PSMA expression: a potential ally for the pathologist in prostate cancer diagnosis

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

Genomic profiles of primary and metastatic esophageal adenocarcinoma identified via digital sorting of pure cell populations: results from a case report

Abstract Background We report on a female patient who underwent primary radical resection for a stage 2B Her-2-positive Barrett’s-type esophageal adenocarcinoma (EAC). Despite Her-2 targeted therapy, her disease recurred and required repeated metastectomies. Case presentation Digital cell sorting and targeted sequencing of cancer sub-clones from EAC and metastases revealed a completely mutated TP53, whereas the sorted stromal cells were wild-type. Her-2 amplification was significantly lower in the metastases when the patient became therapy-resistant. Conclusions The mechanism of therapy resistance illustrated by this case could only be detected through accurate analysis of tumor sub-populations. Investigating tumor sub-populations of recurrent disease is important for adjusting therapy in recurrent EAC

The Prognostic Impact of Histology in Esophageal and Esophago-Gastric Junction Adenocarcinoma

Stage significantly affects survival of esophageal and esophago-gastric junction adenocarcinomas (EA/EGJAs), however, limited evidence for the prognostic role of histologic subtypes is available. The aim of the study was to describe a morphologic approach to EA/EGJAs and assess its discriminating prognostic power. Histologic slides from 299 neoadjuvant treatment-naïve EA/EGJAs, resected in five European Centers, were retrospectively reviewed. Morphologic features were re-assessed and correlated with survival. In glandular adenocarcinomas (240/299 cases—80%), WHO grade and tumors with a poorly differentiated component ≥6% were the most discriminant factors for survival (both p 72 years (p = 0.008), and vascular invasion (p = 0.015) were prognostically significant in the multivariate analysis. The combined evaluation of stage/histologic group identified 5-year cancer-specific survival ranging from 87.6% (stage II, lower risk) to 14% (stage IVA, higher risk). Detailed characterization of histologic subtypes contributes to EA/EGJA prognostic prediction

Genomic profiles of primary and metastatic esophageal adenocarcinoma identified via digital sorting of pure cell populations: Results from a case report

Background: We report on a female patient who underwent primary radical resection for a stage 2B Her-2-positive Barrett's-type esophageal adenocarcinoma (EAC). Despite Her-2 targeted therapy, her disease recurred and required repeated metastectomies. Case presentation: Digital cell sorting and targeted sequencing of cancer sub-clones from EAC and metastases revealed a completely mutated TP53, whereas the sorted stromal cells were wild-type. Her-2 amplification was significantly lower in the metastases when the patient became therapy-resistant. Conclusions: The mechanism of therapy resistance illustrated by this case could only be detected through accurate analysis of tumor sub-populations. Investigating tumor sub-populations of recurrent disease is important for adjusting therapy in recurrent EAC