基於疾病相關微陣基因群的候選藥物評估

Abstract

由於開發新藥物成本高、研發時程長，舊藥新用為生醫資訊之研究方向之一。本研究利用ONCOMINE資料庫內的癌症基因表現差異，配合Connectivity Map內的不同藥物處理細胞株產生之基因表現差異資料，藉由Connectivity Map評估具有潛力之藥物，並進一步利用DrugBank、POINeT去分析這些藥物之作用路徑、作用標靶、蛋白質交互作用，以得到較可靠之藥物供後續生物實驗測試。 研究中疾病選擇攝護腺癌，經由ONCOMINE資料庫中取不同門檻值之高低表現量基因，分別輸入Connectivity Map以得到具潛力藥物，共獲得12項候選藥物，其中5項屬於癌症治療用藥(vorinostat，皮膚淋巴癌。tanespimycin、alvespimycin，HSP-90抑制劑。camptothecin、fulvestrant，乳癌)，以及1項(alfuzosin)屬於前列腺肥大用藥。查詢候選藥物的Drug Bank直接作用標靶蛋白質，並以POINeT分析疾病高低表現量基因與藥物標靶蛋白。具有S3 排名者有vorinostat之HDAC、HDAC2和fulvestrant之ESR1三個標靶蛋白，但相對於疾病高低表現量基因網路上節點排名為低，表示藥物可能具有療效，但藥物對於整體蛋白質交互作用網路的影響可能較小。

Due to the high cost of money and time for new drug development, new application for old drugs is one of the critical directions in bioinformatics research. In the present study, cancer gene expression differences accessed via the database ONCOMINE along with the differences in gene expression by different drugs dealing with cell lines within the Connectivity Map were utilized. Based on the potential drugs assessed by Connectivity Map, DrugBank and POINeT were used to analyze the pathways of drugs and their therapeutic targets as well as protein interactions in order to obtain putative candidate drugs for follow-up biological testing experiments. Prostate cancer was chosen in this study, and variant volume of gene expressions in different threshold levels retreived via ONCOMINE were keyed in Connectivity Map to obtain 12 potential drug candidates, of which five are associated with cancer treatment medicine (vorinostat, cutaneous lymphoma; tanespimycin, alvespimycin, HSP-90 inhibitors; camptothecin ,fulvestrant, breast cancer), and 1 (alfuzosin) is prostate medication. Querying drug candidates of direct target proteins in Drug Bank and analyzing the performance of the volume of disease genes and drug target proteins using POINeT, the results show as follows: three target proteins are vorinostat of HDAC1, HDAC2 and fulvestrant of ESR1, but the scores of gene network nodes were low relative to the level of performance volume of disease. Thus, it is indicated that the drugs may have effects but may have relatively small impact concerning the overall protein-protein interaction network.