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血清 miR-155 和 miR-24 对早期复发性乳腺癌的预测潜能。

Prediction Potential of Serum miR-155 and miR-24 for Relapsing Early Breast Cancer.

机构信息

BIOCEV, First Faculty of Medicine, Charles University, Vestec 25250, Czech Republic.

Faculty of Mathematics and Physics, Charles University, Prague 18675, Czech Republic.

出版信息

Int J Mol Sci. 2017 Oct 10;18(10):2116. doi: 10.3390/ijms18102116.

Abstract

Oncogenic microRNAs (oncomiRs) accumulate in serum due to their increased stability and thus serve as biomarkers in breast cancer (BC) pathogenesis. Four oncogenic microRNAs (miR-155, miR-19a, miR-181b, and miR-24) and one tumor suppressor microRNA (let-7a) were shown to differentiate between high- and low-risk early breast cancer (EBC) and reflect the surgical tumor removal and adjuvant therapy. Here we applied the longitudinal multivariate data analyses to stochastically model the serum levels of each of the oncomiRs using the RT-PCR measurements in the EBC patients ( = 133) that were followed up 4 years after diagnosis. This study identifies that two of the studied oncomiRs, miR-155 and miR-24, are highly predictive of EBC relapse. Furthermore, combining the oncomiR level with Ki-67 expression further specifies the relapse probability. Our data move further the notion that oncomiRs in serum enable not only monitoring of EBC but also are a very useful tool for predicting relapse independently of any other currently analyzed characteristics in EBC patients. Our approach can be translated into medical practice to estimate individual relapse risk of EBC patients.

摘要

致癌 microRNAs(oncomiRs)由于其稳定性增加而在血清中积累,因此可作为乳腺癌(BC)发病机制中的生物标志物。已经表明四种致癌 microRNAs(miR-155、miR-19a、miR-181b 和 miR-24)和一种肿瘤抑制 microRNA(let-7a)可以区分高风险和低风险早期乳腺癌(EBC),并反映手术切除肿瘤和辅助治疗。在这里,我们应用纵向多变量数据分析,使用 EBC 患者(n = 133)的 RT-PCR 测量值随机模拟每种 oncomiR 的血清水平,这些患者在诊断后随访了 4 年。这项研究确定,研究的两种 oncomiRs,miR-155 和 miR-24,高度预测 EBC 复发。此外,将 oncomiR 水平与 Ki-67 表达相结合,进一步确定了复发的可能性。我们的数据进一步表明,血清中的 oncomiRs 不仅可以监测 EBC,而且还是一种非常有用的工具,可以独立于 EBC 患者目前分析的任何其他特征来预测复发。我们的方法可以转化为医学实践,以估计 EBC 患者的个体复发风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/875a/5666798/36636c663992/ijms-18-02116-g001.jpg

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