Cafeteria diet-induced obesity causes oxidative damage in white adipose

Obesity continues to be one of the most prominent public health dilemmas in the world. The complex interaction among the varied causes of obesity makes it a particularly challenging problem to address. While typical high-fat purified diets successfully induce weight gain in rodents, we have described a more robust model of diet-induced obesity based on feeding rats a diet consisting of highly palatable, energy-dense human junk foods – the “cafeteria” diet (CAF, 45-53% kcal from fat). We previously reported that CAF-fed rats became hyperphagic, gained more weight, and developed more severe hyperinsulinemia, hyperglycemia, and glucose intolerance compared to the lard-based 45% kcal from fat high fat diet–fed group. In addition, the CAF diet-fed group displayed a higher degree of inflammation in adipose and liver, mitochondrial dysfunction, and an increased concentration of lipid-derived, pro-inflammatory mediators. Building upon our previous findings, we aimed to determine mechanisms that underlie physiologic findings in the CAF diet. We investigated the effect of CAF diet-induced obesity on adipose tissue specifically using expression arrays and immunohistochemistry. Genomic evidence indicated the CAF diet induced alterations in the white adipose gene transcriptome, with notable suppression of glutathione-related genes and pathways involved in mitigating oxidative stress. Immunohistochemical analysis indicated a doubling in adipose lipid peroxidation marker 4-HNE levels compared to rats that remained lean on control standard chow diet. Our data indicates that the CAF diet drives an increase in oxidative damage in white adipose tissue that may affect tissue homeostasis. Oxidative stress drives activation of inflammatory kinases that can perturb insulin signaling leading to glucose intolerance and diabetes

Healthy Worker Survivor Bias in the Colorado Plateau Uranium Miners Cohort

Cohort mortality studies of underground miners have been used to estimate the number of lung cancer deaths attributable to radon exposure. However, previous studies of the radon–lung cancer association among underground miners may have been subject to healthy worker survivor bias, a type of time-varying confounding by employment status. We examined radon-mortality associations in a study of 4,124 male uranium miners from the Colorado Plateau who were followed from 1950 through 2005. We estimated the time ratio (relative change in median survival time) per 100 working level months (radon exposure averaging 130,000 mega-electron volts of potential α energy per liter of air, per working month) using G-estimation of structural nested models. After controlling for healthy worker survivor bias, the time ratio for lung cancer per 100 working level months was 1.168 (95% confidence interval: 1.152, 1.174). In an unadjusted model, the estimate was 1.102 (95% confidence interval: 1.099, 1.112)—39% lower. Controlling for this bias, we estimated that among 617 lung cancer deaths, 6,071 person-years of life were lost due to occupational radon exposure during follow-up. Our analysis suggests that healthy worker survivor bias in miner cohort studies can be substantial, warranting reexamination of current estimates of radon's estimated impact on lung cancer mortality

Associations among personal care product use patterns and exogenous hormone use in the NIEHS Sister Study

It is hypothesized that certain chemicals in personal care products may alter the risk of adverse health outcomes. The primary aim of this study was to use a data-centered approach to classify complex patterns of exposure to personal care products and to understand how these patterns vary according to use of exogenous hormone exposures, oral contraceptives (OCs) and post-menopausal hormone therapy (HT). The NIEHS Sister Study is a prospective cohort study of 50,884 US women. Limiting the sample to non-Hispanic blacks and whites (N = 47,019), latent class analysis (LCA) was used to identify groups of individuals with similar patterns of personal care product use based on responses to 48 survey questions. Personal care products were categorized into three product types (beauty, hair, and skincare products) and separate latent classes were constructed for each type. Adjusted prevalence differences (PD) were calculated to estimate the association between exogenous hormone use, as measured by ever/never OC or HT use, and patterns of personal care product use. LCA reduced data dimensionality by grouping of individuals with similar patterns of personal care product use into mutually exclusive latent classes (three latent classes for beauty product use, three for hair, and four for skin care. There were strong differences in personal care usage by race, particularly for haircare products. For both blacks and whites, exogenous hormone exposures were associated with higher levels of product use, especially beauty and skincare products. Relative to individual product use questions, latent class variables capture complex patterns of personal care product usage. These patterns differed by race and were associated with ever OC and HT use. Future studies should consider personal care product exposures with other exogenous exposures when modeling health risks

Molecular features of androgen-receptor low, estrogen receptor-negative breast cancers in the Carolina breast cancer study

Purpose: Androgen receptor (AR) expression is absent in 40–90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored. Methods: We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; N = 669) and The Cancer Genome Atlas (TCGA; N = 237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response]. Results: AR-low tumors were more prevalent among younger (RFD = + 10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2 negativity (RFD = − 35%, 95% CI = − 44% to − 26%), higher grade (RFD = + 17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD = + 22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD = + 33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD = + 41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression. Conclusion: Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients

Risk factors for Luminal A ductal carcinoma in situ (DCIS) and invasive breast cancer in the Carolina Breast Cancer Study

Purpose Invasive breast cancers are thought to arise from in situ lesions, but some ductal carcinoma in situ (DCIS) are indolent with low likelihood of progressing to invasive carcinoma. Comparison of risk factor associations between DCIS and invasive disease may elucidate which factors influence early versus late stages of carcinogenesis. Therefore, we determined whether there were differences in risk factor profiles for screen-detected DCIS and invasive breast cancer among Luminal A lesions. Methods We conducted a case-control analysis using data from the Carolina Breast Cancer Study (1993-2001). Analyses were restricted to Luminal A tumors and screen-detected tumors among mammography-eligible women, to limit confounding by mode of detection (N = 108 DCIS; N = 203 invasive). Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between risk factors and lesion type. Results In stratified analyses, we observed qualitative differences in the direction of association for ever smoking, obese BMI, high waist-To-hip-ratio (WHR), and ?10 years of oral contraceptive use between DCIS and invasive disease. Breastfeeding was inversely associated with invasive disease and was not associated with DCIS. Interaction tests for risk factor associations between Luminal A DCIS and invasive breast cancer were not statistically significant (p>0.05). Conclusions Among Luminal A tumors, established breast cancer risk factors may exert stronger effects on progression of early lesions to invasive disease, with lesser effects on risk of DCIS

Non-steroidal anti-inflammatory drug use, hormone receptor status, and breast cancer-specific mortality in the Carolina Breast Cancer Study

Epidemiologic studies report a protective association between non-steroidal anti-inflammatory drug (NSAID) use and hormone receptor-positive breast cancer risk, a finding consistent with NSAID-mediated suppression of aromatase-driven estrogen biosynthesis. However, the association between NSAID use and breast cancer-specific mortality is uncertain and it is unknown whether this relationship differs by hormone receptor status. This study comprised 935 invasive breast cancer cases, of which 490 were estrogen receptor (ER)-positive, enrolled between 1996 and 2001 in the Carolina Breast Cancer Study. Self-reported NSAID use in the decade prior to diagnosis was categorized by duration and regularity of use. Differences in tumor size, stage, node, and receptor status by NSAID use were examined using Chi-square tests. Associations between NSAID use and breast cancer-specific mortality were examined using age- and race-adjusted Cox proportional hazards analysis. Tumor characteristics did not differ by NSAID use. Increased duration and regularity of NSAID use was associated with reduced breast cancer-specific mortality in women with ER-positive tumors (long-term regular use (≥8 days/month for ≥ 3 - years) versus no use; hazard ratio (HR) 0.48; 95 % confidence interval (CI) 0.23–0.98), with a statistically significant trend with increasing duration and regularity (p-trend = 0.036). There was no association for ER-negative cases (HR 1.19; 95 %CI 0.50–2.81; p-trend = 0.891). Long-term, regular NSAID use in the decade prior to breast cancer diagnosis was associated with reduced breast cancer-specific mortality in ER-positive cases. If confirmed, these findings support the hypothesis that potential chemopreventive properties of NSAIDs are mediated, at least in part, through suppression of estrogen biosynthesis

Metabolic reprogramming of macrophages: Glucose transporter 1 (GLUT1)-mediated glucose metabolism drives a proinflammatory phenotype

Glucose is a critical component in the proinflammatory response of macrophages (MΦs). However, the contribution of glucose transporters (GLUTs) and the mechanisms regulating subsequent glucose metabolism in the inflammatory response are not well understood. Because MΦs contribute to obesity-induced inflammation, it is important to understand how substrate metabolism may alter inflammatory function. We report that GLUT1 (SLC2A1) is the primary rate-limiting glucose transporter on proinflammatory-polarized MΦs. Furthermore, in high fat diet-fed rodents, MΦs in crown-like structures and inflammatory loci in adipose and liver, respectively, stain positively for GLUT1. We hypothesized that metabolic reprogramming via increased glucose availability could modulate the MΦ inflammatory response. To increase glucose uptake, we stably overexpressed the GLUT1 transporter in RAW264.7 MΦs (GLUT1-OE MΦs). Cellular bioenergetics analysis, metabolomics, and radiotracer studies demonstrated that GLUT1 overexpression resulted in elevated glucose uptake and metabolism, increased pentose phosphate pathway intermediates, with a complimentary reduction in cellular oxygen consumption rates. Gene expression and proteome profiling analysis revealed that GLUT1-OE MΦs demonstrated a hyperinflammatory state characterized by elevated secretion of inflammatory mediators and that this effect could be blunted by pharmacologic inhibition of glycolysis. Finally, reactive oxygen species production and evidence of oxidative stress were significantly enhanced in GLUT1-OEMΦs; antioxidant treatment blunted the expression of inflammatory mediators such as PAI-1 (plasminogen activator inhibitor 1), suggesting that glucose-mediated oxidative stress was driving the proinflammatory response. Our results indicate that increased utilization of glucose induced a ROS-driven proinflammatory phenotype in MΦs, which may play an integral role in the promotion of obesity-associated insulin resistance

Anti-Mullerian Hormone Concentrations in Premenopausal Women and Breast Cancer Risk

Laboratory models support an inverse association between anti-Müllerian hormone (AMH) and breast tumor development. Human studies are lacking; one study (N=105 cases, 204 controls) with prospectively-collected serum reported the opposite—an approximate 10-fold increase in breast cancer risk comparing 4th to 1st quartile AMH levels. We investigated the relation between serum AMH levels and breast cancer risk in a case-control (N=452 cases, 902 controls) study nested within the prospective Sister Study cohort of 50,884 women. At enrollment, participants were ages 35-54, premenopausal, and completed questionnaires on medical and family history, lifestyle factors, and demographics. AMH (ng/ml) was measured by ultrasensitive ELISA in serum collected at enrollment and log-transformed for analysis. Multivariate conditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) to account for matching on age and enrollment year. Mean age at enrollment was 46.8 years with an average 2.9 years from blood draw to breast cancer diagnosis (SD=1.9). AMH concentrations were below the limit of detection (0.003 ng/ml) for ~25% of samples. Compared with samples below the LOD, women with AMH >2.84 ng/ml (90th percentile among controls) had a two-fold increase in breast cancer odds (OR=2.25; 95% CI: 1.26-4.02). For each 1-unit increase in lnAMH, overall breast cancer odds increased by 8% (OR=1.08; 95% CI: 1.02-1.15) and odds of ER-positive, invasive disease increased by 15% (OR=1.15; 95% CI: 1.05-1.25). Our findings demonstrate an overall positive relation between AMH and breast cancer

Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples

Abstract Background Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. Methods To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Results Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Conclusions Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor