肺肿瘤组织MicroRNA谱与高危血浆miRNA信号相关

Orazio Fortunato, Carla Verri, Ugo Pastorino, Gabriella Sozzi, Mattia Boeri
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引用次数: 10

摘要

肺癌是全世界最常见的癌症死亡原因。MicroRNAs (miRNAs)是调节基因表达的短的非编码rna。许多研究报道了miRNA表达的改变与几种人类肿瘤有关。我们之前已经确定了一种循环miRNA特征分类器(MSC),能够区分具有更强侵袭性特征的肺癌。在本研究中,我们对19例肺癌患者的肿瘤组织进行了miRNA微阵列分析,以寻找miRNA表达与MSC风险水平之间的可能关联。观察到11个组织成熟miRNA和6个miRNA前体与患者血浆MSC风险水平相关。这些mirna没有一个被包括在MSC算法中。途径富集分析揭示了这些miRNA在决定肺癌侵袭性的主要途径中的作用。总的来说,这些发现增加了组织和血浆mirna作为出色的诊断和预后生物标志物的认识,这可能会在临床环境中得到快速应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MicroRNA Profile of Lung Tumor Tissues Is Associated with a High Risk Plasma miRNA Signature.

MicroRNA Profile of Lung Tumor Tissues Is Associated with a High Risk Plasma miRNA Signature.

MicroRNA Profile of Lung Tumor Tissues Is Associated with a High Risk Plasma miRNA Signature.

Lung cancer is the most common cause of cancer deaths worldwide. MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression. Many studies have reported that alterations in miRNA expression are involved in several human tumors. We have previously identified a circulating miRNA signature classifier (MSC) able to discriminate lung cancer with more aggressive features. In the present work, microarray miRNA profiling of tumor tissues collected from 19 lung cancer patients with an available MSC result were perform in order to find a possible association between miRNA expression and the MSC risk level. Eleven tissue mature miRNAs and six miRNA precursors were observed to be associated with the plasma MSC risk level of patients. Not one of these miRNAs was included in the MSC algorithm. A pathway enrichment analysis revealed a role of these miRNA in the main pathways determining lung cancer aggressiveness. Overall, these findings add to the knowledge that tissue and plasma miRNAs behave as excellent diagnostic and prognostic biomarkers, which may find rapid application in clinical settings.

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来源期刊
自引率
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审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
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