Cancer is a disease of functional dysregulations within and in surrounding affected cells, tissues and organs. These dysregulations confer cancerous cells with the adage to: proliferate; evade differentiation; develop new blood vessels (angiogenesis); evade death; migrate and metastasise; and resist growth inhibitory, as well as reprogram energy metabolism and evade immune destruction. Treatment modalities for cancer have traditionally been chemotherapy, surgery, radiotherapy or hormone-based. The common mechanism of action of these therapeutic approaches is cytotoxicity towards the cancer cells. However, their anticancer effectiveness has been limited by lack of outstanding target specificity and the capacity to identify and fully understand all the possible myriad modes of their actions and effects on cancerous cells, as well as normal cells. The overall progress in the diagnosis and treatment of cancer continued to be limited, despite the tremendous breakthrough on the discovery and development of new novel anticancer therapeutics. A major factor limiting the diagnosis and treatment of cancer is the dominance of qualitative data to inform and validate these parameters. A novel approach to improve upon is the use and identification of quantifiable parametric biological and molecular targets that are tumour specific or differentially regulated in tumour relative to normal tissue, especially those that interfere with tumour cell or tissue response to anticancer therapeutic strategies. This presentation will highlight and exemplify some novel quantitative approaches to understanding cancer cells dynamics to inform treatment design. Specifically the dynamic effects/changes of the signalling pathways in cancer following targeted therapies will be addressed and discussed.
|Number of pages||2|
|Journal||Current Opinion in Biotechnology|
|Issue number||Suppl 1|
|Publication status||Published - Jul 2013|
|Event||European Biotechnology Congress - Comenius University, Bratislava, Slovakia|
Duration: 16 May 2013 → 18 May 2013
Deeni, Y. Y. (2013). Cancer biology: quantitative approach to understanding cancer cells dynamics to inform treatment design. Current Opinion in Biotechnology, 24(Suppl 1), S24-S25. https://doi.org/10.1016/j.copbio.2013.05.034