[Early Experience with MRI-Ultrasound Fusion-Guided Prostate Biopsy in Our Institution].

A total of 100 patients were retrospectively analyzed with magnetic resonance imaging-ultrasonography (MRI-US) fusion biopsy(KOELIS, TRINITY®) at our institution between October 2019 and May 2020. The median patient age was 71 years, median prostate specific antigen (PSA) level was 7.4 ng/ml, and median PSA-density was 0.183 mg/ml. Sixty-one of the patients were positive for cancer ; 14 of them were positive by targeted biopsy only, 9 were positive by systematic biopsy only, and 38 were positive by both. Clinically significant prostate cancer (CPSC ; Gleason Score ≥3＋4 and % core ≥50%) was detected by target biopsies in 46 patients and by systematic biopsies in 33 patients. The positive core detection rate for CSPC was 32.5% for targeted biopsies and 7.0% for systematic biopsies(P＜0.0001), with a significantly higher rate for targeted biopsies. These results indicate that in MRI-US fusion biopsy, targeted biopsy has a higher detection rate for cancer and a significantly higher detection rate for clinically significant prostate cancer compared with systematic biopsy.

A new bioinformatics approach identifies overexpression of GRB2 as a poor prognostic biomarker for prostate cancer.

A subset of prostate cancer displays a poor clinical outcome. Therefore, identifying this poor prognostic subset within clinically aggressive groups (defined as a Gleason score (GS) ≧8) and developing effective treatments are essential if we are to improve prostate cancer survival. Here, we performed a bioinformatics analysis of a TCGA dataset (GS ≧8) to identify pathways upregulated in a prostate cancer cohort with short survival. When conducting bioinformatics analyses, the definition of factors such as "overexpression" and "shorter survival" is vital, as poor definition may lead to mis-estimations. To eliminate this possibility, we defined an expression cutoff value using an algorithm calculated by a Cox regression model, and the hazard ratio for each gene was set so as to identify genes whose expression levels were associated with shorter survival. Next, genes associated with shorter survival were entered into pathway analysis to identify pathways that were altered in a shorter survival cohort. We identified pathways involving upregulation of GRB2. Overexpression of GRB2 was linked to shorter survival in the TCGA dataset, a finding validated by histological examination of biopsy samples taken from the patients for diagnostic purposes. Thus, GRB2 is a novel biomarker that predicts shorter survival of patients with aggressive prostate cancer (GS ≧8).