Prostate cancer (PCa) progression and treatment resistance are driven by tumor-intrinsic mechanisms and adaptive remodeling of the tumor microenvironment, in which cancer-associated fibroblasts (CAFs) play a crucial role. Although CAF biology is increasingly recognized, a major translational gap remains: CAFs are highly heterogeneous, and comprise distinct functional states with divergent effects on disease progression, immune regulation, and therapeutic resistance. To bridge this gap, we synthesize evidence from single-cell and spatial transcriptomic studies, tissue-based pathology, liquid biopsy assays, and molecular imaging to construct an evidence-tiered, decision-oriented translational framework that connects stromal mechanisms, translational measurement strategies, and therapeutic interventions in PCa. Single-cell and spatial transcriptomic analyses have consistently identified multiple CAF programs, including matrix-remodeling, inflammatory, immunoregulatory, antigen-presenting, and therapy-imprinted states, each with distinct functional outputs and clinical correlates. Tissue-based readouts, including reactive stromal grade (RSG) and fibroblast activation protein (FAP) immunohistochemistry, provide practical proxies for stromal activation and correlate with disease-specific mortality and imaging phenotypes. Circulating CAFs (cCAFs) represent an emerging liquid biopsy modality for longitudinal stromal monitoring, although technical standardization is required before clinical implementation. FAP-targeted PET imaging and emerging dual prostate-specific membrane antigen (PSMA)/FAP-targeted theranostic strategies provide noninvasive tools for patient selection and response assessment, particularly in PSMA-discordant or tracer-heterogeneous disease. Androgen receptor (AR)-targeted therapy can reprogram stromal states toward resistance-promoting circuits, highlighting the dynamic and plastic nature of the CAF compartment. A state-based CAF framework organizes stromal biology into testable translational hypotheses rather than immediate clinical standards. RSG and FAP-based tissue or imaging readouts are practical markers of stromal activation, whereas spatial CAF-immune signatures and cCAF assays remain investigational and require assay harmonization and prospective validation. Future trials should pre-specify stromal biomarkers as enrichment or pharmacodynamic variables when matched to the intervention and should avoid treating CAFs as a uniform therapeutic target.

Introduction: Kidney cancer is the third most common malignancy of the urinary system. Non-renal cell carcinoma kidney cancer (non-RCC kidney cancer), though accounting for only 15%–20% of cases, displays distinct biological features and prognosis, require specific diagnosis and therapeutic strategies. This study aims to determine the clinical and paraclinical characteristics, the histopathological subtypes and factors associated with overall survival of patients diagnosed with non-RCC kidney cancer. Patients and methods: We conducted a retrospective single-center cohort study on 81 patients diagnosed with non-RCC kidney cancer at Cho Ray Hospital between January 2019 and April 2024. Data were collected from medical records, including clinical, imaging, and histopathological characteristics. Statistical analysis was performed using Stata 14.0 software. Results: The mean age of the patients was 57.2 ± 15.2 years, with males comprising 65.4% of the cohort. A significant 95.1% of patients were diagnosed after being presented with symptoms. The most common symptoms were flank pain (58.9%) and gross hematuria (25.9%). The average tumor size was 8.3 ± 4.5 cm, with renal sarcoma showing the largest average tumor size of 13.32 ± 4.13 cm. The histopathological distribution was as follows: squamous cell carcinoma (SCC; 40.7%), upper tract urothelial carcinoma (UTUC; 30.9%), sarcoma (21%), lymphoma (3.7%), and metastatic kidney cancer (2.5%). Larger tumor size was associated with worse overall survival (OS) in exploratory analysis (HR = 1.12, 95% CI: 1.001–1.26, p = 0.049). Conclusions: Non-RCC kidney cancers present with a variety of clinical features, predominantly in males, and are generally diagnosed after symptom onset. SCC and UTUC are the most common histopathological subtypes. Early identification and accurate pathological classification are essential for optimal treatment strategies and prognosis.