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鉴定和评估循环中小细胞外囊泡 microRNAs 作为诊断不确定肺结节患者的生物标志物。

Identification and evaluation of circulating small extracellular vesicle microRNAs as diagnostic biomarkers for patients with indeterminate pulmonary nodules.

机构信息

Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, No. 507 Zhengmin Road, Yangpu District, Shanghai, 200433, China.

Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, No. 507 Zhengmin Road, Yangpu District, Shanghai, 200433, China.

出版信息

J Nanobiotechnology. 2022 Apr 2;20(1):172. doi: 10.1186/s12951-022-01366-0.

Abstract

BACKGROUND

The identification of indeterminate pulmonary nodules (IPNs) following a low-dose computed tomography (LDCT) is a major challenge for early diagnosis of lung cancer. The inadequate assessment of IPNs' malignancy risk results in a large number of unnecessary surgeries or an increased risk of cancer metastases. However, limited studies on non-invasive diagnosis of IPNs have been reported.

METHODS

In this study, we identified and evaluated the diagnostic value of circulating small extracellular vesicle (sEV) microRNAs (miRNAs) in patients with IPNs that had been newly detected using LDCT scanning and were scheduled for surgery. Out of 459 recruited patients, 109 eligible patients with IPNs were enrolled in the training cohort (n = 47) and the test cohort (n = 62). An external cohort (n = 99) was used for validation. MiRNAs were extracted from plasma sEVs, and assessed using Small RNA sequencing. 490 lung adenocarcinoma samples and follow-up data were used to investigate the role of miRNAs in overall survival.

RESULTS

A circulating sEV miRNA (CirsEV-miR) model was constructed from five differentially expressed miRNAs (DEMs), showing 0.920 AUC in the training cohort (n = 47), and further identified in the test cohort (n = 62) and in an external validation cohort (n = 99). Among five DEMs of the CirsEV-miR model, miR-101-3p and miR-150-5p were significantly associated with better overall survival (p = 0.0001 and p = 0.0069). The CirsEV-miR scores were calculated, which significantly correlated with IPNs diameters (p < 0.05), and were able to discriminate between benign and malignant PNs (diameter ≤ 1 cm). The expression patterns of sEV miRNAs in the benign, adenocarcinoma in situ/minimally invasive adenocarcinoma, and invasive adenocarcinoma subgroups were found to gradually change with the increase in aggressiveness for the first time. Among all DEMs of the three subgroups, five miRNAs (miR-30c-5p, miR-30e-5p, miR-500a-3p, miR-125a-5p, and miR-99a-5p) were also significantly associated with overall survival of lung adenocarcinoma patients.

CONCLUSIONS

Our results indicate that the CirsEV-miR model could help distinguish between benign and malignant PNs, providing insights into the feasibility of circulating sEV miRNAs in diagnostic biomarker development.

TRIAL REGISTRATION

Chinese Clinical Trials: ChiCTR1800019877. Registered 05 December 2018, https://www.chictr.org.cn/showproj.aspx?proj=31346 .

摘要

背景

低剂量计算机断层扫描(LDCT)后发现的不确定肺结节(IPN)是肺癌早期诊断的主要挑战。对 IPN 恶性风险的评估不足导致大量不必要的手术或癌症转移风险增加。然而,关于 IPN 的非侵入性诊断的研究有限。

方法

在这项研究中,我们鉴定并评估了新发现的通过 LDCT 扫描检测到的 IPN 患者循环中小细胞外囊泡(sEV)microRNAs(miRNAs)的诊断价值。在 459 名入选的患者中,共有 109 名符合条件的 IPN 患者被纳入训练队列(n=47)和测试队列(n=62)。另外还有一个外部队列(n=99)用于验证。从血浆 sEV 中提取 miRNA,并使用 Small RNA 测序进行评估。490 例肺腺癌样本和随访数据用于研究 miRNA 在总生存中的作用。

结果

从 5 个差异表达的 miRNAs(DEMs)构建了一个循环 sEV miRNA(CirsEV-miR)模型,在训练队列(n=47)中具有 0.920 AUC,并且在测试队列(n=62)和外部验证队列(n=99)中得到了进一步的验证。在 CirsEV-miR 模型的 5 个 DEMs 中,miR-101-3p 和 miR-150-5p 与更好的总生存率显著相关(p=0.0001 和 p=0.0069)。计算 CirsEV-miR 评分,其与 IPN 直径显著相关(p<0.05),并能够区分良性和恶性 PNs(直径≤1cm)。首次发现 sEV miRNA 在良性、原位癌/微浸润腺癌和浸润性腺癌亚组中的表达模式随着侵袭性的增加而逐渐改变。在三个亚组的所有 DEMs 中,有 5 个 miRNA(miR-30c-5p、miR-30e-5p、miR-500a-3p、miR-125a-5p 和 miR-99a-5p)也与肺腺癌患者的总生存率显著相关。

结论

我们的结果表明,CirsEV-miR 模型可以帮助区分良性和恶性 PNs,为循环 sEV miRNAs 在诊断生物标志物开发中的可行性提供了新的见解。

试验注册

中国临床试验:ChiCTR1800019877。注册于 2018 年 12 月 5 日,https://www.chictr.org.cn/showproj.aspx?proj=31346。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e9/8976298/6942674307ac/12951_2022_1366_Fig1_HTML.jpg

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