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平均基于秩的评分来衡量分子通路基因集的去调控。

Average rank-based score to measure deregulation of molecular pathway gene sets.

机构信息

Department of Reproductive Endocrinology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China.

出版信息

PLoS One. 2011;6(11):e27579. doi: 10.1371/journal.pone.0027579. Epub 2011 Nov 9.

Abstract

BACKGROUND

Deregulation of biological pathways has been shown to be involved in the turmorigenesis of a variety of cancers. The co-regulation of pathways in tumor and normal tissues has not been studied in a systematic manner.

RESULTS

In this study we propose a novel statistic named AR-score (average rank based score) to measure pathway activities based on microarray gene expression profiles. We calculate and compare the AR-scores of pathways in microarray datasets containing expression profiles for a wide range of cancer types as well as the corresponding normal tissues. We find that many pathways undergo significant activity changes in tumors with respect to normal tissues. AR-scores for a small subset of pathways are capable of distinguishing tumor from normal tissues or classifying tumor subtypes. In normal tissues many pathways are highly correlated in their activities, whereas their correlations reduce significantly in tumors and cancer cell lines. The co-expression of genes in the same pathways was also significantly perturbed in tumors.

CONCLUSIONS

The co-regulation of genes in the same pathways and co-regulation of different pathways are significantly perturbed in tumors versus normal tissues. Our method provides a useful tool for better understanding the mechanistic changes in tumors, which can also be used for exploring other biological problems.

摘要

背景

生物途径的失调已被证明与多种癌症的肿瘤发生有关。肿瘤和正常组织中途径的共同调节尚未以系统的方式进行研究。

结果

在这项研究中,我们提出了一种新的统计量,称为 AR 分数(基于平均秩的分数),用于根据微阵列基因表达谱测量途径活性。我们计算并比较了包含广泛癌症类型表达谱的微阵列数据集以及相应的正常组织中的途径的 AR 分数。我们发现,许多途径在肿瘤与正常组织相比时经历了明显的活性变化。一小部分途径的 AR 分数能够区分肿瘤与正常组织或对肿瘤亚型进行分类。在正常组织中,许多途径的活性高度相关,而在肿瘤和癌细胞系中,它们的相关性显著降低。同一途径中的基因的共表达在肿瘤中也受到显著干扰。

结论

与正常组织相比,同一途径中的基因的共同调节和不同途径的共同调节在肿瘤中受到显著干扰。我们的方法为更好地理解肿瘤中的机制变化提供了有用的工具,也可用于探索其他生物学问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c5b/3212578/bc784ce19475/pone.0027579.g001.jpg

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