[논문]Microarray Data Analysis of Perturbed Pathways in Breast Cancer Tissues

Kim, Chang-Sik; Choi, Ji-Won; Yoon, Suk-Joon

doi:10.5808/gi.2008.6.4.210

Microarray Data Analysis of Perturbed Pathways in Breast Cancer Tissues 원문보기

Genomics & informatics, v.6 no.4, 2008년, pp.210 - 222

Kim, Chang-Sik (Department of Biological Sciences, Research Center for Women's Diseases (RCWD), Sookmyung Women's University) , Choi, Ji-Won (Department of Biological Sciences, Research Center for Women's Diseases (RCWD), Sookmyung Women's University) , Yoon, Suk-Joon (Department of Biological Sciences, Research Center for Women's Diseases (RCWD), Sookmyung Women's University)

Abstract ▼ AI-Helper

Due to the polygenic nature of cancer, it is believed that breast cancer is caused by the perturbation of multiple genes and their complex interactions, which contribute to the wide aspects of disease phenotypes. A systems biology approach for the identification of subnetworks of interconnected genes as functional modules is required to understand the complex nature of diseases such as breast cancer. In this study, we apply a 3-step strategy for the interpretation of microarray data, focusing on identifying significantly perturbed metabolic pathways rather than analyzing a large amount of overexpressed and underexpressed individual genes. The selected pathways are considered to be dysregulated functional modules that putatively contribute to the progression of disease. The subnetwork of protein-protein interactions for these dysregulated pathways are constructed for further detailed analysis. We evaluated the method by analyzing microarray datasets of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Using the strategy of microarray analysis, we selected several significantly perturbed pathways that are implicated in the regulation of progression of breast cancers, including the extracellular matrix-receptor interaction pathway and the focal adhesion pathway. Moreover, these selected pathways include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting interesting perturbed pathways that putatively play a role in the progression of breast cancer and provides an improved interpretability of networks of protein-protein interactions.

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제안 방법

The selected pathways are then considered to be dysregulated functional modules that putatively con tribute to the progression of disease. The result of this study suggests that the strategy of microarray analysis, using the score of perturbation, selects several interesting perturbed pathways that are implicated in the progression of breast cancer. It also was found that these selected pathways include several known breast cancer-related genes.

대상 데이터

The dataset was standardized such that each sample array has a mean of 0 and a standard deviation of 1. The dataset contains samples of 2 breast cancer tissues and their corresponding normal cells. The standard t test was used to score genes for overexpression or underexpression in breast cancer tissues in comparison with their normal tissues.
e, invasive lobular and ductal carcinomas. This dataset includes a total of 30 samples that consist of normal ductal cells from 10 patients, normal lobular cells from 10 patients, invasive ductal carcinoma cells from 5 patients, and invasive lobular carcinoma cells from 5 patients, which were microdissected from cryosections of 10 mastectomy specimens from postmenopausal patients. In this dataset, 50 nanograms of total RNA was amplified and labeled by PCR and in vitro transcription, and samples were analyzed using Affymetrix U133 Plus 2.

데이터처리

Based on these points of view, we applied 3 steps of microarray data analysis. First, differentially expressed genes were selected using the standard t test. Second, significantly perturbed metabolic pathways were selected based on those differentially expressed genes.

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동의어: Packet Collision Rate

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