基因表現與乳癌亞型的關聯性分析;Association analysis of gene expression with breast cancer subtype

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題名:	基因表現與乳癌亞型的關聯性分析;Association analysis of gene expression with breast cancer subtype
作者:	劉佳媛;Liu, Chia-Yuan
貢獻者:	生醫科學與工程學系
關鍵詞:	乳癌;亞型;高表達基因;TCGA;UALCAN;Breast cancer;Subtypes;Gene expression;TCGA;UALCAN
日期:	2025-07-01
上傳時間:	2025-10-17 11:26:42 (UTC+8)
出版者:	國立中央大學
摘要:	乳癌是女性最常見的癌症，對全球健康構成重大威脅。隨著次世代基因定序（NGS，next generation sequencing）的快速發展，我們得以更深入地研究與乳癌相關的基因。特定基因的異常表達與乳癌的發展和預後息息相關。乳癌具有異質性，包含多種不同的亞型，每種亞型在基因表達、生物學特性和對治療的反應上都存在顯著差異。因此，在乳癌研究中考慮亞型因素至關重要，有助於更精準地理解不同亞型的發病機制和尋找更有效的治療策略。癌症基因組圖譜（TCGA）大型基因組計畫為研究這些基因提供了大量且完整的數據資源，能以系統性地分析大量乳癌樣本的基因。不僅有助於我們更深入地了解乳癌的分子機制，還能為開發更有效的標靶治療策略奠定基礎。標靶治療通過精準鎖定癌細胞中的特定基因，達到抑制腫瘤生長、擴散的目的，從而提高治療效果並降低副作用。更重要的是，發現新的標靶可以為那些對現有治療方法產生抗藥性的患者提供新的治療選擇，並有助於開發更個性化的治療方案。本篇在利用 UALCAN 平台和 TCGA 數據庫。UALCAN 平台支持基於轉錄組數據的基因表達量分析和 Kaplan-Meier 存活曲線生成，能夠快速篩選出在腫瘤組織中表達量顯著高於正常組織的基因。本篇的研究方法包括基因表達分析和存活分析，在分析特定高表達基因在乳癌中的角色，並探討這些基因與患者預後之間的關聯，同時考慮乳癌亞型的影響，以及快速地發現新的診斷標誌物和標靶治療，通過深入研究這些基因從而改善乳癌患者的預後，並為克服現有治療的局限性提供新的機會。最終為乳癌的早期診斷、精準治療和預後改善做出貢獻。;Breast cancer is the most common cancer among women and poses a significant global health threat. As Next generation sequencing (NGS)improves by leaps and bounds, researchers are now able to gain deeper insights into genes associated with breast cancer. Abnormal expression of specific genes is closely linked to the development and prognosis of the disease. Breast cancer is a heterogeneous disease composed of multiple subtypes, each characterized by distinct gene expression patterns, biological behaviors, and treatment responses. Therefore, considering breast cancer subtypes is crucial for accurately understanding tumorigenesis and for identifying more effective therapeutic strategies.The Cancer Genome Atlas (TCGA), a large-scale genomics initiative, offers a comprehensive dataset that enables systematic analysis of gene expression across numerous breast cancer samples. This resource not only enhances our understanding of the molecular mechanisms of breast cancer but also lays the foundation for the development of more effective targeted therapies. Targeted therapies work by precisely inhibiting specific genes in cancer cells to suppress tumor growth and metastasis, thereby improving treatment outcomes and minimizing side effects. Moreover, the discovery of novel targets may offer alternative treatment options for patients who develop resistance to existing therapies, and it facilitates the advancement of personalized medicine.In this study, we utilized the UALCAN platform and TCGA database. UALCAN supports transcriptome-based gene expression analysis and Kaplan–Meier survival curve enabling rapid identification of genes that are significantly overexpressed in tumor tissues compared to normal tissues. The research methodology includes gene expression analysis and survival analysis to investigate the role of specific highly expressed genes in breast cancer, examine their association with patient prognosis, and assess the impact of molecular subtypes. The ultimate goal is to identify novel diagnostic biomarkers and therapeutic targets, improve patient outcomes, and provide new opportunities to overcome the limitations of current treatments—thereby contributing to early diagnosis, precision medicine, and enhanced prognosis in breast cancer.
顯示於類別:	[生物醫學工程研究所 ] 博碩士論文

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