| Summary: | 碩士 === 國立臺灣大學 === 生醫電子與資訊學研究所 === 102 === 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.
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