Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation

碩士 === 國防醫學院 === 公共衛生學研究所 === 103 === Background:Recent studies present many candidate genes of colorectal cancer by microarray data analysis. These genes are association between category, predict, prognosis and targeted therapy of colorectal cancer. These studies present many genes but some genes w...

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Main Authors: Chen Chien-Ting, 陳建廷
Other Authors: Chu Chi-Ming
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/94175445038823155311
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spelling ndltd-TW-103NDMC00580332017-02-19T04:30:41Z http://ndltd.ncl.edu.tw/handle/94175445038823155311 Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation 彙集結直腸癌微陣列基因資料集-建立癌症發生之候選基因表現譜及其調控途徑與細胞培養及動物模型之驗證 Chen Chien-Ting 陳建廷 碩士 國防醫學院 公共衛生學研究所 103 Background:Recent studies present many candidate genes of colorectal cancer by microarray data analysis. These genes are association between category, predict, prognosis and targeted therapy of colorectal cancer. These studies present many genes but some genes will overlap which maybe these genes in the same pathway. Objective:Find the candidate genes which upstream or downstream in pathway by coefficient of variation, principal component analysis, logistic regression and Pearson correlation. Methods:We collect microarray data of colorectal cancer from GEO database. Pooled difference microarray data to two dataset. Using Prediction Analysis of Microarray select candidate genes of colorectal cancer and establish prediction model. Association of candidate genes would effect significance of genes in logistic regression. Selected important candidate genes by logistic regression model. These important candidate genes and other genes in dataset analyze by Pearson correlation. We select some the relative gene in same pathway with candidate genes possibly by two difference microarray dataset. We utilize principal component analysis to check these candidate genes and the relative genes which whether in same pathway. Sorted these genes in same pathway and confirmed genes place in upstream or downstream. Results: We utilize statistics analysis to find CWH43, GUCA2B, SCNN1B, AQP8 and SPIB in same pathway. IL6R, GUCA2B, SLC30A10, SCNN1B and AQP8 are in same pathway. AQP8 and CLDN8 are in same pathway. SPP1 and TNFAIP6 are in same pathway. SPIB, BANK1 and MS4A1 are in same pathway. Conclusion:Using these analysis can find these genes in same pathway. We also confirm difference candidate gene in difference studies since these genes are in same pathway possibly. Chu Chi-Ming 朱基銘 2015 學位論文 ; thesis 170 zh-TW
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language zh-TW
format Others
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description 碩士 === 國防醫學院 === 公共衛生學研究所 === 103 === Background:Recent studies present many candidate genes of colorectal cancer by microarray data analysis. These genes are association between category, predict, prognosis and targeted therapy of colorectal cancer. These studies present many genes but some genes will overlap which maybe these genes in the same pathway. Objective:Find the candidate genes which upstream or downstream in pathway by coefficient of variation, principal component analysis, logistic regression and Pearson correlation. Methods:We collect microarray data of colorectal cancer from GEO database. Pooled difference microarray data to two dataset. Using Prediction Analysis of Microarray select candidate genes of colorectal cancer and establish prediction model. Association of candidate genes would effect significance of genes in logistic regression. Selected important candidate genes by logistic regression model. These important candidate genes and other genes in dataset analyze by Pearson correlation. We select some the relative gene in same pathway with candidate genes possibly by two difference microarray dataset. We utilize principal component analysis to check these candidate genes and the relative genes which whether in same pathway. Sorted these genes in same pathway and confirmed genes place in upstream or downstream. Results: We utilize statistics analysis to find CWH43, GUCA2B, SCNN1B, AQP8 and SPIB in same pathway. IL6R, GUCA2B, SLC30A10, SCNN1B and AQP8 are in same pathway. AQP8 and CLDN8 are in same pathway. SPP1 and TNFAIP6 are in same pathway. SPIB, BANK1 and MS4A1 are in same pathway. Conclusion:Using these analysis can find these genes in same pathway. We also confirm difference candidate gene in difference studies since these genes are in same pathway possibly.
author2 Chu Chi-Ming
author_facet Chu Chi-Ming
Chen Chien-Ting
陳建廷
author Chen Chien-Ting
陳建廷
spellingShingle Chen Chien-Ting
陳建廷
Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
author_sort Chen Chien-Ting
title Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
title_short Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
title_full Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
title_fullStr Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
title_full_unstemmed Gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
title_sort gene expression profile and regulation pathway of candidate genes for colorectal cancer: cell culture and animal validation
publishDate 2015
url http://ndltd.ncl.edu.tw/handle/94175445038823155311
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