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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/113733


    Title: 利用生醫大數據全面性分析乳癌患者相關基因及其預後
    Comprehensive analysis of related genes and prognosis of breast cancer patients using biomedical big data
    Authors: 王念酉
    WANG, NIAN-YOU
    Contributors: 生物資訊與醫學工程學系碩士在職專班
    Keywords: 預後;基因突變;基因表現;乳癌;多體學資料
    prognosis;gene mutation;gene expression;breast cancer;omics data
    Date: 2021-10-01
    Issue Date: 2022-10-31 05:32:20 (UTC+0)
    Publisher: 亞洲大學
    Abstract: 數據顯示,2020年女性乳癌首次超越肺癌,成為全球最常見癌症。雖然台灣的乳癌好發率並未像全球數據一樣成為發生量最多的癌症,卻也是目前台灣成長率最快的癌症。乳癌發生率升高,多為肥胖及環境荷爾蒙所造成,而大部分死亡卻是因癌細胞轉移性擴散導致。因此,本研究建立一系列方法分析乳癌患者與健康人之omics data,試圖找出影響預後存活之因子。第一步驟,從GEO及TCGA資料庫裡獲取乳癌患者與健康者基因之表現及突變圖譜;接著,分析其差異表現基因及其突變率;第三步驟,將上述具有特殊意義的基因群,進行功能註解,及分析臨床預後關聯性;最後,透過文獻進行佐證。我們的研究結果顯示,有623個基因至少具有二倍差異表現,其中37個基因參與癌症代謝途徑,而且該途徑中有10個基因(RUNX1T1、MMP1、TCF7L2、ZBTB16、FOS、CCNE2、CKS2、AGTR1、PPARG、FGFR2)與臨床預後有關聯。另有9個至少四倍差異表現基因(COL10A1、ESRP1、MMP1、S100P、CA4、TRARG1、MUCL1、KRT5、WIF1)也與臨床預後有關。而前40名基因突變率分析結果顯示,有9個基因(DMD、DST、PTPRB、COL14A1、RUNX1T1、ABCA8、COL5A1、ITPR1、ATAD2)與臨床預後有關。最後,結合PubMed進行文獻探勘證實都與乳癌相關。我們相信這些結果若能提供給臨床學者做進一步的研究與探討,有望成為治療乳癌的研究方向。
    In 2020, breast cancer will surpass lung cancer for the first time and, become the most common cancer in the world. Although cancer incidence rate has not become the most frequent cancer like the global data in Taiwan, it is currently the fastest-growing cancer in Taiwan. The increased incidence of breast cancer is mostly caused by obesity and environmental hormones, while most deaths are caused by the metastatic spread of cancer cells. Therefore, we created pipeline to compare the omics data of breast cancer patients and healthy people, trying to find out the factors that affect the prognosis of survival. The first, we obtained the gene expression and mutation profiles of breast cancer patients and healthy people from GEO and TCGA databases. Second, analyzed the differentially expressed genes (DEGs) and mutation rates. Third, we further analyzed the functions of genes with specially significance and their relationship with clinical prognosis. Finally, verified the results by literatures.The results showed that there are 623 DEGs with at least two-fold changes, 37 of which are involved in the cancer metabolic pathway, and there are 10 genes (RUNX1T1, MMP1, TCF7L2, ZBTB16, FOS, CCNE2, CKS2, AGTR1, PPARG, FGFR2) is associated with clinical prognosis. Another 9 DEGs at least four-fold changes (COL10A1, ESRP1, MMP1, S100P, CA4, TRARG1, MUCL1, KRT5, WIF1) are also related to clinical prognosis. The analysis of the mutation rate of the top 40 genes showed that 9 genes (DMD, DST, PTPRB, COL14A1, RUNX1T1, ABCA8, COL5A1, ITPR1, ATAD2) are related to clinical prognosis. Finally, a literature survey with PubMed confirmed that they are all related to breast cancer. We believe that these results can be provided to clinical scholars for further study, and it is expected to become a research direction for the treatment of breast cancer.
    Appears in Collections:[生物資訊與醫學工程學系 ] 博碩士論文

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