开发和验证尿液 microRNA 生物标志物谱作为一种工具，用于在中国人群中早期检测前列腺癌。

Development and validation of a urinary microRNA biomarker panel as a tool for early detection of prostate cancer in a Chinese population.

机构信息

The second Affiliated Hospital of Medical College of Zhejiang University, Hangzhou, Zhejiang, China.

Hangzhou Ninth People's Hospital, Hangzhou, Zhejiang, China.

出版信息

Biomarkers. 2023 Jun;28(4):372-378. doi: 10.1080/1354750X.2023.2166587. Epub 2023 Apr 26.

DOI:10.1080/1354750X.2023.2166587

PMID:37185057

Abstract

INTRODUCTION

Urinary microRNAs (miRNAs) may serve as promising biomarkers for non-invasive early detection of prostate cancer (PCa). We aimed to identify multi-miRNA urinary biomarker panel for early detection of PCa.

METHODS

Urine samples from 83 PCa patients and 88 healthy control subjects in a Chinese population were collected for miRNA profiling. The absolute expression of 360 unique miRNAs were measured in each sample using a highly sensitive and robust RT-qPCR workflow. Candidate urinary miRNA biomarkers were identified based on differential expression between PCa patients and healthy controls. Multi-miRNA biomarker panels were optimised for detection of PCa using three regression algorithms (Lasso, Stepwise, Exhaustive) to identify an optimal biomarker panel with best detection performance and least number of miRNAs.

RESULTS

A total of 312 miRNAs were detected in urine samples, 10 candidate urinary miRNA biomarkers differentially expressed between PCa and healthy samples were identified. A panel comprising these 10 miRNAs detected PCa with an area under the curve (AUC) of 0.738. Optimization of multi-miRNA panels resulted in a 6-miRNA biomarker panel (hsa-miR-375, hsa-miR-520d-5p, hsa-miR-199b-5p, hsa-miR-518e-5p, hsa-miR-31-3p and hsa-miR-4306) that had an AUC of 0.750.

CONCLUSION

We identified a urinary miRNA biomarker panel for early detection of PCa in a Chinese population.

摘要

简介

尿液 microRNAs（miRNAs）可能成为前列腺癌（PCa）非侵入性早期检测有前途的生物标志物。我们旨在确定用于早期检测 PCa 的多 miRNA 尿液生物标志物。

方法

在中国人群中收集了 83 例 PCa 患者和 88 例健康对照者的尿液样本进行 miRNA 谱分析。使用高度敏感和稳健的 RT-qPCR 工作流程测量每个样本中 360 个独特 miRNA 的绝对表达。基于 PCa 患者与健康对照之间的差异表达，确定候选尿液 miRNA 生物标志物。使用三种回归算法（lasso、逐步、穷尽）优化多 miRNA 生物标志物面板，以确定具有最佳检测性能和最少 miRNA 数的最佳生物标志物面板。

结果

共检测到 312 个 miRNA，在 PCa 和健康样本之间有 10 个候选尿液 miRNA 生物标志物差异表达。由这 10 个 miRNA 组成的面板检测 PCa 的曲线下面积（AUC）为 0.738。多 miRNA 面板的优化产生了一个由 6 个 miRNA 生物标志物组成的面板（hsa-miR-375、hsa-miR-520d-5p、hsa-miR-199b-5p、hsa-miR-518e-5p、hsa-miR-31-3p 和 hsa-miR-4306），其 AUC 为 0.750。