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基于细胞内信号通路激活的新型人类膀胱癌稳健生物标志物

Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways.

作者信息

Lezhnina Ksenia, Kovalchuk Olga, Zhavoronkov Alexander A, Korzinkin Mikhail B, Zabolotneva Anastasia A, Shegay Peter V, Sokov Dmitry G, Gaifullin Nurshat M, Rusakov Igor G, Aliper Alexander M, Roumiantsev Sergey A, Alekseev Boris Y, Borisov Nikolay M, Buzdin Anton A

机构信息

Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR. Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.

Department of Biological Sciences, University of Lethbridge, 4401 University Drive, Lethbridge, AB, T1K 3M4. Canada Cancer and Aging Research Laboratories, Lethbridge, AB, Canada.

出版信息

Oncotarget. 2014 Oct 15;5(19):9022-32. doi: 10.18632/oncotarget.2493.

Abstract

We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer. Using Illumina HT12v4 microarrays, we profiled gene expression in 17 cancer and seven non-cancerous bladder tissue samples. These experiments were done in two independent laboratories located in Russia and Canada. We calculated pathway activation strength values for the investigated transcriptomes and identified signaling pathways that were regulated differently in bladder cancer (BC) tissues compared with normal controls. We found, for both experimental datasets, 44 signaling pathways that serve as excellent new biomarkers of BC, supported by high area under the curve (AUC) values. We conclude that the OncoFinder approach is highly efficient in finding new biomarkers for cancer. These markers are mathematical functions involving multiple gene products, which distinguishes them from "traditional" expression biomarkers that only assess concentrations of single genes.

摘要

我们最近提出了一种名为OncoFinder的新生物信息学算法,用于量化细胞内信号通路的激活情况。事实证明,该算法有利于将高通量基因表达分析的误差降至最低,并显示出识别新生物标志物的强大潜力。在此,我们首次将OncoFinder应用于人类膀胱的正常组织和癌组织,以识别膀胱癌的生物标志物。我们使用Illumina HT12v4微阵列,对17个癌性和7个非癌性膀胱组织样本的基因表达进行了分析。这些实验在位于俄罗斯和加拿大的两个独立实验室中进行。我们计算了所研究转录组的信号通路激活强度值,并确定了与正常对照相比,在膀胱癌(BC)组织中受到不同调控的信号通路。对于这两个实验数据集,我们发现44条信号通路可作为BC的优良新型生物标志物,曲线下面积(AUC)值很高,这为其提供了支持。我们得出结论,OncoFinder方法在寻找癌症新生物标志物方面非常高效。这些标志物是涉及多种基因产物的数学函数,这使它们有别于仅评估单个基因浓度的“传统”表达生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22c4/4253415/1d12c228a6a1/oncotarget-05-9022-g001.jpg

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