Analysis of A 6-Mirna Signature in Serum from Colorectal Cancer Screening Participants as Non-Invasive Biomarkers for Advanced Adenoma and Colorectal Cancer Detection

分析结直肠癌筛查参与者血清中的6-mirna特征作为非侵入性生物标志物用于检测进展期腺瘤和结直肠癌

阅读:1

Abstract

Early detection of colorectal cancer (CRC) and its precancerous lesion, advanced adenomas (AA), is critical to improve CRC incidence and prognosis. Circulating microRNAs (miRNAs or miR) are promising non-invasive biomarkers for cancer detection. Our previous results showed that a plasma 6-miRNA signature (miR-15b-5p, miR-18a-5p, miR-29a-3p, miR-335-5p, miR-19a-3p and miR-19b-3p) could distinguish between CRC or AA and healthy individuals (controls). However, its diagnostic performance in serum is unknown. In this exploratory study we aim to evaluate the diagnostic performance of the 6-miRNA signature in serum samples in a cohort of individuals participating in Barcelona's CRC Screening Programme. We prospectively collected serums from 264 faecal immunochemical test (FIT)-positive participants and total RNA was extracted. Finally, 213 individuals (CRC, 59, AA, 74, controls, 80) were included. MiRNA expression was quantified by real-time RT-qPCR and data analysis was performed by logistic regression. Faecal hemoglobin concentration (f(Hb)) from FIT of the same individuals was also considered. As previously described in plasma, serum from patients with AA or CRC presented significant differences in the 6-miRNA signature compared to controls. Moreover, when combined with f(Hb), the final signature showed high discriminative capacity to distinguish CRC from controls (area under the curve (AUC) = 0.88), and even AA (AUC = 0.81) that otherwise are poorly detected if we only consider f(Hb) (AUC = 0.64). Addition of the serum 6-miRNA signature to quantitative f(Hb) show high accuracy to detect patients with advanced colorectal neoplasia in average-risk individuals. A combination of these two non-invasive methods could be a good strategy to improve diagnostic performances of current CRC screening programmes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。