Prof. Peter Csermely LINK-Group, Semmelweis University, Budapest, Hungary Network biology in cancer ...

Prof. Peter Csermely LINK-Group,

Semmelweis University,Budapest, Hungary

Network biology in cancer

[email protected]

Traditional view

cause effect

(Paul Ehrlich’s magic bullet)

Recently changed view

100 causes 100 effects

Networks may help!

major causes major effects

Advantages of the network approach

Watts & Strogatz,1998

Networks have general properties• small-worldness• hubs (scale-free degree distribution)• nested hierarchy• stabilization by weak links

Karinthy,1929

Generality of network properties offers• judgment of importance• innovation-transfer across different layers of complexity

Barabasi & Albert, 1999

Csermely, 2004; 2009

Influential nodes in different systems:example to break conceptual barriers

ecosystem, market, climate• slower recovery from perturbations• increased self-similarity of behaviour• increased variance of fluctuation-patternsNature 461:53

Aging is an early warning signal of a critical transition:

Prevention: nodes with less predictable behaviour• omnivores, top-predators• market gurus • stem cells

Farkas et al., Science Signaling 4:pt3

death

Adaptation of complex systems

homeostasis stress

homeorhesis cybernetics

Conrad Waddington

NorbertWiener

Ludwigvon Bertalanffy

A possible adaptation mechanism

Plasticity Rigidity

Plasticity-rigidity cyclesform a general

adaptation mechanism.

Plasticity[functional &

structural]

Rigidity[functional &

structural]

stability

learning memoryevolution

canalizationevolvability

complexity

degeneracy

robustness

exploitation (focus)

emergent property

exploration (diversify)

creativity aging

scientificrevolution

Plasticity and rigidity:two key, but ill-defined concepts

robustness

stabilitycomplexity

emergent property

memory

aging

evolution

creativity

learning

evolvability

Plasticity and rigidity:two key, but ill-defined concepts

2-dimension proof:Laman, 1970

~100

years

structural rigidity:Maxwell, 1864

3-dimension proof:XXX, 2070?

~100

years?

Nature Rev. Genet. 5, 826

plasticity ??? flexibility

Definition of functionalplasticity and rigidity

large numberof responses

small numberof responses

plastic systems:smooth state space

rigid systems: rough state space

Functional plasticity and rigidityand system stability

rigid plastic rigid transition

localminimum

small – largeLyapunov stabilitysmall – large

Lyapunov stabilitysmall – large

Lyapunov stabilitysimplesystems

small ← large → smallstructural stability

complexsystems

smooth perturbation(not necessarily small)

Plasticity-rigidity cyclesform a general adaptation mechanism

Plasticity Rigidity

alternating changes of plasticity- and rigidity-dominance

allow the recalibration of the system to find the maximal structural stability

in a changed environment

Properties of plastic and rigid systemsProperties of plastic and rigid systems

extremelyplastic

structurallystable, robust

extremelyrigid

effect of adaptation

possibility of adaptation

memorycompetent

(exploitation) learningcompetent(exploration)

Gáspár & Csermely, Brief. Funct. Genom. 11:443Gyurkó et al. Curr. Prot. Pept. Sci. 15:171

+ ++ +

dissipation signaling

Example 1:Example 1: Molecular mechanisms Molecular mechanismsof protein structure optimizationof protein structure optimization

Todd et al, PNAS 93:4030Csermely BioEssays 21:959Lin & Rye, Mol. Cell 16:23

Hsp60: iterative annealing: pull/release of folding protein

Hsp60 chaperone

chaperonecycle

substrateexpansion

(rigid)

foldedsubstrate

(rigid)

Hsp70: push/release of extended peptide bonds

Bukau & Horwich, Cell 92:351

Hsp70 chaperone

extendedpeptidebonds

unfoldedsubstrate(plastic)

substraterelease(plastic)

Example 2: Example 2: cell differentiationcell differentiationcancer attractorscancer attractors

Huang, Ernberg, Kauffman, Semin. Cell Developm. Biol. 20:869

SuiHuang

IngemarErnberg

StuartKauffman

progenitor

differentiated cells

Example 3: Example 3: cell differentiationcell differentiation

Rajapakse et al., PNAS 108:17257

more rigidrigid

plastic

progenitorcells

differentiatedcells

gene expression correlation networkschromatin networks

rigid

plastic

rigid

Scientific Reports2:342; 813

phosgene inhalation-induced lung injury,chronic hepatitis B/C, liver cancer

Example 4: Example 4: disease progressiondisease progression

Example 5: Example 5: cancer stem cellscancer stem cells

Csermely et al., Seminars in Cancer Biologydoi: 10.1016/j.semcancer.2013.12.004

Network-independent mechanisms of plasticity-rigidy cycles

1. noise: reaching hidden attractors coloured noise, node-plasticity2. medium-effects: water, chaperones membrane-fluidity, volume transmission as neuromodulation, money

Socialism: shortage economy rigidCapitalism: surplus economy plastic

Network-dependent mechanisms of plasticity-rigidy cycles

• extended, fuzzy core• fuzzy modules• no hierarchy• source-dominated

soft spots creative nodes, prions (Q/N-

rich proteins), chaperones

rigidity seeds rigidity promoting

nodes

• small, dense core• disjunct, dense modules• strong hierarchy• sink-dominated

Csermely et al., Seminars in Cancer Biologydoi: 10.1016/j.semcancer.2013.12.004

TopologicalTopologicalphase transitions:phase transitions:plastic plastic rigid rigid networks with networks with diminished resourcesdiminished resources

resources

stress

co

mp

lex

ity scale-free

network

subgraphs

star network

Derényi et al., Physica A 334:583

Brede, PRE 81:066104

edge-lengthcontributes to its cost

randomgraph

Mihalik & Csermely PLoS Comput. Biol. 7:e1002187

Yeast stress induces module condensation of the interactome

Stressed yeast cell:• nodes belong to less modules• modules have less contactsmore condensed modules == more separated modules

• yeast protein-protein interaction network: 5223 nodes, 44314 links + several other conditions• stress: 15 min 37°C heat shock + other 4 stresses• link-weight changes: mRNA expression level changes

Csermely et al, Pharmacol & Therap 138: 333-408

Drug design strategiesfor plastic and rigid cells

e.g.: antibioticse.g.: rapamycin

Central hit + network-influence: Central hit + network-influence: cancercancer

Gyurkó et al, Seminars in Cancer Biology 23:262-269

most test systemsare in this stage

most patientsare in this stage

cancerstemcells

János Hódsági, MSc thesis

network entropylow high

Network entropy increases than decreases in cancer propagationcancer propagation

János HódságiMSc thesis network entropy

of cancer stem cellsis larger than that of

their parental cells

plastic

rigid colon

adenoma

carcinoma


Drug design strategiesfor plastic cells


PLoS ONE 5:e12528Bioinformatics 28:2202Science Signaling 4:pt3PLoS ONE 8:e67159PLoS ONE 8:e78059

perturbation centrality (www.Turbine.linkgroup.hu)

community centrality(www.modules.linkgroup.hu)

game centrality (www.NetworGame.linkgroup.hu)

3 novel network centralities 3 novel network centralities reveal influential nodesreveal influential nodes

Bridges are key nodes

of social regulationhispanic old

young

BCBC

BC

union leaders: strike

sociogram leaders: work

Farkas et al., Science Signaling 4:pt3; Simko & Csermely: PLoS ONE 8: e67159www.linkgroup.hu/NetworGame.phpMichael’s strike network; Michael, Forest Prod. J. 47:41

Hawk-dove game (PD game: same)Start: all-cooperation = strikeStrike-breaker: defectsBC-s are the best strike-breakers

prediction of keyamino acids inallosteric signaling



perturbation centrality (www.Turbine.linkgroup.hu)


game centrality (www.NetworGame.linkgroup.hu)

influencezones of allnodes/links

networkhierachy

communitiesas landscape hills

Kovacs et al, PLoS ONE 5:e12528www.modules.linkgroup.hunetwork of network scientists; Newman PRE 74:036104

available as

Cytoscape plug-in

communitycentrality:a measureof the influenceof all other nodes

communitylandscape

extensive overlaps +

centre of modules +

bridges

ModuLand method family: module centres & bridges

Szalay-Bekő et al.Bioinformatics

28:2202


Drug design strategiesfor rigid cells


Network-influence: Network-influence: Allo-network drugsAllo-network drugs

• atomic resolution interactome of allosteric protein complexes• identification of allosteric pathsNussinov et al,

Trends Pharmacol Sci 32:686

hit of intra-cellular paths

Examples: BRAF inhibition restoring MEK inhibition• rapamycin effects on mTOR complexes

Network influence: Network influence: Multi-target drugsMulti-target drugs

Csermely et al, Trends Pharmacol Sci 26:178

perturbation centrality (www.Turbine.linkgroup.hu


game centrality (www.NetworGame.linkgroup.hu



Turbine: general network dynamics toolTurbine: general network dynamics toolany real networks can be added, modifiednormalizes the input networkany perturbation types (communicating vessel model, multiple, repeated, etc.)any models of dissipation, teaching and agingMatlab compatible

www.Turbine.linkgroup.hu Szalay & Csermely, Science Signaling 4:pt3PLoS ONE 8:e78059

Attractors of T-LGL network using Turbine::Attractor

proliferation

apoptosis

Multi-drug design with Turbine::Designer

Network: Zhang R, Shah MV, Yang J, Nyland SB, Liu X, Yun JK, Albert R, Loughran TP Jr. (2008) Network model of survival signaling in large granular lymphocyte leukemia. PNAS 105: 16308–13.

Inactive proteinActivated protein

Phospholipase Cϒ1(inhibition; Cancer Res. 68:10187)

CD45(activation; Blood 119:4446)

T-LGL survival signaling network: leukemia specific edgesStarting state: IL7-activation; target-state: all blackTurbine::Designer solution to reach target state

starting state

apoptosis

Inactive proteinActivated protein

Interferon α1(activation; CA Cancer J Clin 38:258)

Take-home messages

Influential nodes of plastic networks aretheir central nodes; influential nodes of rigid networks are their neighbours andcan be efficiently predicted by network topology and dynamics methods

3.

When you build up your network(or use other’s networks) be EXTREMELY cautious how you define your nodes and edges

1.

2. Plasticity-rigidity cyclesform a general adaptation mechanism

A core of 8 people + a multidisciplinary group of +34 people with a background of +100 members

and a HU/EU-talent support network

Acknowledgment: the LINK-Group + the associated talent-pool

India

Sevilla Nashville

South AfricaSan Francisco

St. Paul

BethesdaZürich Sanghai Hong Kong

Prof. Peter Csermely LINK-Group, Semmelweis University, Budapest, Hungary Network biology in cancer ...

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