Molecular Mechanisms in Urothelial Cancer – Invasiveness: Systems Approach This document discusses molecular pathways involved in the progression of urothelial carcinoma from non-invasive to invasive stages. It describes alterations in key pathways such as p53 and Rb that control cell cycle regulation and apoptosis. Proteases like MMPs degrade the extracellular matrix and promote angiogenesis, facilitating tumour invasion and metastasis. The interactions between pathways that regulate the extracellular environment, cell proliferation and cell death determine the invasiveness of urothelial carcinoma.

1. Molecular Mechanisms in Urothelial Cancer –
Invasiveness: Systems Approach
By
Akshay Bhat

2. Today’s Menu...!
● Background
● ECM and its components
● Proteases
● Network Biology - Interactome
● Its applications in clinical diagnostics

3. Bladder Carcinoma
● Cancers of urinary bladder present as
– Urothelial carcinomas (UC) or Transitional cell Carcinoma
(TCC)
– Squamous cell carcinoma
– Adenocarcinoma
● Two clinical staging types
– Non-invasive – Papillary Carcinoma (Ta) & Tis
– Invasive – T1 – T4 (infiltrating tumour)
● All these transformations are due altering molecular pathways
– Low-Grade – Papillary tumours
• Ras-MAPK pathways (FGFR3 and HRAS)
– High-Grade – Ta tumours
• Homozygous deletions (p16 gene)
– CIS and Invasive tumours
• p53 and Rb pathways (TP53 and RB gene)
● Moving from non-invasive to invasive (Occasionally)
– Seen to show molecules that effect p53 pathway
● Alterations in Cadherins, MMPs, VEGF, TSP-1 (Used to remodel
ECM and promote angiogenesis)
– Common in muscle invasive (T2 - T4)
Bladder cancer stages. Superficial cancers that have not yet invaded
muscle include stages Tis (Cis), Ta and T1 while invasive tumours are
stages T2, T3 and T4. (Fig. Downloaded from “Challenges of using mass
spectrometry as a bladder cancer biomarker discovery platform, Eric
Schiffer, Harald Mischak, Dan Theodorescu, Antonia Vlahou: World J Urol
(2008) 26:67–74”)

4. Alterations in Molecular pathways
● Strong evidence that malignant transformation of bladder urothelium is caused by the alteration
in molecular pathways mainly;
– Intrinsic processes
● Cell cycle regulation
● Cell death - Apoptosis
● Cell growth
● Signal transduction
● Gene regulation
– Extrinsic processes
● Tumour angiogenesis
● Tumour invasion
Here we focus on the invasive phenotype of bladder carcinoma mainly looking at pathways like cell-
cycle regulation; cell death; angiogenesis and muscle infiltration (invasion)

5. Alterations in a Urothelial carcinoma cell – Not Biomarkers
Fig. downloaded with permission from Molecular Pathogenesis and Diagnostics of Bladder Cancer; Anirban P. Mitra and
Richard J. Cote1; Annu Rev Pathol. 2009;4:251-85. doi: 10.1146/annurev.pathol.4.110807.092230; PMID:18840072

6. Controlled by p53 and Rb pathways – in turn are associated with
apoptotic,signal transduction and gene regulation processes.
P53 pathway
§ Located on Chromosome 17, TP53 gene encodes p53 → central protein for the
pathway
§ Normal process p53 → inhibits G1-S transition (cell-cycle progression) and
controls activation of p21
§ P53 has a short half-life hence preventing its accumulation in the nucleus.
During TP53 mutation → high intra-nuclear accumulation.
§ P21 → chromosome 6 and encodes a CDK inhibitor p21 → regulated by p53
→ involved in tumour progression.
§ MDM2 → chromosome 12 and involves in auto-regulatory feedback loop with
p53.
Increased levels of p53 → activates Mdm2 → upregulates p53 →
proteasomal degradation of p53 (reduces level) hence reducing Mdm2 causing
increasing tumour stage and grade.
§ Mdm2 is inhibited by p14 → derived from CDKN2A (chromosome 9) →
induced by E2F.
§ P14 → Plays a leading role in both pathways (p53 and Rb) → deregulates
them.
§ Other CDKN2A → p16 acts like a CDKI and inhibits Cyclin D1 → involved in
Rb pathway.
Cell cycle regulation
Rb Pathway
RB gene → located on chromosome 13 → encodes for pRb
pRb → interacts with multiple regulatory proteins in G1-S transition
Rb (dephosphorylated) binds to E2F (transcription factor).
When pRb is phosphorylated by cyclin-dependent CDKs, E2F is withdrawn from the bond
(Rb-E2F) → transcription of genes in DNA synthesis.
Inactivation of Rb mutation leads to loss of protein expression → shown to be in all stages
and grades of UCs.
High levels of Rb expression is due to loss of p16 expression (inhibits CDK4/6) and/or cyclin
D1 over-expression.
Negative regulation of CDKs |-- by CDKIs ( p21, p16, p27) → these are tumour suppressors
too.
Key features/markers playing in p53 and Rb pathways.

7. Cell Death Pathways
Apoptosis
Extrinsic apoptotic pathway
§ Members of TNFR superfamily include death receptors → Fas
§ Interaction of ligands with Fas → FADD protein and recruits Caspase 8 and 10
(initiators)
§ Caspase 8 induces apoptosis by activating Caspase -3, 6, and 7 (effector)
§ Caspase 10 activates Bid (protein) which activates pro-apoptotic protein Bax
Apoptosis (programmed cell death) is a key process in cancer
development and progression.
Ability of tumour cells to avoid apoptosis and continue to proliferate is a
fundamental hallmark in UC development.
Apoptosis can be initiated by two pathways:
Extrinsic pathways → activation of death receptors on cell surface
Intrinsic pathways → mediated by mitochondria
Both pathways activate Caspases → cleave cellular substrates and lead to
morphological changes
Intrinsic Apoptotic pathways
§ Bcl-2 family of proteins → Bcl-2 and Bcl-XL (anti-apoptotic members)
→ Bax, Bid and Bad (pro-apoptotic)
§ Mitochondrial megapores open & close rapidly due to cellular stress → directs
Bax to the site
§ This alters the membrane potential and releases Cytochrome c and calcium →
activating Caspases.
§ Bax expression is controlled by p53 and JNK (c-jun N-terminal kinase)
§ In cytoplasm, Cytochrome c binds → Apaf-1 → activated complex binds to ATP
→ triggers procaspase-9 → then activates Caspase-9 → activates downstream
effector (caspase-3) → apoptosis.
§ Inhibitor of apoptosis (IAP), protein cIAP bind and inhibits to caspases and may
be involved in their degradation.

8. Tumour AngiogensisAll tissues develop vascular networks that provide cells with nutrients and
oxygen which enable them to eliminate metabolic wastes.
Angiogenesis – Can be understood as follows;
§ A cell activated by a lack of oxygen releases angiogeneic molecules that
attract inflammatory and endothelial cells to promote proliferation
§ During their migration, inflammatory cells also secrete molecules that
intensify angiogenic stimuli.
§ Endothelial cells that form blood vessels respond to the angiogenic call
by differentiating and secreting MMPs which digest blood-vessel walls
(BVW) enabling them to escape and migrate towards the site of
angiogenic stimuli.
§ Several protein fragments produced by the digestion of the BVW
intensify the proliferation and migration of the activity of endothelial cells
which then form a capillary tube by altering the arrangement of their
adherence-membrane proteins.
Angiogenesis is measured by micro-vessel density (MVD)
In UC,
§ Hypoxia-inducible factors (HIF-1 and HIF-2) bind to DNA-regulating genes.
§ HIF-1alpha is in conjunction with altered p53 expression → induces VEGF downstream
§ VEGF over-expression in Ta is associated with early recurrence and progression to
invasive phenotype
§ High expression in VEGF in serum → associated with high grade and stage UC,
vascular invasion, CIS and metastasis.
§ Enzyme TP promotes IL-8 production and MMPs.
§ IL-8 → enhances angiogenesis via endothelial cells (found in cell line invasion)
§ MMPs activate basic and acidic growth factors (bFGF and aFGF) → re-stimulates
MMPs → endothelial migration.
§ MMPs activates SF → stimulates angiogenesis.VEGF induces formation of uPA →
generates plasmin → stimulates bFGF, aFGF and SF.
§ uPA degrades ECM leading to endothelial migration and invasion
§ Urine bFGF → high recurrence; Urine aFGF → invasive phenotype
§ p53 upregulates TSP-1 expression → angiogenesis inhibitor
Fig downloaded from “The extracellular matrix: a dynamic niche in cancer progression; Lu P, Weaver VM,
Werb Z; doi: 10.1083/jcb.201102147; J Cell Biol. 2012 February 20; PMID: 22351925”

9. Tumour Invasion Potential Process of invasion is a key feature in malignant growths.
In UCs, the process contributes towards invasion of tumour cells
into vasculature and lymphatics in addition to spreading to
adjacent and distant sites.
Invasive tumour cells can migrate as single cells or collectively in
files, clusters and sheets.
Many adhesion and signaling molecules, including integrins,
CD44, cadherins and IgCAMs have been implicated in
tumour migration and invaison.
Cadherins are prime mediators of intercellular adhesion and are
localized to adherens junctions in addition to binding to
adjoining cells.
E-cadherin plays a key role in epithelial cell-cell adhesion →
decreased expression correlates to increased tumour
recurrence and progression
Integrin signalling is critical for cell migration/invasion by FAK/
SRC signaling and the activity of RHO family GTPases.
Tumours ability to degrade the matrix and invade is facilitated
by proteases like MMPs and uPA's
High levels of MMP-2 and MMP-9 → associated with increasing
stage and grade. (Shown with clinical proof further)
Tissue inhibitors of metalloproteinases (TIMPs), proteins
produced, antagonize MMP function → inhibiting tumour cell
invasion. (doubt is whether TIMP1 or TIMP2)
Created using PathViso (“http://www.pathvisio.org/”)

10. Extracellular Matrix (ECM)
“Spare the rod, Spoil the child” → The Holy Bible
The local microenvironment (niche) of a cancer cell plays important roles in cancer development
And the major component → ECM
What happens outside the house makes
an effect inside!

11. The ECM
Stable structure → Maintains tissue morphology
ECM → essential milieu of a cell, dynamic, versatile and regulates
almost all cellular processes directly or indirectly.
Multiple regulatory mechanisms in its dynamics → production,
degradation, remodelling → organ development and function.
Disruption to such controlled mechanisms deregulates and
disorganizes ECM → abnormal behaviours of cell residing in
the “Niche” → Ultimately failure of organ homeostasis and
function.
ECM → composed of biochemically distinct components →
proteins, glycoproteins, proteoglycans and polysaccharides.
All these components make up;
u Basement Membrane (BM) – epithelium, endothelium, stromal
cells
u Interstitial Matrix (IM) – Stromal cells
BM → compact, less porous → Collagen IV, Laminins, Fibronectin
Nidogen and Entactin → Linker proteins (connect collagens to other proteins)
IM → Fibrillar collages, proteoglycans and glycoproteins (tenascin C and
fibronectin) → tensile strength of tissues
When put together in order, ECM → confers unique physical, biochemical and bio-mechanical
properties essential for regulating cell behavior

12. ECM during cell invasion
➔ Abnormal ECM compromises BM as physical barrier → promotes epithelial-mesenchymal transition
(EMT) → facilitates invasion of cancer cells.
➔ Over expression of MMPs → removes basement membrane.
➔ Tumour/stromal/immune cells bearing MMPs → exit or enter BM with changes in ECM
➔ Stiffening and linearisation of collagen fibres → common in active tumour invasion.
➔ Deregulation of ECM dynamics → cellular dedifferentiation, disruption of tissue polarity and promotion
of tissue invasion with direct affects to epithelial cells.
Epithelial-Mesenchymal transition (EMT) – is a natural cellular process
where individual epithelial cells lose their gene expression pattern and
behaviour to gain phenotypic traits of mesenchymal cells.
In doing so, they lose adhesion and apical-basal polarity to migrate and
invade through the extracellular matrix.
EMT is specially important during embryonic development, but also its seen
in tumour types especially in invasive, inflammation and metastasis
phenotypes.
Fig downloaded with permission from BerGenBio AS (http://www.bergenbio.com)

13. Matrix MetalloProteinases (MMPs)
MMPs are a class of 25 zinc-dependent endogenous
proteases involved in degradation of all the
components in the ECM.
Increased MMP activity → several pathological
conditions and cancers phenotypes including
invasion.
MMPs are regulated by
u Transcription factors
u Endogenous inhibitors
u Pro-enzymes
MMPs are involved in several physiological and tumour
supporting cellular processes → loss of cell-
adhesion, tumour angiogenesis, cell poliferation,
apoptosis and EMT. → Fig
Fig downloaded with permission from “Matrix metalloproteinases and their clinical relevance
in urinary bladder cancer; Szarvas, T. et al. Nat. Rev. Urol. 8, 241–254 (2011); published
online 12April 2011; doi:10.1038/nrurol.2011.44”
Activating other MMPs Can process non-bound proteins

14. MMPs in Urothelial cancer - Invasion
➔ There are many MMPs studied in bladder cancer biology but only few are extensively studies; mainly MMP-1,
MMP-2, MMP-3, MMP-7, MMP-9, TIMP-1 and TIMP-2
➔ MMP-2 and MMP-9 are known to be playing roles in invasive phenotypes – Recently MMP14 has been also
involved by triggering MMP-2 as for TIMP-1.
➔ Growth factors and cytokines (e.g. bFGF) → upregulates MMP-2 and 9 → enhances invasiveness.
EMMPRIN (ECM MMP inducer) – represses MMP-2 and -9 → decreasing proliferation, migration and invasion
42 individuals (11 healthy controls, 31 patients with bladder cancer of different stages) – Sample type
Serum.
Patients with metastatic disease also had increased MMP-9, MMP-2 and TIMP-2 mRNA levels
Detection and molecular staging of bladder cancer using real-time RT-PCR for gelatinases (MMP-2,
MMP-9) and TIMP-2 in peripheral blood. Actas Urol Esp. 2011 Mar;35(3):127-36. doi: 10.1016/
j.acuro.2010.10.006. Epub 2011 Feb 18. Angulo JC, Ferruelo A, Rodríguez-Barbero JM, Núñez C, de
Fata FR, González J. PMID: 21334102
Matrix metalloproteinase-9 measured in urine from bladder cancer patients is an independent
prognostic marker of poor survival. Offersen BV, Knap MM, Horsman MR, Verheijen J, Hanemaaijer
R, Overgaard J. Acta Oncol. 2010 Nov;49(8):1283-7. doi: 10.3109/0284186X.2010.509109. Epub
2010 Sep 15. PMID: 20843171
188 patients diagnosed with bladder cancer (Cystectomy and TUR)
Sample – Voided Urine
Result- Poor survival – 175 died after 13 year follow-up → MMP9 highly activated in invasive
phenotypes

15. Integrins: masters and slaves of transport
Integrins are family of adhesion molecules
involved in interactions between the cell and
ECM.
Integrins control many cellular processes that
occur during development. If altered →
promotes tumour progression, invasion and
metastasis
How? → By conveying outside signals inside
“Outside -in signaling” or vice versa
“inside-out signaling”.
Integrins act as receptors for ECM proteins such
as laminin and collagen VII
Integrin trafficking on cell migration could be
controlled by Rho GTPase signaling or by
altering receptors i.e. EGFR, VEGFR →
contributes to polymerization of fibronectin
(ECM component) causing cell progression.
α6β4 integrin → well studied in bladder
tumourigenesis. → normal process α6β4
integrin has close relationship with collagen
VII and restricts cell migration of laminin.
Loss of α6β4 integrin has been seen in Ta and
muscle invasive phenotypes.
Disruption of ECM affects integrin expression and hence disturbs its
normal function.

16. Invasion → Inflammation → Metastasis
Cancer Progression – Invasion to Inflammation to Metastasis.
A. ECM remodelling is tightly controlled for organ homeostasis and functions. ECM dynamics are essential for maintaining tissue integrity and
overall healthy microenvironment.
B. With age or under pathological conditions, tissue can enter tumourigenic events;
Stage I – generation of activated fibroblasts (CAFs) – contributes to abnormal ECM build-up
Stage II – deregulated expression of ECM modelling enzymes – promotes epithelial cellular transformation and hyperplasia (Stage III)
C. In high stages tumours, immune cells are recruited to tumour site → promotes progression (Stage IV); (Stage V) deregulated ECM affects
vascular biology → promotes tumour angiogenesis; This in turn facilitates tumour invasion and metastasis (Stage VI)
D. At distant sites, tumour cells leave the circulation and take hold of local tissues creating a local metastatic niche. Abnormal ECM →
extravasation, survival and proliferation of cancer cells (Stage VII) and also turns into angiogenic switch (Stage VIII)
Fig downloaded from “The extracellular matrix: a dynamic niche in cancer progression; Lu P, Weaver VM,
Werb Z; doi: 10.1083/jcb.201102147; J Cell Biol. 2012 February 20; PMID: 22351925”

17. Molecular Features - Summary
Bca-associated feature Molecular
pathway
Normal function Regulation No. of
cohort
p53 p53 Inhibits G1-S progression Down 341/692
p21 p53 Cyclin-dependent kinase inhibitor Down 36/56
Mdm2 p53 Mediates proteasomal degradation of p53 Down 73/164
p16 p53 Cyclin-dependent kinase inhibitor Down 25/39
p14 Rb Inhibits MDM2-gene Down 20/64
Rb Rb Sequesters E2F; inhibits cell-cycle progression Down 39/80
CDK4 Rb Complexes with cyclin-D1; involved in G1-S
transition
Down 15/26
p27 Rb Cyclin-dependent kinase inhibitor Down 46/99
Cell-cycle regulation

18. Molecular Features - Summary
Bca-associated feature Molecular
pathway
Normal function Regulation No. of
cohort
HIF Transcribes genes responsible for angiogenesis Up 35/92
VEGF Ras-MAPK;PI3K-
Akt
Promotes angiogenesis → (NO) synthase Up 156/171
TP Promotes VEGF, IL8 secretion; induces MMP Up 29/71
uPA Degrades ECM Up 46/100
bFGF Ras-MAPK Growth factor stimulating angiogenesis Up 161/204
aFGF Ras-MAPK Growth factor stimulating angiogenesis Up 17/40
SF Growth factor stimulating angiogenesis Up 57/60
TSP-1 p53 Inhibits angiogenesis Up 128/204
Tumour Angiogenesis

19. Bca-associated
feature
Molecular
pathway
Normal function Regulation No. of
cohort
Fas Extrinsic apoptosis Promotes apoptosis; activates death-inducing signalling
complex
Down 28/54
Bcl-2 Intrinsic apoptosis Inhibits caspase activation Up 73/226
Bax Intrinsic apoptosis Releases cytochrome c → mitochondria; promotes
apoptosis
Down 25/41
Caspase-3 Common apoptosis
effector
Promotes apoptosis Down 120/226
Cell death - Apoptosis
Tumour Invasion
Bca-associated
feature
Molecular pathway Normal function Regulation No. of
cohort
E-Cadherin Cadherin Mediates intercellular adhesion Down 33/94
β-catenin Wnt/β-catenin Links cadherins to actin cytoskeleton Down -
α6β4-integrin Cytoskeletal signalling Links collagen VII to actin cytoskeleton; traduces
regulatory signals
Down 21/57
MMP-2 Degrades ECM Up 45/50
MMP-9 Degrades ECM Up 39/60
TIMP-1 Antagonizes MMP function Up 18/33
TIMP-2 Antagonizes MMP function Up 38/84

20. Interactome - An old adage says: “Show me your friends, and I’ll know who you are.”
u Protein-Protein Interactions (PPIs) are fundamental to all biological processes.
u To understand an integrated tumor cell system – a comprehensive determination of all possible PPIs that take place in
a tumour cell is necessary.
u By knowing their fold change and p-values, we scientists can
further group these proteins based on whether certain features
are up- or down-regulated.
u This specific/comprehensive network would then help us in
determining how certain proteins/molecules behave if their
expression is perturbed and how it could be used in clinics to
develop strategies for disease classifying in diagnosis and
treatment.
u On the other hand, many features still lack knowledge of their
biological role.
u A network cluster could help overcome this limitation by
predicting their functions through their interactors and then
validating them using IHC, ELISA etc.
u 96 proteins à specific to urothelial invasiveness à collected
from Literature mined databases à Web of Science, PubMed,
Google Scholars.
u Omics databases à GEO and Array Express (In
process)
u MeSH terms à Bladder/Urothelial, neoplasm/tumor, clinc*,
invas*, molecular
Invasive urothelial carcinoma features (96 literature mined) with their
physical neighbours (First order interactions) - Performed using
Cytoscape and MiMI plugin (“http://mimiplugin.ncibi.org/” “http://
www.cytoscape.org/”)

21. Interactome for ECM components
➔ Our main goal is to scavenge for new features that interact with our core protein list.
➔ These molecules could also be the role players in the ECM disruption and the cause for invasion and inflammation
phenotypes.
I. Existing intermolecular interactions
ECM - Features
II. 1st group node extension
III. 2Nd group node extension
Based on Public Interactome database results

22. How do you know they are the Players?
Linking back to the paper
Further, read literature on omics profiling and find for regulation
on tissue, urine, cell line, serum and plasma.

23. ➔ It is easier to predict the function of a
module than a function of a gene symbol.
➔ Many functions of proteins are still
unknown → predicting functional role of a
module contains sufficient number of
proteins of known functions.
➔ Such enrichment analysis builds on the
assumption that a function of protein can
be assigned a functional category such as
Gene Ontology (GO)
➔ The question whether the no. of proteins
with functional annotation in a given protein
module is higher than expected?
➔ Can be determined by statistical
tests such as χ2 or Fisher's exact
test.
Modules and Pathways
This is the visualisation of the selected terms in a functionally grouped annotation network that
reflects the relationships between the terms based on the similarity of their associated gene
symbols. The size of the node reflects the statistical significance of the terms. The degree of
connectivity between terms (edges) is calculated using kappa statistics. The calculated kappa
score is also used for defining functional groups.
Advantage working with Network clusters rather than Individual proteins..!

24. Gene Ontology - GO
GO – Is a method to group molecules based on their cellular component, biological processes and
molecular pathways that they play in.
The GO analysis was performed on the feature list by using another Cytoscape plugin – ClueGO to achieve this
graph. (“Bindea G, Galon J, Mlecnik B, CluePedia Cytoscape plugin: pathway insights using integrated
experimental and in silico data. Bioinformatics. 2013, 29(5):661-3.”)
The histogram chart presents the specific terms for the core proteins and the
information related to their associated genes. The bars represent the number of
the gene symbols from the analysed cluster found associated with the term, and
the label displayed on the bar is the percentage of found proteins compared to all
the proteins associated with the term.
➔ In total, 1294 cellular pathways and 96 potential molecular features were included in
this study from BioCarta, Kegg, GO, Reactome.
➔ Criteria for accepting a marker was occurrence in 50 or more samples/cohorts in a
study.
➔ 406 cellular pathways were enriched using the 96 features in ClueGO.
➔ Of which 14 fundamental pathways that were associated to invasion phenotype
➔ From this, we understand that the invasive phenotype of bladder carcinoma involves
certain signalling pathways that trigger the known molecular pathways like (p53, Rb,
RAS-MAPK, etc.) through the degradation of the extracellular matrix components
especially done by MMPs leading to tumour inflammation and metastasis.

25. Applications of Network Modules – Disease Diagnosis &
Treatment
How can network modules help facilitate approaches in clinical diagnosis and treatment?
Traditional approach (Clinical Disease Diagnosis)
➔ Based on pathological analysis & existing knowledge on disease.
➔ Prone to “Errors”
Current network approach
➔ Knowledge of dys-regulated pathways → used to subtype disease.
➔ Helps to develop relevant treatments for individual disease subgroups.
➔ For e.g network clusters → used to predict
u Patient survival
u Inflammation
u Metastasis
u Drug response
for various cancers and their phenotypes

26. Network modules – Clinical diagnosis & Treatment
Disease Classification
➔ Starts with set of samples with known partition into disease subtypes (Invasive or non)
➔ Attempts to identify classifying principle using molecular features.
Strategy:
➔ Search for subnetwork markers (whose activity best discriminates two disease subtypes)
➔ Network markers → distinguishes “Some” but not all disease cases → leads to multiple subnetworks.
➔ Among selected candidate network markers → “Best” markers are selected (based on training samples)
Some markers take unsupervised approaches → subclasses and features are discovered without knowing
training set.
Developed network based approaches for classifying cancer subtypes by identifying densely connected subnetworks and randomized
algorithms

27. Disease Similarity
➔ Overlaps of dys-regulated network clusters explains why complex diseases share similar
phenotypic traits.
➔ Various tools support similarity network modules e.g iRefscape, PanGIA, DisGeNET
(Cytoscape plugins), PathBlast, etc.
Network modules – Clinical diagnosis & Treatment
This explains why... some drugs can treat many different diseases!
Several dys-regulated modules were found common
Analyses disease similarity by comparing expression patterns of various disease modules (subnetworks)

28. Response to treatment
➔ Network modules may help determine whether a given patient responds to a particular drug →
Valuable for treatment design
➔ Understanding molecular differences b/w responder & non-responder → development of alternative
treatments.
Network modules – Clinical diagnosis & Treatment
Comparing result subnetworks helped shed light on the mechanisms leading to apoptosis and
to identify potential drug targets

29. Pictures adaped from: A. vandenBerg, L. Ringrose, First annual meeting of the EpiGeneSys Network of Excellence: moving epigenetics towards
systems biology. BioEssays : news and reviews in molecular, cellular and developmental biology34, 620 (Jul, 2012).
SYSTEMS BIOLOGY
Using information about parts of a system
(left) → to build a working biological
system. (right)
u Models are built on mathematical descriptions of interconnected parts.
u Can be changed AND/OR rebuilt infinitely → explore behavior of the system and incorporate new experimental
information
u Predict outcome of changes to a system → then tested experimentally.

30. SYSTEMS BIOLOGY
Proteomics
Metabolomics
Theoretical biology
Functional genomics
Bioinformatics
Computational biology
Transcriptomics
Synthetic biology
Structural genomics
You name it.... We've got it...!!

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32. Acknowledgement
u Prof. Dr. Dr. Harald Mischak
u Mr. Joachim Conrads
u Dr. Jochen Metzger
u Justyna Siwy
u Dr. Petra Zürbig
u Dr. Mohammed Dakna
Daniel Kolbe; Clemens Rumpf; Igor
Golovko; Thomas Soeffing; Janosh
Hoffmann
u Dr. Holger Husi
u Dr. William Mullen
u Dr. Angelique Stalmach
u Dr. Bernd Mayer
u Dr Paul Perco
u Andreas Heinzel
Dr. Joost-Peter Schanstra
u Dr. Antonia Vlahou
u Maria Frantzi
u Agnieszka Latosińska

33. My goal is to publish a number of papers…. And my Boss must
be happy to know about this…!
-
Akshay Bhat