6 Circulating miRNAs can be used as Non-invasive Biomarkers for the Detection of Cervical Lesions.
6 Circulating miRNAs can be used as Non-invasive Biomarkers for the Detection of Cervical Lesions.
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DOI：
10.7150/jca.51141
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发表时间：
2021
影响因子：
3.9
通讯作者：
Li S
中科院分区：
文献类型：
--
作者：
Ning R;Meng S;Wang L;Jia Y;Tang F;Sun H;Zhang Z;Zhang C;Fan X;Xiao B;Yang C;Li S
背景资料：宫颈癌是女性生殖系统最常见的恶性肿瘤，常规筛查的效果不理想。需要开发新的分子测试。miRNA参与多种病理过程，循环中的miRNA是一种很有前途的肿瘤非侵袭性生物标志物。目的：本研究旨在鉴定与宫颈癌和宫颈上皮内瘤样病变（CIN）相关的循环miRNAs，并利用循环miRNAs建立宫颈病变的无创分类器。研究方法：该研究包括5个步骤：miRNAs筛选、miRNAs验证、分类器建立、独立验证和计算机分析。本研究共纳入3个队列：筛选阶段共纳入样本24例，其中病例组14例，对照组10例;验证阶段共纳入样本380例，其中病例组200例，对照组180例;独立验证阶段共纳入样本47例，其中病例组26例，对照组21例。通过RT-qPCR定量miRNA。使用验证样本和选择的miRNA，使用随机森林算法构建分类器，然后在独立队列中验证。为了探索所选miRNA的功能，进行了计算机模拟分析。通过三种在线工具的重叠预测所选miRNAs的靶基因。用预测的靶基因进行富集分析。利用开放获取的宫颈组织表达测定数据集进行靶基因的差异分析。结果：从754条miRNAs中筛选出6条miRNAs（hsa-miR-26 b-5 p、hsa-miR-146 b-5 p、hsa-miR-191- 5 p、hsa-miR-484、hsa-miR-574- 3 p、hsa-miR-625- 3 p）。它们与宫颈病变相关，并被选择来建立分类器。在验证样本中，分类器的准确率为0.7218（0.7117，0.7319），在独立队列中为0.7021。预测并富集了23条通路（MAPK、人乳头瘤病毒感染、Wnt信号通路等）的958个靶基因。通过差异分析确定了55个基因为最可能的靶基因。结论：6种循环miRNAs与宫颈病变相关，可作为非侵袭性的生物标志物。
Background: Cervical cancer is the most common malignant tumor in the female reproductive system, while the efficacy of routine screening strategy is unsatisfied. New molecular tests need to be developed. miRNAs participate in many pathologic processes, and circulating miRNAs are promising non-invasive biomarkers in tumors. Objectives: This study aimed to identify the circulating miRNAs associated with both cervical cancer and cervical intraepithelial neoplasia (CIN), and establish a non-invasive classifier for cervical lesions using circulating miRNAs. Methods: This study consisted of 5 steps: miRNAs screening, miRNAs validation, classifier establishment, independent validation and in silico analyses. Three cohorts were included in our study: In screening stage, 24 samples including 14 cases and 10 controls were retrieved; In validation stage, 380 samples including 200 cases and 180 controls were recruited; In independent validation stage, 47 samples comprising 26 cases and 21 controls were included. miRNAs were quantified by RT-qPCR. A classifier was built with random forest algorithm using validation samples and selected miRNAs, which were then validated in an independent cohort. To explore the function of selected miRNAs, in silico analyses were performed. Target genes of selected miRNAs were predicted by the overlap of three online tools. Enrichment analyses were executed with predicted target genes. Differential analysis of target genes was carried out with open access expression assay datasets of cervical tissues. Results: 6 miRNAs (hsa-miR-26b-5p, hsa-miR-146b-5p, hsa-miR-191-5p, hsa-miR-484, hsa-miR-574-3p, hsa-miR-625-3p) were screened out from 754 miRNAs. They were associated with cervical lesions and were selected to establish a classifier. The accuracy of the classifier were 0.7218 (0.7117, 0.7319) in validation samples, which was 0.7021 in the independent cohort. 958 target genes were predicted and enriched in 23 pathways (MAPK, human papillomavirus infection and Wnt signaling pathway, etc.). 55 genes were identified as the most likely target genes by differential analysis. Conclusion: The 6 circulating miRNAs were related to cervical lesions and could serve as non-invasive biomarkers.
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影响因子：
3.7
作者：
Roth C;Stückrath I;Pantel K;Izbicki JR;Tachezy M;Schwarzenbach H
通讯作者：
Schwarzenbach H
影响因子：
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作者：
Liu Z;He W;Gao J;Luo J;Huang X;Gao C
通讯作者：
Gao C
影响因子：
8.5
作者：
Tian, Fang;Yu, Chengtao;Zhu, Xuejun
通讯作者：
Zhu, Xuejun
影响因子：
2.9
作者：
Du, Xinjie;Lin, Li;Jiang, Jie
通讯作者：
Jiang, Jie
影响因子：
4.7
作者：
Wu, D;Suo, ZH;Nesland, JM
通讯作者：
Nesland, JM