Plasma Exosomal RNA Signature for Predicting PSMA PET-Defined Bone Metastasis in Prostate Cancer: A Prospective, Multicenter Discovery, Development, and Validation Study
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,000
- 试验地点
- 9
- 主要终点
- Specificity of the plasma exosomal RNA-based predictive signature for detecting PSMA PET-defined bone metastasis at a prespecified sensitivity threshold of ≥95%
研究概览
简要总结
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:
- Secondary metrics include negative predictive value (NPV), positive predictive value (PPV), area under the ROC curve (AUC), calibration, and decision curve analysis.
- Correlation between exosomal RNA levels and number of bone metastatic lesions (PSMA PET).
- Association with PSA, PSMA PET SUVmax, and MRI findings.
- Tissue-plasma correlation to confirm tumor origin (exploratory).
- Mechanistic exploration of key candidates via in vitro/in vivo assays (exploratory).
- Subgroup analyses by hormone sensitivity, metastatic pattern, Gleason grade (exploratory).
Inclusion Criteria:
- Histologically confirmed prostate cancer scheduled for baseline PSMA PET.
- PSMA PET performed prior to any prostate cancer-related treatment.
- Blood samples collected prior to any treatment AND prior to prostate biopsy.
- Willing to undergo prostate biopsy if clinically indicated (after blood collection).
- Written informed consent.
- Age ≥18 years.
Exclusion Criteria:
- Any prior prostate cancer treatment before baseline PSMA PET.
- Blood samples collected after prostate biopsy.
- Other active malignancy within past two years (excluding non-melanoma skin cancer).
- Inadequate blood sample quality or quantity.
- Severe comorbidities interfering with study conduct.
详细描述
Background Prostate cancer (PCa) is a leading cause of cancer-related morbidity worldwide, with bone metastasis being the most frequent and devastating complication. Early and accurate detection of bone metastasis is critical for timely intervention and improved patient outcomes. However, current biomarkers such as PSA lack sufficient sensitivity and specificity for early metastasis detection, and conventional imaging (e.g., bone scan, CT) often identifies metastases only after they become clinically apparent. PSMA PET has emerged as the most sensitive imaging modality for defining metastatic status at baseline, but its high cost, limited availability, and radiation exposure preclude its use as a universal screening tool.
Concurrently, liquid biopsy-particularly the analysis of plasma exosomal RNAs-offers a unique window into tumor biology. Exosomal RNAs are stable in circulation, reflect the molecular characteristics of the primary tumor, and can be detected using sensitive methods such as high-throughput sequencing and digital droplet PCR. Despite their promise, large-scale prospective multicenter studies with rigorous multi-phase validation are lacking.
Need There is a critical unmet need for a non-invasive, robust biomarker that can identify patients at very low risk of bone metastasis, thereby allowing safe deferral of PSMA PET/CT. Existing tools lack adequate negative predictive value to confidently rule out bone metastasis in low-risk populations. A successful rule-out test would reduce unnecessary imaging, lower healthcare costs, and minimize patient radiation exposure. This study implements a four-stage design with phase-specific sample size considerations aligned with contemporary standards for biomarker development.
Study Design and Technical Phases This is a prospective, multicenter, phase-sequential biomarker development and validation study. The gold standard for bone metastasis status is baseline, treatment-naïve PSMA PET/CT. All blood samples are collected prior to any prostate cancer-related treatment and prior to prostate biopsy (if performed) to avoid biopsy-induced contamination. Whole blood (approximately 10 mL in EDTA tubes) is processed within 2 hours to obtain plasma, which is stored at -80°C until analysis.
The four phases are defined as:
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Male
- 接受健康志愿者
- 否
入选标准
- •Patients with histologically confirmed prostate cancer who are scheduled to undergo baseline PSMA PET imaging.
- •Patients who undergo PSMA PET imaging prior to any prostate cancer-related treatment (including androgen deprivation therapy, radiotherapy, or surgery).
- •Patients who provide blood samples for plasma exosomal RNA analysis collected prior to any treatment AND prior to prostate biopsy (if applicable).
- •Whole blood samples (approximately 10 mL) will be collected in EDTA tubes at this specified time point. Samples will be processed within 2 hours to obtain plasma and stored at -80°C until analysis.This timing ensures circulating exosomal RNA profiles reflect tumor biology without biopsy-induced contamination.
- •Patients who are willing to undergo prostate biopsy if clinically indicated (biopsy performed after blood collection).
- •Patients who provide written informed consent to participate in the study.
- •Age ≥18 years.
排除标准
- •Patients who have received any prior prostate cancer-related treatment before the baseline PSMA PET scan (including hormonal therapy, radiotherapy, chemotherapy, or surgery).
- •Patients whose blood samples were collected after prostate biopsy.
- •Patients with a history of other active malignancies within the past two years (excluding non-melanoma skin cancer).
- •Patients with inadequate blood sample quality or quantity for exosomal RNA extraction and analysis (e.g., hemolysis, insufficient volume <8 mL).
- •Patients with severe comorbidities or conditions that, in the judgment of the investigator, could interfere with study compliance or pose significant risk.
研究组 & 干预措施
Prostate Cancer Cohort
A single cohort of 1000 patients with suspected or histologically confirmed prostate cancer who undergo baseline treatment-naïve PSMA PET imaging. All patients provide blood samples for plasma exosomal RNA analysis, collected prior to any treatment and prior to prostate biopsy. This cohort is used for a four-phase biomarker study: Phase 1 (Discovery, n=250) for RNA sequencing to identify candidate biomarkers; Phase 2 (Model Development, n=300) for digital PCR-based signature development; Phase 3 (Internal Validation, n=300) for independent validation in a consecutive cohort; and Phase 4 (External Validation, n=150) for multi-center validation. Bone metastasis status is defined by PSMA PET. Phase 2 and Phase 3 cohorts are temporally and geographically independent. No patient is included in more than one phase
结局指标
主要结局
Specificity of the plasma exosomal RNA-based predictive signature for detecting PSMA PET-defined bone metastasis at a prespecified sensitivity threshold of ≥95%
时间窗: Baseline
Description: The signature will be developed as a continuous risk score using machine learning in an independent development cohort (Phase 2, n≥300, enriched for bone metastasis). After locking the model, a single cut-off value will be selected in the internal validation cohort (Phase 3, n≥300, reflecting natural disease prevalence) to achieve a sensitivity of ≥95% for detecting PSMA PET/CT-defined bone metastasis. The primary outcome is the specificity of the signature at that cut-off. A specificity of ≥30% (or a lower bound of the 95% confidence interval exceeding 20%) will be considered supportive of clinical utility. Measurement tools and units: Plasma exosomal RNA level: digital droplet PCR (ddPCR), expressed as absolute copy number per mL of plasma. Bone metastasis status: PSMA PET/CT, binary (positive/negative). Sensitivity and specificity: proportions with 95% confidence intervals (Clopper-Pearson exact method).
次要结局
- Correlation between plasma exosomal RNA level and bone metastatic lesion count on PSMA PET(Baseline)
- Correlation between plasma exosomal RNA level and serum PSA level(Baseline)
- Correlation between plasma exosomal RNA level and PSMA PET SUVmax(Baseline)
- Association between exo-RNA and MRI findings (exploratory)(Baseline)
- Correlation between tissue RNA expression (RNA-seq, normalized counts like FPKM/TPM) and plasma exosomal RNA level (ddPCR, copies/mL)(Baseline)
- Mechanistic exploration of key driver candidates via functional assays (exploratory)(Baseline)
- Subgroup analyses of diagnostic performance (exploratory)(Baseline)