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Systems pathology—taking molecular pathology into a new dimension

Nature Reviews Clinical Oncology volume 6, pages 455–464 (2009)Cite this article

Abstract

The wealth of morphological, histological, and molecular data from human cancers available to pathologists means that pathology is poised to become a truly quantitative systems science. By measuring morphological parameters such as tumor stage and grade, and by measuring molecular biomarkers such as hormone receptor status, pathologists have sometimes accurately predicted what will happen to a patient's tumor. While 'omic' technologies have seemingly improved prognostication and prediction, some molecular 'signatures' are not useful in clinical practice because of the failure to independently validate these approaches. Many associations between gene 'signatures' and clinical response are correlative rather than mechanistic, and such associations are poor predictors of how cellular biochemical networks will behave in perturbed, diseased cells. Using systems biology, the dynamics of reactions in cells and the behavior between cells can be integrated into models of cancer. The challenge is how to integrate multiple data from the clinic into tractable models using mathematical models and systems biology, and how to make the resultant model sufficiently robust to be of practical use. We discuss the difficulties in using mathematics to model cancer, and review some approaches that may be used to allow systems biology to be successfully applied in the clinic.

Key Points

  • Morphological assessment by histopathology can be a good surrogate for underlying molecular biology, which may be used in treatment decision-making

  • Drug mechanisms of action and signaling pathways that may not be understood fully may be predicted by mathematical models

  • Cancer is dynamic, complex, and heterogeneous, and therefore requires integration of molecular biology and pathology data in new predictive frameworks that embrace the dynamic nature of the disease

  • Developments in mathematics and quantitative pathology provide the foundation for this new predictive framework to aid in the diagnosis, prognostication, and prediction of response in patients with cancer

  • Mathematical models can be used to predict drug responses under a given set of conditions or to predict what combinations of drug could result in a given cell fate

  • Systems biology has been successful in predicting molecular responses in well-described cancer pathways (for example, mitogen activated protein kinase pathway) or in physiology, but has not yet been applied to the cancer clinic

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Figure 1: Simulation of molecular activity in breast cancer using an ordinary differential based model.
Figure 2: Network interactions in cancer derived from quantitative protein time-series data (obtained in vitro using the S-systems Biochemical Systems Theory approach).
Figure 3: New analytical tools and biological models for systems biology.

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Acknowledgements

This work is supported by Breast Cancer Campaign and Breakthrough Breast Cancer.

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Authors and Affiliations

  1. Division of Pathology and Breakthrough Research Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK

    Dana Faratian & David J. Harrison

  2. SIMBIOS, University of Abertay, Dundee, UK

    Robert G. Clyde & John W. Crawford

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Correspondence to Dana Faratian.

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Faratian, D., Clyde, R., Crawford, J. et al. Systems pathology—taking molecular pathology into a new dimension. Nat Rev Clin Oncol 6, 455–464 (2009). https://doi.org/10.1038/nrclinonc.2009.102

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