PURPOSE We explored the mechanism of aspirin in SCLC by dissecting many publicly available databases. METHODS AND RESULTS Firstly, 11 direct protein targets (DPTs) of aspirin were identified by DrugBank 5.0. Then protein-protein interaction (PPI) network and signaling pathways of aspirin DPTs were analyzed. We found that aspirin was linked with many kinds of cancer, and the most significant one is SCLC. Next, we classified the mutation of 4 aspirin DPTs in SCLC (IKBKB, NFKBIA, PTGS2 and TP53) using cBio Portal. Further, we identified top 50 overexpressed genes of SCLC by Oncomine, and the interconnected genes with the 4 aspirin DPTs in SCLC (IKBKB, NFKBIA, PTGS2 and TP53) by STRING. Lastly, we figured out 5 consistently genes as potential therapeutic targets of aspirin in SCLC. CONCLUSION The integrated bioinformatical analysis could improve our understanding of the underlying molecular mechanism about how aspirin working in SCLC. Integrated bioinformatical analysis may be considered as a new paradigm for guiding future studies about interaction in drugs and diseases.

中文翻译：

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综合生物信息学分析，可确定阿司匹林在小细胞肺癌中的治疗目标。

目的我们通过剖析许多公开可用的数据库，探索了阿司匹林在小细胞肺癌中的作用机理。方法和结果首先，通过DrugBank 5.0鉴定了11种阿司匹林直接蛋白靶标（DPT）。然后分析了阿司匹林DPT的蛋白-蛋白相互作用（PPI）网络和信号通路。我们发现阿司匹林与多种癌症有关，其中最重要的一种是小细胞肺癌。接下来，我们使用cBio Portal对SCLC中4种阿司匹林DPT的突变（IKBKB，NFKBIA，PTGS2和TP53）进行了分类。此外，我们通过STRING鉴定了Oncomine的SCLC的前50个过表达基因，以及与SCLC中的4种阿司匹林DPT（IKBKB，NFKBIA，PTGS2和TP53）相关的基因。最后，我们找出了5个一致的基因作为SCLC中阿司匹林的潜在治疗靶标。结论整合的生物信息学分析可以增进我们对阿司匹林如何在SCLC中起作用的潜在分子机制的理解。综合的生物信息学分析可以被认为是指导有关药物和疾病相互作用的未来研究的新范例。