Mejía-Pedroza Raúl A, Espinal-Enríquez Jesús, Hernández-Lemus Enrique
Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.
Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Front Pharmacol. 2018 Aug 15;9:905. doi: 10.3389/fphar.2018.00905. eCollection 2018.
Breast cancer is a major public health problem which treatment needs new pharmacological options. In the last decades, during the postgenomic era new theoretical and technological tools that give us novel and promising ways to address these problems have emerged. In this work, we integrate several tools that exploit disease-specific experimental transcriptomic results in addition to information from biological and pharmacological data bases obtaining a contextual prioritization of pathways and drugs in breast cancer subtypes. The usefulness of these results should be evaluated in terms of drug repurposing in each breast cancer molecular subtype therapy. In favor of breast cancer patients, this methodology could be further developed to provide personalized treatment schemes. The latter are particularly needed in those breast cancer subtypes with limited therapeutic options or those who have developed resistance to the current pharmacological schemes.
乳腺癌是一个重大的公共卫生问题,其治疗需要新的药理学选择。在过去几十年的后基因组时代,出现了新的理论和技术工具,为我们解决这些问题提供了新颖且有前景的方法。在这项工作中,我们整合了多种工具,这些工具除了利用来自生物和药理学数据库的信息外,还利用特定疾病的实验转录组学结果,从而获得乳腺癌亚型中通路和药物的背景优先级。这些结果的实用性应根据每种乳腺癌分子亚型治疗中的药物重新利用来评估。为了乳腺癌患者的利益,这种方法可以进一步发展以提供个性化的治疗方案。在那些治疗选择有限的乳腺癌亚型或对当前药理学方案产生耐药性的患者中,尤其需要个性化治疗方案。