Mismatch Repair Deficiency and Programmed Death-Ligand 1 Expression in Treatment-Naïve High-Risk and Very High-Risk Locally Advanced Prostate Cancer: Histomorphological Associations and Prognostic Value

Abstract

High-risk (HR) and very high-risk (VHR) prostate cancer (PCa) are associated with poor outcomes despite multimodal therapy. Although immunotherapy is a last-line option for advanced disease, its role in locally advanced prostate cancer (LAPCa) remains unclear. This study aimed to evaluate the association between programmed death-ligand 1 (PD-L1) expression, mismatch repair deficiency (dMMR), and histomorphological features, and to assess their prognostic significance in treatment-naïve HR/VHR LAPCa. Eighty-five patients who underwent robotic radical prostatectomy between 2014 and 2024 were retrospectively analyzed. Clinicopathological variables were assessed comprehensively. MMR status was determined using immunohistochemistry, and loss of expression prompted microsatellite instability analysis by polymerase chain reaction. PD-L1 expression was evaluated using tumor proportion score, immune cell proportion score, and combined positive score (CPS). Binary logistic regression was used to identify independent predictors of PD-L1 CPS positivity. Survival outcomes were analyzed using Kaplan-Meier and Cox regression analyses. The cohort comprised 41 HR and 44 VHR LAPCa patients, and dMMR was identified in 2 patients (2.4%), both in VHR group. Ductal adenocarcinoma component, higher tumor volume, and increased tumor-infiltrating lymphocyte score independently predicted PD-L1 CPS positivity. Among VHR patients, PD-L1 CPS positivity was associated with shorter biochemical recurrence-free survival (BCRFS). In the entire cohort, ductal adenocarcinoma component was an independent prognostic factor for BCRFS, whereas lymphovascular invasion independently predicted metastasis-free survival. dMMR and PD-L1 positivity are rare in HR/VHR LAPCa, supporting “cold” tumor profile. Routine testing may be unnecessary; however, selective histopathology-based biomarker assessment could improve risk stratification and inform personalized therapies.