Colorectal cancer through simulation and experiment

Sophie K. Kershaw, Helen M. Byrne, David J. Gavaghan, James M. Osborne

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Colorectal cancer (CRC) has formed a canonical example of tumourigenesis ever since its use in Fearon and Vogelstein's linear model of genetic mutation, and continues to generate a huge amount of research interest. Over time, the field has witnessed a transition from solely experimental work to the inclusion of mathematical and computational modelling. The fusion of these disciplines has the potential to provide valuable insights into oncologic processes, but also presents the challenge of uniting many diverse perspectives. Furthermore, the cancer cell phenotype defined by the 'Hallmarks of Cancer' has been extended in recent times and provides an excellent basis for future research. The authors present a timely summary of the literature relating to CRC, addressing the traditional experimental findings, summarising the key mathematical and computational approaches, and emphasising the role of the Hallmarks in current and future developments. The authors conclude with a discussion of interdisciplinary work, outlining areas of experimental interest which would benefit from the insight that theoretical modelling can provide. © The institution of engineering and technology 2013.
Original languageEnglish (US)
Pages (from-to)57-73
Number of pages17
JournalIET Systems Biology
Volume7
Issue number3
DOIs
StatePublished - Jun 1 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: SKK is supported by an EPSRC-funded Systems Biology Doctoral Training Centre studentship and a Google Europe Scholarship. HMB: This publication was based on work supported in part by Award No KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). DJG is funded through the OCISB project (BB/D020190/1) and the Systems Biology Doctoral Training Centre (EP/G50029/1). JMO is supported by Microsoft Research UK and the Life Sciences Interface and Systems Biology Doctoral Training Centres, and the Systems Approaches to Biomedical Science Industrial Doctorate Centre (EP/E501605/1, EP/G50029/1 and EP/G037280/1, respectively).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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