The decline of FANCM immunohistochemical expression in prostate cancer stroma correlates with the grade group.

Prostate adenocarcinoma (PCa) stromal markers have recently gained attention as complementary diagnostic tools. The DNA reparation complex protein FANCM has been shown to express in the normal prostate stroma and FANCM gene alterations to be associated with PCa susceptibility; this has led to the hypothesis that an insufficient level of FANCM expression may provide additional information for the evaluation of PCa. The study cohort comprised 60 radical prostatectomy specimens. The controls involved 11 autopsies (CTRL) and non-cancerous tissue (NCT) areas from the prostatectomy specimen. The samples were stained with the FANCM antibody. The quantification of the stromal staining index (SSI) was made using ImageJ and QuPath. Overall, 655 regions of interest (ROI) were analyzed. FANCM expression appeared equally intense and stroma specific in both CTRL and NCT, indicating the absence of underlying baseline alterations. Within the age span of the cohort 47-89 years, no significant effect of the age of the patients on the FANCM expression was seen. FANCM demonstrated Gleason grade (G) dependent decline in PCa, being statistically significant in controls versus G1 and G2 versus G3. In other adjacent International Society of Urological Pathology (ISUP) groups, it remained insignificant, still being meaningful between high and low-grade cancers.

Diagnostic significance of stromal changes in biopsies of prostate adenocarcinoma.

The diagnostic value of stromal changes in carcinomas, including prostate, is under debate; in terms of limited sample tissue of biopsy, in addition to glandular alterations, the stromal changes could have additional diagnostic value, but the results in clinical settings are controversial. The research aims to evaluate the potential of stromal changes as a supplementary tool to predict the presence of higher grade carcinomas in the prostate using Masson's trichrome and Fanconi anemia complementation group M (FANCM) antibody stainings. 385 biopsies and corresponding radical prostatectomy specimens were analyzed to evaluate the rates of the diversity of ISUP grades. Of 128 upgraded prostatectomy cases, 82 were diagnosed with ISUP Gleason Grade 1 (GG1) in a biopsy. All 82 cancerous samples were stained with Masson's trichrome and FACNM antibody and compared with 82 samples without cancer to see if there was a difference in stromal composition. Additionally, 50 GG1 samples without the upgrade were stained to demonstrate if stromal changes can predict less differentiated carcinomas in the prostate. In FANCM stained samples, the average percentage of positively staining stroma over the total in non-upgraded GG1 biopsies was 36 % (13-59 %, SD = 11); 34 % (9-58, SD = 13) in samples from the upgraded cancerous group, and 44 % (22-69, SD = 11) in samples without cancer. In Masson's trichrome stained samples, with collagen quantified, the percentage in non-upgraded GG1 biopsies was 41 % (20-78 %, SD = 11); 44 % (23-89, SD = 15) in samples from upgraded cancerous group and 37 % (15-57, SD = 9) in samples without cancer. In both FANCM and Masson's trichrome, no statistical significance was found between upgraded and non-upgraded groups (p = 0.84 and p = 0.5, respectively), although some upgrades from GG1 to GG4 showed extreme values. The statistical significance was found in cancerous vs. benign samples with both FANCM (p < 0.01) and Masson's trichrome (p = 0.012). The main limiting factor is a significant overlap in staining intensity between cancerous and cancer-free groups.

Pathadin - The essential set of tools to start with whole slide analysis.

Pathadin (https://gitlab.com/Digipathology/Pathadin) was designed as a WSI oriented open-source set of tools for beginners to experience the advantages of computer-assisted image analysis and cover essential features, frequently strenuous to access with the alternative programs. It is mainly oriented to work with histology slides but also includes a significant part of modern image formats. Introducing Pathadin, the manuscript aims to improve understanding of contemporary image analysis components, resolve technophobia and misbeliefs in the computational field, simplifying pathology research work, and shifting it into a quantitative paradigm. Despite being easy to use, Pathadin includes both basic and advanced analytical algorithms, as the application of machine learning. The functionality of Pathadin is demonstrated by AI-enhanced quantification of epithelial and stromal changes in prostate carcinoma, and their dependence on ISUP grade. The material included 5 radical prostatectomy samples for training and 83 (including 11 autopsies) samples for analysis. The analytical material was stained with Masson's trichrome and Ki67, as widely available and potentially prognostic markers. An integrated solution by HistomicsTK for Ki67 evaluation was used. A U-net model for separating glands and stroma was trained, simplifying the independent analysis of these components. During the process, the model successfully highlighted glands and stroma. Masson's trichrome stain demonstrated a gradual increase in collagen expression, being statistically significant between controls vs. G1, and G3 vs. G4. Although there was considerable overlap between adjacent groups, there was only a minor overlap in collagen amount between high- and low-grade carcinomas, affirming that with further research, stroma could be an additional diagnostic marker in prostate adenocarcinoma. Ki67 showed a statistically significant gradual increase in all groups except G1 vs. G2 and G4 vs. G5. Pathadin demonstrates that there is no need for significant resources to experience the advantages of modern computer-assisted analysis.