CICO: Consortium for Integrative Computational Oncology at USC

Examples of ongoing projects at CICO

Our computational modeling projects focus on integrating expertise, insight, and data across disciplines to understand, predict, and ultimately control cancer in individual patients. The following projects illustrate our approach. Interested students and potential collaborators are highly encouraged to contact us!.

Markov model screenshot

Markov chain Monte Carlo models of cancer metastasis

PI: Paul Newton

Overview: Markov chain models are constructed based on large autopsy data sets of untreated patients for a statistical model of 'natural' cancer progression. Data assimilation methods are currently being used to tailor these models to smaller sub-groups and individual patient histories.

Recent publications

P. Newton et al., A Stochastic Markov Chain Model to Describe Lung Cancer Growth and Metastasis, PLoS One 7 (2012)

Recent multimedia

none available

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breast cancer simulation screenshot

Patient-calibrated breast cancer simulations

PI: Paul Macklin

Overview: In this work, an agent-based model is calibrated to individual pathology to make patient-specific predictions of clinical progression of ductal carcinoma in situ--a significant precursor of invasive breast cancer. In a follow-up study, we are predicting progression in 10-15 patients and validating each patient's predictions against radiology data.

In ongoing work, we are developing complementary compartmental models of tumor-stromal-vascular interactions and their role in progression from in situ (DCIS) to invasive carcinoma (IBC). This work will facilitate calibration to in vitro data. We are also integrating the simulator to our recent tissue mechanics model to understand the role of basement membrane mechanics on the time scale of DCIS to IBC, and to eventually predict this progression on a patient-by-patient basis. In this shorter term, this multidisciplinary work gives us a platform to assess, test, and refine the state-of-the-art in cancer biology hypotheses.

Recent publications

P. Macklin et al., Patient-calibrated agent-based modelling of ductal carcinoma in situ (DCIS): From microscopic measurements to macroscopic predictions of clinical progression. J. Theor. Biol. 301 (2012)

P. Macklin et al., Modeling multiscale necrotic and calcified tissue biomechanics in cancer patients: application to ductal carcinoma in situ (DCIS), in: A. Gefen (ed.) Multiscale Computer Modeling in Biomechanics and Biomedical Engineering Springer (2012, in press).

G. D'Antonio et al., An agent-based model for elasto-plastic mechanical interactions between cells, basement membrane and extracellular matrix. Math. Biosci. Eng. (2012, in press)

Recent multimedia

Simulation of 45 days of DCIS in a patient

Demonstration of an improved cell volume regulation model, virtual H&E stains, and virtual transmitted light microscopy

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