Personalized Medicine in Oncology

The development of cost-effective technologies able to comprehensively assess DNA, RNA, protein, and metabolites in patient tumours has fuelled efforts to tailor medical care. Indeed validated molecular tests assessing tumour tissue or patient germ line 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 tumours determines cellular behaviour 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 tumours by prognosis and response to therapeutic modalities and to identify the drivers of tumour behaviour that are optimal targets for therapy. An understanding of the effects of targeted therapeutics on signalling networks and homeostatic regulatory loops will be necessary to prevent inadvertent effects as well as to develop rational combinatorial

 

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