response signature (TBRS) to assess TGF-β signaling response as a biomarker for cancer predisposition, clinical outcome, and therapeutic response. It utilizes up to 153 genes as probes, which include mainly the TGF-β superfamily ligands , TGF-β receptors (TGFBR1 and TGFBR2), transcription factors , and TGF-β responsive genes 85. Padua, 200883 and Wahdan-Alaswad 201685, used the TGF-β gene response signature (TBRS) to classify breast tumors as TGF-β gene responsive (TBRS+) and TGF-β gene unresponsive (TBRS-) breast tumor subtypes and found a higher correlation between TBRS+, and ER-83 and TNBC85 breast tumor subtypes. Additionally, recent studies relate TGF-β signaling with several cross-talk pathways including microRNA synthesis, stromal fibrosis, and endoplasmic reticulum (ER) stress that regulate immune checkpoint inhibitors, stem cell formation, and metastasis90.Over the last decade, efforts aimed at developing anti-TGF-β drugs has for the most part led to inconclusive pre-clinical and clinical results and serious adverse events. This is at least partly due to imprecise biomarkers and drug targets identified so far. For example, in a recent phase I study of LY3022859TGFBR1*6A functions singularly or in combination with other pro-oncogenic pathways to signal modifications in oncogenic traits needs to be answered to provide clues for tailored drug and biomarker development for the affected TGFBR1*6A individuals95. First, it is imperative to firmly establish whether TGFBR1*6A signaling is a signal peptide or receptor-mediated in various breast cancer subtypes and cell lines. Subsequent interactions and networking with identified cross-talk pathways and mediators can be traced using recent investigational tools such as Whole Transcriptome RNA Sequencing (RNA-seq) and proteomic profiling techniques coupled with computational network analyses such as comparative gene ontology (GO) enrichment analyses, ingenuity pathway analyses (IPA), and protein–protein interaction (PPI) network analyses98. In all, the development of a unique TGF-β gene response signature (TBRS) for TGFBR1*6A as well as the elucidation of a druggable target from the TGFBR1*6A transcriptomic and proteomic studies will be valuable for the prognosis of at-risk individuals and clinical evaluation for precision medicine.The question of whether TGFBR1*6A as a high frequency, low penetrance breast cancer susceptibility allele in breast cancer patients of varied ethnic backgrounds and geographical locations. Its oncogenic influence is attributed to the promotion of cell proliferation, migration, and invasion. Further investigations into the risk associated with individual TGFBR1*6A genotypes as well as their correlation with breast cancer subtypes, disease progression (tumor grade), metastasis, and survival are needed to clarify the population-specific susceptibilities of TGFBR1*6A carriers.Genetic association studies have identified


Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this.P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test.We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6).After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk.Our study suggests a limited role of gene–environment interactions in breast cancer risk. Breast cancer is the most commonly diagnosed malignancy in women. In 2020, breast cancer was estimated to be newly diagnosed in 2.3 million women, and meanwhile caused more than 680,000 deaths worldwide . Both ge21q22.12 may interact with postmenopausal BMI to significantly affect the risk of breast cancer (The Breast Cancer Association Consortium (BCAC) has published multiple studies which reported various interactions between individual SNPs and established risk factors. Nickels and colleagues reported potential interactions between genetic variants and several environmental and lifestyle factors, including number of full-term pregnancies, alcohol consumption, and ever being parous . Schoepst cancer . Howevert cancer . Statistt cancer .Novel statistical methods, such as gene-based testing that incorporates functional information, can substantially reduce the burden of multiple comparisons. As most GWAS hits fall outside of the coding region of genes and are enriched in regulatory elements, it has been hypothesized that many GWAS-identified genotype–phenotype associations are driven by the regulatory function on the expression of nearby genes . Wu and In this study, we utilized the genotype and environmental risk factor data collected by the Breast Cancer Association Consortium (BCAC). Using breast tissue–specific transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project, we built gene expression prediction models for 4,864 genes with a significant heritable component. We then systematically assessed the interactions between these genes and 14 established risk factors in relation to the risk of breast cancer, using a mixed-effects score test called MiSTi , LASSO regression, and elastic-net regression, were then utilized to build expression models for each heritable gene. The prediction accuracy of each derived model was then estimated using 5-fold cross-validation, and the best performing model was selected as the final model for each gene. We built gene expression prediction models for a total of 5,043 genes, of which we had breast cancer genotype data for 4,864 genes. The gene expression prediction models were then used as functional weights in the subsequent interaction analyses.We built gene expression prediction models for each gene using the “FUSION” pipeline. Only the 1,217,312 SNPs included in the HapMap Phase 3 were included in building the prediction models. To estimate the genetically modulated expression of each gene, we included variants located within 500 kb on either side of the gene boundary. SNP-heritability of each gene was estimated using the REML algorithm implemented in the GCTA software . Gene ex2), postmenopausal BMI (per 5 kg/m2), breastfeeding history (yes/no), duration of breastfeeding (per 12-month), height (per 5 cm), history of oral contraceptive (OC) use (yes/no), parous (yes/no), number of full-term births (1/2/3/4+), current smoking status, current use of estrogen only (E-only) MHT, and current use of estrogen plus progestogen (E+P) MHT. BMI was analyzed separately for pre- and postmenopausal women, as the association between BMI and breast cancer risk varies across life stages (All demographic and breast cancer risk factor data were self-reported via interview or questionnaire prior to or shortly after breast cancer diagnosis (for cases) or the reference date . A total of 14 risk factors were included in the present analysis: age at first full-term pregnancy (per 5-year), average lifetime alcohol consumption (per 10 g/day), age at menarche (per 2-year), premenopausal BMI  to assess potential GxE interactions . MiSTi i−7 as statistically significant. Because Bonferroni correction makes the strong assumption of independent tests and results in a stringent threshold for significance, we also report GxE interactions with a P value corresponding to a false discovery rate (FDR)<0.2 using the Benjamini–Hochberg (BH) approach as suggestive findings.In each GxE interaction model, we adjusted for study, age , and first five principal components for population structure. For tests of current MHT use (E-only and E+P), we further adjusted for former use of the corresponding MHT (yes/no) in the model, to account for the association between former use of MHT (which attenuates with time since cessation) and breast cancer. To adjust for multiple comparisons, we considered any interactions with aMiSTi p-value < 0.05/ = 7.34 × 10The data generated in this study are available upon request from the corresponding author.The distribution of environmental factors in the study sample is summarized in P values for GxE interactions are shown in C13orf45 gene on chromosome 13 and age at the first full-term pregnancy (PGXE = 4.44 × 10−6). The heritability of C13orf45 expression was estimated to 0.21, based on 580 SNPs. However, the interaction was mainly driven by the random effects component (P = 1.03 × 10−6) rather than fixed effects component (P = 0.62), which indicates there may be some SNP interaction effects that are beyond the predicted gene expression. Six additional GxE interactions were identified with an FDR-corrected PGXE < 0.2 (RP11–219D15.3 (3q23) and age at menarche (PGXE = 1.60 × 10−5); EML4 (2p21) and use of OCs (PGXE = 2.91 × 10−5); history of breastfeeding and AC114730.3  and AKAP3  in parous women; smoking status and PMS2P3 , and RP11–7I15.4 .The full list of GxE interaction results is reported in XE < 0.2 . These iP < 0.20. Our findings did not support a significant role played by gene expression in modifying the associations between established risk factors and breast cancer risk.In this large transcriptome-informed investigation of GxE interactions in breast cancer, we systematically studied the interactions between predicted gene expression and fourteen behavioral and environmental risk factors. No interaction remained statistically significant after adjusting for number of tests. However, we identified seven interactions between genes and environmental factors, including age at first full-term pregnancy, age at menarche, breast feeding history, smoking status, and use of OCs, as suggestive findings with FDR-corrected C13orf45 gene and age at the first full-term pregnancy. C13orf45, or LMO7DN, is a long noncoding RNA (lncRNA) located downstream of the LIM domain only protein 7 (LMO7). Few studies have directly focused on the function of C13orf45 gene. The expression of LMO7 has been found to play an important role in skeletal muscle transcription and cardiac development  and anaplastic lymphoma kinase (ALK) have been implicated in various cancers. For example, the EML4-ALK1 fusion has been observed in patients with non–small cell lung cancer  system, which has been observed to have a stronger effect among smokers in affecting colorectal cancer risk, relative to the never smokers  performed in our analysis, we performed a conservative Bonferroni correction approach and defined a threshold of Our study has several strengths. First, to our knowledge this is the first study to incorporate breast tissue specific gene expression models to inform our GxE interaction analysis. Previous research has suggested that breast cancer susceptibility loci are enriched in regulatory regions identified in breast tissue or cell lines . Based oIn conclusion, our study incorporated information on gene expression to investigate comprehensively the interactions between environmental risk factors and genetic variants on breast cancer risk using a mixed-effects score test approach. Our findings suggest a lack of evidence to demonstrate the role played by gene expression in modifying the associations between established risk factors and breast cancer risk.Supplementary Figure 1Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.Click here for additional data file.Supplementary Tables 1-3Supplementary Table 1. Sample Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.Click here for additional data file.Supplementary InformationFunding and acknowledgements.Click here for additional data file.


The COVID-19 pandemic led to the prioritization of breast cancer services towards patients who are currently in treatment or diagnosed with advanced stages of breast cancer, and the self-assessment of both tumor growth and treatment side effects. Alongside the stress associated with cancer itself, delays and complications due to COVID-19 may impact patients’ mental health.To describe the experiences of Canadians living with breast cancer who received a diagnosis and/or treatment during the pandemic, and to identify their recommendations for improving patients well-being during future pandemics.Semi-structured interviews were conducted with eighteen women living with breast cancer who also completed the Distress Thermometer questionnaire. The transcripts were analyzed using a descriptive thematic content methodology.Women who started their breast cancer screening or treatment before the pandemic reported fewer delays and less psychological distress than those who started during the pandemic. Participants reported feeling dehumanized while receiving their medical care, being unable to be accompanied during medical visits, and fearing treatment interruption during the pandemic. Patient recommendations for improving care and psychological support included the presence of family caregivers at consultations to receive the diagnosis and for the first treatment session.Study findings provide new insights on how healthcare restrictions during the pandemic impacted on patient experiences and their well-being during screening and treatment for breast cancer. The need for cancer nursing practices and care delivery strategies that promote the delivery of compassionate, patient-centred care and the provision of psychological support during future pandemics are identified. As a result of the COVID-19 pandemic, infection prevention and control measures have transformed to protect at-risk populations, such as patients diagnosed with cancer . ConsequPrior to the pandemic, the breast cancer screening phase was already considered stressful, as it involves waiting for a potential diagnosis , which mA meta-analysis using pre-pandemic data reported that the psychological impact of screening wait times and the receipt of a breast cancer diagnosis can be detrimental to a patient's mental health even before treatments begin . During Although cancer screenings and treatments have resumed in North America, particular concerns reinforced by the media and/or healthcare teams persist amongst oncology patients, such as fear of appointment cancelation, fear of contracting the COVID-19 at the hospital, and diagnosis and treatment delays . MedicalThe main objectives of this qualitative study were to describe the experiences of patients living with breast cancer who received a diagnosis and/or treatment during the pandemic, as well as to identify their recommendations to improve patients well-being during current and future time of health crisis. In addition, we measured psychological distress levels for descriptive purposes and to contextualize participant experiences.This study employed a qualitative descriptive design, allowing us to capture a broad overview of the experience of receiving a breast cancer diagnosis and/or treatment during the pandemic . This meTo enrich the quality of this study, we consulted the expertize of a patient partner who received both her diagnosis and treatments during the pandemic [IL]. She provided input on the conceptualization of the study protocol, and the development of the materials, and the recruitment strategy. Her advice throughout the various phases of the study is discussed in later sections of this paper.The sampling approach used in this study was selected based on the literature. We expected to recruit between 9 and 15 participants  who were diagnosed with breast cancer and/or started treatment during the pandemic. This target sample size was inspired by qualitative studies with similar populations, where data saturation was achieved after 9 , 10 Lan and 15 pParticipants were recruited in February 2021 via advertisements through Canadian Community-Based Cancer Support Services, breast cancer Facebook pages, and word of mouth through our patient partner. Participants interested in the study were screened by a research team member  by phone to confirm their eligibility.during the pandemic . The following participants were excluded from participating in the study: participants lacking the technology to attend the interview virtually on a videoconference platform , individuals diagnosed or treated for any other type of cancer/health condition, individuals undergoing screening or awaiting a potential breast cancer diagnosis.To be included, the participants needed to 1) speak French, 2) be 18 years of age or older, 3) have been diagnosed with breast cancer and/or treated Ethics approval was obtained from the Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Est-de-l’Île-de-Montréal (CEMTL-24267). After confirming eligibility, participants were asked to sign the information consent form via the secure online platform LimeSurvey. Next, interviews were conducted remotely via the Zoom platform . All intInterviews were transcribed by a research team member and then reviewed by two independent research assistants to ensure accuracy and completeness of the ideas presented in the interview. The first author [JF], who also conducted the interviews, revised and finalized all the transcripts.The interview guide was developed based on different Canadian cancer-related guidelines during the COVID-19 pandemic  to 10 (extreme distress). First, participants were asked to explain and rate their distress level during their worst breast cancer-related experience, as previously done in the literature . Then, tAnalysis was performed using thematic content analysis . A themaA narrative synthesis was written for each participant to contextualize the data concerning each participant's own experience. The synthesis included narrative descriptions, classification of evidence, commentaries, and interpretations that could build a body of knowledge from the participant's individual experience . Four meDescriptive analyses were conducted to add quantitative input to the qualitative data. All statistical analyses were conducted in SPSS V. 27 to present retrospective and current distress scores obtained with the Distress Thermometer.Eighteen participants identifying as women were included in the final sample with ages ranging from 30 to 64 years old. For further sample characteristics, see n = 3), receiving the diagnosis (n = 6), fear of the unknown caused by the pandemic regarding their diagnosis/treatments (n = 4), diagnosis or treatment changes due to the pandemic (n = 3), comorbidity (lung cancer diagnosed during breast cancer treatments) (n = 1), and the side effects of the treatments (n = 1). According to the Distress Thermometer, women reported high levels of psychological distress at the time of their worst breast cancer-related moment . At the time of the interview, women reported levels of psychological distress below the clinical cut-off score . All participants were above the cut-off score at their worst moment, while only six women reported high levels of current distress (scores > 4) at the time of the interview.The worst moments reported by the participants related to the screening period  COVID-related delays and preventive measures for breast cancer diagnosis and treatment, 2) social and medical support, and 3) proposed recommendations. Each of the themes were defined and further divided into subcategories which are discussed below.The narrative syntheses identified three trajectories of pandemic-induced delays and preventive measures depending on when participants were diagnosed and started treatment. From this, three groups of participants are presented in This central theme includes the participants’ experience at the first potential signs of breast cancer  until the moment of the official breast cancer diagnosis. This theme also addresses how COVID-19-related delays and preventive measures in healthcare influenced the screening and diagnosis process.According to the participants, no one from Group I and II experienced significant delays between screening and formal diagnosis. The diagnosis was given in person, and only one person was not accompanied during the appointment. The remaining participants were grateful for the moral support during this emotionally difficult appointment.low priority.” The delays led her to report anger and injustice:“I was not a victim, but I became one because of COVID. A victim of the delays […]. I wasn't revolted to have been diagnosed with cancer; I was revolted to get it during COVID. […] It went from ‘we’ll remove a little bit of your breast’ to ‘we’ll remove both your breasts.’ That was the impact of COVID.”Women from Group III experienced stressful delays when receiving their screening appointments and diagnoses. One participant was told by her healthcare team that these delays caused her diagnosis to worsen, evolving from stage 0 to stage 1, as she was initially classified as “more empathy“ from her physician. However, her expectations were not met:“The distance with the medical team who practically greet you with a five-foot pole [laughs]. I’m exaggerating, but you get that, you know. When I was diagnosed, he [her physician] kind of pushed the Kleenex box towards me. He couldn't do otherwise, he had to keep his distance and all that. That kind of distance is very difficult.”The experience of obtaining a diagnosis during the pandemic was very heterogeneous in Group III depending on the date, specific regulations of the hospitals, or the decisions made by the healthcare team. Four women received their diagnosis in person, of whom only three were allowed to be accompanied. All women who were accompanied acknowledged that they were fortunate to have had the support of their partner during this appointment. On the other hand, a participant who was alone due to COVID-related regulations found her experience very difficult. As she was unable to seek comfort from a partner, she expected “n = 5), videoconference (n = 2), or instant messaging . Some participants appreciated these modalities as they were grateful to have their support system present during this moment. They also recognized other advantages, such as avoiding exposure to the virus by going to the hospital and reducing the stressful wait time before receiving their results. However, two of the participants who received their diagnosis by phone would have preferred a diagnosis via videoconference to “humanize“ the experience. Despite asking, their request was denied. One participant asked if she could use the speakerphone to allow her spouse to hear the information, but the doctor refused due to a fear of being recorded.The rest of the participants from Group III obtained their diagnosis either by phone  were required to self-assess their symptoms and side effects after their surgery and during their treatments to determine how well they were recovering. One participant reported that she was not able to determine if her tumor was shrinking and thus, did not notice that it had continued to grow. The latter could have been avoided if follow-up appointments were made via videoconference/in person rather than by phone. Psychologically, the restrictions regarding accompaniment during medical appointments and treatments were the most difficult experience for 12 women. For some, the experience of surgery was stressful and difficult, as they were alone before and after the procedure. In addition, they felt that the process of being dropped off at the hospital was dehumanizing. For others, having someone with them would have been less stressful, as it would have prevented them from being alone when asking questions and receiving information from the healthcare team. During these particular circumstances, several women mentioned taking the initiative to help other patients who appeared distressed without a caregiver in the chemotherapy room. Regarding esthetic procedures, all women  who wished to have breast reconstruction were unsure when they would have access to this service due to the low priority nature of the surgery, despite its apparent impact on their well-being and body image.As they had no point of reference, it was difficult for some women from Groups II and III to determine whether the delays they experienced were directly related to the pandemic or whether these delays were typical. The treatment experience was positive for one participant who was happy to be on hormone therapy, as it allowed her to stay home during the pandemic, and for two other participants who wanted to receive treatment regardless of the circumstances. However, for many, the preventive measures were harmful to their physical and psychological health. Regarding physical health, a few women (n = 15) across all groups . Women reported that they did not want to be affected by the COVID-19 virus, not because of its side effects, but because they feared it would prevent them from continuing their breast cancer treatments. For this reason, they used several preventive techniques to reduce anxiety, such as avoiding frequent travel, wearing a mask, and disinfecting their hands. When the healthcare team did not use preventive measures , stress amongst patients increased. However, when the healthcare team used preventive measures, participants reported experiencing less stress.The experience of being immunosuppressed during the pandemic was one of the most anxiety-provoking factors among many of the women (n = 7) in each group . Media reports and government decisions were “contradictory“ and caused “anxiety“ or “paranoia“ during all phases of the disease . Due to this, four participants waited weeks to go to the hospital as they minimized the urgency of consulting a medical professional concerning the lump in their breast. Moreover, many felt that COVID-19 patients were taking over their medical services. In consequence, some questioned whether they were “really sick”. The decisions made by the public system related to priority care in times of crisis at the expense of medical care for illnesses such as cancer were also questioned by several participants:“I was also shocked at the government. There's not just COVID in life! You know, it's not just that. There are people with cancer, there are people undergoing treatments. Hospitals are full every day, and then, all of a sudden, it's just COVID? Wow, that, I was not happy about. So yes, I felt that they [patients with COVID-19 infection] were taking my place.”Additionally, socio-political issues were raised by some participants . All women who did not live alone (n = 7) acknowledged that they were “lucky“ to always have someone to help them with daily tasks, medical appointments, or to clear their heads. The most widely reported type of support was holding discussions with other patients who were going through similar experiences facilitated by virtual or face-to-face activities offered by Community-Based Cancer Support Services or on breast cancer Facebook groups.The social support received by the participants was more “empathy,” “availability and quick call returns,” and “positive encouragement“ made them feel “safe“ and “improved their experience.” The remaining participants did not feel supported by their healthcare team as they would have preferred for the team to provide more answers to their questions (n = 6),to be more involved in decisions related to their care (n = 4), and to have a pivot nurse who was more available to return calls and do follow-ups (n = 4).In terms of support from the healthcare team, more than half of the participants felt supported by various professionals. Indeed, many reported that the “All participants offered recommendations to improve patients’ well-being during COVID-19, which were directed either to the Canadian healthcare system, healthcare teams, or other patients living with breast cancer who were undergoing or soon to undergo the same experience. The most-reported recommendations were related to the importance of recognizing that decision-makers must be more considerate of breast cancer care (both screening and treatment) in times of crisis. Additionally, despite the inevitable preventive measures and delays, it was recommended that healthcare teams remain empathetic. No consistent pattern was found between participant groups  and proposed recommendations. See The objective of this study was to describe the experience of patients who received a breast cancer diagnosis or treatment during the pandemic and to inform medical and nursing teams of meaningful ways to improve decision-making and planning regarding the delivery of essential cancer care services. Our results show that the different delays and preventive measures related to the pandemic had both positive and negative impacts on our sample. Mostly, women who were diagnosed and began their treatments before the pandemic (Group I) had less difficult experiences as they were already in the medical system when the pandemic unfolded. However, for participants who were diagnosed (before or during the pandemic) and began their treatments during the pandemic (Groups II and III), the delays and preventive measures caused by the pandemic took the form of psychological and emotional distress, stress, and fear. In our study, psychological distress was mostly related to wait times and uncertainties about whether the pandemic would impact disease progression or potential delays in medical care. Two previous studies reported similar results where higher levels of psychological distress among patients living with breast cancer was associated with fear of disease progression , 2021.Moreover, the inability to be accompanied during medical appointments was identified by the majority of our participants. This restriction enhanced fear of unpredictability regarding their diagnosis or first treatment appointments, and highlighted the lack of social support in times of need. This result is supported by the literature showing that body proximity and touch are therapeutic during difficult or uncertain times and can contribute to the reduction of stress and fear . In the In addition, fear of contracting the COVID-19 virus was reported by all participants. Interestingly, the fear was, for most, related to the fact that their cancer care and treatments would be interrupted if they contracted the virus. These factors were often associated with fear generated by the media and medico-political decisions. A previous study has also shown that the constantly changing government decisions have led to many medical appointments cancelations and the avoidance of screening appointments among patients diagnosed with breast cancer . Our stuIt is clear that medical and nursing teams made efforts to adapt their services to the challenges brought by the pandemic. However, unaccompanied mandatory medical appointments were difficult for patients, as they felt that their partner's absence was not always compensated by an empathetic attitude from the healthcare team. However, it is important to note that elevated stress levels experienced by medical teams during clinic visits have been shown to enhance the patients’ perception of feeling dehumanized . This fiIn addition, self-assessment of treatment side effects and cancer mass evolution was not effective for all participants. Indeed, some women still reported disease progression and avoidable treatment side effects. This medical practice is currently under investigation by researchers, and primary results show that patients can assess themselves as effectively as physicians . HoweverOn a positive note, many women reported that they wanted to help other patients by supporting them during difficult medical appointments or by participating in this research study, which allowed them to feel useful. Such empathetic responses correspond with post-traumatic growth, an indicator of resilience that stems from potentially traumatic or highly stressful experiences such as the COVID-19 pandemic and living with breast cancer . Their rAlthough the pandemic led to spontaneous medico-political decisions, COVID patients prioritized over cancer patients was at the heart of much discontentment. The most reported issue was the inability to be accompanied during medical appointments. The patients’ caregivers  were treated as “distance-caregivers,” which prevented patients from receiving emotional, physical, and functional support . The impRecommendations directed towards other patients living with breast cancer revolve heavily around spirituality and optimism, which have been shown to be protective factors for mental health in oncology . AlthougGiven the similarities that were found across international studies on the experience of screening and treatments for patients living with breast cancer during the pandemic, the recommendations for Canadian medical and nursing practices proposed in this paper could serve as steppingstone for other countries.This study is not without limitations. The participants are not representative of the breast cancer population as our sample was largely younger than the average age at which women are diagnosed (50 years and older). It is important to note that all participants verbalized that they were highly educated and therefore, were more inclined to find solutions to the various obstacles experienced during their medical experience . In light of this, it is likely that our results do not accurately capture the experience of women with lower levels of education.The results of this study present valuable and important insights into the impact of the delays and preventive measures caused by the pandemic on the well-being of patients living with breast cancer. The experience and recommendations provided by women living with breast cancer should serve as an example for future pandemics or health emergencies, where important decisions need to be made about healthcare services. Additionally, this study highlighted priorities to improve patients’ experiences, support their psychological well-being, and improve cancer outcomes that oncological teams should consider in circumstances beyond the COVID-19 pandemic.


A few available African studies have reported inconsistent findings using different single socio-economic measures. Our aim was to investigate the association between socio-economic status and the risk of breast cancer among Nigerian women based on a range of socio-economic status measures.we conducted a hospital-based case-control study involving participants from five hospitals in Lagos and Abuja. Women were interviewed in-person between October 2016 and May 2017 using a semi-structured questionnaire. Socio-economic status was assessed based on education, occupation, income, wealth, and socio-economic index. Multivariable logistic regression was applied in data analysis using Statistical Package for Social Sciences (SPSS) version 23. Level of significance was based on 95% confidence interval or p-values less than 0.05.we recruited 379 histologically confirmed breast cancer cases and 403 controls. Following full adjustments, breast cancer risk reduced as socio-economic index increased (p for trend=0.028). Although women in the highest categories of educational attainment , and personal income  had a reduced risk of breast cancer compared to women in the lowest categories respectively after adjustments for relevant covariates, income alone exhibited a significant risk reduction following mutual adjustment for other socio-economic status measures (p for trend=0.014).the observed associations between high socio-economic status and lower breast cancer risk in Nigeria contrast with predominant findings in high-income countries. It suggests the need for socio-economic intervention and other preventive programmes such as improved access to screening and diagnostic services targeted at women of low socio-economic status in Nigeria. Evidence of rising incidence of breast cancer has been reported in Africa . In NigeOne factor that has been rather consistently associated with risk of breast cancer in other parts of the world is socio-economic status (SES) ,5. High To date, the association between socio-economic status and the risk of breast cancer in Africa has only been reported in studies based on single measures of SES such as education and property index . The finStudy design and setting: a hospital-based case-control study was conducted in four public tertiary hospitals , Lagos State University Teaching Hospital (LASUTH), University of Abuja Teaching Hospital, Gwagwalada-UATH, National Hospital Abuja (NHA) and one secondary health facility . Lagos (Southern Nigeria) and Abuja (Northern Nigeria) are the two most important cities in Nigeria being the former and current federal capital city respectively. With a population of more than 12.5 million in 2016, Lagos is the largest city in sub-Saharan Africa, and projected to be the largest city in the world by 2100 [ by 2100 . Abuja h by 2100 . Hospita by 2100 . AvailabStudy population: the study population comprised incident cases of female breast cancer attending public hospitals  between July 2015 and March 2017. Available records suggest that about 700 cases of breast cancer were seen across public tertiary health care facilities in Lagos and Abuja the year prior to the beginning of the study.Sample size: the suitability of the sample size was confirmed based on the data available from a previous Nigerian study [an study , using tan study  below.β represents the standard normal deviate for power of 80%, while Zα/2 represents the standard normal deviate for 95% confidence interval. Allowance of 20% non-response rate was made.r = ratio of controls to cases, p1 represents proportion of cases, while p2 represents the proportion of controls exposed to putative risk or protective factors, p* represents the average proportion of cases and controls exposed to the putative risk or protective factor, ZSampling technique, selection criteria, recruitment: all eligible cases who were receiving treatment at the participating hospitals within the period of the study were consecutively sampled in proportion to the population of cases available in each study site. This was done in the order in which the patients arrived at the clinics each day as shown in the attendance register. This was the process acceptable to the oncology departmental heads who did not permit any contact with patients outside of clinic hours for recruitment purpose citing ethical concerns. No access was possible to the attendance registers in the ophthalmology clinics (source of controls), so controls were consecutively sampled based on the order of arrival/sitting in the waiting area. We adopted this approach because we have no evidence that the order of attendance and sitting during clinic hours was associated with socio-economic status. Moreover, a similar method has been applied in a previous study.Cases were women, aged 20-80 years, diagnosed with histologically confirmed invasive breast cancer who attended oncology clinics in the oncology departments of the participating hospitals between October 2016 and May 2017. All cases whose date of diagnosis had exceeded 18 months at the time of interview were excluded to reduce information bias due to forgetfulness. The original intention was to include cases who were diagnosed not more than 12 months before the interview, but because of difficulties in confirming dates of diagnosis pre-interview, some participants (16.4%) were diagnosed 13-18 months before the interview. Controls were women who attended outpatient ophthalmology clinics in the ophthalmology departments of the same hospitals during the same period. The ophthalmology departments offered comprehensive eye services involving preventive, curative, and rehabilitative services. Hence, they attracted people of all SES. Controls were either female ophthalmology patients or female relatives (visitors)  aged 20-The study aims and what participation would involve were explained to potential participants (both cases and controls) during clinic hours. Afterwards, interviewers  approached the potential participants in the waiting area to confirm their eligibility and willingness to participate in the study.Data collection procedure: all eligible participants who provided written or oral consent were interviewed in person using a semi-structured questionnaire. The instrument was developed specifically for the study based on information from previously validated questionnaires, taking local context into consideration [deration ,21,22. TThere were a mix of interviewers comprising people who could speak English, the local language of the study area, as well as Pidgin English (the Nigerian version of English) which most urban dwellers in Nigeria understand. During the early phase of the study, participants were offered a modest payment or soap; they were informed about this after completing the interview. Some participants indicated that there was no need for these tokens and so this process ceased. In total 26% of participants received a payment or soap. To enhance the quality of data generated, we provided a 2 to 4 hour training session for the interviewers (involving recorded mock interviews) ahead of the study. Interviewers recorded the initial study interviews using digital voice recorders (ICD-PX 333 series). However, some patients expressed concern over privacy of the recordings so not every interview was recorded. We checked all completed questionnaires before the end of each day of data collection and efforts were made to re-contact patients where possible for any detected error or missing information.Measurement of socio-economic status: two variables for educational attainment were defined-educational achievement of the woman herself, and that of her husband (excluding never married women). Respondents with (or those whose husbands had) a Higher National Diploma Certificate (HND) were classified as first-degree holders, while post-secondary education was defined as any training including technical and vocational education leading to an award of certificate following completion of secondary education but falling below HND or first degree. Educational attainment was classified, for analysis, as non-formal/primary, secondary, postsecondary, first degree/HND and >first degree.Information was collected on the specific job held by the participants and their husbands. Occupational status was defined based on the International Standard Classification of Occupational Status, issue 08 volume 1  . SpecifiData on wealth index was based on property ownership. We collected data on the type of accommodation/tenement the woman lived in  and ownership of a private car . These two variables were scored from 4 to 0 (in the order of presentation above), summed and categorised into three equal groups as high, middle, and low. Given the potential correlations among the socio-economic variables of interest, we computed a socio-economic index (SEI) - a single indicator that captured the average effect of all the variables. This was derived by converting the dummy variables assigned to each ordinal category of personal educational attainment, husband´s educational attainment, personal occupational status, husband´s occupational status, personal income, husbands/helpers´ income, and wealth index into scores and computing the average sum for each participant. The average sum was split into 4 equal groups categorised as very low, low, high and very high socio-economic index (SEI).Statistical analyses: the differences in distribution of demographic factors and explanatory variables between cases and controls were assessed using t-tests or Mann Whitney U  for continuous variables. Categorical data were compared using Chi square (χ2) tests. Unconditional binary logistic regression was used to model the relationship between breast cancer and socio-economic status using Statistical Package for Social Sciences (SPSS) version 23. Unadjusted odds ratios and 95% confidence intervals were computed for each SES variable. Multicollinearity for continuous variables was assessed and assumed not to be present if the tolerance value was >0.1 and the variance inflation factor <10 [ctor <10 . Pairwisctor <10 . For exactor <10 . Howeverrd stage (model 3-core-2 model), we additionally adjusted for the effects of body mass index (BMI) (continuous variables), urbanicity , family history of breast cancer (FHBC) (yes and no), alcohol consumption (yes and no), total physical activity (PA) (tertiles). In the 4th stage (model 4) mutual adjustments for other composite SES variables were done. This order of variable adjustments was maintained for SEI (except for the 4th stage which was not applicable) for consistency purpose. Model goodness of fit was checked using the Hosmer and Lemeshow test, as well as assessment of residuals .The relevant explanatory variables were selected based on the existing literature . They weWe explored the modifying effects of menopausal status and age (<50 and ≥50yrs) on SES (based on SEI) using a stratified analysis. All reported p values were based on likelihood ratio tests. Throughout p <0.05 (two-sided) was considered statistically significant. Sensitivity analyses restricted to (1) participants resident within the geographic boundaries of Lagos and Abuja, (2) cases diagnosed within 12 months, (3) controls (patients/visitors) seen in the ophthalmology department were carried out to determine if the excluded participants affected the models substantially.Ethical consideration: the study protocol and data collection instruments were approved by the Ethics Committees of the five participating hospitals  described earlier as well as those of Newcastle University, United Kingdom (1031/2016) and Lagos State Health Services Commission, Lagos, Nigeria (LSHSC/2222/Vol.XIX/48). Informed consent was obtained in writing from all participants using a consent form specifically prepared for the purpose. In the case of the aged and illiterate participants, it was obtained by proxy through a relative they trusted and designated to act on their behalf. The questionnaires did not carry the name of the patients nor any other information capable of identifying them. Unique identification codes were generated for each participant.A total of 372 cases and 403 controls were recruited . The cooThe multivariable analysis shows a decreasing trend in breast cancer risk as personal educational attainment increased . The estAnnex 1) conducted showed consistency with the results shown in There was also evidence of decreasing risk of breast cancer as personal income and husband´s income, increased . The linAnnex 2). Occupational status was not significantly associated with a reduced risk of breast cancer. Measurements based on husband´s SES were not independently associated with risk of breast cancer.This study found that a reduced risk of breast cancer was associated with higher personal educational attainment, income, wealth and socio-economic index after adjusting for other explanatory variables. The association was only partially accounted for by other traditional risk factors especially age, menopausal status, age at first birth, BMI, physical activity, and family history of breast cancer  might be influenced by the SES measures being investigated.The consistency of our findings with the case control study in the USA  and the In addition to the potential role of stage at diagnosis and oestrogen receptor status distribution, our findings could be potentially explained by the fact that women of high socio-economic status tend to have a higher-level of awareness which increases their capacity to reduce exposures to other breast cancer-predisposing factors such as physical inactivity, alcohol consumption (which we adjusted for) and postmenopausal obesity (which we did not have separate information on) ,48-50. TThe stronger role of income compared to other SES measures in predicting breast cancer emphasises its stronger role in health protection in low socio-economic settings compared to observations in high income countries where education has been identified as playing a greater role ,53. IncoOur study is expected not only to generate discussion (e.g. to rethink and broaden preventive policies tailored towards the peculiarities in sub-Saharan African countries), but also to suggest the need to consider the socio-economic empowerment of women through improved educational and income/ wealth creation opportunities (mostly targeted at women of low SES) as part of breast cancer preventive strategy in Nigeria. As our findings suggest, socio-economic status of women in this context cannot be substituted with those of their husbands. Alternatively, in the short term, the cost of screening, diagnoses and treatment of breast cancer could be subsidised alongside awareness intervention targeted at women of low SES. This will encourage early presentation, improve health seeking behaviour and reduce the incidence of advanced stage invasive breast cancers associated with low SES. These recommendations, however, should be implemented bearing in mind the potential breast cancer risk associated with high SES as has been reported in HIC. All the same, given the discrepancy with the findings of other previous studies, we recommend a confirmation of the findings based on more methodologically robust hypothesis-driven studies where all relevant SES indicators, confounders and mediators are considered at the design stage.Annex 4, Annex 4 (suite) and Annex 5). Interestingly, we observed similarities in their distributions. We also observed a similarity between the distribution of the educational profile of our controls and that reported in a previous population-based case-control study in Nigeria [Our study is the first to explore the relationship between SES and risk of breast cancer in Africa based on a range of individual-level SES measures including education, income, occupation, and wealth index which were selected a priori. We adjusted for several explanatory variables  which were not accounted for in previous studies. Nevertheless, our study has limitations. Breast cancer patients of high SES might seek treatment overseas . That could create the potential for overrepresentation of women of high SES among our controls. Hence, giving the impression that high SES is protective. While we have no data on breast cancer patients who might seek treatment overseas, the preference for private hospital visits has been reported among ophthalmology patients (controls) of high SES as well . Moreove Nigeria . While tThis study shows a strong association between higher SES and lower breast cancer risk among Nigerian women. The findings contrast predominant observations in high income countries and indicate the need for preventive policies based on local experience. While we recommend that the findings be confirmed in future studies, it suggests the need to consider socio-economic improvement of women as part of breast cancer prevention in Nigeria alongside intervention to educate lower SES women about breast cancer risk factors and need to present early to health services (and providing access to facilities for these women).Most studies especially in high income countries (HIC) have shown that high socio-economic status is associated with an increased risk of breast cancer;Among populations with predominantly high risk or advance metastatic breast cancer, a few studies in high income countries have shown that low socio-economic status was associated with an increased risk of breast cancer;The findings on the relationship between socio-economic status and breast cancer risk in sub-Saharan Africa based on the available studies have been inconsistent.Our study is the first African study to explore the relationship between socio-economic status and the risk of breast cancer based on multiple socio-economic measures-occupational status, educational attainment, income, wealth index and socio-economic index;The socio-economic status of women cannot effectively be substituted with those of their husbands/partners with respect to any socio-economic intervention towards the prevention of breast cancer in Nigeria;Our study (subject to confirmation) might query the assumption that high socio-economic status increases the risk of breast cancer in Nigeria (and other sub-Saharan African countries) similar to the experience in high income countries. Hence, the study will provide a basis for more investigations on the topic.


Is the concurrent use of tamoxifen and a direct oral anticoagulant (DOAC) associated with important drug-drug interactions and an increased risk of hemorrhage?In this large population-based cohort study including 4753 adult patients with breast cancer, tamoxifen combined with a DOAC was not associated with a higher risk of major hemorrhage requiring an emergency department visit or hospitalization compared with the combination of an aromatase inhibitor and a DOAC.These findings suggest that among DOAC users, the concurrent use of tamoxifen is not associated with a higher risk of hemorrhage compared with concurrent use of aromatase inhibitors. This cohort study evaluates the risk of hemorrhage requiring hospitalization or emergency department visits in patients with breast cancer taking direct oral anticoagulants (DOACs) concurrently with tamoxifen compared with an aromatase inhibitor. Tamoxifen is commonly used as adjuvant therapy in breast cancer and is proposed to interfere with cytochrome P450 enzyme and P-glycoprotein pathways. Concurrent use with direct oral anticoagulants (DOACs) poses the threat of a potentially dangerous drug-drug interaction by leading to an increase in hemorrhage risk.To assess the risk of hemorrhage in patients with breast cancer coprescribed a DOAC and tamoxifen compared with a DOAC and an aromatase inhibitor (AI).This population-based, retrospective cohort study was conducted among adults aged 66 years or older who were prescribed tamoxifen (compared with an AI) concurrently with a DOAC in Ontario, Canada, between June 23, 2009, and November 30, 2020, and followed up until December 31, 2020.Concurrent prescription of a DOAC and tamoxifen compared with a DOAC and an AI.The primary outcome was major hemorrhage requiring an emergency department visit or hospitalization after prescription. Overlap weighted Cox proportional hazards models, accounting for multiple covariates, were used to assess the association between hemorrhage and tamoxifen or AI use with a DOAC.Among a total of 4753 patients , 1179 (24.8%) were prescribed tamoxifen, and 3574 (75.2%) were prescribed an AI. Rivaroxaban (2530 [53.2%]) and apixaban (1665 [35.0%]) were the most frequently used DOACs. Patients taking AIs were younger than patients taking tamoxifen , with higher Charlson Comorbidity Index  and more advanced cancer stage . During a median follow-up of 166 days , tamoxifen was not associated with a higher risk of major hemorrhage (29 of 1179 [2.5%]) compared with an AI (119 of 3574 [3.3%]) when combined with a DOAC . These results were similar in additional analyses using a more liberal definition of hemorrhage, accounting for kidney function, limiting follow-up to 90 days, stratifying by incident and prevalent DOAC users, and accounting for cancer duration and the competing risk of death.In this cohort study, findings suggest that among DOAC users, the concurrent use of tamoxifen was not associated with a higher risk of hemorrhage compared with the concurrent use of an AI. These findings should directly inform prescribers regarding the apparent safety of concurrent DOAC and tamoxifen use. Patients with cancer are at a 12-fold higher risk of VTE compared with those without cancer, and this risk increases to 23-fold with cancer therapy.9 Direct oral anticoagulants are substrates of 2 main metabolic pathways: P-glycoprotein (P-gp) cell transporters and cytochrome P450 enzyme (CYP3A4) in the liver.10 Edoxaban and dabigatran are involved in the P-gp pathway, whereas apixaban and rivaroxaban are involved in both. Concomitant medications that inhibit P-gp and/or CYP3A4 pathways can lead to higher DOAC concentrations and a heightened risk of hemorrhage, largely based on in vitro pharmacokinetic data.12 Major international guidelines, product monographs, and consensus statements suggest caution when using DOACs with potentially strong interfering drugs in patients with cancer.8 However, whether this results in clinically relevant bleeding events remains largely unknown.Direct oral anticoagulants (DOACs) are becoming the preferred anticoagulant for patients with cancer for the prevention and treatment of thromboembolism.13 It is associated with a heightened risk of thromboembolic events 14 and a 2-fold risk of AF; thus, patients with breast cancer commonly use anticoagulation therapy.16 Tamoxifen, used for hormone receptor–positive breast cancer, is reported as an inhibitor in the CYP3A4 and P-gp pathways,19 posing a possible drug-drug interaction (DDI) with DOACs and heightened bleeding risk.20 Because clinical evidence of this proposed drug interaction is limited, we evaluated the risk of hemorrhage requiring hospitalization or emergency department visits in patients with breast cancer taking DOACs with tamoxifen compared with the concurrent use of DOACs and an aromatase inhibitor (AI), an active comparator that is also used to treat hormone receptor–positive breast cancer but is not involved in CYP3A4 or P-gp pathways.Breast cancer is the most common nonskin cancer in women, accounting for 25% of new female cancer cases in 2020.21 Records were linked to other health administrative databases that were used to capture the occurrence of major bleeding or thrombotic events. Hospitalization data were obtained from the Discharge Abstract Database, which contains clinical and demographic data. Emergency department visits were identified through the National Ambulatory Care Reporting System. The Ontario Cancer Registry, which captures more than 95% of Ontario pathology reports, was used to identify individuals who received a diagnosis of breast cancer.22 These data sets were linked using unique encoded identifiers and analyzed at ICES. The use of ICES data was authorized under section 45 of Ontario’s Personal Health Information Protection Act,23 and additional review by the ethics board was not required. All data used were deidentified, and patient informed consent was waived as per the Ontario Ministry of Health. We report our findings according to the recommended Reporting of Studies Conducted Using Observational Routinely Collected Health Data (RECORD) statement and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.In this population-based retrospective cohort study, we used deidentified linked electronic health care databases held in ICES, an independent, nonprofit research organization that houses multiple linked databases with population-based health and social data in Ontario  received chronic dialysis or had a kidney transplant before the index date; (8) had an index date and stop date on the same day; or (9) switched tamoxifen or AIs within 1 year before the index date  who had filled an outpatient prescription for a DOAC  and a cancer drug of interest   in patients receiving a concurrent DOAC and tamoxifen compared with a concurrent DOAC and an AI. Confounders considered included age; sex; index year; income; residence in a long-term care facility; rural residence; previous hemorrhage; comorbidities, such as history of hypertension, diabetes, stroke or transient ischemic attacks, AF, myocardial infarction, heart failure, coronary artery disease, angina, coronary artery bypass graft surgery, percutaneous coronary intervention, acute coronary syndrome, peripheral vascular disease, VTE, liver disease, or chronic kidney disease; Charlson Comorbidity IndexInternational Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10), codes in the Canadian Institute for Health Information Discharge Abstract Database and National Ambulatory Care Reporting System , neighborhood-level income quintile (16 [0.3%] missing), and cancer stage (381 [8.0%] missing) were imputed 5 times and incorporated in the modeling. After assessing the stability of the results across imputations, the first imputation was used for graphing  values were calculated for variables with continuous distributions , and frequencies and proportions for categorical variables. Standardized differences were used to compare characteristics between groups, by describing differences between group means relative to the pooled SD, and a significant difference was considered to be greater than 0.100.We conducted several additional analyses to evaluate for the consistency of our findings. First, we restricted analyses to those with an estimated glomerular filtration rate (eGFR) measure and further added eGFR in our models. Second, we limited our outcome ascertainment window to the first 90 days after concurrent prescription. Third, we stratified by new DOAC users  vs prevalent DOAC users  because the risk of hemorrhage may differ. Fourth, we adjusted our models for duration from cancer diagnosis. Fifth, we examined death as a competing risk. Last, we assessed for residual confounding by using a composite of cholecystitis, diverticulitis, and appendicitis as negative dummy outcomes, for which we expected no association with drug use , among a total of 539 366 patients prescribed DOACs, 4753 who were 66 years or older had a diagnosis of breast cancer and received tamoxifen or an AI. Of these, 4679 patients (98.4%) were women, and 74 patients (1.6%) were men; the mean (SD) age was 77.4 (7.4) years. Race and ethnicity data were not available in the database so could not be included in the analysis. In this cohort, 1179 patients received tamoxifen, and 3574 received an AI . Prescriptions for DOACs included rivaroxaban for 2530 patients (53.2%), apixaban for 1665 patients (35.0%), dabigatran for 502 patients (10.6%), and edoxaban for 56 patients (1.2%) .During a median follow-up of 166 days , a total of 148 patients (3.1%) had major hemorrhage events, corresponding to 29.2  per 1000 person-years: 131 of these (88.5%) had GI tract bleeding and 17 (11.5%) had brain bleeding. The risk of major hemorrhage while receiving a DOAC was not higher with concurrent tamoxifen  compared with a concurrent AI . This was consistent in weighted models  . When weTamoxifen was not associated with a higher hemorrhage risk in several additional analyses, including accounting for eGFR, limiting the follow-up window to 90 days, accounting for incident and prevalent DOAC users, and accounting for cancer duration and the competing risk of death . No asso19 In this population-level study of older adults (≥66 years) with breast cancer, we detected no evidence of a higher hemorrhage risk with concurrent use of a DOAC and tamoxifen compared with an AI. The results were consistent when we used a more liberal definition of hemorrhage, restricting to those with eGFR measures, limiting follow-up duration to the first 90 days, stratifying by start of tamoxifen or AIs first or a DOAC first, considering duration from cancer diagnosis, and using death as a competing risk. These findings suggest that concerns of a higher risk of clinically relevant hemorrhage with coadministration of tamoxifen and a DOAC for patients with breast cancer are unwarranted and should not influence DOAC use when indicated.For individuals with breast cancer, concurrent use of tamoxifen with DOACs was postulated to increase DOAC levels and lead to an elevated risk of hemorrhage based on the report of tamoxifen’s pharmacokinetic data.32 were performed in a limited number of participants and excluded those patients receiving potentially interfering medications, thereby limiting the ability to detect important clinical effects of DDI. In this regard, large administrative database studies are ideally suited to investigate adverse drug reactions as part of postmarketing surveillance and often inform safe prescribing practices. Tamoxifen is reported as an inhibitor of CYP3A4 and P-gp pathways,33 leading to a potentially higher risk of hemorrhage when combined with DOACs. However, limited clinical data exist regarding outcomes in patients with breast cancer taking concurrent DOACs and hormonal agents. A small retrospective study of 48 patients with breast cancer receiving adjuvant endocrine therapy (50% tamoxifen and 50% AI) and DOACs  for AF reported 3 gastrointestinal tract hemorrhages, all in individuals receiving tamoxifen plus rivaroxaban.20 This study raised possible concerns of a clinically relevant DDI, which could alter prescription practices such as empirical change or avoidance of certain anticoagulants or anticancer therapies, as recommended by major guidelines or guidance statements.33 Unnecessary switching to alternate anticoagulants could be detrimental to patients owing to the increased burden with low-molecular-weight heparin injections or frequent laboratory monitoring with vitamin K antagonists and decreased persistence.34 In addition, hemorrhage risk concerns may lead to empirical underdosing of DOACs and an increased risk of thromboembolic complications.35 Our study showed no clinical evidence of a higher risk of bleeding with concurrent use of a DOAC and tamoxifen relative to an AI, reassuring prescribers of the safety of their use and dismissing the need to switch either DOAC or hormonal agents because of concerns related to hemorrhage. Our findings are consistent with another study in patients with cancer and AF,36 which reported no increased risk of major bleeding when comparing 147 users of tamoxifen plus a DOAC with users of a DOAC only . Compared with that study,36 our present study includes a much larger number of concurrent tamoxifen and DOAC users (n = 1179), used AIs as active comparators, and included patients with breast cancer only to allow comparison within a more homogeneous population.Randomized clinical trials to date21 and little emigration from the province (<1% per year).37 Our findings remain consistent across multiple sensitivity analyses. Our 3.1% rate of major hemorrhage events during a median follow-up of 166 days is comparable to reported rates from meta-analyses of randomized clinical trials of cancer-associated thrombosis and from the international registry of patients with venous thromboembolism.39 In addition, our study revealed that hemorrhage should not be underappreciated in this population because the major hemorrhage rate of 29.2 per 1000 person-years was not low but was similar to rates for patients with severe kidney dysfunction (eGFR <15 mL/min/1.73 m2), a known population with a high risk of hemorrhage.40To our knowledge, this is the largest study of its kind to investigate the potential DDIs in patients with breast cancer taking a concurrent DOAC and hormonal agents. Our study can provide reassurance to clinicians and inform safe prescription decisions about concurrent use of a DOAC and tamoxifen. We included all patients in Ontario who met eligibility criteria, which provides a high degree of external validity. In addition, Ontario’s health care databases have several strengths, including extremely well-recorded prescription drug use43 Nevertheless, differences in baseline characteristics were noted between tamoxifen and AI users that were well balanced after weighting , given the later approval and less frequent use in Ontario. The causes of death are not available in the database. Last, because this is administrative database research and only prescription information is available, the actual adherence is unknown and assumed.Our study has limitations. Retrospective observational cohort studies are subject to residual confounding. We attempted to overcome this by demonstrating no difference in the risk for a dummy outcome that serves as a negative control. A further limitation is confounding by treatment indication that we attempted to minimize by comparing tamoxifen and AI users, both common therapies in breast cancer given to similar patient populations.eighting . Our stuIn this population-based cohort study of individuals 66 years or older with breast cancer, the hemorrhage risk was not higher with tamoxifen-DOAC combination compared with AI-DOAC. This is consistent in multiple additional analyses and suggests that concurrent use of tamoxifen and DOACs is safe when clinically indicated.