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Evidence from literature, including the BRIDGES study, indicates that germline protein truncating variants (PTVs) in FANCM confer moderately increased risk of ER-negative and triple-negative breast cancer (TNBC), especially for women with a family history of the disease. Association between FANCM missense variants (MVs) and breast cancer risk has been postulated. In this study, we further used the BRIDGES study to test 689 FANCM MVs for association with breast cancer risk, overall and in ER-negative and TNBC subtypes, in 39,885 cases (7566 selected for family history) and 35,271 controls of European ancestry. Sixteen common MVs were tested individually; the remaining rare 673 MVs were tested by burden analyses considering their position and pathogenicity score. We also conducted a meta-analysis of our results and those from published studies. We did not find evidence for association for any of the 16 variants individually tested. The rare MVs were significantly associated with increased risk of ER-negative breast cancer by burden analysis comparing familial cases to controls (OR = 1.48; 95% CI 1.07-2.04; P = 0.017). Higher ORs were found for the subgroup of MVs located in functional domains or predicted to be pathogenic. The meta-analysis indicated that FANCM MVs overall are associated with breast cancer risk (OR = 1.22; 95% CI 1.08-1.38; P = 0.002). Our results support the definition from previous analyses of FANCM as a moderate-risk breast cancer gene and provide evidence that FANCM MVs could be low/moderate risk factors for ER-negative and TNBC subtypes. Further genetic and functional analyses are necessary to clarify better the increased risks due to FANCM MVs.

DNA methylation marks that are inherited from parents to offspring are known to play a role in cancer risk and could explain part of the familial risk for cancer. We therefore conducted a genome-wide search for heritable methylation marks associated with prostate cancer risk. Peripheral blood DNA methylation was measured for 133 of the 469 members of 25 multiple-case prostate cancer families, using the EPIC array. We used these families to systematically search the genome for methylation marks with Mendelian patterns of inheritance, then we tested the 1,000 most heritable marks for association with prostate cancer risk. After correcting for multiple testing, 41 heritable methylation marks were associated with prostate cancer risk. Separate analyses, based on 869 incident cases and 869 controls from a prospective cohort study, showed that 9 of these marks near the metastable epiallele VTRNA2-1 were also nominally associated with aggressive prostate cancer risk in the population.

BACKGROUND: The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC. METHODS: LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source. RESULTS: LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at menarche, also associated with EOC. The estimated model coefficient for oral contraceptive use and pregnancies were 4.45 times and 12- to 15-fold greater than expected, respectively. LOY was associated with high-grade serous, low-grade serous, endometrioid, and clear cell histotypes (ORs per year increase = 1.054, 1.040, 1.065, and 1.098, respectively) but not mucinous tumors. Estimated coefficients of LOY components were close to expected estimates for high-grade serous but larger than expected for low-grade serous, endometrioid, and clear cell histotypes. CONCLUSIONS: LOY is positively associated with nonmucinous EOC. Differences between estimated and expected model coefficients for LOY components suggest factors beyond ovulation underlie the associations between LOY components and EOC in general and for non-HGSOC.

BACKGROUND: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis. METHODS: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only. FINDINGS: There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10-1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61-0.66), compared with 0.62 (95% CI: 0.59-0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: -0.003 to 0.035). INTERPRETATION: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information. FUNDING: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute (U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden (AMP19-962), and Swedish Department of Health Ministry.

PURPOSE: Women with preeclampsia are more likely to deliver preterm. Reports of inverse associations between preeclampsia and breast cancer risk, and positive associations between preterm birth and breast cancer risk are difficult to reconcile. We investigated the co-occurrence of preeclampsia/gestational hypertension with preterm birth and breast cancer risk using data from the Premenopausal Breast Cancer Collaborative Group. METHODS: Across 6 cohorts, 3096 premenopausal breast cancers were diagnosed among 184,866 parous women. We estimated multivariable hazard ratios (HR) and 95% confidence intervals (CI) for premenopausal breast cancer risk using Cox proportional hazards regression. RESULTS: Overall, preterm birth was not associated (HR 1.02, 95% CI 0.92, 1.14), and preeclampsia was inversely associated (HR 0.86, 95% CI 0.76, 0.99), with premenopausal breast cancer risk. In stratified analyses using data from 3 cohorts, preterm birth associations with breast cancer risk were modified by hypertensive conditions in first pregnancies (P-interaction = 0.09). Preterm birth was positively associated with premenopausal breast cancer in strata of women with preeclampsia or gestational hypertension (HR 1.52, 95% CI: 1.06, 2.18), but not among women with normotensive pregnancy (HR = 1.09, 95% CI: 0.93, 1.28). When stratified by preterm birth, the inverse association with preeclampsia was more apparent, but not statistically different (P-interaction = 0.2), among women who did not deliver preterm (HR = 0.82, 95% CI 0.68, 1.00) than those who did (HR = 1.07, 95% CI 0.73, 1.56). CONCLUSION: Findings support an overall inverse association of preeclampsia history with premenopausal breast cancer risk. Estimates for preterm birth and breast cancer may vary according to other conditions of pregnancy.

BACKGROUND: Previous studies of dietary patterns and pancreatic cancer risk have been inconclusive; we aimed to investigate the association of Mediterranean Diet Score (MDS), Alternative Healthy Eating Index-2010 (AHEI-2010), and Dietary Inflammatory Index (DII®) with risk of pancreatic cancer. METHODS: We used data from the Melbourne Collaborative Cohort Study including 33,690 men and women aged 40-69 years at recruitment in 1990-1994. A total of 258 incident cases of pancreatic cancer was identified over an average of 23.7 years of follow-up. Hazard ratios (HR) were estimated using Cox regression, with age as the underlying time metric, adjusting for potential confounders including sex, height, country of birth, education, socio-economic position, physical activity, energy intake, smoking status, pack-years smoking, years since quitting smoking, and alcohol intake. RESULTS: A healthier diet as assessed by the AHEI-2010 was associated with a lower risk of pancreatic cancer [HRQuartile4 vs Quartile1 = 0.58; 95%CI 0.40 - 0.85; p for trend 0.003]. Weaker but consistent evidence was observed for the other indexes [DII® HRQuartile4 vs Quartile1 = 1.30; 95%CI 0.82 - 2.06; p for trend 0.1], [MDS HRCategory3 vs Category1 = 0.79; 95%CI 0.49 - 1.26; p for trend 0.06]. CONCLUSION: Adherence to a healthier diet, as assessed by the AHEI-2010, may reduce the risk of pancreatic cancer.

Abstract Background Higher levels of time spent sitting (sedentary behavior) contribute to adverse health outcomes, including earlier death. This effect may be modified by other lifestyle factors. We examined the association of television viewing (TV), a common leisure-time sedentary behavior, with all-cause mortality, and whether this is modified by body mass index (BMI), physical activity, smoking, alcohol intake, soft drink consumption, or diet-associated inflammation. Methods Using data from participants in the Melbourne Collaborative Cohort Study, flexible parametric survival models assessed the time-dependent association of self-reported TV time (three categories: < 2 h/day, 2–3 h/day, > 3 h/day) with all-cause mortality. Interaction terms were fitted to test whether there was effect modification of TV time by the other risk factors. Results From 19,570 participants, 4,417 deaths were reported over a median follow up of 14.5 years. More TV time was associated with earlier mortality; however, this relationship diminished with increasing age. The hazard ratio (HR) and 95% confidence interval (95% CI) for > 3 h/day compared with < 2 h/day of TV time was 1.34 (1.16, 1.55) at 70 years, 1.14 (1.04, 1.23) at 80 years, and 0.95 (0.84, 1.06) at 90 years. The TV time/mortality relationship was more evident in participants who were physically inactive (compared with active; p for interaction < 0.01) or had a higher dietary inflammatory index score (compared with a lower score; p for interaction = 0.03). No interactions were detected between TV time and BMI, smoking, alcohol intake, nor soft-drink consumption (all p for interaction&

BACKGROUND: 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. METHODS: 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 (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. RESULTS: 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 C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). CONCLUSION: 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. IMPACT: Our study suggests a limited role of gene-environment interactions in breast cancer risk.

BACKGROUND: Higher levels of time spent sitting (sedentary behavior) contribute to adverse health outcomes, including earlier death. This effect may be modified by other lifestyle factors. We examined the association of television viewing (TV), a common leisure-time sedentary behavior, with all-cause mortality, and whether this is modified by body mass index (BMI), physical activity, smoking, alcohol intake, soft drink consumption, or diet-associated inflammation. METHODS: Using data from participants in the Melbourne Collaborative Cohort Study, flexible parametric survival models assessed the time-dependent association of self-reported TV time (three categories: < 2 h/day, 2-3 h/day, > 3 h/day) with all-cause mortality. Interaction terms were fitted to test whether there was effect modification of TV time by the other risk factors. RESULTS: From 19,570 participants, 4,417 deaths were reported over a median follow up of 14.5 years. More TV time was associated with earlier mortality; however, this relationship diminished with increasing age. The hazard ratio (HR) and 95% confidence interval (95% CI) for > 3 h/day compared with < 2 h/day of TV time was 1.34 (1.16, 1.55) at 70 years, 1.14 (1.04, 1.23) at 80 years, and 0.95 (0.84, 1.06) at 90 years. The TV time/mortality relationship was more evident in participants who were physically inactive (compared with active; p for interaction < 0.01) or had a higher dietary inflammatory index score (compared with a lower score; p for interaction = 0.03). No interactions were detected between TV time and BMI, smoking, alcohol intake, nor soft-drink consumption (all p for interaction > 0.16). CONCLUSIONS: The relationship between TV time and all-cause mortality may change with age. It may also be more pronounced in those who are otherwise inactive or who have a pro-inflammatory diet.

INTRODUCTION: To describe the pattern of the use of advanced radiation therapy (RT) techniques, including intensity-modulated RT (IMRT), volumetric modulated arc therapy (VMAT), and stereotactic body RT (SBRT) for the management of bone metastases (BM), and the associated factors in Victoria. METHODS: We used a population-based cohort of patients from the state-wide Victorian Radiotherapy Minimum Data Set (VRMDS) who received RT for BM between 2012 and 2017. The primary outcome was proportion of RT courses using advanced RT techniques. The Cochran-Armitage test for trend was used to evaluate temporal trend in advanced RT use. Multinomial logistic regression was used to identify factors associated with advanced RT use. RESULTS: A total of 18,158 courses of RT were delivered to 10,956 patients-16,626 (91.6%) courses were 3D conformal RT, 857 (4.7%) IMRT/VMAT and 675 (3.7%) SBRT. There was a sharp increase in IMRT/VMAT use from <1% in 2012-2015, to 10.1% in 2016 and 16.3% in 2017 (P-trend < 0.001). Increase in SBRT use was more gradual, from 1.2% in 2012 to 4.8% in 2016 and 5.5% in 2017 for SBRT (P-trend<0.001). In multivariate analyses, year of RT was the strongest predictor of IMRT/VMAT use (OR = 41; 95%CI = 25-67; P < 0.001, comparing 2012-2013 and 2016-2017). Primary tumour type (prostate cancer) was the strongest predictor of SBRT use (OR = 6.07; 95% CI = 4.19-8.80; P < 0.001). CONCLUSION: Overall, there was increasing trend in the use of advanced RT techniques for BM in Victoria, with a distinct pattern for IMRT/VMAT compared with SBRT - SBRT uptake was more gradual while IMRT/VMAT uptake was abrupt, occurring contemporaneously with Medicare Benefit Scheme funding changes in 2016.

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

INTRODUCTION: To evaluate the proportion of cancer patients who received radiation therapy (RT) within 12 months of cancer diagnosis (RTU12) and identify factors associated with RTU12. METHODS: This is a population-based cohort of individuals with incident cancer, diagnosed between 2013 and 2017 in Victoria. Data linkages were performed between the Victorian Cancer Registry and Victorian Radiotherapy Minimum Dataset. The primary outcome was the proportion of patients who had RTU12. For the three most common cancers (i.e., prostate, breast and lung cancer), the time trend in RTU12 and factors associated with RTU12 were evaluated. RESULTS: The overall RTU12 in our study cohort was 26-20% radical RT and 6% palliative RT. Of the 21,735 men with prostate cancer, RTU12 was 17%, with no significant change over time (P-trend = 0.53). In multivariate analyses, increasing age and lower socioeconomic status were independently associated with higher RTU12 for prostate cancer. Of the 20,883 women with breast cancer, RTU12 was 64%, which increased from 62% in 2013 to 65% in 2017 (P-trend < 0.05). In multivariate analyses, age, socioeconomic status and area of residency were independently associated with RTU12 for breast cancer. Of the 13,093 patients with lung cancer, RTU12 was 42%, with no significant change over time (P-trend = 0.16). In multivariate analyses, younger age, male and lower socioeconomic status were independently associated with higher RTU12. CONCLUSION: In this large population-based state-wide cohort of cancer patients, only 1 in 4 had RT within 12 months of diagnosis. There were marked sociodemographic disparities in RTU12 for prostate, breast and lung cancer patients.

BACKGROUND: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. METHODS: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. RESULTS: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. CONCLUSION: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

BACKGROUND: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

PURPOSE: High-grade disease accounts for ~ 70% of all glioma, and has a high mortality rate. Few modifiable exposures are known to be related to glioma risk or mortality. METHODS: We examined associations between lifetime physical activity and physical activity at different ages (15-18 years, 19-29 years, 30-39 years, last 10 years) with the risk of glioma diagnosis, using data from a hospital-based family case-control study (495 cases; 371 controls). We followed up cases over a median of 25 months to examine whether physical activity was associated with all-cause mortality. Physical activity and potential confounders were assessed by self-administered questionnaire. We examined associations between physical activity (metabolic equivalent [MET]-h/wk) and glioma risk using unconditional logistic regression and with all-cause mortality in cases using Cox regression. RESULTS: We noted a reduced risk of glioma for the highest (≥ 47 MET-h/wk) versus lowest (< 24 METh/wk) category of physical activity for lifetime activity (OR = 0.58, 95% CI: 0.38-0.89) and at 15-18 years (OR = 0.57, 95% CI: 0.39-0.83). We did not observe any association between physical activity and all-cause mortality (HR for lifetime physical activity = 0.91, 95% CI: 0.64-1.29). CONCLUSION: Our findings are consistent with previous research that suggested physical activity during adolescence might be protective against glioma. Engaging in physical activity during adolescence has many health benefits; this health behavior may also offer protection against glioma.

BACKGROUND: To help BRCA1 and 2 mutation carriers make informed decisions regarding use of combined-type oral contraceptive preparation (COCP), absolute risk-benefit estimates are needed for COCP-associated cancer. METHODS: For a hypothetical cohort of 10 000 women, we calculated the increased or decreased cumulative incidence of COCP-associated (breast, ovarian, endometrial) cancer, examining 18 scenarios with differences in duration and timing of COCP use, uptake of prophylactic surgeries, and menopausal hormone therapy. RESULTS: COCP use initially increased breast cancer risk and decreased ovarian and endometrial cancer risk long term. For 10 000 BRCA1 mutation carriers, 10 years of COCP use from age 20 to 30 years resulted in 66 additional COCP-associated cancer cases by the age of 35 years, in addition to 625 cases expected for never users. By the age of 70 years such COCP use resulted in 907 fewer cancer cases than the expected 9093 cases in never users. Triple-negative breast cancer estimates resulted in 196 additional COCP-associated cases by age 40 years, in addition to the 1454 expected. For 10 000 BRCA2 mutation carriers using COCP from age 20 to 30 years, 80 excess cancer cases were estimated by age 40 years in addition to 651 expected cases; by the age of 70 years, we calculated 382 fewer cases compared with the 6156 cases expected. The long-term benefit of COCP use diminished after risk-reducing bilateral salpingo-oophorectomy followed by menopausal hormone therapy use. CONCLUSION: Although COCP use in BRCA1 and BRCA2 mutation carriers initially increases breast, ovarian, and endometrial cancer risk, it strongly decreases lifetime cancer risk. Risk-reducing bilateral salpingo-oophorectomy and menopausal hormone therapy use appear to counteract the long-term COCP-benefit.

IMPORTANCE: Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction. OBJECTIVE: To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies. DESIGN, SETTING, AND PARTICIPANTS: The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021. EXPOSURES: Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53. MAIN OUTCOMES AND MEASURES: The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes. RESULTS: The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subt

BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

PURPOSE: Seropositivity for the HPV16-E6 oncoprotein is a promising marker for early detection of oropharyngeal cancer (OPC), but the absolute risk of OPC after a positive or negative test is unknown. METHODS: We constructed an OPC risk prediction model that integrates (1) relative odds of OPC for HPV16-E6 serostatus and cigarette smoking from the human papillomavirus (HPV) Cancer Cohort Consortium (HPVC3), (2) US population risk factor data from the National Health Interview Survey, and (3) US sex-specific population rates of OPC and mortality. RESULTS: The nine HPVC3 cohorts included 365 participants with OPC with up to 10 years between blood draw and diagnosis and 5,794 controls. The estimated 10-year OPC risk for HPV16-E6 seropositive males at age 50 years was 17.4% (95% CI, 12.4 to 28.6) and at age 60 years was 27.1% (95% CI, 19.2 to 45.4). Corresponding 5-year risk estimates were 7.3% and 14.4%, respectively. For HPV16-E6 seropositive females, 10-year risk estimates were 3.6% (95% CI, 2.5 to 5.9) at age 50 years and 5.5% (95% CI, 3.8 to 9.2) at age 60 years and 5-year risk estimates were 1.5% and 2.7%, respectively. Over 30 years, after a seropositive result at age 50 years, an estimated 49.9% of males and 13.3% of females would develop OPC. By contrast, 10-year risks among HPV16-E6 seronegative people were very low, ranging from 0.01% to 0.25% depending on age, sex, and smoking status. CONCLUSION: We estimate that a substantial proportion of HPV16-E6 seropositive individuals will develop OPC, with 10-year risks of 17%-27% for males and 4%-6% for females age 50-60 years in the United States. This high level of risk may warrant periodic, minimally invasive surveillance after a positive HPV16-E6 serology test, particularly for males in high-incidence regions. However, an appropriate clinical protocol for surveillance remains to be established.

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.

BACKGROUND: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). METHOD: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. RESULTS: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. CONCLUSION: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

BACKGROUND: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. METHODS: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. RESULTS: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. CONCLUSIONS: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

BACKGROUND: Mechanisms for how Helicobacter pylori infection affects risk of gastroesophageal reflux disease (GERD) and Barrett's esophagus are incompletely understood and might differ by sex. METHODS: In a case-control study nested in the Melbourne Collaborative Cohort Study with 425 GERD cases and 169 Barrett's esophagus cases (identified at 2007-2010 follow-up), we estimated sex-specific odds ratios for participants who were H. pylori seronegative versus seropositive at baseline (1990-1994). To explore possible mechanisms, we (i) compared patterns of H. pylori-induced gastritis by sex using serum pepsinogen-I and gastrin-17 data and (ii) quantified the effect of H. pylori seronegativity on Barrett's esophagus mediated by GERD using causal mediation analysis. RESULTS: For men, H. pylori seronegativity was associated with 1.69-fold [95% confidence interval (CI), 1.03-2.75] and 2.28-fold (95% CI, 1.27-4.12) higher odds of GERD and Barrett's esophagus, respectively. No association was observed for women. H. pylori-induced atrophic antral gastritis was more common in men (68%) than in women (56%; P = 0.015). For men, 5 of the 15 per 1,000 excess Barrett's esophagus risk from being seronegative were mediated by GERD. CONCLUSIONS: Men, but not women, who were H. pylori seronegative had increased risks of GERD and Barrett's esophagus. A possible explanation might be sex differences in patterns of H. pylori-induced atrophic antral gastritis, which could lead to less erosive reflux for men. Evidence of GERD mediating the effect of H. pylori on Barrett's esophagus risk among men supports this proposed mechanism. IMPACT: The findings highlight the importance of investigating sex differences in the effect of H. pylori on risk of GERD and Barrett's esophagus in future studies.

BACKGROUND: DNA methylation in blood may reflect adverse exposures accumulated over the lifetime and could therefore provide potential improvements in the prediction of cancer risk. A substantial body of research has shown associations between epigenetic aging and risk of disease, including cancer. Here we aimed to study epigenetic measures of aging and lifestyle-related factors in association with risk of breast cancer. METHODS: Using data from four prospective case-control studies nested in three cohorts of European ancestry participants, including a total of 1,655 breast cancer cases, we calculated three methylation-based measures of lifestyle factors (body mass index [BMI], tobacco smoking and alcohol consumption) and seven measures of epigenetic aging (Horvath-based, Hannum-based, PhenoAge and GrimAge). All measures were regression-adjusted for their respective risk factors and expressed per standard deviation (SD). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional or unconditional logistic regression and pooled using fixed-effects meta-analysis. Subgroup analyses were conducted by age at blood draw, time from blood sample to diagnosis, oestrogen receptor-positivity status and tumour stage. RESULTS: None of the measures of epigenetic aging were associated with risk of breast cancer in the pooled analysis: Horvath 'age acceleration' (AA): OR per SD = 1.02, 95%CI: 0.95-1.10; AA-Hannum: OR = 1.03, 95%CI:0.95-1.12; PhenoAge: OR = 1.01, 95%CI: 0.94-1.09 and GrimAge: OR = 1.03, 95%CI: 0.94-1.12, in models adjusting for white blood cell proportions, body mass index, smoking and alcohol consumption. The BMI-adjusted predictor of BMI was associated with breast cancer risk, OR per SD = 1.09, 95%CI: 1.01-1.17. The results for the alcohol and smoking methylation-based predictors were consistent with a null association. Risk did not appear to substantially vary by age at blood draw, time to diagnosis or tumour characteristics. CONCLUSION

INTRODUCTION: We aim to evaluate the use of different whole brain radiation therapy (WBRT) fractionation schedules for brain metastases (BM) in Victoria, and the factors associated with it. METHODS: This is a population-based cohort of patients who received radiation therapy for BM between 2012 and 2017, as captured in the Victorian Radiotherapy Minimum Dataset. We excluded patients with primary brain tumour and those who had 'prophylactic' intent treatment. The Cochran-Armitage test was used to evaluate changing trend in WBRT fractionation. Multivariate multinomial logistic regressions were used to evaluate factors associated with WBRT fractionation. RESULTS: Of the 3111 patients who had WBRT, 1048 (45%), 1291 (42%) and 312 (13%) had ≤5, 6-10 and >10 fractions WBRT respectively. There was progressive increase in ≤5 fractions WBRT use over time, from 37% in 2012 to 50% in 2017 (P-trend < 0.001). In multivariate analyses, increasing age, patients with gastrointestinal cancer, patients living in remote/regional areas and more recent treatment were associated with the use of shorter WBRT fractionation (≤5 fractions), while patients who had WBRT plus stereotactic radiosurgery, and those treated in private institutions were associated with the use of prolonged WBRT fractionation (≥6 fractions). Three hundred eighty-nine (13%) patients died within 30 days of WBRT, of which 241 (64%), 119 (32%) and 17 (5%) had ≤5, 6-10 and > 10 fractions WBRT respectively. CONCLUSION: We observed large variations in WBRT fractionation that are associated with patient, tumour, treatment and institutional factors. It is important to continuously monitor and benchmark our practice in order to reduce potentially unwarranted variations.

Limited evidence exists on the link between inflammation and epigenetic aging. We aimed to (a) assess the cross-sectional and prospective associations of 22 inflammation-related plasma markers and a signature of inflammaging with epigenetic aging and (b) determine whether epigenetic aging and inflammaging are independently associated with mortality. Blood samples from 940 participants in the Melbourne Collaborative Cohort Study collected at baseline (1990-1994) and follow-up (2003-2007) were assayed for DNA methylation and 22 inflammation-related markers, including well-established markers (eg, interleukins and C-reactive protein) and metabolites of the tryptophan-kynurenine pathway. Four measures of epigenetic aging (PhenoAge, GrimAge, DunedinPoAm, and Zhang) and a signature of inflammaging were considered, adjusted for age, and transformed to Z scores. Associations were assessed using linear regression, and mortality hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated using Cox regression. Cross-sectionally, most inflammation-related markers were associated with epigenetic aging measures, although with generally modest effect sizes (regression coefficients per SD ≤ 0.26) and explaining altogether between 1% and 11% of their variation. Prospectively, baseline inflammation-related markers were not, or only weakly, associated with epigenetic aging after 11 years of follow-up. Epigenetic aging and inflammaging were strongly and independently associated with mortality, for example, inflammaging: HR = 1.41, 95% CI = 1.27-1.56, p = 2 × 10-10, which was only slightly attenuated after adjustment for 4 epigenetic aging measures: HR = 1.35, 95% CI = 1.22-1.51, p = 7 × 10-9). Although cross-sectionally associated with epigenetic aging, inflammation-related markers accounted for a modest proportion of its variation. Inflammaging and epigenetic aging are essentially nonoverlapping markers of biological aging and may be used jointly to predict mortality.

Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene-environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case-control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 (GSTA1; p = 4.3E-4), Tonsuko Like, DNA Repair Protein (TONSL; p = 4.3E-4), and Aspartylglucosaminidase (AGA: p = 4.5E-4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.

BACKGROUND: Reproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear. METHODS: Analyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided. RESULTS: Compared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all

We examined associations between sex-specific alcohol intake trajectories and alcohol-related cancer risk using data from 22 756 women and 15 701 men aged 40 to 69 years at baseline in the Melbourne Collaborative Cohort Study. Alcohol intake for 10-year periods from age 20 until the decade encompassing recruitment, calculated using recalled beverage-specific frequency and quantity, was used to estimate group-based sex-specific intake trajectories. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for primary invasive alcohol-related cancer (upper aerodigestive tract, breast, liver and colorectum). Three distinct alcohol intake trajectories for women (lifetime abstention, stable light, increasing moderate) and six for men (lifetime abstention, stable light, stable moderate, increasing heavy, early decreasing heavy, late decreasing heavy) were identified. 2303 incident alcohol-related cancers were diagnosed during 485 525 person-years in women and 789 during 303 218 person-years in men. For men, compared with lifetime abstention, heavy intake (mean ≥ 60 g/day) at age 20 to 39 followed by either an early (from age 40 to 49) (early decreasing heavy; HR = 1.75, 95% CI: 1.25-2.44) or late decrease (from age 60 to 69) (late decreasing heavy; HR = 1.94, 95% CI: 1.28-2.93), and moderate intake (mean <60 g/day) at age 20 to 39 increasing to heavy intake in middle-age (increasing heavy; HR = 1.45, 95% CI: 1.06-1.97) were associated with increased risk of alcohol-related cancer. For women, compared with lifetime abstention, increasing intake from age 20 (increasing moderate) was associated with increased alcohol-related cancer risk (HR = 1.25, 95% CI: 1.06-1.48). Similar associations were observed for colorectal (men) and breast cancer. Heavy drinking during early adulthood might increase cancer risk later in life.

OBJECTIVES: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics. METHODS: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity. RESULTS: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger). CONCLUSION: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer r

BACKGROUND: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. METHODS: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2- or 3-degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. RESULTS: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2-degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10-4). CONCLUSION: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.

AIM: To evaluate the patterns of use of different radiation therapy (RT) fractionation for multiple myeloma (MM) bone disease. METHODS: This is a population-based cohort of patients with MM who had RT between 2012 and 2017 as captured in the statewide Victorian Radiotherapy Minimum Data Set in Australia. Data linkage was performed to identify subsets of RT delivered within 3 months of death. RT fractionation was classified into four groups: single-fraction (SFRT), 2-5, 6-10, and > 10 fractions. Changes in RT fractionation use over time were evaluated with the Cochran-Armitage test for trend. Factors associated with RT fractionation were evaluated using multivariate logistic regressions. RESULTS: Nine hundred and sixty-seven courses of RT were delivered in 623 patients. The proportion of SFRT, 2-5, 6-10 and > 10 fractions RT was 18%, 47%, 28%, and 7%, respectively. There was an increase in the use of 2-5 fractions, from 48% in 2012 to 60% in 2017 (p-trend < .001), with corresponding decrease in the use of 6-10 fractions, from 26% in 2012 to 20% in 2017 (p-trend = .003). Nine percent (40/430) of RT courses at private institutions were SFRT, compared to 25% (135/537) in public institutions (p < .001). In multivariate analyses, treatment in private institution was the strongest predictor of multifraction RT use. SFRT use was more common closer to the end of life-18%, 14%, and 33% of RT within 2-3, 1-2, < 1 month of death, respectively. CONCLUSION: There is increasing use of shorter course RT (2-5 fractions) for MM over time. SFRT use remains low, with large variation in practice.

Epidemiologic research suggests that physical activity is associated with a reduced risk of breast cancer, but the causal nature of this link is not clear. Investigating mechanistic pathways can provide evidence of biological plausibility and improve causal inference. This project will examine three putative pathways (sex steroid hormones, insulin signaling, and inflammation) in a series of two-stage systematic reviews. Stage 1 used Text Mining for Mechanism Prioritisation (TeMMPo) to identify and prioritize relevant biological intermediates. Stage 2 will systematically review the findings from studies of (i) physical activity and intermediates and (ii) intermediates and breast cancer. Ovid MEDLINE, EMBASE, and SPORTDiscus will be searched using a combination of subject headings and free-text terms. Human intervention and prospective, observational studies will be eligible for inclusion. Meta-analysis will be performed where possible. Risk of bias will be assessed using the Cochrane Collaboration tool, or the ROBINS-I or ROBINS-E tool, depending on study type. Strength of evidence will be assessed using the GRADE system. In addition to synthesizing the mechanistic evidence that links physical activity with breast cancer risk, this project may also identify priority areas for future research and help inform the design and implementation of physical activity interventions.See related reviews by Swain et al., p. 16 and Drummond et al., p. 28.

OBJECTIVE: To examine the socio-economic and ethnocultural characteristics of geographical areas that may influence variation in breast cancer screening participation. METHODS: In a cross-sectional analysis breast cancer screening participation for statistical areas in Victoria, Australia (2015-2017) was linked with data from the 2016 Australian Census. We selected four commonly used area-level measures of socio-economic status from the Australian Census (i) income (ii) educational level (iii) occupational status and (iv) employment profile. To assess the ethnocultural characteristics of statistical areas we used the Census measures (i) country of birth (ii) language spoken at home (iii) fluency in English (iv) religion and (v) the proportion of immigrants in an area, together with their recency of migration. RESULTS: All the selected measures were related to screening participation. There was a high degree of association both within and between socio-economic and ethnocultural characteristics of areas as they relate to screening. Ethnocultural characteristics alone accounted for most of the explained geographical disparity in screening participation. CONCLUSIONS: Geographical disparities in breast cancer screening participation may be due to ethnocultural factors that are confounded with socio-economic factors.

Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene-environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10-14), ~0.6% (P = 2 × 10-7), and ~8.7% (P = 7 × 10-87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: -0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: -0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.