A color/near-infrared camera inspired by the mantis shrimp visual system enables tumor detection and lymph node mapping during cancer surgery.

Despite the overall success of prostate specific antigen (PSA) in screening and detection of prostate cancer (PCa), its use has been limited due to the lack of specificity. The principal driving goal currently within PCa research is to identify non-invasive biomarker(s) for early detection of aggressive tumors with greater sensitivity and specificity than PSA. In this study, we focused on identification of non-invasive biomarkers in urine with higher specificity than PSA. We tested urine samples from PCa and benign prostatic hyperplasia (BPH) patients by 2-D DIGE coupled with MS and bioinformatics analysis. Statistically significant (p < 0.05), 1.8 fold variation or more in abundance, showed 41 spots, corresponding to 23 proteins. The Ingenuity Pathway Analysis showed significant association with the Acute Phase Response Signaling pathway. Nine proteins with differential abundances were included in this pathway: AMBP, APOA1, FGA, FGG, HP, ITIH4, SERPINA1, TF and TTR. The expression pattern of 4 acute phase response proteins differed from the defined expression in the canonical pathway. The urine levels of TF, AMPB and HP were measured by immunoturbidimetry in an independent validation set. The concentration of AMPB in urine was significantly higher in PCa while levels of TF and HP were opposite (p < 0.05). The AUC for the individual proteins ranged from 0.723 to 0.754. The combination of HP and AMBP yielded the highest accuracy (AUC = 0.848), greater than PSA. The proposed biomarker set is quickly quantifiable and economical with potential to improve the sensitivity and specificity of PCa detection.

Detecting prostate cancer (PCa) using non-invasive diagnostic markers still remains a challenge. The aim of this study was the identification of urine proteins that are sufficiently sensitive and specific to detect PCa in the early stages. Comparative proteomics profiling of urine from patients with PCa, benign prostate hyperplasia, bladder cancer, and renal cancer, coupled with bioinformatics analysis, were performed. Statistically significant difference in abundance showed 20 and 85 proteins in the 2-D DIGE/MS and label-free LC-MS/MS experiments, respectively. In silico analysis indicated activation, binding, and cell movement of subset of immune cells as the top affected cellular functions in PCa, together with the down-regulation of Acute Phase Response Signaling and Liver X Receptor/ Retinoid X Receptor (LXR/RXR) activation pathways. The most promising biomarkers were 35, altered in PCa when compared to more than one group. Half of these have confirmed localization in normal or PCa tissues. Twenty proteins (CD14, AHSG, ENO1, ANXA1, CLU, COL6A1, C3, FGA, FGG, HPX, PTGDS, S100A9, LMAN2, ITIH4, ACTA2, GRN, HBB, PEBP1, CTSB, SPP1) are oncogenes, tumor suppressors, and multifunctional proteins with highly confirmed involvement in PCa, while 9 (AZU1, IGHG1, RNASE2, PZP, REG1A, AMY1A, AMY2A, ACTG2, COL18A1) have been associated with different cancers, but not with PCa so far, and may represent novel findings. LC-MS/MS data are available via ProteomeXchange with identifier PXD008407.

Objective: This study aimed to measure the AHNAK2 urinary levels in bladder cancer patients. Material and methods: This prospective case–control study enrolled 67 participants between January and March 2019 and were categorized into bladder cancer group (n=37), with histologically proven bladder cancer, and control group (n=30), with histologically verified benign lesions or with no bladder cancer indication during follow-up. Urine samples of 15 mL were collected in the mid-morning before cystoscopy/surger y and an enzyme-linked immunosorbent assay was performed as per the manufacturer’s protocol. Bladder malignancies were classified according to the World Health Organization Tumor Classification. Group’s associations were evaluated with the Student t-test, Spearman’s rank correlation, and Mann–Whitney U test, while receiver operating curve was plotted for assessing the test’s performance. Results: Mean age of the bladder cancer group was 66.41 years (standard deviation=10.04, range=43-82 years) and the control group was 59.67 years (standard deviation=10.44, range=38-77 years). All bladder cancers were of the urothelial histotype, with the following pT distribution: pTa/papillary urothelial neoplasm of low malignant potential (n=19; 28.4%), Primary tumor (pT) in situ (n=4; 6%), pT1 (n=7; 10.4%), and pT≥2 (n=7; 10.48%). Mean AHNAK2 levels were higher in bladder cancer patients 49.08 pg/mL (standard deviation=114.91) compared to controls 5.28 pg/mL (standard deviation=6.65), P < .05). Significant differences were noted between non-invasive bladder cancer (n=23; mean=7.14 pg/mL; standard deviation=7.26) and invasive bladder cancer (n=14; mean=117.99 pg/mL; standard deviation=168.08) and between non-muscle invasive bladder cancer (mean=23.19 pg/mL; standard deviation=66.93) and muscle-invasive bladder cancer (mean=160.05 pg/mL; standard deviation=199.65) (P < .001). The result of the assays was given as follows: sensitivity: 64.19%, specificity: 66.67%, positive predictive value: 22.07%, negative predictive value: 92.37%, area under curve: 0.695, and 95% CI: 0.57-0.82. Conclusion: AHNAK2 protein could be used as bladder cancer surveillance biomarker. The inclusion of AHNAK2 levels in stratification nomograms might reduce the number of unnecessary cystoscopies. Cite this article as: Komina S, Petrusevska G, Jovanovic R, et al. AHNAK2 urinary protein expression as potential biomarker for bladder cancer detection: A pilot study. Turk J Urol. 2022;48(6):423-430.

Diffuse large B-cell lymphoma is a diffuse proliferation of large neoplastic B lymphoid cells with a nuclear size equal to or exceeding the normal macrophage nuclei. We report a case of a clear cell variant of diffuse large B-cell lymphoma involving a lymph node in the neck, which was clinically suspected of being metastatic carcinoma.