Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer
碩士 === 國立清華大學 === 生醫工程與環境科學系 === 103 === Breast cancer (BC) is the first and second female leading cause of death respectively in Taiwan and worldwide. Metastasis is a process that cancer cells migrate from one organ to another enhancing the mortality in BC patients. The molecular mechanism is still...
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ndltd-TW-103NTHU58100462016-08-15T04:17:33Z http://ndltd.ncl.edu.tw/handle/24330533627076008502 Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer 以視覺化分析跨平台資料庫探究人類乳癌轉移基因之調控網絡 Huang, Yu Ting 黃郁婷 碩士 國立清華大學 生醫工程與環境科學系 103 Breast cancer (BC) is the first and second female leading cause of death respectively in Taiwan and worldwide. Metastasis is a process that cancer cells migrate from one organ to another enhancing the mortality in BC patients. The molecular mechanism is still unclear that BC patients with estrogen receptor (ER)-negative have been observed poorer prognosis and higher incidence of metastasis than ER-positive patients. This study conducted a meta-analysis in 353 primary and metastatic breast tumor microarray datasets of ER-positive and ER-negative patients to identify the potential target genes and their regulatory pathways in the progression of metastasis. This study used weighted gene co-expression network analysis (WGCNA) and Cytoscape to explore metastasis-specific module genes, gene network and regulatory pathways. Two human BC cell lines, MCF-7 (ER-positive) cells and MDA-MB-231 (ER-negative) cells, were used to validate the regulation pattern of these target genes in the aspect of cell migration and invasion to initiate BC metastasis. The results of the gene network analysis showed four target genes to regulate the progression of metastasis in ER-positive and ER-negative breast tumors, including TNFα (tumor necrosis factor alpha), PRKCA (protein kinase C alpha), ICAM1 (intercellular adhesion molecule 1) and VWF (Von Willebrand factor). With the treatment of siPRKCA, this study demonstrated that the reduction of PRKCA attenuated ICAM1 and VWF expression in both ER-positive and ER-negative BC cells. Moreover, the attenuation of VWF by siVWF obviously decreased cell migration and invasion in ER-negative (30.4%, 46.8%) more than in ER-positive BC cells (8.6%, 30.4%). The further results of the ER-negative BC network analysis found that VWF was also regulated by BMP4 (Bone morphogenetic protein 4) in BMP4-ICAM1-VWF pathway. With the treatment of siBMP4, this study indicated that the reduction of BMP4 attenuated ICAM1 and VWF expression in ER-negative BC cells only. This study found TNFα-PRKCA-ICAM1-VWF and BMP4-ICAM1-VWF eventually contributed to cell migration and invasion, and VWF attenuation would be a new therapeutic way to retard metastasis particularly in ER-negative BC patients. Chuang, Chun Yu 莊淳宇 2015 學位論文 ; thesis 101 en_US |
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碩士 === 國立清華大學 === 生醫工程與環境科學系 === 103 === Breast cancer (BC) is the first and second female leading cause of death respectively in Taiwan and worldwide. Metastasis is a process that cancer cells migrate from one organ to another enhancing the mortality in BC patients. The molecular mechanism is still unclear that BC patients with estrogen receptor (ER)-negative have been observed poorer prognosis and higher incidence of metastasis than ER-positive patients. This study conducted a meta-analysis in 353 primary and metastatic breast tumor microarray datasets of ER-positive and ER-negative patients to identify the potential target genes and their regulatory pathways in the progression of metastasis. This study used weighted gene co-expression network analysis (WGCNA) and Cytoscape to explore metastasis-specific module genes, gene network and regulatory pathways. Two human BC cell lines, MCF-7 (ER-positive) cells and MDA-MB-231 (ER-negative) cells, were used to validate the regulation pattern of these target genes in the aspect of cell migration and invasion to initiate BC metastasis.
The results of the gene network analysis showed four target genes to regulate the progression of metastasis in ER-positive and ER-negative breast tumors, including TNFα (tumor necrosis factor alpha), PRKCA (protein kinase C alpha), ICAM1 (intercellular adhesion molecule 1) and VWF (Von Willebrand factor). With the treatment of siPRKCA, this study demonstrated that the reduction of PRKCA attenuated ICAM1 and VWF expression in both ER-positive and ER-negative BC cells. Moreover, the attenuation of VWF by siVWF obviously decreased cell migration and invasion in ER-negative (30.4%, 46.8%) more than in ER-positive BC cells (8.6%, 30.4%). The further results of the ER-negative BC network analysis found that VWF was also regulated by BMP4 (Bone morphogenetic protein 4) in BMP4-ICAM1-VWF pathway. With the treatment of siBMP4, this study indicated that the reduction of BMP4 attenuated ICAM1 and VWF expression in ER-negative BC cells only. This study found TNFα-PRKCA-ICAM1-VWF and BMP4-ICAM1-VWF eventually contributed to cell migration and invasion, and VWF attenuation would be a new therapeutic way to retard metastasis particularly in ER-negative BC patients.
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author2 |
Chuang, Chun Yu |
author_facet |
Chuang, Chun Yu Huang, Yu Ting 黃郁婷 |
author |
Huang, Yu Ting 黃郁婷 |
spellingShingle |
Huang, Yu Ting 黃郁婷 Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
author_sort |
Huang, Yu Ting |
title |
Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
title_short |
Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
title_full |
Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
title_fullStr |
Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
title_full_unstemmed |
Visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
title_sort |
visual gene-network analysis of cross-platform datasets reveals the potential metastasis pathway in human breast cancer |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/24330533627076008502 |
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