生物信息技术加速开发旧药新用途

传统的技术路线研发新药，不仅周期很长而且耗资巨大，开发已获批准药物新的治疗用途，又称为药物重定位，比传统的新药研发具有明显的优势．基于芯片的基因表达谱分析，已常规地广泛用于各种人类疾病的临床研究，提供了在全基因组水平描述疾病状态的特征信号．同时，基因芯片也广泛地用于对比药物处理前后细胞基因表达模式的变化，这也提供了反映药物效应的高质量信号．最近出版的Science Translational Medicine杂志同时发表了一个研究组的两篇论文，为我们展示了如何利用生物信息学手段重新解析和比较全基因组基因表达谱数据，以高效地预测药物的新用途．这两篇论文使用了公共数据库中的100种疾病基因表达谱数据，以及164种药物处理前后细胞基因表达谱数据，通过比较和配对疾病与药物基因表达谱，得到了一些可以逆转疾病异常表达基因的药物，其中证实了一些已知的药物-疾病组合，也预测了一些新的药物-疾病组合．最后通过实验验证了抗溃疡药可用于治疗肺癌，而抗癫痫药可治疗炎症性肠道疾病，进一步证实了他们所采用研究策略的正确性．于是，肺癌和炎性肠道疾病这两种临床上难治的疾病有了新的候选治疗药物，我们也有了一种挖掘已有数据快速发现药物新用途的思路和方法．

Bioinformatics Accelerates Drug Repositioning

Traditional approaches to drug discovery are generally regarded as protracted and costly. The application of established drug compounds to new therapeutic indications, known as drug repositioning, offers several advantages over traditional drug development. Gene expression microarrays are regularly and broadly applied in clinical studies of human diseases, providing genome-wide characterization of a disease state. Microarrays are also widely used to discover gene expression patterns that signify pharmacologic perturbation, allowing for the development of high-quality signatures of drug effect. A pair of papers from one group recently published in Science Translational Medicine provided a concrete example of how to using bioinformatics approach to reinterpret and compare genome-wide gene expression data, that allows us to effectively hypothesize which drugs from one disease-indication can be repurposed for another disease. They examined publicly available gene expression data and determined the genes affected in 100 diseases and 164 drugs. By pairing drugs that correct abnormal gene expression in diseases, they confirmed known effective drug-disease pairs and predicted new indications for already approved agents. Experimental validation that an antiulcer drug and an antiepileptic can be reused for lung cancer and inflammatory bowel disease reinforced the promise of this approach. These two drugs are therefore good candidates for repositioning to treat lung cancer and inflammatory bowel disease that in need of better therapies, and we now have a way to mine available data for fast routes to new disease therapies.