The current evidence on statin use and prostate cancer prevention: are we there yet?

An increasing amount of data supports an inverse association between statin use and cancer risk. The findings for prostate cancer, particularly advanced disease, are the most promising of all cancers studied. Use of these agents seems to also be associated with improved prostate-cancer-specific survival, particularly in men undergoing radiotherapy, suggesting usefulness of statins in secondary and tertiary prevention. Some study results might be influenced by increased PSA screening and health-conscious behaviour in statin users but these factors are unlikely to completely account for observed beneficial effects. The epidemiological evidence is supported by preclinical studies that show that statins directly inhibit prostate cancer development and progression in cell-based and animal-based models. The antineoplastic effect of statins might arise from a number of cholesterol-mediated and non-cholesterol-mediated mechanisms that affect pathways essential for cancer formation and progression. Understanding these mechanisms is instrumental in drug discovery research for the development of future prostate cancer therapeutics, as well as in designing clinical trials to test a role for statins in prostate cancer prevention. Currently, sufficient data are lacking to support the use of statins for the primary prevention of prostate cancer and further research is clearly warranted. Secondary and tertiary prevention trials in men who have been diagnosed with prostate cancer might soon be performed

Increased Biodiversity in the Environment Improves the Humoral Response of Rats

Previous studies have compared the immune systems of wild and of laboratory rodents in an effort to determine how laboratory rodents differ from their naturally occurring relatives. This comparison serves as an indicator of what sorts of changes might exist between modern humans living in Western culture compared to our hunter-gatherer ancestors. However, immunological experiments on wild-caught animals are difficult and potentially confounded by increased levels of stress in the captive animals. In this study, the humoral immune responses of laboratory rats in a traditional laboratory environment and in an environment with enriched biodiversity were examined following immunization with a panel of antigens. Biodiversity enrichment included colonization of the laboratory animals with helminths and co-housing the laboratory animals with wild-caught rats. Increased biodiversity did not apparently affect the IgE response to peanut antigens following immunization with those antigens. However, animals housed in the enriched biodiversity setting demonstrated an increased mean humoral response to T-independent and T-dependent antigens and increased levels of “natural” antibodies directed at a xenogeneic protein and at an autologous tissue extract that were not used as immunogens

Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification

Abstract Background Spatial heterogeneity in biomarker expression may impact breast cancer classification. The aims of this study were to estimate the frequency of spatial heterogeneity in biomarker expression within tumors, to identify technical and biological factors contributing to spatial heterogeneity, and to examine the impact of discordant biomarker status within tumors on clinical record agreement. Methods Tissue microarrays (TMAs) were constructed using two to four cores (1.0 mm) for each of 1085 invasive breast cancers from the Carolina Breast Cancer Study, which is part of the AMBER Consortium. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) was quantified using automated digital imaging analysis. The biomarker status for each core and for each case was assigned using clinical thresholds. Cases with core-to-core biomarker discordance were manually reviewed to distinguish intratumoral biomarker heterogeneity from misclassification of biomarker status by the automated algorithm. The impact of core-to-core biomarker discordance on case-level agreement between TMAs and the clinical record was evaluated. Results On the basis of automated analysis, discordant biomarker status between TMA cores occurred in 9 %, 16 %, and 18 % of cases for ER, PR, and HER2, respectively. Misclassification of benign epithelium and/or ductal carcinoma in situ as invasive carcinoma by the automated algorithm was implicated in discordance among cores. However, manual review of discordant cases confirmed spatial heterogeneity as a source of discordant biomarker status between cores in 2 %, 7 %, and 8 % of cases for ER, PR, and HER2, respectively. Overall, agreement between TMA and clinical record was high for ER (94 %), PR (89 %), and HER2 (88 %), but it was reduced in cases with core-to-core discordance (agreement 70 % for ER, 61 % for PR, and 57 % for HER2). Conclusions Intratumoral biomarker heterogeneity may impact breast cancer classification accuracy, with implications for clinical management. Both manually confirmed biomarker heterogeneity and misclassification of biomarker status by automated image analysis contribute to discordant biomarker status between TMA cores. Given that manually confirmed heterogeneity is uncommon (<10 % of cases), large studies are needed to study the impact of heterogeneous biomarker expression on breast cancer classification and outcomes

Performance of Three-Biomarker Immunohistochemistry for Intrinsic Breast Cancer Subtyping in the AMBER Consortium

Classification of breast cancer into intrinsic subtypes has clinical and epidemiologic importance. To examine accuracy of immunohistochemistry (IHC)-based methods for identifying intrinsic subtypes, a three-biomarker IHC panel was compared to the clinical record and RNA-based intrinsic (PAM50) subtypes

Racial Differences in PAM50 Subtypes in the Carolina Breast Cancer Study

Background: African American breast cancer patients have lower frequency of hormone receptor-positive (HR+)/human epidermal growth factor receptor 2 (HER2)-negative disease and higher subtype-specific mortality. Racial differences in molecular subtype within clinically defined subgroups are not well understood. Methods: Using data and biospecimens from the population-based Carolina Breast Cancer Study (CBCS) Phase 3 (2008-2013), we classified 980 invasive breast cancers using RNA expression-based PAM50 subtype and recurrence (ROR) score that reflects proliferation and tumor size. Molecular subtypes (Luminal A, Luminal B, HER2-enriched, and Basal-like) and ROR scores (high vs low/medium) were compared by race (blacks vs whites) and age (≤50 years vs≥50 years) using chi-square tests and analysis of variance tests. Results: Black women of all ages had a statistically significantly lower frequency of Luminal A breast cancer (25.4% and 33.6% in blacks vs 42.8% and 52.1% in whites; younger and older, respectively). All other subtype frequencies were higher in black women (case-only odds ratio [OR] = 3.11, 95% confidence interval [CI] = 2.22 to 4.37, for Basal-like; OR=1.45, 95% CI=1.02 to 2.06, for Luminal B; OR=2.04, 95% CI=1.33 to 3.13, for HER2-enriched). Among clinically HR+/HER2- cases, Luminal A subtype was less common and ROR scores were statistically significantly higher among black women. Conclusions: Multigene assays highlight racial disparities in tumor subtype distribution that persist even in clinically defined subgroups. Differences in tumor biology (eg, HER2-enriched status) may be targetable to reduce disparities among clinically ER+/HER2- cases

Frequency of breast cancer subtypes among African American women in the AMBER consortium

Abstract Background Breast cancer subtype can be classified using standard clinical markers (estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2)), supplemented with additional markers. However, automated biomarker scoring and classification schemes have not been standardized. The aim of this study was to optimize tumor classification using automated methods in order to describe subtype frequency in the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Methods Using immunohistochemistry (IHC), we quantified the expression of ER, PR, HER2, the proliferation marker Ki67, and two basal-like biomarkers, epidermal growth factor receptor (EGFR) and cytokeratin (CK)5/6, in 1381 invasive breast tumors from African American women. RNA-based (prediction analysis of microarray 50 (PAM50)) subtype, available for 574 (42%) cases, was used to optimize classification. Subtype frequency was calculated, and associations between subtype and tumor characteristics were estimated using logistic regression. Results Relative to ER, PR and HER2 from medical records, central IHC staining and the addition of Ki67 or combined tumor grade improved accuracy for classifying PAM50-based luminal subtypes. Few triple negative cases (< 2%) lacked EGFR and CK5/6 expression, thereby providing little improvement in accuracy for identifying basal-like tumors. Relative to luminal A subtype, all other subtypes had higher combined grade and were larger, and ER-/HER2+ tumors were more often lymph node positive and late stage tumors. The frequency of basal-like tumors was 31%, exceeded only slightly by luminal A tumors (37%). Conclusions Our findings indicate that automated IHC-based classification produces tumor subtype frequencies approximating those from PAM50-based classification and highlight high frequency of basal-like and low frequency of luminal A breast cancer in a large study of African American women

Obesity and cancer: mechanistic insights from transdisciplinary studies

Obesity is associated with a range of health outcomes that are of clinical and public health significance, including cancer. Herein, we summarize epidemiologic and preclinical evidence for an association between obesity and increased risk of breast and prostate cancer incidence and mortality. Moreover, we describe data from observational studies of weight change in humans and from calorie restriction studies in mouse models which support a potential role for weight loss in counteracting tumor-promoting properties of obesity in breast and prostate cancers. Given that weight loss is challenging to achieve and maintain, we also consider evidence linking treatments for obesity-associated co-morbidities, including metformin, statins and non-steroidal anti-inflammatory drugs, with reduced breast and prostate cancer incidence and mortality. Finally, we highlight several challenges that should be considered when conducting epidemiologic and preclinical research in the area of obesity and cancer, including the measurement of obesity in population-based studies, the timing of obesity and weight change in relation to tumor latency and cancer diagnosis, and the heterogeneous nature of obesity and its associated co-morbidities. Given that obesity is a complex trait, comprised of behavioral, epidemiologic and molecular/metabolic factors, we argue that a transdisciplinary approach is the key to understanding the mechanisms linking obesity and cancer. As such, this review highlights the critical need to integrate evidence from both epidemiologic and preclinical studies to gain insight into both biologic and non-biologic mechanisms contributing to the obesity-cancer link