Systems biology in cancer research

1
Systems biology in cancer research
2
What is systems biology?
Molecular physiology? physiology is the
science of the mechanical, physical, and
biochemical functions of humans Wikipedia
Systems biology is a study field that focuses
on the systematic study of complex interactions
in biological systems, thus using a new
perspective (holism instead of reduction) to
study them. Because the scientific method has
been used primarily toward reductionism, one of
the goals of systems biology is to discover new
emergent properties that may arise from the
systemic view used by this discipline in order to
understand better the entirety of processes that
happen in a biological system. Wikipedia
3
What is cancer?
A disease of many genes and their interactions
4
Cancer attractors A systems view of tumors Sui
Huang, Ingemar Ernberg, Stuart Kauffman
5

• Biological complexity reduction is crucial.
• Tool complexity ? Vision complexity
• Modelling. What is a model?
• Topological vs. quantitative
• Relevance vs. causality

The Cancer Genome Atlas Research Network. 2008
6
Wholesome vision All proteins? All
interactions? All diseases? All organisms?
7
Human Protein Atlas
8
(No Transcript)
9
Oncomine
10
FunCoup a data integration framework to discover
functional coupling
Andrey Alexeyenko and Erik L.L. Sonnhammer.
Global networks of functional coupling in
eukaryotes from comprehensive data integration.
Genome Research. Published in Advance February
25, 2009
11
FunCoup recapitulation of known cancer pathways
Figure 5 from The Cancer Genome Atlas Research
Network Comprehensive genomic characterization
defines human glioblastoma genes and core
pathways. Nature. 2008 Sep 4. Epub ahead of
print
The same genes submitted to FunCoup No TCGA
data were used. Outgoing links are not shown.
12
TGFß lt-gt cancer pathway cross-talk
FunCoup was queried for any links between members
of TGFß pathway (left blue circle) and habituées
of known cancer pathways (members of at least 7
out of 18 groups right blue circle). MAPK1 and
MAPK3 belonged to both categories.
13

• What is FEASIBLE in systems biology?
• Holistic view?
• Comparison between healthy and ill?
• Disease prevention?
• Drug targets?

14
From genes to pathways
15
Enrichment of functional groups
Group 1
Group 2
Enrichment analysis in the networks turns to be
more powerful than on gene lists
16
Discerning cancer-specific wiring

• Pathway network of normal vs. tumor tissues
• Edges connect pathways given a higher (Ngt9
  p0lt0.01 pFDRlt0.20) number of gene-gene links
  (pfcgt0.5) between them (seen as edge labels).
• Known pathways (circles) are classified as
• signaling,
• metabolic,
• cancer,
• other disease.
• Blue lines evidence from mRNA co-expression
  under normal conditions ALL human mouse data.
• Red lines evidence from mRNA co-expression in
  expO tumor samples ALL human data mouse PPI.
• Node size number of pathway members in the
  network.
• Edge opacity p0.
• Edge thickness number of gene-gene links.

17
Level of functional groups
Zebrafish transcriptome under dioxin treatment
18
Accounting for edge featuresdioxin- enabled
vs. sensitive links
Andrey Alexeyenko, Deena M Wassenberg, Edward K
Lobenhofer, Jerry Yen, Erik LL Sonnhammer, Elwood
Linney, Joel N Meyer Transcriptional response to
dioxin in the interactome of developing
zebrafish. PLoS One
19
Single molecular markers are often far from
perfect. Combinations (signatures) should
perform better. How to select optimal
combinations?
Biomarker signatures in the network

Severity, Optimal treatment, Prognosis etc.
20
Cancer data for basic research a testbed
Sonic hedgehog pathway
21
Tumour tcga-02-0114-01a-01w
Cancer individuality
There is a CAUSATIVE gene network behind each
individual cancer
22
Cancer individuality in clinic
23
Conclusions

• Cancer is a disease of multiple alternatives,
  hence PERSONALIZED medicine.
• Systems biology enormous complexity, great
  challenge.
• Focus on feasible today, think of possible in the
  future.
• Descriptive and analytic HUMAN language?