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...

Full description

Bibliographic Details
Main Authors: Huang, Yu Ting, 黃郁婷
Other Authors: Chuang, Chun Yu
Format: Others
Language:en_US
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/24330533627076008502
id ndltd-TW-103NTHU5810046
record_format oai_dc
spelling 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
collection NDLTD
language en_US
format Others
sources NDLTD
description 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.
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
work_keys_str_mv AT huangyuting visualgenenetworkanalysisofcrossplatformdatasetsrevealsthepotentialmetastasispathwayinhumanbreastcancer
AT huángyùtíng visualgenenetworkanalysisofcrossplatformdatasetsrevealsthepotentialmetastasispathwayinhumanbreastcancer
AT huangyuting yǐshìjuéhuàfēnxīkuàpíngtáizīliàokùtànjiūrénlèirǔáizhuǎnyíjīyīnzhīdiàokòngwǎngluò
AT huángyùtíng yǐshìjuéhuàfēnxīkuàpíngtáizīliàokùtànjiūrénlèirǔáizhuǎnyíjīyīnzhīdiàokòngwǎngluò
_version_ 1718376394380017664