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標題: | 利用大規模患者小分子核糖核酸測序數據探索癌症相關微生物菌相 Exploring Cancer-Associated Microbiome Characteristics Using Large-Scale Patient Small RNA Sequencing Data |
作者: | Wei-Hao Lee 李偉豪 |
指導教授: | 阮雪芬(Hsueh-Fen Juan) |
關鍵字: | 菌相,小分子核糖核酸,大腸直腸癌,美國癌症基因體圖譜計畫, Microbiome,small RNA,colorectal cancer,The Cancer Genome Atlas,miRNA sequencing, |
出版年 : | 2019 |
學位: | 碩士 |
摘要: | 微生物就像是我們人體的類器官,他與我們緊緊的相依,尤其是腸道。近幾年的腸道菌相研究蓬勃發展,多虧於定序技術的革新,讓人類有機會揭曉腸道菌相。目前已知腸道菌相與人類的許多生物功能相關,例如人體免疫功能、腦腸迴、新陳代謝、和腫瘤生成。然而,當微生物菌相的生態失調發生時,微生物的變化可能有助於微環境改變,這可能誘導炎症以及免疫反應並為腫瘤提供一個生長利基。尤其腫瘤生成與菌相的關聯目前了解的甚少。因此我們設計新的分析流程,搭配The Cancer Genome Atlas(TCGA)癌症的小分子核糖核酸測序數據,進行癌症菌相分析的。本篇使用大腸直腸癌病患的miRNA-Seq資料做主要分析資料來源,透過從miRNA-Seq取出非人類miRNA序列數據與微生物基因序列比對分析以獲得癌症相關微生物菌相。在本篇研究裡,我們在630個結腸直腸癌樣本中鑑定了數千個細菌的屬,並將所有樣本分成三個獨特的腸道型別。每個腸道型別都有自己獨特的微生物組成和微生物間的相互作用。我們不僅能找到與先前研究相同的癌症相關菌相,我們另外辨識出12個癌症階段相關的屬。本研究提供了一種全新檢測癌症相關微生物菌相的分析方法,而且這個分析方法具有很好的應用性,可以搭配TCGA更多的癌症菌相分析,如乳腺癌,肺癌和前列腺癌,這些揭示些很難收集微生物樣本的癌症。 The microbiome is recognized as a quasi-organ in the human body. In particular, the gut microbiome is strongly correlated with immune function, metabolism, and tumorigenesis. When dysbiosis of the microbiome occurs, this variation may contribute to alterations in the microenvironment, potentially inducing an inflammatory immune response and providing a niche for neoplastic growth. However, there is limited evidence regarding the correlation and interaction between the microbiome and tumorigenesis. By utilizing microRNA sequencing data of patients with colon and rectal cancer from The Cancer Genome Atlas, we designed a novel analytical process to extract non-human small RNA sequence data and align it with the microbial genome to obtain a comprehensive view of the cancer-associated microbiome. In the present study, we identified > 1,000 genera among 630 colorectal cancer sample and clustered these samples into three distinctive colorectal enterotypes. Each cluster has its own distinctive microbial composition and interactions. The observed characteristics of the colorectal cancer microbiome are consistent with previous findings. Furthermore, we found 12 genera from these clusters that are associated with cancer stages and revealed their putative functions through correlation with gene expression signatures in patient tissues. Our results indicate that the proposed analytical approach can effectively determine the cancer-associated microbiome. It may be readily applied to explore other types of cancer (e.g., breast, lung, and prostate), in which specimens of the microbiome are difficult to collect. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74124 |
DOI: | 10.6342/NTU201903294 |
全文授權: | 有償授權 |
顯示於系所單位: | 分子與細胞生物學研究所 |
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