基於奈米點誘導細胞轉化分析之藥物篩選平台開發

生物途徑包含了複雜的組成元素與交互作用，高度動態的調控網絡會隨著不同時間與空間分布而改變，而內因性與外源性的刺激也會引發不同的細胞反應，造成細胞有許多的連續時間序列性變化和狀態的轉化。是以在探討生物機制時若僅以單一靜態條件來考量，並不能完整體現生物的動態性特徵，動態性的分析方法便顯得更加重要。在考量細胞於不同狀態條件下的動態轉化，可以提供更深入的資訊，以用於更多的生物醫學應用。而進一步考量進藥物與體內生物途徑的關聯性並結合生物資訊分析的優勢，計算藥物基因體學可以提供更全面性的觀點，去探討生物調控網路與藥物反應的資訊，進而助於推展個人化醫學，並能用於藥物的篩選與開發。藉由結合基因表現資料、生物功能性註釋、臨床資訊與藥物標的交互作用等多類型的資訊，可以提供系統性的分析助於開發新的藥物應用、篩選藥物適合的施用濃度與降低藥物開發成本。在此篇研究中，為了進一步探討生物的動態性變化，我們藉由建構10到200奈米不同尺度大小的奈米點晶片所建構的人工微環境模型，來探討奈米拓樸結構所誘導的癌細胞特性轉化；並利用動態時間序列性的分析方法取代傳統上單一靜態的分析方式，探討奈米點尺度變化間的動態調控。利用分析不同大小奈米點晶片之基因表現，我們發現奈米點誘發的細胞轉化和細胞移動、黏附與細胞外基質（ECM）的生物功能有所關聯。而利用時間序列的分析方法，我們找出了具有統計顯著性的正向調控基因表現趨勢；為了深入探討關聯的生物功能途徑，我們選出和表皮生長因子與其受體（EGF/EGFR）、上皮細胞間質轉化（EMT）、細胞外基質（ECM）與細胞黏附（adhesion）相關的四個功能性基因組進行探討。進一步將奈米點誘導之細胞轉化與時間序列轉化的資料進行比較，我們於四個功能性基因組中以時間序列分析方法找出的正向調控轉化之基因中發現，百分之二十到四十的基因具有與時間序列性轉化之資料有類似的基因表現變化趨勢；這樣的結果提供了利用奈米點變化作為模擬時間性變化的應用可能性。此外，藉由結合計算藥物基因體學的方式，奈米點誘導所調控的基因可用於篩選具有相似與相反調控作用的小分子藥物，進而作為藥物篩選的應用。藉由細胞藥物作用的試驗結果中可以發現，基因層面的表現趨勢與細胞形態上的變化可以藉由兩種不同作用的小分子藥物進行調控。本篇研究以一個新的角度，提出了一個整合性的方式來分析奈米點誘導的動態細胞轉化，並呈現其於藥物篩選平台開發上的應用潛能。

關鍵字

藥物篩選；細胞轉化；生物資訊；奈米點；藥物基因組學

並列摘要

Biological processes are highly dynamic, involving various components, interactions and regulatory networks with spatiotemporal modulation. Internal and external stimuli and signals trigger different cell responses that associated with time-varying events and cell state transition. As genetic networks and pathways are continuously changed over time, the algorithms and tools developed for single static state analysis without considering the dynamic nature of biological processes can only provide limited insight and will lose the information about overall trends of transition patterns. Therefore, computational approaches using dynamic models are introduced for the investigation of transient changes across various states, conditions and time-dependent events which can provide more comprehensive information for biomedical application. Combing with the advantages of bioinformatics approaches and pharmacology, computational pharmacogenomics analysis enable a more holistic view of biological network and drug response, and thus can be applied for personalized medicine, drug discovery and drug development. Various kinds of data including gene expression, functional annotation, clinical data and drug-target interaction can provide systematic information for selecting new drug target, optimal dose and shorten the cost of drug development. In this study, to investigate the dynamic nature of biological processes instead of single static state analysis, different size of nanodots array ranging from 10 to 200 nm were fabricated as an artificial microenvironment model to study the size-varying nanotopographical effects on cancer cell behaviors and method for time-series data analysis was used for the analysis of nanotopography induced cellular transition. With analysis of the gene expression data from all different size nanodot arrays, functional annotation results showed that the enriched biological processes and pathway were associated with cell migration, motility, cell adhesion and extracellular matrix. In the result of transition pattern analysis, up-regulated profile was labeled as statistically significant. To more precisely assess the related biological processes, 4 functional gene modules including epidermal growth factor receptor (EGF/EGFR), epithelial mesenchymal transition (EMT), extracellular matrix (ECM) and cell adhesion were selected for further analysis. By comparing the time-series transition data set with nanodot induced transition data, around 20 to 40 percent genes in the up-regulated transition genes of 4 gene modules were found to have similar gene expression transition pattern with the time-series data. These results provide the potential application that the nanodot size-varying transition pattern identified by time-series analysis method can be used as a model of time-varying transition process. Furthermore, genes associated with the nanodot induced transition can be applied with the computational pharmacogenomics approach to investigate the association between transition gene patterns and small molecule drugs for drug screening purpose. Two small molecule compounds with similar and opposing signature related to the up-regulated transition genes were selected for further validation. In the results of drug treatment, the selected compounds with similar and opposing function showed the modulation effect on cellular transition of gene expression and cell morphology. As a new point of view, current study proposed an integrated approach for drug screening platform development by nanotopography induced cellular transition pattern analysis.

並列關鍵字

Drug screening ； Cellular transition ； Bioinformatics ； Nanodot ； Pharmacogenomics

參考文獻

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