Department of Urology, Fujian Union Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Shenzhen Huixin Lifetechnologies Co., Ltd., Longhua, Shenzhen, Guangdong, China.
J Extracell Vesicles. 2024 Aug;13(8):e12491. doi: 10.1002/jev2.12491.
In the quest for efficient tumor diagnosis via liquid biopsy, extracellular vesicles (EVs) have shown promise as a source of potential biomarkers. This study addresses the gap in biomarker efficacy for predicting clinically significant prostate cancer (csPCa) between the Western and Chinese populations. We developed a urinary extracellular vesicles-based prostate score (EPS) model, utilizing the EXODUS technique for EV isolation from 598 patients and incorporating gene expressions of FOXA1, PCA3, and KLK3. Our findings reveal that the EPS model surpasses prostate-specific antigen (PSA) testing in diagnostic accuracy within a training cohort of 234 patients, achieving an area under the curve (AUC) of 0.730 compared to 0.659 for PSA (p = 0.018). Similarly, in a validation cohort of 101 men, the EPS model achieved an AUC of 0.749, which was significantly better than PSA's 0.577 (p < 0.001). Our model has demonstrated a potential reduction in unnecessary prostate biopsies by 26%, with only a 3% miss rate for csPCa cases, indicating its effectiveness in the Chinese population.
在通过液体活检进行高效肿瘤诊断的探索中,细胞外囊泡 (EVs) 作为潜在生物标志物的来源显示出了一定的前景。本研究旨在解决中西方人群在预测临床显著前列腺癌 (csPCa) 的生物标志物功效方面存在的差距。我们开发了一种基于尿液细胞外囊泡的前列腺评分 (EPS) 模型,利用 EXODUS 技术从 598 名患者中分离 EVs,并结合 FOXA1、PCA3 和 KLK3 的基因表达。我们的研究结果表明,在一个包含 234 名患者的训练队列中,与 PSA 检测相比,EPS 模型在诊断准确性方面具有优势,其曲线下面积 (AUC) 为 0.730,而 PSA 的 AUC 为 0.659 (p=0.018)。同样,在一个包含 101 名男性的验证队列中,EPS 模型的 AUC 为 0.749,明显优于 PSA 的 0.577 (p<0.001)。我们的模型显示,通过该模型可以减少 26%的不必要的前列腺活检,同时 csPCa 病例的漏诊率仅为 3%,表明其在中国人群中的有效性。