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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.

Background: Breast cancer (BrCa) is the most common cancer for women globally. BrCa incidence varies by age and differs between racial groups, with Black women having an earlier age of onset and higher mortality compared to White women. The underlying biological mechanisms of this disparity remain uncertain. Here, we address this knowledge gap by examining the association between overall epigenetic age acceleration and BrCa initiation as well as the mediating role of race. Results: We measured whole-genome methylation (866,238 CpGs) using the Illumina EPIC array in blood DNA extracted from 209 women recruited from University Hospitals Cleveland Medical Center. Overall and intrinsic epigenetic age acceleration was calculated–accounting for the estimated white blood cell distribution–using the second-generation biological clock GrimAge. After quality control, 149 BrCa patients and 42 disease-free controls remained. The overall chronological mean age at BrCa diagnosis was 57.4 ± 11.4 years and nearly one-third of BrCa cases were self-reported Black women (29.5%). When comparing BrCa cases to disease-free controls, GrimAge acceleration was 2.48 years greater (p-value = 0.0056), while intrinsic epigenetic age acceleration was 1.72 years higher (p-value = 0.026) for cases compared to controls. After adjusting for known BrCa risk factors, we observed BrCa risk increased by 14% [odds ratio (OR) = 1.14; 95% CI: 1.05, 1.25] for a one-year increase in GrimAge acceleration. The stratified analysis by self-reported race revealed differing ORs for GrimAge acceleration: White women (OR = 1.17; 95% CI: 1.03, 1.36), and Black women (OR = 1.08; 95% CI: 0.96, 1.23). However, our limited sample size failed to detect a statistically significant interaction for self-reported race (p-value >0.05) when examining GrimAge acceleration with BrCa risk. Conclusions: Our study demonstrated that epigenetic age acceleration is associated with BrCa risk, and the association suggests variation by self-reported race. Although our sample size is limited, these results highlight a potential biological mechanism for BrCa risk and identifies a novel research area of BrCa health disparities requiring further inquiry. [ABSTRACT FROM AUTHOR]

PurposeEpidemiological studies suggest that short sleep duration and poor sleep quality may increase breast cancer risk. However, whether sleep is associated with breast tumor aggressiveness characteristics has largely been unexplored.MethodsThe study included 4171 non-Hispanic whites (NHW) and 235 African Americans (AA) diagnosed with incident, primary, invasive breast cancer in the Women's Health Initiative (WHI) Observational Study (1994-2013). We used logistic regression to examine the association of baseline sleep (sleep duration, sleep quality, WHI Insomnia Rating Scale) with tumor grade, stage, hormone receptor status, HER2 status.ResultsIn NHW, women who reported 6 h of sleep/night were more likely to have tumors classified as regional/distant stage at diagnosis compared to women who slept 7-8 h/night (adjusted odds ratio (OR): 1.25, 95% confidence interval (CI): 1.05-1.48). AA women who reported their typical night's sleep as 'average quality' or 'restless or very restless sleep' were more likely to be diagnosed with triple-negative tumors than those who reported 'sound or restful' sleep (adjusted ORs: 2.91 (1.11, 7.63) and 3.74 (1.10, 12.77), respectively).ConclusionsOur findings provide indications that aspects of sleep (sleep duration and quality), partially modifiable health behaviors, may be associated with development of aggressive tumor characteristics in postmenopausal women. The role of these sleep attributes may differ for NHW and AA women; however, further study in robust, racial diverse samples is needed. This study provides evidence that facets of sleep behavior are associated with the development of aggressive tumor features and these associations differ by race.

Since improvements in cancer screening, diagnosis, and therapeutics, cancer disparities have existed. Marginalized populations (e.g., racial and ethnic minorities, sexual and gender minorities, lower-income individuals, those living in rural areas, and persons living with disabilities) have worse cancer-related outcomes. Early detection of cancer substantially improves outcomes, yet uptake of recommended cancer screenings varies widely. Multi-cancer early detection (MCED) tests use biomarkers in the blood to detect two or more cancers in a single assay. These assays show potential for population screening for some cancers--including those disproportionally affecting marginalized communities. MCEDs may also reduce access barriers to early detection, a primary factor in cancer-related outcome disparities. However, for the promise of MCEDs to be realized, during their development and testing, we are obligated to be cautious to design them in a way that reduces the myriad of structural, systematic, and personal barriers contributing to disparities. Further, they must not create new barriers. Population studies and clinical trials should include diverse populations, and tests must work equally well in all populations. The tests must be affordable. It is critical that we establish trust within marginalized communities, the healthcare system, and the MCED tests themselves. Tests should be expected to have high specificity, as a positive MCED finding will trigger additional, oftentimes invasive and expensive, imaging or other diagnosis tests and/or biopsies. Finally, there should be a way to help all individuals with a positive test to navigate the system for follow-up diagnostics and treatment, if warranted, that is accessible to all. [ABSTRACT FROM AUTHOR]

Late-stage breast cancer metastasis is driven by dysregulated TGF-β signaling, but the underlying molecular mechanisms have not been fully elucidated. We attempted to recapitulate tumor and metastatic micro-environments via the [...]

A population of African American (AA) families with sarcoidosis is clustered into subsets in order to examine linkage analysis stratified by ancestry similarity estimated from highly polymorphic genetic markers, instead of race, as a means of reducing sample heterogeneity. Strong evidence for previously unidentified population-specific effects is provided for the presence of sarcoidosis-susceptibility genes in the AA sample.