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Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which is qualitative and does not account for non-cancerous elements within the tumor microenvironment (TME). We present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast TME morphology. HiPS uses deep learning to accurately map cellular and tissue structures in order to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study (CPS)-II and validated using data from three independent cohorts, including the PLCO trial, CPS-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists’ performance in predicting survival outcomes, independent of TNM stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve prognosis.

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Purpose:Ovarian cancer is a heterogeneous disease that can be divided into multiple subtypes with variable etiology, pathogenesis, and prognosis. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes, copy number variation, RNA expression data, and outcomes.Experimental Design:A total of 162 paraffin-embedded ovarian epithelial tumor tissues, including the five major epithelial ovarian tumor subtypes (high- and low-grade serous, endometrioid, mucinous, and clear cell) and tumors of low malignant potential were selected from two different sources: The Polish Ovarian Cancer study, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR). Analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. For 45 tumors array copy number data were available. NanoString gene expression data for 39 genes were available for 61 high-grade serous carcinomas (HGSC).Results:Consensus nonnegative matrix factorization clustering of the 1,000 most variable CpG sites showed four major clusters among all epithelial ovarian cancers. We observed statistically significant differences in survival (log-rank test, P = 9.1 × 10−7) and genomic instability across these clusters. Within HGSC, clustering showed three subgroups with survival differences (log-rank test, P = 0.002). Comparing models with and without methylation subgroups in addition to previously identified gene expression subtypes suggested that the methylation subgroups added significant survival information (P = 0.007).Conclusions:DNA methylation profiling of ovarian cancer identified novel molecular subgroups that had significant survival difference and provided insights into the molecular underpinnings of ovarian cancer.See related commentary by Ishak et al., p. 5729

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Background Elevated mammographic breast density is a strong breast cancer risk factor with poorly understood etiology. Increased deposition of collagen, one of the main fibrous proteins present in breast stroma, has been associated with increased mammographic density. Collagen fiber architecture has been linked to poor outcomes in breast cancer. However, relationships of quantitative collagen fiber features assessed in diagnostic biopsies with mammographic density and lesion severity are not well-established. Methods Clinically indicated breast biopsies from 65 in situ or invasive breast cancer cases and 73 frequency matched-controls with a benign biopsy result were used to measure collagen fiber features (length, straightness, width, alignment, orientation and density (fibers/µm2)) using second harmonic generation microscopy in up to three regions of interest (ROIs) per biopsy: normal, benign breast disease, and cancer. Local and global mammographic density volumes were quantified in the ipsilateral breast in pre-biopsy full-field digital mammograms. Associations of fibrillar collagen features with mammographic density and severity of biopsy diagnosis were evaluated using generalized estimating equation models with an independent correlation structure to account for multiple ROIs within each biopsy section. Results Collagen fiber density was positively associated with the proportion of stroma on the biopsy slide (p p = 0.035) and within a 2 mm perilesional ring (p = 0.02), but not with global mammographic density measures. As severity of the breast biopsy diagnosis increased at the ROI level, collagen fibers tended to be less dense, shorter, straighter, thinner, and more aligned with one another (p Conclusions Collagen fiber density was positively associated with local, but not global, mammographic density, suggesting that collagen microarchitecture may not translate into macroscopic mammographic features. However, collagen fiber features may be markers of cancer risk and/or progression among women referred for biopsy based on abnormal breast imaging.

Soft tissue sarcoma is a rare but serious side-effect of radiotherapy to treat breast cancer, and rates are increasing in the USA. We evaluated potential co-factors in two complimentary cohorts of US breast cancer survivors.In this retrospective cohort study, we sourced data from the Kaiser Permanente (KP) cohort and the Surveillance, Epidemiology, and End Results (SEER) 13 registries cohort, both in the USA. The KP cohort included 15 940 women diagnosed with breast cancer from Jan 1, 1990, to Dec 31, 2016, in KP Colorado, KP Northwest (which serves Oregon and Southwest Washington state), or KP Washington, with detailed treatment data and comorbidities (including hypertension and diabetes at or before breast cancer diagnosis) from electronic medical records. The SEER cohort included 457 300 women diagnosed with breast cancer from Jan 1, 1992, to Dec 31, 2016, within the 13 SEER registries across the USA, with initial treatment data (yes vs no or unknown). Eligibility criteria in both cohorts were female breast cancer survivors (stage I-III) aged 20-84 years at diagnosis who had breast cancer surgery, and had survived at least 1 year after breast cancer diagnosis. The outcome of interest was any second thoracic soft tissue sarcoma (angiosarcomas and other subtypes) that developed at least 1 year after breast cancer diagnosis. Risk factors for thoracic soft tissue sarcoma were assessed using multivariable Poisson regression models.In the KP cohort, median follow-up was 9·3 years (IQR 5·7-13·9) and 19 (0·1%) of 15 940 eligible, evaluable women developed a thoracic soft tissue sarcoma (11 angiosarcomas, eight other subtypes). Most (94·7%; 18 of 19) thoracic soft tissue sarcomas occurred in women treated with radiotherapy; thus, radiotherapy was associated with a significantly increased risk of developing a thoracic soft tissue sarcoma (relative risk [RR] 8·1 [95% CI 1·1-60·4]; p=0·0052), but there was no association with prescribed dose, fractionation, or boost. The RR of angiosarcoma after anthracyclines was 3·6 (95% CI 1·0-13·3; p=0·058). Alkylating agents were associated with an increased risk of developing other sarcomas (RR 7·7 [95% CI 1·2-150·8]; p=0·026). History of hypertension (RR 4·8 [95% CI 1·3-17·6]; p=0·017) and diabetes (5·3 [1·4-20·8]; p=0·036) were each associated with around a five-times increased risk of angiosarcoma. In the SEER cohort, 430 (0·1%) of 457 300 patients had subsequent thoracic soft tissue sarcomas (268 angiosarcomas and 162 other subtypes) after a median follow-up of 8·3 years (IQR 4·3-13·9). Most (77·9%; 335 of 430) cases occurred after radiotherapy; thus, radiotherapy was associated with a significantly increased risk of developing a thoracic soft tissue sarcoma (RR 3·0 [95% CI 2·4-3·8]; plt;0·0001) and, for angiosarcomas, the RR for breast-conserving surgery plus radiotherapy versus mastectomy plus radiotherapy was 1·9 (1·1-3·3; p=0·012). By 10 years after radiotherapy, the cumulative incidence of thoracic soft tissue sarcoma was 0·21% (95% CI 0·12-0·34) in the KP cohort and 0·15% (95% CI 0·13-0·17) in SEER.Radiotherapy was the strongest risk factor for thoracic soft tissue sarcoma in both cohorts. This finding, along with the novel findings for diabetes and hypertension as potential risk factors for angiosarcomas, warrant further investigation as potential targets for prevention strategies and increased surveillance.US National Cancer Institute and National Institutes of Health.

Genomics of radiation-induced damage The potential adverse effects of exposures to radioactivity from nuclear accidents can include acute consequences such as radiation sickness, as well as long-term sequelae such as increased risk of cancer. There have been a few studies examining transgenerational risks of radiation exposure but the results have been inconclusive. Morton et al. analyzed papillary thyroid tumors, normal thyroid tissue, and blood from hundreds of survivors of the Chernobyl nuclear accident and compared them against those of unexposed patients. The findings offer insight into the process of radiation-induced carcinogenesis and characteristic patterns of DNA damage associated with environmental radiation exposure. In a separate study, Yeager et al. analyzed the genomes of 130 children and parents from families in which one or both parents had experienced gonadal radiation exposure related to the Chernobyl accident and the children were conceived between 1987 and 2002. Reassuringly, the authors did not find an increase in new germline mutations in this population. Science , this issue p. eabg2538 , p. 725

Background Breast cancer survivors are at increased risk for developing second primary cancers compared with the general population. Little is known about whether body mass index (BMI) increases this risk. We examined the association between BMI and second cancers among women with incident invasive breast cancer. Methods This retrospective cohort included 6481 patients from Kaiser Permanente Colorado and Washington of whom 822 (12.7%) developed a second cancer (mean follow-up was 88.0 months). BMI at the first cancer was extracted from the medical record. Outcomes included: 1) all second cancers, 2) obesity-related second cancers, 3) any second breast cancer, and 4) estrogen receptor–positive second breast cancers. Multivariable Poisson regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CIs) for second cancers associated with BMI adjusted for site, diagnosis year, treatment, demographic, and tumor characteristics. Results The mean age at initial breast cancer diagnosis was 61.2 (SD = 11.8) years. Most cases were overweight (33.4%) or obese (33.8%) and diagnosed at stage I (62.0%). In multivariable models, for every 5 kg/m2 increase in BMI, the risk of any second cancer diagnosis increased by 7% (RR = 1.07, 95% CI = 1.01 to 1.14); 13% (RR = 1.13, 95% CI = 1.05 to 1.21) for obesity-related cancers, 11% (RR = 1.11, 95% CI = 1.02 to 1.21) for a second breast cancer, and 15% (RR = 1.15, 95% CI = 1.04 to 1.27) for a second estrogen receptor–positive breast cancer. Conclusions We observed a statistically significant increased risk of second cancers associated with increasing BMI. These findings have important public health implications given the prevalence of overweight and obesity in breast cancer survivors and underscore the need for effective prevention strategies.

Background Mammographic breast density (MBD) decline post-tamoxifen initiation is a favorable prognostic factor in estrogen receptor (ER)–positive breast cancer (BC) and has potential utility as a biomarker of tamoxifen response. However, the prognostic value of MBD decline may vary by molecular characteristics among ER–positive patients. Methods We investigated associations between MBD decline (≥10% vs Results MBD decline was statistically significantly associated with reduced risk of BCSM overall (OR = 0.38, 95% CI = 0.15 to 0.92). This association was, however, stronger among women with aggressive tumor characteristics including luminal B–like (OR = 0.17, 95% CI = 0.04 to 0.73) vs A–like (OR = 0.74, 95% CI = 0.19 to 2.92); large (OR = 0.26, 95% CI = 0.08 to 0.78) vs small (OR = 0.41, 95% CI = 0.04 to 3.79) tumors; PR–negative (OR = 0.02, 95% CI = 0.001 to 0.37) vs PR–positive (OR = 0.50, 95% CI = 0.18 to 1.40) disease; and high (OR = 0.25, 95% CI = 0.07 to 0.93) vs low (OR = 0.44, 95% CI = 0.10 to 2.09) mIHC3 score. Conclusion The findings support MBD decline as a prognostic marker of tamoxifen response among patients with aggressive ER–positive BC phenotypes, for whom understanding treatment effectiveness is critical.

PURPOSE: This retrospective cohort study examined patterns of endocrine therapy initiation over time and by demographic, tumor, and treatment characteristics. METHODS: We included 7,777 women from three U.S. integrated healthcare systems diagnosed with incident stage I-III hormone receptor-positive breast cancer between 2001-2016. We extracted endocrine therapy from pharmacy dispensings, defining initiation as dispensings within 12 months of diagnosis. Demographic, tumor, and treatment characteristics were collected from electronic health records. Using generalized linear models with a log link and Poisson distribution, we estimated initiation of any endocrine therapy, tamoxifen, and aromatase inhibitors (AI) over time with relative risks (RR) and 95% confidence intervals (CI) adjusted for age, tumor characteristics, diagnosis year, other treatment, and study site. RESULTS: Among women aged 20+ (mean 62 years), 6,329 (81.4%) initiated any endocrine therapy, and 1,448 (18.6%) did not initiate endocrine therapy. Tamoxifen initiation declined from 67% to 15% between 2001-2016. AI initiation increased from 6% to 69% between 2001-2016 in women aged ≥55 years. The proportion of women who did not initiate endocrine therapy decreased from 19% to 12% between 2002-2014 then increased to 17% by 2016. After adjustment, women least likely to initiate endocrine therapy were older (RR=0.81, 95%CI=0.77-0.85 for age 75+ versus 55-64), Black (RR=0.93, 95%CI=0.87-1.00 versus white), and had stage I disease (RR=0.88, 95%CI=0.85-0.91 versus stage III). CONCLUSIONS: Despite an increase in AI use over time, at least one in six eligible women did not initiate endocrine therapy, highlighting opportunities for improving endocrine therapy uptake in breast cancer survivors.

Purpose: Gene expression–based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications. See related commentary by McMullen et al., p. 5271

This retrospective cohort study examined patterns of endocrine therapy initiation over time and by demographic, tumor, and treatment characteristics.We included 7777 women from three U.S. integrated healthcare systems diagnosed with incident stage I-III hormone receptor-positive breast cancer between 2001 and 2016. We extracted endocrine therapy from pharmacy dispensings, defining initiation as dispensings within 12 months of diagnosis. Demographic, tumor, and treatment characteristics were collected from electronic health records. Using generalized linear models with a log link and Poisson distribution, we estimated initiation of any endocrine therapy, tamoxifen, and aromatase inhibitors (AI) over time with relative risks (RR) and 95% confidence intervals (CI) adjusted for age, tumor characteristics, diagnosis year, other treatment, and study site.Among women aged 20+ (mean 62 years), 6329 (81.4%) initiated any endocrine therapy, and 1448 (18.6%) did not initiate endocrine therapy. Tamoxifen initiation declined from 67 to 15% between 2001 and 2016. AI initiation increased from 6 to 69% between 2001 and 2016 in women aged ≥ 55 years. The proportion of women who did not initiate endocrine therapy decreased from 19 to 12% between 2002 and 2014 then increased to 17% by 2016. After adjustment, women least likely to initiate endocrine therapy were older (RR = 0.81, 95% CI 0.77-0.85 for age 75+ vs. 55-64), Black (RR = 0.93, 95% CI 0.87-1.00 vs. white), and had stage I disease (RR = 0.88, 95% CI 0.85-0.91 vs. stage III).Despite an increase in AI use over time, at least one in six eligible women did not initiate endocrine therapy, highlighting opportunities for improving endocrine therapy uptake in breast cancer survivors.

Estrogen receptor (ER) + /progesterone receptor (PR) - or ER-/PR + breast cancer prognosis has not been well-described outside of clinical trials. We evaluated the relationship between ER/PR (ER + /PR-, ER-/PR + , ER + /PR + , ER-/PR-) subgroups and breast cancer-specific mortality within a general community setting in the US.A Retrospective cohort of 11,737 women diagnosed with breast cancer between 1990 and 2016 within US integrated healthcare systems (median follow-up = 7 years; 1,104 breast cancer-specific deaths) were included in this analysis. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) adjusting for site, demographic and clinicopathological characteristics, and treatment (surgery/radiotherapy, chemotherapy, endocrine therapy).Breast cancer-specific mortality was higher for those with ER + /PR- (n = 1,233) compared with ER + /PR + tumors (n = 8,439) before (HR = 1.43; 95% CI = 1.17-1.75) and after treatment adjustment (HR = 1.58; 95% CI = 1.27-1.97). ER + /PR- breast cancer-specific mortality remained higher than ER + /PR + tumors when stratified by treatment received. Breast cancer-specific mortality was similar in ER-/PR + (n = 161) compared with ER + /PR + tumors.Our findings suggest that ER + /PR- tumors may have worse breast cancer-specific mortality than ER + /PR + tumors in a community setting.

Contains fulltext : 237689.pdf (Publisher’s version ) (Open Access) Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

Black women in the United States are disproportionately affected by early-onset, triple-negative breast cancer. DNA methylation has shown differences by race in healthy and tumor breast tissues. We examined associations between genome-wide DNA methylation levels in breast milk and breast cancer risk factors, including race, to explain how this reproductive stage influences a woman's risk for, and potentially contributes to racial disparities in, breast cancer. Breast milk samples and demographic, behavioral, and reproductive data, were obtained from cancer-free, uniparous, and lactating U.S. black (n = 57) and white (n = 82) women, ages 19–44. Genome-wide DNA methylation analysis was performed on extracted breast milk DNA using the Infinium HumanMethylation450 BeadChip. Statistically significant associations between breast cancer risk factors and DNA methylation beta values, adjusting for potential confounders, were determined using linear regression followed by Bonferroni Correction (P < 1.63 × 10−7). Epigenetic analysis in breast milk revealed statistically significant associations with race and lactation duration. Of the 284 CpG sites associated with race, 242 were hypermethylated in black women. All 227 CpG sites associated with lactation duration were hypomethylated in women who lactated longer. Ingenuity Pathway Analysis of differentially methylated promoter region CpGs by race and lactation duration revealed enrichment for networks implicated in carcinogenesis. Associations between DNA methylation and lactation duration may offer insight on its role in lowering breast cancer risk. Epigenetic associations with race may mediate social, behavioral, or other factors related to breast cancer and may provide insight into potential mechanisms underlying racial disparities in breast cancer incidence.

Background Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis ( 10 years). The false discovery rate (q value) was used to account for multiple testing. Results The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). Conclusions Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.

We report a meta-analysis of breast, prostate, ovarian, and endometrial cancer genome-wide association data (effective sample size: 237,483 cases/317,006 controls). This identified 465 independent lead variants (P−8) across 192 genomic regions. Four lead variants were >1Mb from previously identified risk loci for the four cancers and an additional 23 lead variant-cancer associations were novel for one of the cancers. Bayesian models supported pleiotropic effects involving at least two cancers at 222/465 lead variants in 118/192 regions. Gene-level association analysis identified 13 shared susceptibility genes (P−6) in 13 regions not previously implicated in any of the four cancers and not uncovered by our variant-level meta-analysis. Several lead variants had opposite effects across cancers, including a cluster of such variants in the TP53 pathway. Fifty-four lead variants were associated with blood cell traits and suggested genetic overlaps with clonal hematopoiesis. Our study highlights the remarkable pervasiveness of pleiotropy across hormone-related cancers, further illuminating their shared genetic and mechanistic origins at variant- and gene-level resolution.

Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

Familial, genome-wide association (GWAS), and sequencing studies and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWAS) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through novel application of a pleiotropy-guided conditional/conjunction false discovery rate approach for the first time in the setting of a TWAS. This identified 14 new candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 new candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were > 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. Overlaying candidate causal risk variants identified by GWAS fine mapping onto expression prediction models for genes at known loci suggested that the association for 55% of these genes was driven by the underlying GWAS signal.SignificanceThe 22 new genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

Introduction: Identifying biomarkers of breast cancer risk among young women would have value in developing effective screening and prevention strategies at early ages. We have proposed that DNA methylation analysis of breast milk may provide breast cancer risk information among young women, and could possibly provide etiologic clues related to the higher rates of early onset cancers among African American as compared with White women in the US. Objective: The purpose of this project was to identify associations between genome-wide DNA methylation levels in breast milk and race adjusted for other breast cancer risk factors. Study Population: Cancer-free, lactating U.S. Black (n=57) and White (n=82) women, ages 19 to 44, provided frozen breast milk samples, as well as demographic, behavioral, and reproductive data, to the Breastmilk Laboratory at University of Massachusetts Amherst. Women were uniparous and did not have a personal history of breast cancer at the time of milk donation. Methods: DNA was extracted from breast milk samples using the phenol-chloroform method. Genome-wide methylation analysis was performed on breast milk samples using the Infinium HumanMethylation450 BeadChip. Probes with 50% or more missing data, cross-reactive probes, as well as probes with minor allelic frequency greater than 0.05 in European- or African-Americans were removed, leaving 379,042 CpG sites for analysis. Multivariate generalized linear regression models were used to examine associations between race and other breast cancer risk factors and methylation beta values, adjusting for potential confounding factors. P-values less than 1E-7 were considered statistically significant. Results: Black women in this study were more likely to be never smokers, to not have used over-the-counter pain medication in the past week, and to breastfeed longer. After adjustment by age, BMI, smoking status, and batch number, race was significantly associated with differential methylation at 1143 CpG sites, including 1024 at which Black women demonstrated increased methylation levels. Additionally, breastfeeding duration was associated with 269 CpG sites, with 268 showing a significant inverse relationship with methylation. Methylation sites significantly associated with Black race and lactation duration were located within tumor suppressor and promoter genes as well as in genes implicated in obesity and diabetes. Conclusion: This preliminarily analysis of DNA methylation in breast milk suggests that Black women have increased methylation and longer breastfeeding is associated with reduced methylation. Further research to understand how etiologic factors related to breast cancer may alter DNA methylation patterns in normal breast may lead to improved understanding of breast cancer risk at a young age and potentially causes of racial disparities in breast cancer incidence between White and Black women. Citation Format: Davis Lynn BC, Bodelon C, Pfeiffer RM, Yang HP, Yang H, Lee M, Laird PW, Campan M, Weisenberger DJ, Murphy J, Sherman ME, Browne EP, Anderton DL, Arcaro KF, Gierach GL. Differences in genome-wide DNA methylation levels in breast milk by race and lactation duration [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P6-10-07.

Human papillomavirus (HPV) testing has been recently introduced as an alternative to cytology for cervical cancer screening. However, since most HPV infections clear without causing clinically relevant lesions, additional triage tests are required to identify women who are at high risk of developing cancer. We performed DNA methylation profiling on formalin-fixed, paraffin-embedded tissue specimens from women with benign HPV16 infection and histologically confirmed cervical intraepithelial neoplasia grade 3, and cancer using a bead-based microarray covering 1,500 CpG sites in over 800 genes. Methylation levels in individual CpG sites were compared using a t-test, and results were summarized by computing p-values. A total of 12 candidate genes (ADCYAP1, ASCL1, ATP10, CADM1, DCC, DBC1, HS3ST2, MOS, MYOD1, SOX1, SOX17 and TMEFF2) identified by DNA methylation profiling, plus an additional three genes identified from the literature (EPB41L3, MAL and miR-124) were chosen for validation in an independent set of 167 liquid-based cytology specimens using pyrosequencing and targeted, next-generation bisulfite sequencing. Of the 15 candidate gene markers, 10 had an area under the curve (AUC) of ≥ 0.75 for discrimination of high grade squamous intraepithelial lesions or worse (HSIL+) from

Although transgenerational effects of exposure to ionizing radiation have long been a concern, human research to date has been confined to studies of disease phenotypes in groups exposed to high doses and high dose rates, such as the Japanese atomic bomb survivors. Transgenerational effects of parental irradiation can be addressed using powerful new genomic technologies. In collaboration with the Ukrainian National Research Center for Radiation Medicine, the US National Cancer Institute, in 2014–2018, initiated a genomic alterations study among children born in selected regions of Ukraine to cleanup workers and/or evacuees exposed to low–dose-rate radiation after the 1986 Chornobyl (Chernobyl) nuclear accident. To investigate whether parental radiation exposure is associated with germline mutations and genomic alterations in the offspring, we are collecting biospecimens from father-mother-offspring constellations to study de novo mutations, minisatellite mutations, copy-number changes, structural variants, genomic insertions and deletions, methylation profiles, and telomere length. Genomic alterations are being examined in relation to parental gonadal dose, reconstructed using questionnaire and measurement data. Subjects are being recruited in exposure categories that will allow examination of parental origin, duration, and timing of exposure in relation to conception. Here we describe the study methodology and recruitment results and provide descriptive information on the first 150 families (mother-father-child(ren)) enrolled.

Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P

Persistent infection with carcinogenic human papillomaviruses (HPV) causes the majority of anogenital cancers and a subset of head and neck cancers. The HPV genome is frequently found integrated into the host genome of invasive cancers. The mechanisms of how it may promote disease progression are not well understood. Thoroughly characterizing integration events can provide insights into HPV carcinogenesis. Individual studies have reported limited number of integration sites in cell lines and human samples. We performed a systematic review of published integration sites in HPV-related cancers and conducted a pooled analysis to formally test for integration hotspots and genomic features enriched in integration events using data from the Encyclopedia of DNA Elements (ENCODE). Over 1,500 integration sites were reported in the literature, of which 90.8% (N = 1,407) were in human tissues. We found 10 cytobands enriched for integration events, three previously reported ones (3q28, 8q24.21 and 13q22.1) and seven additional ones (2q22.3, 3p14.2, 8q24.22, 14q24.1, 17p11.1, 17q23.1 and 17q23.2). Cervical infections with HPV18 were more likely to have breakpoints in 8q24.21 (p = 7.68 × 10(-4) ) than those with HPV16. Overall, integration sites were more likely to be in gene regions than expected by chance (p = 6.93 × 10(-9) ). They were also significantly closer to CpG regions, fragile sites, transcriptionally active regions and enhancers. Few integration events occurred within 50 Kb of known cervical cancer driver genes. This suggests that HPV integrates in accessible regions of the genome, preferentially genes and enhancers, which may affect the expression of target genes.

Background. Endogenous estrogen and its metabolites have widespread physiological actions and have been associated with several conditions and diseases, including bone density, atherosclerosis, and different cancers. The two parent estrogens, estrone and estradiol, are irreversibly hydroxylated at the C-2, C-4, and C-16 positions of the steroid ring, leading to a cascade of metabolites with potentially different effects on disease risk. Little is known about the relation between estrogen metabolism and DNA methylation, although different estrogen metabolites may alter DNA methylation, which could ultimately result in expression changes in genes affecting hormonally related diseases. Here, we analyze the relationship between circulating parent estrogens and estrogen metabolites and blood DNA methylation. Methods. Estrone, estradiol (total and unconjugated) and 13 estrogen metabolites (five metabolites in the 2-hydroxylation pathway, three in the 4-pathway, and five in the 16-pathway) were measured using highly sensitive liquid chromatography-tandem mass spectrometry in serum from 260 postmenopausal women from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial who were not currently taking exogenous hormones at the time of blood collection. Using the same blood draw, DNA methylation was measured in 638,586 CpG sites using the Ilumina MethylationEPIC BeadChip array. Associations between estrogens and estrogen metabolites and methylation were estimated using linear regression, adjusting for age, BMI, smoking, and alcohol intake. The Bonferroni correction at the 5% level was used to account for multiple testing. The relationships between estrogens and estrogen metabolites and previously derived methylation measures of age acceleration were also investigated. Results. Median age at blood collection was 63 years. We identified 235 statistically significant associations between different parent estrogens and estrogen metabolites and CpG sites at the Bonferroni level. Approximately 60-70% of these sites, depending on the estrogen/estrogen metabolite, lie in the promoter or the body of a gene. Genes included GPR180 and SDK1, which are related to vascular function and fat metabolism. Approximately 40% of the CpG sites associated with the 2- and 4-hydroxylation pathways lie in enhancer regions. The Horvath measure of age acceleration was inversely associated with 4-hydroxyestrone (P=0.02) and the overall 4-hydroxylation pathway (P=0.04). Conclusions. Circulating estrogens and estrogen metabolites were statistically significantly associated with blood DNA methylation at several hormonally related genes, which could partially explain mechanisms underlying associations between estrogen and hormonally related cancers and other conditions. Work is ongoing to validate these findings. Citation Format: Clara Bodelon. Associations between circulating estrogens and estrogens metabolites and blood DNA methylation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3495.

Purpose: Ovarian cancer is a heterogeneous disease that can be divided into multiple subtypes with variable etiology, pathogenesis, and prognosis. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes, copy number variation, RNA expression data, and outcomes. Experimental Design: A total of 162 paraffin-embedded ovarian epithelial tumor tissues, including the five major epithelial ovarian tumor subtypes (high- and low-grade serous, endometrioid, mucinous, and clear cell) and tumors of low malignant potential were selected from two different sources: The Polish Ovarian Cancer study, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR). Analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. For 45 tumors array copy number data were available. NanoString gene expression data for 39 genes were available for 61 high-grade serous carcinomas (HGSC). Results: Consensus nonnegative matrix factorization clustering of the 1,000 most variable CpG sites showed four major clusters among all epithelial ovarian cancers. We observed statistically significant differences in survival (log-rank test, P = 9.1 × 10−7) and genomic instability across these clusters. Within HGSC, clustering showed three subgroups with survival differences (log-rank test, P = 0.002). Comparing models with and without methylation subgroups in addition to previously identified gene expression subtypes suggested that the methylation subgroups added significant survival information (P = 0.007). Conclusions: DNA methylation profiling of ovarian cancer identified novel molecular subgroups that had significant survival difference and provided insights into the molecular underpinnings of ovarian cancer. See related commentary by Ishak et al., p. 5729

The OCAC OncoArray genotyping project: et al., To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC., The OCAC OncoArray genotyping project was funded through grants from the US National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.) and R01-CA058598 (M.T.G.)); Canadian Institutes of Health Research (MOP-86727 (L.E.K.)); and the Ovarian Cancer Research Fund (A.B.). Funding for the CIMBA OncoArray genotyping was provided by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Génome Québec, the Quebec Breast Cancer Foundation for the PERSPECTIVE project, the US National Institutes of Health (CA1X01HG007491-01 (C.I.A.)), the Odense University Hospital Research Foundation (M.T.), the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (1420190 (S.K.P.)), the Italian Association for Cancer Research (IG16933 (L.O.)) and German Cancer Aid (110837 (R.K.S.).

Genital infection with the oncogenic human papillomavirus is the necessary cause of cervical cancer and of a large fraction of vulvar cancers. The toll-like receptor and the nuclear factor κB (NF-κB) signaling pathways have been implicated in inflammation, autoimmune disease and cancer, but whether common nucleotide variation in these pathways is associated with the risk of cervical and vulvar cancers has received little study. Using data from a population-based case-control study of cervical and vulvar cancers, we genotyped 205 single nucleotide polymorphisms (SNPs) in and around 32 candidate gene regions within these pathways. Gene-based analyses were used to estimate the associations between individual gene regions and the risk of cervical and vulvar cancers. Odds ratio (OR) and 95% confidence intervals (CI) were calculated to assess the risk of cervical and vulvar cancers for each SNP. p-Values were adjusted for multiple testing. A total of 876 cervical cancer cases, 517 vulvar cancer cases and 1,100 controls were included in the analysis. The TNF region was significantly associated with the risks of cervical cancer (gene-based p-value: 2.0 × 10(-4) ) and vulvar cancer (gene-based p-value: 1.0 × 10(-4) ). The rare allele (A) of SNP rs2239704 in the 5' UTR of the LTA gene was significantly associated with increased risks of cervical cancer (OR=1.31, 95% CI: 1.15-1.50; adjusted p-value: 0.013) and vulvar cancer (OR=1.51, 95% CI: 1.30-1.75; adjusted p-value: 1.9 × 10(-5) ). These findings add to the evidence of the importance of the immune system in the etiology of cervical and vulvar cancers.

Background: Recent studies have suggested that several ovarian cancer risk factors differ by parity status, but these findings have not been confirmed. We evaluated whether known risk factors of ovarian cancer differ between nulliparous and parous women using data from two large prospective cohorts. Methods: Data from the National Institutes of Health-AARP Diet and Health Study and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial were combined for this analysis. Cox regression models were used to estimate associations with ovarian cancer risk. Risk heterogeneity by parity status was assessed using likelihood-ratio tests. Results: Among the 125 437 women included in the analysis, there were 16 589 (13%) nulliparous women and 108 848 (87%) parous women. Of the 623 women diagnosed with invasive epithelial ovarian cancer, 102 (16%) were nulliparous and 521 (84%) were parous. While parity reduced ovarian cancer risk, no differences were found for other risk factors by parity. Among ever users of hormone therapy, body mass index suggestively increased the risk of ovarian cancer by 1.5-fold in nulliparous but not parous women (P-heterogeneity=0.08). Conclusion: While nulliparous women have higher ovarian cancer risk than parous women, our findings suggest that the relative effects of most other risk factors do not differ by parity.

Human papillomavirus (HPV) testing has been recently introduced as an alternative to cytology for cervical cancer screening. However, since most HPV infections clear without causing clinically relevant lesions, additional triage tests are required to identify women who are at high risk of developing cancer. We performed DNA methylation profiling on formalin-fixed, paraffin-embedded tissue specimens from women with benign HPV16 infection and histologically confirmed cervical intraepithelial neoplasia grade 3 (CIN3), and cancer using a bead-based microarray covering 1,500 CpG sites in over 800 genes. Methylation levels in individual CpG sites were compared using a t-test, and results were summarized by computing p-values. A total of 12 candidate genes (ADCYAP1, ASCL1, ATP10, CADM1, DCC, DBC1, HS3ST2, MOS, MYOD1, SOX1, SOX17, and TMEFF2) identified by DNA methylation profiling, plus an additional three genes identified from the literature (EPB41L3, MAL, miR-124) were chosen for validation in an independent set of 167 liquid-based cytology specimens using pyrosequencing and targeted, next-generation bisulfite sequencing. Of the 15 candidate gene markers, 10 had an area under the curve (AUC) of ≥ 0.75 for discrimination of high grade squamous intraepithelial lesions or worse (HSIL+) from

Reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have been associated with higher breast cancer risk. Younger age at menarche and older age at menopause have been previously related to lower levels of TDLU involution. To determine a possible genetic link, we examined whether single-nucleotide polymorphisms (SNPs) previously established in genome-wide association studies (GWAS) for ages at menarche and menopause are associated with TDLU involution. We conducted a pooled analysis of 862 women from two studies. H&E tissue sections were assessed for numbers of TDLUs and acini/TDLU. Poisson regression models were used to estimate associations of 36 menarche- and 21 menopause-SNPs with TDLU counts, acini counts/TDLU, and the product of these two measures, adjusting for age and study site. Fourteen percent of evaluated SNPs (eight SNPs) were associated with TDLU counts at p < 0.05, suggesting an enrichment of associations with TDLU counts. However, only menopause-SNPs had >50 % that were either significantly or nonsignificantly associated with TDLU measures in the directions consistent with their relationships shown in GWAS. Among ten SNPs that were statistically significantly associated with at least one TDLU involution measure (p < 0.05), seven SNPs (rs466639: RXRG; rs2243803: SLC14A2; rs2292573: GAB2; rs6438424: 3q13.32; rs7606918: METAP1D; rs11668344: TMEM150B; rs1635501: EXO1) were associated in the consistent directions. Our data suggest that the loci associated with ages at menarche and menopause may influence TDLU involution, suggesting some shared genetic mechanisms. However, larger studies are needed to confirm the results.

Background. Environmental and genetic factors play an important role in the etiology of breast cancer; however the potential epigenetic component to the risk remains largely unexplored. DNA methylation in blood cells could serve as a biomarker for exposure and breast cancer risk. Several small blood-based DNA methylation studies have reported risk associations with individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1,941 cases and 1,952 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods. We assessed associations with methylation at 365,589 CpGs present in the HumanMethylation450 Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts (the Melbourne Collaborative Cohort Study, the Italian and IARC cohorts of the European Prospective Investigation into Cancer and Nutrition and the Prostate, Lung, Colorectal and Ovarian screening trial) estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. The false discovery rate (q-value) was used to account for multiple testing. Results. Methylation measured at individual CpGs in blood DNA was not associated with breast cancer risk (q-value>0.6). In addition, higher average methylation level was not associated with risk of breast cancer (OR=0.94, 95% CI=0.85, 1.04; P=0.25; P for study heterogeneity=0.83). We found no evidence of modification of this association by age at diagnosis, time since blood collection or CpG location (P-heterogeneity>0.05). Conclusions. Overall, our data indicates that DNA methylation measured in blood prior to breast cancer diagnosis is unlikely to be associated with substantial breast cancer risk. Larger studies are needed to determine if modest to weak associations exist between blood DNA methylation and breast cancer risk. Citation Format: Clara Bodelon, Srikant Ambatipudi, Pierre-Antoine Dugué, Annelie Johansson, Joshua N. Sampson, Melissa C. Southey, Graham G. Giles, Silvia Polidoro, Zdenko Herceg, James M. Flanagan, Roger L. Milne, Montserrat Garcia-Closas. Genome-wide blood DNA methylation and breast cancer risk: A meta-analysis of four prospective studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3230.

Results of 3 previous studies suggest that use of aspirin is related to a reduced risk of endometrial cancer, at least in obese women (body mass index, > or =30 kg/m(2)). Using data obtained in a population-based, case-control study in western Washington State, the authors examined this question. Between 2003 and 2005, 410 women diagnosed with invasive endometrial cancer and 356 controls were interviewed regarding the use of aspirin and other nonsteroidal antiinflammatory drugs (NSAIDs). A history of use of NSAIDs was not associated with the risk of endometrial cancer (odds ratio = 1.04, 95% confidence interval: 0.76, 1.42). The lack of association was also present specifically for use of aspirin (odds ratio = 1.06, 95% confidence interval: 0.73, 1.53). NSAID use was unrelated to risk of endometrial cancer in both obese and nonobese women. Results from this study suggest that the use of aspirin or other NSAIDs has little or no influence on the risk of endometrial cancer.

We developed a compartmental model for hantavirus infection in deer mice (Peromyscus maniculatus) with the goal of comparing relative importance of direct and indirect transmission in sylvan and peridomestic environments. A direct transmission occurs when the infection is mediated by the contact of an infected and an uninfected mouse, while an indirect transmission occurs when the infection is mediated by the contact of an uninfected mouse with, for instance, infected soil. Based on population dynamics data and estimates of hantavirus decay in the two types of environments, our model predicts that direct transmission dominates in the sylvan environment, while both pathways are important in peridomestic environments. The model allows us to compute a basic reproduction number R 0, which indicates whether the virus will be endemic or eradicated from the mouse population, in both an autonomous and a time-periodic model. Our analysis can be used to evaluate various eradication strategies.

To document incidence rates of vulvar cancer, specifically invasive vulvar cancer, from 1973 to 2004 in the United States.Nine US cancer registries from the Surveillance, Epidemiology, and End Results (SEER) databases were used to identify women aged 15-84 years, who were first diagnosed with vulvar cancer during 1973-2004. Age-adjusted incidence rates and annual percentage changes were calculated for different time periods, stage of the disease, age, race, and geographic area.During 1973-2004, the incidence of in situ vulvar tumors increased by an average of 3.5% per year (95% CI: 2.9%, 4.1%), while the incidence of invasive tumors increased 1.0% per year (95% CI: 0.6%, 1.4%). An increasing incidence was observed for localized and regional invasive tumors. To at least some degree, the rise of incidence rates of incidence tumors was evident in every age category, race, and geographic region.Incidence rates of invasive vulvar cancer have increased in the United States during the last three decades. The reasons for this increase are unknown.