Prostate cancer (PCa) patients are risk-stratified on the basis of clinical stage and PSA level at diagnosis and the Gleason Score (GS) in prostate biopsy. However, these parameters are not completely accurate in discriminating between high- and low-risk disease, creating a need for a reliable marker to determine aggressiveness. Prostate-specific membrane antigen (PSMA) appears to fulfill this need. We analyzed 79 prostate biopsies and 28 prostatectomies to assess whether PSMA expression detected by immunohistochemistry is related to GS. PSMA expression was correlated with GS in both sample types (biopsies, P < 0.0001 and prostatectomy samples, P = 0.007). We observed lower PSMA expression in Gleason pattern 3 than Gleason pattern 4, suggesting that this biomarker could be useful to distinguish between these entities (p < 0.0001). The best cut-off value of 45% immunopositivity was determined by receiver operating characteristic (ROC) curve analysis. In Gleason pattern 3 vs. Gleason pattern 4 and 5, PSMA sensitivity was 84.1% (95% CI 76.5%-91.7%) and specificity was 95.2% (95% CI 90.6%-99.8%), with an area under the curve of 93.1 (95% CI 88.8–97.4). Our results suggest that PSMA represents a potential ally for the pathologist in the diagnostic work-up of PCa to overcome long-standing morphological classification limits.

The androgen receptor (AR) is a ligand-dependent transcription factor, and its effects on breast range from physiological pubertal development and age-related modifications to cancer onset and proliferation. The prevalence of AR in early breast cancer is around 60%, and AR is more frequently expressed in ER-positive than in ER-negative tumors. We offer an overview of AR signaling pathways in different breast cancer subtypes, providing evidence that its oncogenic role is likely to be different in distinct biological and clinical scenarios. In particular, in ER-positive breast cancer, AR signaling often antagonizes the growth stimulatory effect of ER signaling; in triple-negative breast cancer (TNBC), AR seems to drive tumor progression (at least in luminal AR subtype of TNBC with a gene expression profile mimicking luminal subtypes despite being negative to ER and enriched in AR expression); in HER2-positive breast cancer, in the absence of ER expression, AR signaling has a proliferative role. These data represent the rationale for AR-targeting treatment as a potentially new target therapy in breast cancer subset using androgen agonists in some AR-positive/ER-positive tumors, AR antagonists in triple-negative/ AR-positive tumors and in combination with anti-HER2 agents or with other signaling pathways inhibitors (including PI3K/MYC/ERK) in HER2-positive/AR-positive tumors. Only the ongoing and future prospective clinical trials will allow us to establish which agents are the best option in every specific condition, keeping in mind that there is evidence of opposite androgens and AR agonist/antagonist drug effects on cell proliferation particularly in AR-positive/ER-positive tumors.

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia associated with alterations in carbohydrate, lipid, and protein metabolism. The prognosis of T2DM patients is highly dependent on the development of complications, and therefore the identification of biomarkers of T2DM progression, with minimally invasive techniques, is a huge need. In the present study, we applied a 1H-Nuclear Magnetic Resonance (1H-NMR)-based metabolomic approach coupled with multivariate data analysis to identify serum metabolite profiles associated with T2DM development and progression. To perform this, we compared the serum metabolome of non-diabetic subjects, treatment-naïve non-complicated T2DM patients, and T2DM patients with complications in insulin monotherapy. Our analysis revealed a significant reduction of alanine, glutamine, glutamate, leucine, lysine, methionine, tyrosine, and phenylalanine in T2DM patients with respect to non-diabetic subjects. Moreover, isoleucine, leucine, lysine, tyrosine, and valine levels distinguished complicated patients from patients without complications. Overall, the metabolic pathway analysis suggested that branched-chain amino acid (BCAA) metabolism is significantly compromised in T2DM patients with complications, while perturbation in the metabolism of gluconeogenic amino acids other than BCAAs characterizes both early and advanced T2DM stages. In conclusion, we identified a metabolic serum signature associated with T2DM stages. These data could be integrated with clinical characteristics to build a composite T2DM/complications risk score to be validated in a prospective cohort.