Background

N-glycolylneuraminic acid (Neu5Gc) is a non-human red-meat-derived sialic acid immunogenic to humans. Neu5Gc can be metabolically incorporated into glycan chains on human endothelial and epithelial surfaces. This represents the first example of a "xeno-autoantigen", against which circulating human "xeno-autoantibodies" can react. The resulting inflammation ("xenosialitis") has been demonstrated in human-like Neu5Gc-deficient mice and contributed to carcinoma progression via antibody-mediated inflammation. Anti-Neu5Gc antibodies have potential as biomarkers for diseases associated with red meat consumption such as carcinomas, atherosclerosis, and type 2 diabetes.

Methods

ELISA assays measured antibodies against Neu5Gc or Neu5Gc-glycans in plasma or serum samples from the Nurses' Health Studies, the Health Professionals Follow-up Study, and the European Prospective Investigation into Cancer and Nutrition, including inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over 1-3 years in archived samples. We also assessed associations between antibody levels and coronary artery disease risk (CAD) or red meat intake. A glycan microarray was used to detected antibodies against multiple Neu5Gc-glycan epitopes. A nested case-control study design assessed the association between total anti-Neu5Gc antibodies detected in the glycan array assay and the risk of colorectal cancer (CRC).

Results

ELISA assays showed a wide range of anti-Neu5Gc responses and good inter-assay reproducibility, stability with delayed sample processing, and within-person reproducibility over time, but these antibody levels did not correlate with CAD risk or red meat intake. Antibodies against Neu5Gc alone or against individual Neu5Gc-bearing epitopes were also not associated with colorectal cancer (CRC) risk. However, a sialoglycan microarray study demonstrated positive association with CRC risk when the total antibody responses against all Neu5Gc-glycans were combined. Individuals in the top quartile of total anti-Neu5Gc IgG antibody concentrations had nearly three times the risk compared to those in the bottom quartile (Multivariate Odds Ratio comparing top to bottom quartile: 2.98, 95% CI: 0.80, 11.1; P for trend = 0.02).

Conclusions

Further work harnessing the utility of these anti-Neu5Gc antibodies as biomarkers in red meat-associated diseases must consider diversity in individual antibody profiles against different Neu5Gc-bearing glycans. Traditional ELISA assays for antibodies directed against Neu5Gc alone, or against specific Neu5Gc-glycans may not be adequate to define risk associations. Our finding of a positive association of total anti-Neu5Gc antibodies with CRC risk also warrants confirmation in larger prospective studies.

Background

Population-based estimates of the risk of breast cancer associated with germline pathogenic variants in cancer-predisposition genes are critically needed for risk assessment and management in women with inherited pathogenic variants.

Methods

In a population-based case-control study, we performed sequencing using a custom multigene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and 32,544 unaffected women (controls) from population-based studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Associations between pathogenic variants in each gene and the risk of breast cancer were assessed.

Results

Pathogenic variants in 12 established breast cancer-predisposition genes were detected in 5.03% of case patients and in 1.63% of controls. Pathogenic variants in BRCA1 and BRCA2 were associated with a high risk of breast cancer, with odds ratios of 7.62 (95% confidence interval [CI], 5.33 to 11.27) and 5.23 (95% CI, 4.09 to 6.77), respectively. Pathogenic variants in PALB2 were associated with a moderate risk (odds ratio, 3.83; 95% CI, 2.68 to 5.63). Pathogenic variants in BARD1, RAD51C, and RAD51D were associated with increased risks of estrogen receptor-negative breast cancer and triple-negative breast cancer, whereas pathogenic variants in ATM, CDH1, and CHEK2 were associated with an increased risk of estrogen receptor-positive breast cancer. Pathogenic variants in 16 candidate breast cancer-predisposition genes, including the c.657_661del5 founder pathogenic variant in NBN, were not associated with an increased risk of breast cancer.

Conclusions

This study provides estimates of the prevalence and risk of breast cancer associated with pathogenic variants in known breast cancer-predisposition genes in the U.S. population. These estimates can inform cancer testing and screening and improve clinical management strategies for women in the general population with inherited pathogenic variants in these genes. (Funded by the National Institutes of Health and the Breast Cancer Research Foundation.).

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.

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.

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.