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OSAnalyzer: A Bioinformatics Tool for the Analysis of Gene Polymorphisms Enriched with Clinical Outcomes

机译:OSAnalyzer:一种用于分析临床结果丰富的基因多态性的生物信息学工具

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摘要

Background: The identification of biomarkers for the estimation of cancer patients’ survival is a crucial problem in modern oncology. Recently, the Affymetrix DMET (Drug Metabolizing Enzymes and Transporters) microarray platform has offered the possibility to determine the ADME (absorption, distribution, metabolism, and excretion) gene variants of a patient and to correlate them with drug-dependent adverse events. Therefore, the analysis of survival distribution of patients starting from their profile obtained using DMET data may reveal important information to clinicians about possible correlations among drug response, survival rate, and gene variants. Methods: In order to provide support to this analysis we developed OSAnalyzer, a software tool able to compute the overall survival (OS) and progression-free survival (PFS) of cancer patients and evaluate their association with ADME gene variants. Results: The tool is able to perform an automatic analysis of DMET data enriched with survival events. Moreover, results are ranked according to statistical significance obtained by comparing the area under the curves that is computed by using the log-rank test, allowing a quick and easy analysis and visualization of high-throughput data. Conclusions: Finally, we present a case study to highlight the usefulness of OSAnalyzer when analyzing a large cohort of patients.
机译:背景:鉴定用于评估癌症患者生存率的生物标志物是现代肿瘤学中的关键问题。最近,Affymetrix DMET(药物代谢酶和转运蛋白)微阵列平台为确定患者的ADME(吸收,分布,代谢和排泄)基因变体并将其与药物依赖性不良事件相关提供了可能性。因此,从使用DMET数据获得的患者资料开始的患者生存分布分析,可能会向临床医生揭示有关​​药物反应,生存率和基因变异之间可能相关性的重要信息。方法:为了为该分析提供支持,我们开发了OSAnalyzer,这是一种软件工具,能够计算癌症患者的总体生存期(OS)和无进展生存期(PFS)并评估其与ADME基因变体的关联。结果:该工具能够对富含生存事件的DMET数据进行自动分析。此外,根据通过比较使用对数秩检验计算的曲线下面积所获得的统计显着性对结果进行排名,从而可以快速,轻松地分析和可视化高通量数据。结论:最后,我们提出一个案例研究,以突出OSAnalyzer在分析大量患者时的有用性。

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