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Cancer systems biology: embracing complexity to develop better anticancer therapeutic strategies

Oncogene volume 34, pages 3215–3225 (2015)Cite this article

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Abstract

The transformation of normal cells into cancer cells and maintenance of the malignant state and phenotypes are associated with genetic and epigenetic deregulations, altered cellular signaling responses and aberrant interactions with the microenvironment. These alterations are constantly evolving as tumor cells face changing selective pressures induced by the cells themselves, the microenvironment and drug treatments. Tumors are also complex ecosystems where different, sometime heterogeneous, subclonal tumor populations and a variety of nontumor cells coexist in a constantly evolving manner. The interactions between molecules and between cells that arise as a result of these alterations and ecosystems are even more complex. The cancer research community is increasingly embracing this complexity and adopting a combination of systems biology methods and integrated analyses to understand and predictively model the activity of cancer cells. Systems biology approaches are helping to understand the mechanisms of tumor progression and design more effective cancer therapies. These approaches work in tandem with rapid technological advancements that enable data acquisition on a broader scale, with finer accuracy, higher dimensionality and higher throughput than ever. Using such data, computational and mathematical models help identify key deregulated functions and processes, establish predictive biomarkers and optimize therapeutic strategies. Moving forward, implementing patient-specific computational and mathematical models of cancer will significantly improve the specificity and efficacy of targeted therapy, and will accelerate the adoption of personalized and precision cancer medicine.

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Acknowledgements

We gratefully acknowledge insightful comments from Dr Yanwen Jiang (Elemento lab) and our anonymous reviewer. We also thank other members in the laboratory and Physiology, Biophysics and Systems Biology program of Weill Cornell Graduate School for helpful discussions. This work was supported by NIH, CAREER Grant from National Science Foundation, Starr Cancer Consortium and Hirschl Trust.

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  1. Department of Physiology and Biophysics, Laboratory of Cancer Systems Biology, Sandra and Edward Meyer Cancer Center, Institute for Computational Biomedicine and Institute for Precision Medicine, Weill Cornell Medical College, New York, NY, USA

    W Du & O Elemento

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Correspondence to O Elemento.

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Du, W., Elemento, O. Cancer systems biology: embracing complexity to develop better anticancer therapeutic strategies. Oncogene 34, 3215–3225 (2015). https://doi.org/10.1038/onc.2014.291

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