Brief Summary: This prospective, multicenter study aims to discover, develop, and validate a plasma exosomal RNA-based signature as a rule-out test for predicting bone metastasis in prostate cancer, using baseline treatment-naïve PSMA PET as the gold standard. The study is designed in four sequential phases: Phase 1 (Discovery, n=250): High-throughput sequencing of plasma exosomal RNAs to identify differentially expressed candidate RNAs. Phase 2 (Model Development, n=300): Digital droplet PCR (ddPCR) analysis of candidates in an independent cohort to construct and lock the final multi-RNA predictive signature using appropriate machine learning methods. Phase 3 (Internal Validation, n=300): Independent validation of the locked signature in a consecutive cohort reflecting natural disease prevalence. Phase 4 (External Validation, n=150): Final independent validation in a multi-center cohort enriched for bone metastasis. Primary Outcome: To evaluate the diagnostic performance of the signature as a rule-out test for PSMA PET-defined bone metastasis. The primary performance metrics are: Sensitivity, with a prespecified target of ≥95% (to ensure minimal false negatives). Specificity at the threshold that achieves the ≥95% sensitivity. A specificity of ≥30% will be considered supportive of clinical utility. A specificity of ≥30% (or a lower bound of the 95% confidence interval exceeding 20%) will be considered supportive of clinical utility. Need: Current biomarkers lack sensitivity and specificity for early detection of bone metastasis. More importantly, existing tools lack adequate negative predictive value to safely rule out bone metastasis in low-risk patients, leading to over-imaging or delayed detection. There is an urgent need for a non-invasive rule-out test to safely defer PSMA PET/CT in very-low-risk patients. Plasma exosomal RNAs offer a promising liquid biopsy approach, but prospective multicenter studies with rigorous validation are lacking. Secondary Outcomes: 1. Secondary metrics include negative predictive value (NPV), positive predictive value (PPV), area under the ROC curve (AUC), calibration, and decision curve analysis. 2. Correlation between exosomal RNA levels and number of bone metastatic lesions (PSMA PET). 3. Association with PSA, PSMA PET SUVmax, and MRI findings. 4. Tissue-plasma correlation to confirm tumor origin (exploratory). 5. Mechanistic exploration of key candidates via in vitro/in vivo assays (exploratory). 6. Subgroup analyses by hormone sensitivity, metastatic pattern, Gleason grade (exploratory). Inclusion Criteria: 1. Histologically confirmed prostate cancer scheduled for baseline PSMA PET. 2. PSMA PET performed prior to any prostate cancer-related treatment. 3. Blood samples collected prior to any treatment AND prior to prostate biopsy. 4. Willing to undergo prostate biopsy if clinically indicated (after blood collection). 5. Written informed consent. 6. Age ≥18 years. Exclusion Criteria: 1. Any prior prostate cancer treatment before baseline PSMA PET. 2. Blood samples collected after prostate biopsy. 3. Other active malignancy within past two years (excluding non-melanoma skin cancer). 4. Inadequate blood sample quality or quantity. 5. Severe comorbidities interfering with study conduct.
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Specificity of the plasma exosomal RNA-based predictive signature for detecting PSMA PET-defined bone metastasis at a prespecified sensitivity threshold of ≥95%
Timeframe: Baseline