Keyan Salari

Objectives Compare the clinical and imaging features of prostate cancer (PCa) patients harboring a germline pathogenic variant (PV) to sporadic controls. Materials and methods A single-center retrospective case-control study was performed by identifying patients with positive germline genetic testing for a PV diagnosed with prostate cancer between December 2015 and October 2025. Clinical, pathologic, and MRI characteristics of PV carriers were compared to a control group of consecutive patients diagnosed with PCa over 1 year. Mann–Whitney U-test was used for continuous data and Fisher’s exact test for categorical comparisons. Results A total of 62 patients with PCa harboring ≥ 1 PV and an MRI at diagnosis were compared to 246 controls. The most frequent genes were Lynch syndrome (LS) associated (17.7%), CHEK2 (21.0%), ATM (17.7%), and BRCA2 (19.4%). Median age of PV carriers was not significantly younger than controls at diagnosis (65 years [IQR, 58–71], vs 67 years [61–73], p = 0.05). The proportion of patients with a positive MRI (PI-RADS ≥ 3) did not differ between groups (98% PV vs 96% control, p = 0.70). PV carriers were more likely to receive a PI-RADS 5 score (OR: 2.7; CI: 1.5–4.9, p < 0.01) and grade 3 extra-prostatic extension (OR: 3.0; CI: 1.5–5.8, p < 0.01). At prostatectomy, the proportion of patients reclassified to a higher-grade group was larger for PV carriers (37% vs 20%, p = 0.046). Conclusion PV carriers with PCa tend to manifest more aggressive imaging findings and are more likely to experience pathologic upgrading at prostatectomy. Key Points Question Differences in the clinical and imaging characteristics of sporadic prostate cancer (PCa) patients compared to patients harboring a PCa-associated germline pathogenic variant remain understudied. Findings PV carriers with PCa manifest more aggressive imaging features and are more likely to demonstrate pathologic upgrading at prostatectomy. Clinical relevance Knowledge of the unique clinical and imaging manifestations of hereditary PCa should support ongoing early detection studies and underscore the need for radiologists to be familiar with patient-centered early detection strategies utilizing MRI. Graphical Abstract

All supplementary tables and figures.

Purpose:Computational pathology has emerged as an attractive option for improving risk stratification in prostate cancer, but most approaches either lack interpretability or focus solely on tumor morphology. We aimed to identify an interpretable, immune microenvironment–derived computational pathology biomarker for prostate cancer. Experimental Design:We identified two cohorts (discovery and validation) with M0 prostate cancer (n = 490) who were treated with radical prostatectomy, with hematoxylin and eosin–stained whole-slide images (WSI) and data on distant metastasis (DM). We identified a third cohort from The Cancer Genome Atlas with M0 prostate cancer (n = 326) with prostatectomy WSIs and bulk sequencing. Immune cells were identified from WSIs using a deep learning method (CellViT), and spatially dense immune clusters were quantified using density-based spatial clustering of applications with noise (DBSCAN). CIBERSORTx was utilized for immune cell deconvolution and TRUST4 for immune receptor repertoire reconstruction. Results:Median follow-up was 12.6 years (discovery) and 8.1 years (validation). Fourteen percent (n = 37, discovery) and seventeen percent (n = 38, validation) had Gleason 8 to 10 disease. Immune cell abundance was not associated with DM. In discovery, increased immune cluster was associated with decreased risk of DM for Gleason 8 to 10 (adjusted hazard ratio, 0.42; 95% confidence interval, 0.19–0.93) but not Gleason 6 to 7 (1.26, 0.77–2.05; Pint = 0.020), with similar results in validation (Gleason 8–10: 0.60, 0.37–0.98; Gleason 6–7: 1.19, 0.74–1.91; Pint = 0.043). In Gleason 8 to 10 but not 6 to 7, high-cluster samples were enriched for CD8+ T cells, activated memory CD4+ T cells, regulatory T cells (P ≤ 0.037), and clonal T-cell populations (P ≤ 0.039). Conclusions:These findings propose immune spatial clustering as a novel, interpretable computational pathology biomarker and provide insight into the unique immune features of high-grade prostate cancer.

Purpose: Computational pathology has emerged as an attractive option for improving risk stratification in prostate cancer, but most approaches either lack interpretability or focus solely on tumor morphology. We aimed to identify an interpretable, immune microenvironment–derived computational pathology biomarker for prostate cancer. Experimental Design: We identified two cohorts (discovery and validation) with M0 prostate cancer (n = 490) who were treated with radical prostatectomy, with hematoxylin and eosin–stained whole-slide images (WSI) and data on distant metastasis (DM). We identified a third cohort from The Cancer Genome Atlas with M0 prostate cancer (n = 326) with prostatectomy WSIs and bulk sequencing. Immune cells were identified from WSIs using a deep learning method (CellViT), and spatially dense immune clusters were quantified using density-based spatial clustering of applications with noise (DBSCAN). CIBERSORTx was utilized for immune cell deconvolution and TRUST4 for immune receptor repertoire reconstruction. Results: Median follow-up was 12.6 years (discovery) and 8.1 years (validation). Fourteen percent (n = 37, discovery) and seventeen percent (n = 38, validation) had Gleason 8 to 10 disease. Immune cell abundance was not associated with DM. In discovery, increased immune cluster was associated with decreased risk of DM for Gleason 8 to 10 (adjusted hazard ratio, 0.42; 95% confidence interval, 0.19–0.93) but not Gleason 6 to 7 (1.26, 0.77–2.05; Pint = 0.020), with similar results in validation (Gleason 8–10: 0.60, 0.37–0.98; Gleason 6–7: 1.19, 0.74–1.91; Pint = 0.043). In Gleason 8 to 10 but not 6 to 7, high-cluster samples were enriched for CD8+ T cells, activated memory CD4+ T cells, regulatory T cells (P ≤ 0.037), and clonal T-cell populations (P ≤ 0.039). Conclusions: These findings propose immune spatial clustering as a novel, interpretable computational pathology biomarker and provide insight into the unique immune features of high-grade prostate cancer.

Background: Indeterminate renal masses (IRMs) frequently require biopsy for characterization and often lead to unnecessary surgical interventions. ⁸⁹Zr-girentuximab is a positron emission tomography (PET) radiopharmaceutical targeting carbonic anhydrase IX, a biomarker overexpressed in clear-cell renal cell carcinoma (ccRCC). This real-world experience demonstrates the impact of ⁸⁹Zr-girentuximab PET on the clinical management of patients with IRM and its role in differentiating primary and metastatic ccRCC from other etiologies. Methods: This prospective single-center study, part of an expanded access program (NCT06090331), investigated patients with IRM on conventional imaging who underwent ⁸⁹Zr-girentuximab PET/computed tomography (PET/CT). Qualitative and quantitative PET/CT features of each lesion were assessed. Pathologic or clinical diagnosis was determined for all lesions. Referring physicians were surveyed to evaluate the impact of PET on patient management. Results: Seven male patients (age range, 57–78 years) were included; four had ccRCC (including two with metastatic disease) and three had oncocytoma (including one with Birt-Hogg-Dubé syndrome). Across all 32 lesions identified, ⁸⁹Zr-girentuximab PET/CT accurately characterized each lesion based on pathologic or clinical diagnosis. ⁸⁹Zr-girentuximab PET/CT identified ccRCC tumor thrombi in the inferior vena cava and renal vein branches (SUV_max 12.0–13.0), a perinephric deposit (SUV_max 36.4), and intramuscular (SUV_max 103.0), pulmonary (SUV_max 4.0–10.5), and osseous (SUV_max 10.2) metastases. ⁸⁹Zr-girentuximab PET/CT enabled the diagnosis of oncocytomatosis in one patient and detected a renal lesion with positive uptake that was occult on MRI. According to referring physicians, ⁸⁹Zr-girentuximab PET/CT changed clinical management in six of seven patients and improved patient care in all cases. Conclusions: ⁸⁹Zr-girentuximab PET/CT provides a noninvasive tool for characterizing indeterminate renal masses and metastatic ccRCC and may improve clinical problem-solving in complex scenarios.

Supplementary Figure 1. Genomic profiles of the validation cohort.

Supplemental Figure 2. uCGP Predicted Recurrence Risk by Subgroup.