Suppr超能文献

用于早期膀胱癌检测的改良尿 DNA 甲基化.panel

Improved urine DNA methylation panel for early bladder cancer detection.

机构信息

Yaneng Bioscience, Co., Ltd, Shenzhen, 518100, China.

South China University of Technology, Guangzhou, 510641, China.

出版信息

BMC Cancer. 2022 Mar 3;22(1):237. doi: 10.1186/s12885-022-09268-y.

Abstract

BACKGROUND

Bladder cancer is one of the most common malignancies but the corresponding diagnostic methods are either invasive or limited in specificity and/or sensitivity. This study aimed to develop a urine-based methylation panel for bladder cancer detection by improving published panels and validate performance of the new panel with clinical samples.

METHODS

Related researches were reviewed and 19 potential panels were selected. RRBS was performed on a cohort with 45 samples to reassess these panels and a new panel inherited best markers was developed. The new panel was applied with qMSP platform to 33 samples from the RRBS cohort and the results were compared to those of RRBS. Lastly, another larger cohort with 207 samples was used to validate new panel performance with qMSP.

RESULTS

Three biomarkers (PCDH17, POU4F2 and PENK) were selected to construct a new panel P3. P3 panel achieved 100% specificity and 71% sensitivity with RRBS in corresponding cohort and then showed a better performance of 100% specificity and 84% sensitivity with qMSP platforms in a balanced cohort. When validated with 207-sample cohort, P3 with qMSP showed a performance of 97% specificity and 87% sensitivity which was modestly improved compared to the panels it derided from.

CONCLUSIONS

Overall, the P3 panel achieved relatively high sensitivity and accuracy in bladder cancer detection.

摘要

背景

膀胱癌是最常见的恶性肿瘤之一,但相应的诊断方法要么具有侵入性,要么特异性和/或灵敏度有限。本研究旨在通过改进已发表的panel 来开发一种基于尿液的膀胱癌检测甲基化panel,并使用临床样本验证新panel 的性能。

方法

综述相关研究,选择 19 个潜在 panel。对 45 个样本进行 RRBS 以重新评估这些 panel,并开发继承最佳标志物的新 panel。将新 panel 应用于 RRBS 队列的 33 个样本的 qMSP 平台,并将结果与 RRBS 进行比较。最后,使用包含 207 个样本的更大队列,使用 qMSP 来验证新 panel 的性能。

结果

选择三个生物标志物(PCDH17、POU4F2 和 PENK)构建新的 P3 面板。P3 面板在相应队列中与 RRBS 达到 100%特异性和 71%敏感性,然后在平衡队列中与 qMSP 平台显示出更好的 100%特异性和 84%敏感性性能。在对包含 207 个样本的队列进行验证时,qMSP 的 P3 表现出 97%的特异性和 87%的敏感性,与它所衍生的 panel 相比略有提高。

结论

总体而言,P3 面板在膀胱癌检测中达到了较高的敏感性和准确性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验