Department of Breast Medical Oncology, The University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030-4009, USA.
J Clin Oncol. 2010 Jun 1;28(16):2777-83. doi: 10.1200/JCO.2009.27.0777. Epub 2010 Apr 20.
The development of cost-effective technologies able to comprehensively assess DNA, RNA, protein, and metabolites in patient tumors has fueled efforts to tailor medical care. Indeed validated molecular tests assessing tumor tissue or patient germline DNA already drive therapeutic decision making. However, many theoretical and regulatory challenges must still be overcome before fully realizing the promise of personalized molecular medicine. The masses of data generated by high-throughput technologies are challenging to manage, visualize, and convert to the knowledge required to improve patient outcomes. Systems biology integrates engineering, physics, and mathematical approaches with biologic and medical insights in an iterative process to visualize the interconnected events within a cell that determine how inputs from the environment and the network rewiring that occurs due to the genomic aberrations acquired by patient tumors determines cellular behavior and patient outcomes. A cross-disciplinary systems biology effort will be necessary to convert the information contained in multidimensional data sets into useful biomarkers that can classify patient tumors by prognosis and response to therapeutic modalities and to identify the drivers of tumor behavior that are optimal targets for therapy. An understanding of the effects of targeted therapeutics on signaling networks and homeostatic regulatory loops will be necessary to prevent inadvertent effects as well as to develop rational combinatorial therapies. Systems biology approaches identifying molecular drivers and biomarkers will lead to the implementation of smaller, shorter, cheaper, and individualized clinical trials that will increase the success rate and hasten the implementation of effective therapies into the clinical armamentarium.
开发具有成本效益的技术,能够全面评估患者肿瘤中的 DNA、RNA、蛋白质和代谢物,这推动了医疗保健个性化的努力。事实上,经过验证的评估肿瘤组织或患者种系 DNA 的分子检测已经可以驱动治疗决策。然而,在充分实现个性化分子医学的承诺之前,仍有许多理论和监管方面的挑战需要克服。高通量技术产生的大量数据在管理、可视化和转化为改善患者预后所需的知识方面具有挑战性。系统生物学将工程学、物理学和数学方法与生物学和医学见解相结合,以迭代的方式可视化细胞内的相互关联事件,这些事件决定了来自环境的输入以及由于患者肿瘤获得的基因组异常而发生的网络重排如何决定细胞行为和患者结局。需要跨学科的系统生物学努力,才能将多维数据集包含的信息转化为有用的生物标志物,这些生物标志物可以根据预后和对治疗方式的反应对患者肿瘤进行分类,并确定肿瘤行为的驱动因素,这些因素是治疗的最佳靶点。需要了解靶向治疗对信号网络和体内平衡调节环的影响,以防止意外影响,并开发合理的组合疗法。确定分子驱动因素和生物标志物的系统生物学方法将导致实施更小、更短、更便宜和个性化的临床试验,这将提高成功率,并加速将有效疗法纳入临床武器库。