Agent-based methods for translational cancer multilevel modelling

1
Agent-based methods for translational cancer
multilevel modelling

• Sylvia Nagl PhD
• Cancer Systems Science Biomedical Informatics
• UCL Cancer Institute
• London

2
Main points of the talk

• Potential of agent-based modelling
• Systems biology perspective on large cell network
  simulation
• A new synergy between modelling and wet biology

3
The hallmarks of cancer
Hanahan and Weinberg (2000) Cell 10057-70
4
Systems biology and medicine

• Diseases are abnormal perturbations of biological
  networks - through defects in molecular
  mechanisms or environmental stimuli
• Therapies are the interventions needed to restore
  networks to their normal states

5
Modelling challenge genome to phenotype
extended genotype
elementary phenotype
Butcher et al. (2004) Nature Biotechnology
221253
6
Systems biology and medicine

• Fundamental question of where function lies
  within a cell
• distributed (networks of interacting molecules)
• hierarchical
• network motifs and modules
• complex network connecting modules
• A globalist view of the dynamics of (large) cell
  networks is therefore needed

E-science
7
Systems biology and cancer

• Given the many components of functional modules,
  there are different paths to disease-inducing
  systems failure
• A multitude of ways to solve the problems of
  achieving a survival advantage in cancer cells
• Each patients cancer cells evolve through an
  independent set of genomic lesions and selective
  environments - a fundamental reason for
  differences in survival and treatment response

8
Supporting treatment optimisation in the
individual patient
DNA damage response network
Likelihood of cancer cell death in response to
DNA damaging drugs and radiotherapy
9
Agent-based modelling
One-to-one mapping of cell components to
computational agents Agents at multiple
levels Protein, network motif, module
(organelle, cell ) Interaction
rules Translates wealth of molecular knowledge
into component-based models Patient-specific
molecular data
?
10
DNA damage
Changes in genome activation
11
Agent-based modelling Agent (protein, motif,
module) gt behaviour rules Kinetics/step
function/Boolean variables scale up to large
networks
12
Challenge Emergence

• Coherent behaviour of cells emerges from
  interactions between a large number of system
  components proliferation, cell death,
  resistance to drugs
• Computational definition of emergence
  Unspecified properties and behaviours arise from
  interaction between agents rather than as a
  consequence of a single agents actions
• Methods for analysis needed e.g. for therapy
  target discovery

13
Detecting event patterns in time

• A simple event is a state transition due to a
  rule execution
• A complex event is made up of a set of
  interrelated simple events
• Classification of complex events in a simulation
  allows one to discover associations between
  processes at different levels
• Published formalism available at
  www.cs.ucl.ac.uk/staff/C.Chen/research.html

14
Challenge the gap
Linking network simulations to integrated cell
behaviour requires knowledge external to the
simulation, the question of biological meaning

15
A new synergy

• Data generation is still largely motivated by a
  non-systems-based research paradigm
• Systems biologists then seek to use these data to
  build and validate models of systems with
  difficulties
• We need to rethink the relationship between
  experiment and modelling
• both need to proceed within a complex systems
  framework
• new kinds of experiments needed to investigate
  multi-level relationships in the wet system
• e. g., global signal network states need to be
  matched to cell-level phenotypic measurements
  over time and under a range of conditions
• E-science systems modelling and experiment need
  to complement and synergise

16
Acknowledgements

• Nuno Rocha Nene (CoMPLEX PhD programme)
• Chih-Chun Chen (interdisciplinary EPSRC DTA
  awards)
• CR UK, Department of Health
• Published formalism available at
  www.cs.ucl.ac.uk/staff/C.Chen/research.html
• Decision support tool for ABM techniques
  www.abmsystemsbiology.info
• My email s.nagl_at_ucl.ac.uk