Germline polygenic risk scores are associated with immune gene expression signature and immune cell infiltration in breast cancer.

The tumor immune microenvironment (TIME) plays key roles in tumor progression and response to immunotherapy. Previous studies have identified individual germline variants associated with differences in TIME. Here, we hypothesize that common variants associated with breast cancer risk or cancer-related traits, represented by polygenic risk scores (PRSs), may jointly influence immune features in TIME. We derived 154 immune traits from bulk gene expression profiles of 764 breast tumors and 598 adjacent normal tissue samples from 825 individuals with breast cancer in the Nurses' Health Study (NHS) and NHSII. Immunohistochemical staining of four immune cell markers were available for a subset of 205 individuals. Germline PRSs were calculated for 16 different traits including breast cancer, autoimmune diseases, type 2 diabetes, ages at menarche and menopause, body mass index (BMI), BMI-adjusted waist-to-hip ratio, alcohol intake, and tobacco smoking. Overall, we identified 44 associations between germline PRSs and immune traits at false discovery rate q < 0.25, including 3 associations with q < 0.05. We observed consistent inverse associations of inflammatory bowel disease (IBD) and Crohn disease (CD) PRSs with interferon signaling and STAT1 scores in breast tumor and adjacent normal tissue; these associations were replicated in a Norwegian cohort. Inverse associations were also consistently observed for IBD PRS and B cell abundance in normal tissue. We also observed positive associations between CD PRS and endothelial cell abundance in tumor. Our findings suggest that the genetic mechanisms that influence immune-related diseases are also associated with TIME in breast cancer.

HSF1 drives a transcriptional program distinct from heat shock to support highly malignant human cancers.

Heat-Shock Factor 1 (HSF1), master regulator of the heat-shock response, facilitates malignant transformation, cancer cell survival, and proliferation in model systems. The common assumption is that these effects are mediated through regulation of heat-shock protein (HSP) expression. However, the transcriptional network that HSF1 coordinates directly in malignancy and its relationship to the heat-shock response have never been defined. By comparing cells with high and low malignant potential alongside their nontransformed counterparts, we identify an HSF1-regulated transcriptional program specific to highly malignant cells and distinct from heat shock. Cancer-specific genes in this program support oncogenic processes: cell-cycle regulation, signaling, metabolism, adhesion and translation. HSP genes are integral to this program, however, many are uniquely regulated in malignancy. This HSF1 cancer program is active in breast, colon and lung tumors isolated directly from human patients and is strongly associated with metastasis and death. Thus, HSF1 rewires the transcriptome in tumorigenesis, with prognostic and therapeutic implications.

Artificial intelligence in cancer imaging: Clinical challenges and applications.

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

A triple hormone receptor ER, AR, and VDR signature is a robust prognosis predictor in breast cancer.

BACKGROUND: Despite evidence indicating the dominance of cell-of-origin signatures in molecular tumor patterns, translating these genome-wide patterns into actionable insights has been challenging. This study introduces breast cancer cell-of-origin signatures that offer significant prognostic value across all breast cancer subtypes and various clinical cohorts, compared to previously developed genomic signatures. METHODS: We previously reported that triple hormone receptor (THR) co-expression patterns of androgen (AR), estrogen (ER), and vitamin D (VDR) receptors are maintained at the protein level in human breast cancers. Here, we developed corresponding mRNA signatures (THR-50 and THR-70) based on these patterns to categorize breast tumors by their THR expression levels. The THR mRNA signatures were evaluated across 56 breast cancer datasets (5040 patients) using Kaplan-Meier survival analysis, Cox proportional hazard regression, and unsupervised clustering. RESULTS: The THR signatures effectively predict both overall and progression-free survival across all evaluated datasets, independent of subtype, grade, or treatment status, suggesting improvement over existing prognostic signatures. Furthermore, they delineate three distinct ER-positive breast cancer subtypes with significant survival in differences-expanding on the conventional two subtypes. Additionally, coupling THR-70 with an immune signature identifies a predominantly ER-negative breast cancer subgroup with a highly favorable prognosis, comparable to ER-positive cases, as well as an ER-negative subgroup with notably poor outcome, characterized by a 15-fold shorter survival. CONCLUSIONS: The THR cell-of-origin signature introduces a novel dimension to breast cancer biology, potentially serving as a robust foundation for integrating additional prognostic biomarkers. These signatures offer utility as a prognostic index for stratifying existing breast cancer subtypes and for de novo classification of breast cancer cases. Moreover, THR signatures may also hold promise in predicting hormone treatment responses targeting AR and/or VDR.

Association of early menarche with breast tumor molecular features and recurrence.

BACKGROUND: Early menarche is an established risk factor for breast cancer but its molecular contribution to tumor biology and prognosis remains unclear. METHODS: We profiled transcriptome-wide gene expression in breast tumors (N = 846) and tumor-adjacent normal tissues (N = 666) from women in the Nurses' Health Studies (NHS) to investigate whether early menarche (age < 12) is associated with tumor molecular and prognostic features in women with breast cancer. Multivariable linear regression and pathway analyses using competitive gene set enrichment analysis were conducted in both tumor and adjacent-normal tissue and externally validated in TCGA (N = 116). Subgroup analyses stratified on ER-status based on the tumor were also performed. PAM50 signatures were used for tumor molecular subtyping and to generate proliferation and risk of recurrence scores. We created a gene expression score using LASSO regression to capture early menarche based on 28 genes from FDR-significant pathways in breast tumor tissue in NHS and tested its association with 10-year disease-free survival in both NHS (N = 836) and METABRIC (N = 952). RESULTS: Early menarche was significantly associated with 369 individual genes in adjacent-normal tissues implicated in extracellular matrix, cell adhesion, and invasion (FDR ≤ 0.1). Early menarche was associated with upregulation of cancer hallmark pathways (18 significant pathways in tumor, 23 in tumor-adjacent normal, FDR ≤ 0.1) related to proliferation (e.g. Myc, PI3K/AKT/mTOR, cell cycle), oxidative stress (e.g. oxidative phosphorylation, unfolded protein response), and inflammation (e.g. pro-inflammatory cytokines IFN α and IFN γ ). Replication in TCGA confirmed these trends. Early menarche was associated with significantly higher PAM50 proliferation scores (ß = 0.082 [0.02-0.14]), odds of aggressive molecular tumor subtypes (basal-like, OR = 1.84 [1.18-2.85] and HER2-enriched, OR = 2.32 [1.46-3.69]), and PAM50 risk of recurrence score (ß = 4.81 [1.71-7.92]). Our NHS-derived early menarche gene expression signature was significantly associated with worse 10-year disease-free survival in METABRIC (N = 952, HR = 1.58 [1.10-2.25]). CONCLUSIONS: Early menarche is associated with more aggressive molecular tumor characteristics and its gene expression signature within tumors is associated with worse 10-year disease-free survival among women with breast cancer. As the age of onset of menarche continues to decline, understanding its relationship to breast tumor characteristics and prognosis may lead to novel secondary prevention strategies.

Metformin and other anti-diabetic medication use and breast cancer incidence in the Nurses' Health Studies.

We aimed to examine the association between the use of metformin and other anti-diabetic medications and breast cancer incidence within two large prospective cohort studies. We followed 185,181 women who participated in the Nurses' Health Study (NHS; 1994-2016) and the NHSII (1995-2017), with baseline corresponding to the date metformin was approved for type 2 diabetes (T2D) treatment in the US Information on T2D diagnosis, anti-diabetes medications, and other covariates was self-reported at baseline and repeatedly assessed by follow-up questionnaires every 2 years. Breast cancer cases were self-reported and confirmed by medical record review. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between medication use and breast cancer were estimated using Cox proportional hazards regression models, adjusting for breast cancer risk factors. During 3,324,881 person-years of follow-up, we ascertained 9,192 incident invasive breast cancer cases, of which 451 were among women with T2D. Compared with women without T2D (n = 169,263), neither metformin use (HR = 0.97; 95% CI = 0.81-1.15) nor other anti-diabetic medications use (HR = 1.11; 95% CI = 0.90-1.36) associated with significantly lower breast cancer incidence. Among women with T2D (n = 15,918), compared with metformin never users, metformin ever use was not significantly inversely associated with breast cancer (HR = 0.92; 95% CI = 0.74-1.15). Although we observed that past use of metformin was inversely associated with breast cancer in the T2D population (HR = 0.67; 95% CI = 0.48-0.94), current use (HR = 1.01; 95% CI = 0.80-1.27) and longer duration of metformin use were not associated with breast cancer (each 2-year interval: HR = 1.01; 95% CI = 0.95-1.07). Overall, metformin use was not associated with the risk of developing breast cancer among the overall cohort population or among women with T2D.

Conception and pregnancy among women with a live birth after breast cancer treatment: A survey study of young breast cancer survivors.

BACKGROUND: Breast cancer (BC) is the most common malignancy in women of reproductive age. This study sought to explore the postcancer conception and pregnancy experience of young BC survivors to inform counseling. METHODS: In the Young Women's Breast Cancer Study (NCT01468246), a multicenter, prospective cohort, participants diagnosed at age ≤40 years with stage 0-III BC who reported ≥1 postdiagnosis live birth were sent an investigator-developed survey. RESULTS: Of 119 eligible women, 94 (79%) completed the survey. Median age at diagnosis was 32 years (range, 17-40) and at first postdiagnosis delivery was 38 years (range, 29-47). Most had stage I or II (77%) and HR+ (78%) BC; 51% were nulligravida at diagnosis. After BC treatment, most (62%) conceived naturally, though 38% used assisted reproductive technology, 74% of whom first attempted natural conception for a median of 9 months (range, 2-48). Among women with a known inherited pathogenic variant (n = 20), two underwent preimplantation genetic testing. Of 59 women on endocrine therapy before pregnancy, 26% did not resume treatment. Hypertensive disorders of pregnancy (20%) was the most common obstetrical condition. Nine percent of newborns required neonatal intensive care unit admission and 9% had low birth weight. CONCLUSION: Among women with live births after BC treatment, most conceived naturally and having a history of BC did not appear to negatively impact pregnancy complications, though the high rate of hypertensive disorders of pregnancy warrants further investigation. The prolonged period of attempting natural conception for some survivors suggests the potential need for improved understanding and counseling surrounding family planning goals after BC.

Associations of stem cell markers CD44, CD24 and ALDH1A1 with mammographic breast density in women with benign breast biopsies.

BACKGROUND: We examined associations of CD44, CD24 and ALDH1A1 breast stem cell markers with mammographic breast density (MBD), a well-established breast cancer (BCa) risk factor. METHODS: We included 218 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on BCa risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was done on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as percent of positively stained cells for each marker out of the total cell count. MBD was assessed with computer-assisted techniques. Generalised linear regression was used to examine the associations of each marker with square root-transformed percent density (PD), absolute dense and non-dense areas (NDA), adjusted for BCa risk factors. RESULTS: Stromal CD44 and ALDH1A1 expression was positively associated with PD (≥ 10% vs. <10% ß = 0.56, 95% confidence interval [CI] [0.06; 1.07] and ß = 0.81 [0.27; 1.34], respectively) and inversely associated with NDA (ß per 10% increase = -0.17 [-0.34; -0.01] and ß for ≥10% vs. <10% = -1.17 [-2.07; -0.28], respectively). Epithelial CD24 expression was inversely associated with PD (ß per 10% increase = -0.14 [-0.28; -0.01]. Stromal and epithelial CD24 expression was positively associated with NDA (ß per 10% increase = 0.35 [0.2 × 10-2; 0.70] and ß per 10% increase = 0.34 [0.11; 0.57], respectively). CONCLUSION: Expression of stem cell markers is associated with MBD.

A polygenic-score-based approach for identification of gene-drug interactions stratifying breast cancer risk.

An individual's genetics can dramatically influence breast cancer (BC) risk. Although clinical measures for prevention do exist, non-invasive personalized measures for reducing BC risk are limited. Commonly used medications are a promising set of modifiable factors, but no previous study has explored whether a range of widely taken approved drugs modulate BC genetics. In this study, we describe a quantitative framework for exploring the interaction between the genetic susceptibility of BC and medication usage among UK Biobank women. We computed BC polygenic scores (PGSs) that summarize BC genetic risk and find that the PGS explains nearly three-times greater variation in disease risk within corticosteroid users compared to non-users. We map 35 genes significantly interacting with corticosteroid use (FDR < 0.1), highlighting the transcription factor NRF2 as a common regulator of gene-corticosteroid interactions in BC. Finally, we discover a regulatory variant strongly stratifying BC risk according to corticosteroid use. Within risk allele carriers, 18.2% of women taking corticosteroids developed BC, compared to 5.1% of the non-users (with an HR = 3.41 per-allele within corticosteroid users). In comparison, there are no differences in BC risk within the reference allele homozygotes. Overall, this work highlights the clinical relevance of gene-drug interactions in disease risk and provides a roadmap for repurposing biobanks in drug repositioning and precision medicine.

A Population-Based Study of Genes Previously Implicated in Breast Cancer.

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.).

The association between infectious agents and breast cancer: a review of the epidemiologic evidence.

PURPOSE: Several viruses have been casually linked to human cancers, including cervical, nasopharyngeal, liver, sarcoma, and Merkel cell carcinomas. However, the etiologic contribution of viral infections to breast cancer, the number one incident cancer among women worldwide, is not well established. Among studies exploring associations of viruses with breast cancer, potential linkages have been identified between breast cancer and five viruses: beta retrovirus, (i.e., mouse mammary tumor virus), human papillomavirus, Epstein Barr virus. bovine leukemia virus, and human cytomegalovirus. METHODS: In this review, we provide a comprehensive evaluation of epidemiological ecologic, case-control, case-only, and cohort studies investigating these associations. We discuss results from several existing reviews and meta-analyses, evaluate epidemiological studies published in the past five years, and assess the relationship between these viruses and breast tumor clinicopathological factors. RESULTS: The strongest epidemiological evidence for a viral role in breast cancer exists for MMTV and HPV, though limitations include lack of prospective studies for MMTV and potential detection bias in HPV studies. Viral detection challenges have limited studies of EBV and HCMV. Fewer studies have evaluated BLV, and though it has been associated with higher risk of breast cancer, sample sizes are quite small.   CONCLUSION: While epidemiologic evidence exists for an association between these five viruses and breast cancer, various methodological issues and lack of prospective studies preclude robust conclusions. Future research should prioritize establishing a temporal relationship between infection and disease, minimizing misclassification of detection assays, and further exploring the influence of co-infections.

Recreational physical activity and breast cancer risk by menopausal status and tumor hormone receptor status: results from the Nurses' Health Studies.

PURPOSE: Physical activity is associated with lower breast cancer risk, especially in postmenopausal women. Associations in premenopausal women are less well established. METHODS: We evaluated recreational physical activity and breast cancer risk in the Nurses' Health Study (NHS) and NHSII (187,278 women; n = 12,785 breast cancers; follow-up: NHS = 1986-2016, NHSII = 1989-2017) by menopausal status and estrogen (ER) and progesterone (PR) receptor status. Physical activity was evaluated as updated cumulative average of metabolic equivalent of task (MET)-h/week. Cox proportional hazards models were used to estimate multivariable hazard ratios (HR) and 95% confidence intervals (CI). RESULTS: Recreational physical activity was inversely associated with breast cancer risk in pre- and postmenopausal women. Higher activity levels were associated with lower risk of ER+/PR + breast cancer in both pre- and postmenopausal women (e.g., total recreational activity, ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83, 95%CI = (0.70-0.99), postmenopausal HR = 0.86 (0.78-0.95); pheterogeneity = 0.97). Results were attenuated with adjustment for current body mass index (BMI) among postmenopausal, but not premenopausal, women (e.g., ≥ 27 vs < 3 MET-h/week, premenopausal HR = 0.83 (0.69-0.98); postmenopausal HR = 0.95 (0.85-1.05); pheterogeneity = 0.99). In analyses of moderate-vigorous activity and breast cancer risk, no heterogeneity by menopausal status was observed (phet ≥ 0.53; e.g., ≥ 27 vs < 3 MET-h/week, ER+/PR+, premenopausal HR = 0.88 (0.69-1.11); postmenopausal HR = 0.71 (0.58-0.88). No associations were observed for ER-/PR- disease. CONCLUSIONS: Recreational physical activity was associated with lower breast cancer risk in both pre- and postmenopausal women, supporting recreational physical activity as an accessible, modifiable exposure associated with reduced breast cancer risk regardless of menopausal status.

Reproductive risk factors for breast cancer and association with novel breast density measurements among Hispanic, Black, and White women.

PURPOSE: There are differences in the distributions of breast cancer incidence and risk factors by race and ethnicity. Given the strong association between breast density and breast cancer, it is of interest describe racial and ethnic variation in the determinants of breast density. METHODS: We characterized racial and ethnic variation in reproductive history and several measures of breast density for Hispanic (n = 286), non-Hispanic Black (n = 255), and non-Hispanic White (n = 1694) women imaged at a single hospital. We quantified associations between reproductive factors and percent volumetric density (PVD), dense volume (DV), non-dense volume (NDV), and a novel measure of pixel intensity variation (V) using multivariable-adjusted linear regression, and tested for statistical heterogeneity by race and ethnicity. RESULTS: Reproductive factors most strongly associated with breast density were age at menarche, parity, and oral contraceptive use. Variation by race and ethnicity was most evident for the associations between reproductive factors and NDV (minimum p-heterogeneity:0.008) and V (minimum p-heterogeneity:0.004) and least evident for PVD (minimum p-heterogeneity:0.042) and DV (minimum p-heterogeneity:0.041). CONCLUSION: Reproductive choices, particularly those related to childbearing and oral contraceptive use, may contribute to racial and ethnic variation in breast density.

Second primary non-breast cancers in young breast cancer survivors.

PURPOSE: We evaluated the incidence, timing, and risk factors for second primary non-breast cancers (SPNBC) among young breast cancer (BC) survivors. METHODS: This study included participants of the Young Women's BC Study (YWS) who were diagnosed with stage 0-III BC between 2006 and 2016 and age 40 or younger at diagnosis (N = 1,230). Patient characteristics, treatment information, and clinical events were collected via serial surveys. Tumor and treatment data were obtained from medical record review. Five- and 10-year risks of SPNBCs were estimated via the cumulative incidence function, considering death, metastasis, or second primary BC as competing events. Fine and Gray subdistribution hazard models estimated subdistribution hazard ratios (sHRs) and 95% confidence intervals (CI) for SPNBC risk based on risk factors including demographics, germline genetics, primary BC characteristics, and treatments. RESULTS: Among 1,230 women, over a median follow-up of 10.1 years, 47 patients (4%) developed an SPNBC. Types of malignancy included melanoma (n = 10), thyroid (n = 10), ovarian (n = 4), sarcoma (n = 4), uterine (n = 3), rectal (n = 3), bladder (n = 2), cervical (n = 2), head/neck (n = 2), lung (n = 2), lymphoma (n = 2), pancreatic (n = 2), and renal (n = 1). Five and 10-year cumulative incidence were 1.4% and 3.2%, respectively. Median time between primary BC and SPNBC was 7.3 years. No patient factors, primary tumor characteristics, or treatments were statistically significantly associated with SPNBC in univariable or multivariable models. CONCLUSION: In this population, five-year cumulative incidence was higher than that reported among healthy women under 50 years of age, highlighting the importance of long-term surveillance for new non-breast cancers in young adult BC survivors.

Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization.

PURPOSE: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). METHODS: We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. RESULTS: Genetically predicted BMI was positively associated with non-dense area (IVW: ß = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: ß = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (ß = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (ß = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches. CONCLUSION: Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.

Prostate-specific antigen testing rates in high-risk populations: results from the All of Us Research Program.

BACKGROUND: Early detection of prostate cancer using prostate-specific antigen (PSA) remains controversial and disparities in the receipt of prostate cancer screening persist in the US. We sought to examine disparities in PSA testing rates among groups with higher prostate cancer risk and differential access to healthcare. METHODS: We identified a cohort of 37,706 males within the All of Us Research Program without a history of prostate cancer between the ages of 40 and 85 at time of enrollment (2017-2021). Incidence rate ratios (IRR) for the number of PSA tests received during follow-up through December 2021 were estimated using age- and multivariable-adjusted negative binomial regression models. PSA testing frequencies in the cohort were compared with population-based estimates from the 2020 Behavioral Risk Factor Surveillance System (BRFSS). RESULTS: A total of 6,486 males (17.2%) received at least one PSA test over the course of follow-up. In multivariable-adjusted models, non-Hispanic Black males received PSA tests at a 17% lower rate (IRR = 0.83, 95% CI 0.76, 0.90) than non-Hispanic White males. Higher educational attainment, higher annual income, having self-/employer-purchased insurance, having a spouse or domestic partner, and having a family history of prostate cancer were all associated with higher rates of PSA testing. The proportion of males ages 55 to 69 who received a PSA test within two years was lower in All of Us (12.4%, 95% CI 11.8-13.0%) relative to population-based estimates from the BRFSS (35.2%, 95% CI 34.2-36.3%). CONCLUSION: Absolute PSA testing rates in All of Us were lower than population-based estimates, but associations with PSA testing in the cohort mirrored previously reported disparities in prostate cancer screening. These findings highlight the importance of addressing barriers to care in order to reduce disparities in cancer screening.

Heavy-metal associated breast cancer and colorectal cancer hot spots and their demographic and socioeconomic characteristics.

PURPOSE: Cancer registries offer an avenue to identify cancer clusters across large populations and efficiently examine potential environmental harms affecting cancer. The role of known metal carcinogens (i.e., cadmium, arsenic, nickel, chromium(VI)) in breast and colorectal carcinogenesis is largely unknown. Historically marginalized communities are disproportionately exposed to metals, which could explain cancer disparities. We examined area-based metal exposures and odds of residing in breast and colorectal cancer hotspots utilizing state tumor registry data and described the characteristics of those living in heavy metal-associated cancer hotspots. METHODS: Breast and colorectal cancer hotspots were mapped across Kentucky, and area-based ambient metal exposure to cadmium, arsenic, nickel, and chromium(VI) were extracted from the 2014 National Air Toxics Assessment for Kentucky census tracts. Among colorectal cancer (n = 56,598) and female breast cancer (n = 77,637) diagnoses in Kentucky, we used logistic regression models to estimate Odds Ratios (ORs) and 95% Confidence Intervals to examine the association between ambient metal concentrations and odds of residing in cancer hotspots, independent of individual-level and neighborhood risk factors. RESULTS: Higher ambient metal exposures were associated with higher odds of residing in breast and colorectal cancer hotspots. Populations in breast and colorectal cancer hotspots were disproportionately Black and had markers of lower socioeconomic status. Furthermore, adjusting for age, race, tobacco and neighborhood factors did not significantly change cancer hotspot ORs for ambient metal exposures analyzed. CONCLUSION: Ambient metal exposures contribute to higher cancer rates in certain geographic areas that are largely composed of marginalized populations. Individual-level assessments of metal exposures and cancer disparities are needed.

Association Between Inflammatory Dietary Pattern and Mammographic Features.

BACKGROUND: The empirical dietary inflammation pattern score (EDIP), which measures the ability of the diet to regulate chronic inflammation, is associated with both higher adiposity and breast cancer (BC) risk. Mammographic density (MD) is an important risk factor for BC. OBJECTIVE: We examined the associations between EDIP and mammographic features overall and stratified by menopausal status, and assessed the extent to which these associations are mediated by adiposity. METHODS: We included 4,145 participants without BC in the Nurses' Health Study (NHS) and NHSII. Cumulative average EDIP was assessed by food frequency questionnaires every 4-6 years. We assessed mammographic density (MD) parameters (percent MD, dense area, and non-dense area) and V (measure of grayscale variation). MD parameters were square root-transformed. Multivariable-adjusted linear regression models were used to analyze the associations between EDIP score and MD parameters. Baron and Kenny's regression method was used to assess the extent to which the associations of EDIP and mammographic traits were mediated by BMI. RESULTS: In multivariable-adjusted models, EDIP was significantly inversely associated with percent MD (top vs. bottom quartile, ß = -0.57, 95% CI: -0.78 - -0.36). Additional adjustment for BMI attenuated the association (ß= -0.15, 95% CI: -0.34 - 0.03), with 68% (ß= 0.68, 20 95% CI: 0.54-0.86) mediation via BMI. In addition, EDIP was positively associated with non-dense area after adjusting for BMI and other covariates. No associations were observed for dense area and V measure. Results were similar when stratified by menopausal status. CONCLUSION: EDIP score was inversely associated with percent MD and positively associated with non-dense area, and these associations were largely mediated by BMI.

Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts.

There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses' Health Study (NHS; n = 2077) and Women's Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences ≥ |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = - 0.98 standard deviations; 95% CI: - 1.11, - 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation.

Associations of alcohol consumption with breast tissue composition.

BACKGROUND: We investigated the associations of alcohol with percentage of epithelium, stroma, fibroglandular tissue (epithelium + stroma), and fat in benign breast biopsy samples. METHODS: We included 857 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII cohorts. Percentage of each tissue was measured on whole slide images using a deep-learning algorithm and then log-transformed. Alcohol consumption (recent and cumulative average) was assessed with semi-quantitative food frequency questionnaires. Regression estimates were adjusted for known breast cancer risk factors. All tests were 2-sided. RESULTS: Alcohol was inversely associated with % of stroma and fibroglandular tissue (recent ≥ 22 g/day vs. none: stroma: ß = - 0.08, 95% Confidence Interval [CI] - 0.13; - 0.03; fibroglandular: ß = - 0.08, 95% CI - 0.13; - 0.04; cumulative ≥ 22 g/day vs. none: stroma: ß = - 0.08, 95% CI - 0.13; - 0.02; fibroglandular: ß = - 0.09, 95% CI - 0.14; - 0.04) and positively associated with fat % (recent ≥ 22 g/day vs. none: ß = 0.30, 95% CI 0.03; 0.57; cumulative ≥ 22 g/day vs. none: ß = 0.32, 95% CI 0.04; 0.61). In stratified analysis, alcohol consumption was not associated with tissue measures in premenopausal women. In postmenopausal women, cumulative alcohol use was inversely associated with % of stroma and fibroglandular tissue and positively associated with fat % (≥ 22 g/day vs. none: stroma: ß = - 0.16, 95% CI - 0.28; - 0.07; fibroglandular: ß = - 0.18, 95% CI - 0.28; - 0.07; fat: ß = 0.61, 95% CI 0.01; 1.22), with similar results for recent alcohol use. CONCLUSION: Our findings suggest that alcohol consumption is associated with smaller % of stroma and fibroglandular tissue and a greater % of fat in postmenopausal women. Future studies are warranted to confirm our findings and to elucidate the underlying biological mechanisms.