Male breast cancer remains understudied despite evidence of rising incidence. Using a co-ordinated multi-centre approach, we present the first large scale biomarker study to define and compare hormone receptor profiles and survival between male and female invasive breast cancer. We defined and compared hormone receptor profiles and survival between 251 male and 263 female breast cancers matched for grade, age, and lymph node status. Tissue microarrays were immunostained for ERα, ERβ1, -2, -5, PR, PRA, PRB and AR, augmented by HER2, CK5/6, 14, 18 and 19 to assist typing. Hierarchical clustering determined differential nature of influences between genders. Luminal A was the most common phenotype in both sexes. Luminal B and HER2 were not seen in males. Basal phenotype was infrequent in both. No differences in overall survival at 5 or 10 years were observed between genders. Notably, AR-positive luminal A male breast cancer had improved overall survival over female breast cancer at 5 (P = 0.01, HR = 0.39, 95% CI = 0.26-0.87) but not 10 years (P = 0.29, HR = 0.75, 95% CI = 0.46-1.26) and both 5 (P = 0.04, HR = 0.37, 95% CI = 0.07-0.97) and 10 years (P = 0.04, HR = 0.43, 95% CI = 0.12-0.97) in the unselected group. Hierarchical clustering revealed common clusters between genders including total PR-PRA-PRB and ERβ1/2 clusters. A striking feature was the occurrence of ERα on distinct clusters between genders. In female breast cancer, ERα clustered with PR and its isoforms; in male breast cancer, ERα clustered with ERβ isoforms and AR. Our data supports the hypothesis that breast cancer is biologically different in males and females suggesting implications for clinical management. With the incidence of male breast cancer increasing this provides impetus for further study.

Increased eukaryotic translation initiation factor 4E (eIF4E) expression occurs in many cancers, and makes fundamental contributions to carcinogenesis by stimulating the expression of cancer-related genes at post-transcriptional levels. This key role is highlighted by the facts that eIF4E levels can predict prognosis, and that eIF4E is an established therapeutic target. However, eIF4E activity is a complex function of expression levels and phosphorylation statuses of eIF4E and eIF4E-binding proteins (4E-BPs). Our hypothesis was that the combined analyses of these pathway components would allow insights into eIF4E activity and its influence on cancer. We have determined expression levels of eIF4E, 4E-BP1, 4E-BP2 and phosphorylated 4E-BP1 within 424 breast tumours, and have carried out analyses to combine these and relate the product to patient survival, in order to estimate eIF4E activity. We show that this analysis gives greater prognostic insights than that of eIF4E alone. We show that eIF4E and 4E-BP expression are positively associated, and that 4E-BP2 has a stronger influence on cancer behaviour than 4E-BP1. Finally, we examine eIF4E, estimated eIF4E activity, and phosphorylated 4E-BP1 as potential predictive biomarkers for eIF4E-targeted therapies, and show that each determines selection of different patient groups. We conclude that eIF4E's influence on cancer survival is modulated substantially by 4E-BPs, and that combined pathway analyses can estimate functional eIF4E.

Objective The pathologic validation of European Alzheimer's Disease Consortium Alzheimer's Disease Neuroimaging Center Harmonized Hippocampal Segmentation Protocol (HarP). Methods Temporal lobes of nine Alzheimer's disease (AD) and seven cognitively normal subjects were scanned post-mortem at 7 Tesla. Hippocampal volumes were obtained with HarP. Six-micrometer-thick hippocampal slices were stained for amyloid beta (Aβ), tau, and cresyl violet. Hippocampal subfields were manually traced. Neuronal counts, Aβ, and tau burden for each hippocampal subfield were obtained. Results We found significant correlations between hippocampal volume and Braak and Braak staging (ρ = −0.75, P = .001), tau (ρ = −0.53, P = .034), Aβ burden (ρ = −0.61, P = .012), and neuronal count (ρ = 0.77, P < .001). Exploratory subfield-wise significant associations were found for Aβ in CA1 (ρ = −0.58, P = .019) and subiculum (ρ = −0.75, P = .001), tau in CA2 (ρ = −0.59, P = .016), and CA3 (ρ = −0.5, P = .047), and neuronal count in CA1 (ρ = 0.55, P = .028), CA3 (ρ = 0.65, P = .006), and CA4 (ρ = 0.76, P = .001). Conclusions The observed associations provide the pathological confirmation of hippocampal morphometry as a valid biomarker for AD and the pathologic validation of HarP.

The thymus is routinely encountered on cross-sectional imaging studies of the chest. It has a variable appearance, undergoes dynamic changes during periods of stress, and demonstrates numerous different pathologic lesions. Understanding the imaging characteristics of these different lesions facilitates accurate radiographic diagnosis and can prevent unnecessary follow-up imaging and intervention. This article will review normal thymic anatomy and development, thymic hyperplasia and associated medical conditions, and the imaging and pathologic features of various benign and malignant thymic lesions.