Carels Nicolas, Spinassé Lizânia Borges, Tilli Tatiana Martins, Tuszynski Jack Adam
Laboratório de Modelagem de Sistemas Biológicos, National Institute of Science and Technology for Innovation in Neglected Diseases (INCT/IDN, CNPq), Centro de Desenvolvimento Tecnológico em Saúde, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Department of Oncology, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, T6G 1Z2, Canada.
Theor Biol Med Model. 2016 Feb 29;13:7. doi: 10.1186/s12976-016-0035-4.
In this review, we report on breast cancer's molecular features and on how high throughput technologies are helping in understanding the dynamics of tumorigenesis and cancer progression with the aim of developing precision medicine methods. We first address the current state of the art in breast cancer therapies and challenges in order to progress towards its cure. Then, we show how the interaction of high-throughput technologies with in silico modeling has led to set up useful inferences for promising strategies of target-specific therapies with low secondary effect incidence for patients. Finally, we discuss the challenge of pharmacogenetics in the clinical practice of cancer therapy. All these issues are explored within the context of precision medicine.
在本综述中，我们报告了乳腺癌的分子特征，以及高通量技术如何有助于理解肿瘤发生和癌症进展的动态过程，旨在开发精准医学方法。我们首先阐述乳腺癌治疗的当前技术水平和面临的挑战，以便在治愈乳腺癌方面取得进展。然后，我们展示了高通量技术与计算机模拟的相互作用如何为低副作用发生率的靶向特异性治疗的有前景策略建立有用的推断。最后，我们讨论了癌症治疗临床实践中药理学遗传学的挑战。所有这些问题都在精准医学的背景下进行探讨。
