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Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Abstract Recent research suggests higher circulating lymphocyte counts may protect against colorectal cancer (CRC). However, the role of specific lymphocyte subtypes and activation states remain unclear. CD4+ T cells—a highly dynamic lymphocyte subtype—undergo gene expression changes upon activation that are critical to their effector function. Previous studies using bulk tissue have limited our understanding of their role in CRC risk to static associations. We applied Mendelian randomization (MR) and genetic colocalisation to evaluate causal relationships of gene expression on CRC risk across multiple CD4+ T cell subtypes and activation states. Genetic proxies were obtained from single-cell transcriptomic data, allowing us to investigate the causal effect of expression of 1,805 genes across CD4+ T cell activation states on CRC risk (78,473 cases; 107,143 controls). Analyses were stratified by CRC anatomical subsites and sex, with sensitivity analyses assessing whether the observed effect estimates were likely to be CD4+ T cell-specific. We identified 6 genes—FADS2, FHL3, HLA-DRB1, HLA-DRB5, RPL28, and TMEM258—with strong evidence for a causal role in CRC development (FDR-P &lt; 0.05; colocalisation H4 &gt; 0.8). Causal estimates varied by CD4+ T cell subtype, activation state, CRC subsite and sex. However, many of genetic proxies used to instrument gene expression in CD4+ T cells also act as eQTLs in other tissues, highlighting the challenges of using genetic proxies to instrument tissue-specific expression changes. We demonstrate the importance of capturing the dynamic nature of CD4+ T cells in understanding CRC risk, and prioritize genes for further investigation in cancer prevention.

Abstract Background Physical activity (PA) is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene–PA interaction analysis. Methods Using logistic regression and two-step and joint tests, we analyzed interactions between common genetic variants across the genome and PA in relation to CRC risk. Self-reported PA levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk) and as study- and sex-specific quartiles of activity. Results PA had an overall protective effect on CRC (OR [active vs. inactive] = 0.85; 95%CI = 0.81–0.90). The two-step GxE method identified an interaction between rs4779584, an intergenic variant near the GREM1 and SCG5 genes, and PA for CRC risk (p-interaction = 2.6×10 − 8 ). Stratification by genotype at this locus showed a significant reduction in CRC risk by 20% in active vs. inactive participants with the CC genotype (OR = 0.80; 95%CI = 0.75–0.85), but no significant PA–CRC association among CT or TT carriers. When PA was modeled as quartiles, the 1-d.f. GxE test identified that rs56906466, an intergenic variant near the KCNG1 gene, modified the association between PA and CRC (p-interaction = 3.5×10 − 8 ). Stratification at this locus showed that increase in PA (highest vs. lowest quartile) was associated with a lower CRC risk solely among TT carriers (OR = 0.77; 95%CI = 0.72–0.82). Conclusions In summary, we identified two genetic variants that modified the association between PA and CRC risk. One of them, related to GREM1 and SCG5 , suggests that the bone morphogenetic protein (BMP)-related, inflammatory, and/or insulin signaling pathways may be associated with the protective influence of PA on colorectal carcinogenesis.

ImportanceEtiologic heterogeneity in breast carcinogenesis needs to be well characterized for targeted prevention. Associations between menopausal hormonal therapy (MHT) and oral contraceptive (OC) use and breast cancer intrinsic-like subtypes are not well understood.ObjectiveTo examine whether exogenous hormone use is differentially associated with breast cancer subtypes and to evaluate heterogeneity by intrinsic-like subtypes.Design, Setting, and ParticipantsThis study pooled data from 31 nested and population-based case-control studies involved in the Breast Cancer Association Consortium. The study population included individuals with breast cancer and control participants from 13 case-control studies nested in prospective cohorts (recruited between 1982 and 2011) and 18 population-based case-control studies (recruited between 1990 and 2013). Data analysis was performed in June 2024.ExposureMHT use (estrogen-progestin therapy [EPT] or estrogen-only therapy [ET]) in postmenopausal women and OC use in premenopausal women (never, past use, or current use).Main Outcomes and MeasuresBreast cancer intrinsic-like subtypes (luminal A–like, luminal B–like, luminal B–ERBB2 [formerly HER2 or HER2/neu]-like, ERBB2 enriched–like, or triple-negative) were determined by immunohistochemistry of tumor sections. Polytomous logistic regression was performed to estimate the association between exogenous hormones and risk of breast cancer by intrinsic-like subtypes. Analyses by subtypes were stratified by body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]; healthy weight, 18.5-&amp;lt;25; overweight, 25-&amp;lt;30; or obesity, ≥30).ResultsThis study included 42 269 individuals with breast cancer (11 901 [28.2%] premenopausal and 30 368 [71.8%] postmenopausal; 23 353 [55.2%] had a known intrinsic-like subtype) and 71 072 control participants. The mean (SD) age of all participants was 57.9 (10.9) years. In postmenopausal women, associations between current MHT use (EPT or ET) and breast cancer differed by subtype. Current EPT users with healthy weight were more likely to be diagnosed with luminal A–like (odds ratio [OR], 2.51 [95% CI, 2.26-2.80]) or luminal B–ERBB2-like (OR, 1.95 [95% CI, 1.61-2.37]) subtypes. These associations were attenuated but remained for individuals with overweight (OR, 1.40 [95% CI, 1.02-1.92]) or obesity (OR, 1.68 [95% CI, 1.01-2.78]). EPT use increased the odds of being diagnosed with luminal B–like tumors solely in women with healthy weight (OR, 1.47 [95% CI, 1.17-1.86]). Current ET use was positively associated with luminal A–like disease in women with healthy weight only (OR, 1.16 [95% CI, 1.01-1.32]), showing inverse associations with higher BMI (obesity: OR, 0.65 [95% CI, 0.50-0.85]). In premenopausal women, recent OC use was associated with luminal B–ERBB2-like (OR, 1.50 [95% CI, 1.09-2.08]), ERBB2 enriched–like (OR, 2.33 [95% CI, 1.55-3.51]), and triple-negative (OR, 1.75 [95% CI, 1.33-2.29]; P &amp;lt; .04 for heterogeneity) tumors.Conclusions and RelevanceIn this study, clear differences were observed in associations between current EPT use and luminal-like breast cancer subtypes and other subtypes. EPT users with healthy weight were more likely to be diagnosed with luminal-like breast cancer compared with nonusers. Subtype heterogeneity was less apparent in associations of OC and ET use. Future studies on contemporary formulations, patterns of use, and routes of administration of exogenous hormone usage are warranted.

PURPOSE There is strong evidence that leisure-time physical activity is protective against postmenopausal breast cancer risk but the association with premenopausal breast cancer is less clear. The purpose of this study was to examine the association of physical activity with the risk of developing premenopausal breast cancer. METHODS We pooled individual-level data on self-reported leisure-time physical activity across 19 cohort studies comprising 547,601 premenopausal women, with 10,231 incident cases of breast cancer. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs for associations of leisure-time physical activity with breast cancer incidence. HRs for high versus low levels of activity were based on a comparison of risk at the 90th versus 10th percentiles of activity. We assessed the linearity of the relationship and examined subtype-specific associations and effect modification across strata of breast cancer risk factors, including adiposity. RESULTS Over a median 11.5 years of follow-up (IQR, 8.0-16.1 years), high versus low levels of leisure-time physical activity were associated with a 6% (HR, 0.94 [95% CI, 0.89 to 0.99]) and a 10% (HR, 0.90 [95% CI, 0.85 to 0.95]) reduction in breast cancer risk, before and after adjustment for BMI, respectively. Tests of nonlinearity suggested an approximately linear relationship ( Pnonlinearity = .94). The inverse association was particularly strong for human epidermal growth factor receptor 2–enriched breast cancer (HR, 0.57 [95% CI, 0.39 to 0.84]; Phet = .07). Associations did not vary significantly across strata of breast cancer risk factors, including subgroups of adiposity. CONCLUSION This large, pooled analysis of cohort studies adds to evidence that engagement in higher levels of leisure-time physical activity may lead to reduced premenopausal breast cancer risk.

Importance Germline gene panel testing is recommended for men with advanced prostate cancer (PCa) or a family history of cancer. While evidence is limited for some genes currently included in panel testing, gene panels are also likely to be incomplete and missing genes that influence PCa risk and aggressive disease. Objective To identify genes associated with aggressive PCa. Design, Setting, and Participants A 2-stage exome sequencing case-only genetic association study was conducted including men of European ancestry from 18 international studies. Data analysis was performed from January 2021 to March 2023. Participants were 9185 men with aggressive PCa (including 6033 who died of PCa and 2397 with confirmed metastasis) and 8361 men with nonaggressive PCa. Exposure Sequencing data were evaluated exome-wide and in a focused investigation of 29 DNA repair pathway and cancer susceptibility genes, many of which are included on gene panels. Main Outcomes and Measures The primary study outcomes were aggressive (category T4 or both T3 and Gleason score ≥8 tumors, metastatic PCa, or PCa death) vs nonaggressive PCa (category T1 or T2 and Gleason score ≤6 tumors without known recurrence), and metastatic vs nonaggressive PCa. Results A total of 17 546 men of European ancestry were included in the analyses; mean (SD) age at diagnosis was 65.1 (9.2) years in patients with aggressive PCa and 63.7 (8.0) years in those with nonaggressive disease. The strongest evidence of association with aggressive or metastatic PCa was noted for rare deleterious variants in known PCa risk genes BRCA2 and ATM ( P ≤ 1.9 × 10 −6 ), followed by NBN ( P = 1.7 × 10 −4 ). This study found nominal evidence ( P &amp;lt; .05) of association with rare deleterious variants in MSH2 , XRCC2 , and MRE11A . Five other genes had evidence of greater risk (OR≥2) but carrier frequency differences between aggressive and nonaggressive PCa were not statistically significant: TP53 , RAD51D , BARD1 , GEN1 , and SLX4 . Deleterious variants in these 11 candidate genes were carried by 2.3% of patients with nonaggressive, 5.6% with aggressive, and 7.0% with metastatic PCa. Conclusions and Relevance The findings of this study provide further support for DNA repair and cancer susceptibility genes to better inform disease management in men with PCa and for extending testing to men with nonaggressive disease, as men carrying deleterious alleles in these genes are likely to develop more advanced disease.

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.

Abstract Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. Significance: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.

Abstract Background: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. Methods: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. Results: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10−8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20–1.30] compared with the other genotypes (OR &lt;1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10−8) and 8q24.23 (rs7005722, P = 2.88 × 10−8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09–1.16) compared with the other genotypes (OR &lt;1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07–1.28) compared with the other genotypes (OR &lt;1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). Conclusions: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. Impact: These findings can guide potential prevention treatments.

AbstractBackgroundKnown 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.MethodsSingle 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.ResultsWe 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 &lt; .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P &lt; .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.ConclusionsCNVs 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.