Molecular Oncology Lab

異常細胞的無限增生與擴散是癌症的核心特徵。儘管現今早篩技術與治療策略的進步已顯著提升患者存活率，癌症仍是威脅人類健康的重大挑戰。其中，抗藥性 (Drug Resistance) 與 癌轉移 (Metastasis) 更是臨床治療面臨的關鍵瓶頸。化療雖能有效針對快速增長的癌細胞造成 DNA 損傷，但也可能是一把雙面刃——在毒殺癌細胞的同時，誘發額外的基因突變或篩選出抗藥性細胞亞群，最終導致治療失效與癌症復發。

隨著高通量定序技術的飛躍，我們已進入精準醫療時代。透過解析 DNA、RNA 及蛋白質層面的分子特徵，我們能更精確地鑑定 腫瘤異質性 (Tumor Heterogeneity)，並以此預測患者預後及藥物反應。特別是 單細胞 RNA 定序 (scRNA-seq) 技術，賦予了我們解析腫瘤微環境複雜性與動態變化的能力。結合 癌症基因體圖譜 (TCGA) 等公共數據庫中豐富的臨床與多體學數據 (如 mRNA 表現量、拷貝數變異、DNA甲基化等)，我們能有效篩選出與不良預後、抗藥性及早期復發高度相關的潛在關鍵基因。

本實驗室致力於探討癌症抗藥性、轉移與復發的分子機轉。我們的研究策略採取「乾濕實驗整合」模式：運用群體研究 (Cohort Studies) 與單細胞定序分析，結合實驗室內部建立的 CRISPR 篩選平台 (CRISPR screen) 以及本團隊新開發的 PxP 技術，進行深入的功能性驗證。我們的目標是透過解開癌症演化的分子機制，為開發新型合併療法提供科學依據，從而克服抗藥性與轉移難題，切實提升癌症治療的臨床效益。

Cancer is defined by the uncontrolled proliferation and dissemination of abnormal cells. Despite significant improvements in patient survival rates driven by advances in early detection and therapeutic strategies, cancer remains a major threat to global health. In particular, drug resistance and metastasis represent critical challenges in clinical oncology, severely impacting patients' quality of life. Chemotherapy, while effective in targeting rapidly dividing cells, often exerts selection pressure that can induce DNA mutations or facilitate the emergence of resistant subclones, ultimately leading to treatment failure and recurrence.

The advent of multi-omics technologies—encompassing DNA, RNA, and protein profiling—has paved the way for precision oncology. By characterizing tumor heterogeneity and specific molecular signatures, we can better predict patient prognosis and therapeutic responses. Currently, public resources such as The Cancer Genome Atlas (TCGA) provide comprehensive multi-omics data (including mRNA expression, copy number variants, and DNA mutations) alongside clinical information, enabling the exploration of clinical relevance. Furthermore, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for dissecting the complexity and dynamics of the tumor microenvironment. Leveraging these growing scRNA-seq datasets in conjunction with large-scale cohort studies allows us to identify potential targets associated with unfavorable outcomes, such as early recurrence.

Our laboratory is dedicated to elucidating the molecular mechanisms underlying drug resistance, metastasis, and recurrence. We employ an integrative approach that combines computational analysis of cohort and scRNA-seq data with rigorous experimental validation. specifically, we utilize in-house CRISPR screens and our newly established PxP technology to functionally validate key targets. Our ultimate goal is to translate these findings into the development of effective combination therapies, thereby overcoming drug resistance and improving clinical outcomes for cancer patients.