A Comparison of c-Myc Regulated
Gene Networks Involved in
Tumourigenesis of Two Distinct Tissues
Sam Robson
MOAC DTC, Senate House, University of Warwick, Gibbet Hill
Road, Coventry CV4 7AL
Cancer
Normal Mitosis
Abnormal Mitosis
= Healthy Cell
= Healthy Cell
= Cancer Cell
= Cancer Cell
= Apoptosis
= Apoptosis
Cell duplicates to form two identical
daughter cells. Errors in DNA replication
result in cell suicide (apoptosis) to avoid
passing aberrant DNA to progeny.
Genetic defects prevent apoptotic
pathways from activating, allowing
abnormal cells to proliferate. With no
proliferative control, tumours can form.
C-Myc
Legend
Myc Box I
Myc Box II
Basic
Amino
terminal
1
45 63
Helix-Loop-Helix
Leucine Zipper
Carboxyl
terminal
129 143
355 368
410
439
C-Myc
Protein
Transactivation
domain
Image adapted from Pelengaris et al. (2002).
Max
Protein
Inactive
Active
MycERTAM
HAT TRRAP
Transgenic Model
RNA
Polymerase
Legend
Myc Box I
Myc Box II
Basic
Helix-Loop-Helix
Leucine Zipper
Estrogen Receptor
Myc-Max
complex
Transformationbinds
E-box
TRRAP
recruits a histone
Transcription
domain
4-Hydroxytamoxifen
Myc
sequence
ofProtein
acetyltransferase
(HAT). This
Associated
Max Max
binds
Myc
target
gene
acetylates
(TRRAP)
binds to nucleosomal
atMBII
leucine
histones
resulting in
with
help from
helix-loop-helix
chromatin remodelling,
MBI
4-OHT
binds
zipper region
allowing access by RNA
Bound
Heat
estrogen
receptor
HSP90
TAM
Polymerase
for gene
ER
ShockupProtein
CACGTG opening
bHLHz90
transcription
domain.
Skin
• Cells proliferate from
epidermal stem cells in
basal layer.
• Migration towards
surface – cells become
keratinized.
• Stratum corneus layer
made up of highly
keratinized nuclei-free
cells – squames.
• Squames constantly
shed from epidermal
surface.
• Homeostasis within the
skin very important.
Image taken from http://kidshealth.org/kid/body/skin_noSW.html
Pancreas
• Homogenous
groupings of cells
within the exocrine –
Islets of Langerhans.
• Islets contain
predominately β-cells
– sole source of insulin
• Insulin responsible for
glucose metabolism.
• Loss of insulin leads to
Type I diabetes.
• Pancreatic ducts
transport pancreatic
enzymes.
c-MycERTAM Activation in Pancreas – Apoptosis
INACTIVE
ACTIVE
+4OHT
Pancreatic
Islet β-Cells
Proliferation
and Apoptosis
Apoptosis
outweighs
proliferation
Islet
involution
c-MycERTAM Activation in Skin – Proliferation
INACTIVE
Cell
Migration
ACTIVE
+4OHT
Skin epidermis
Proliferation
Constant renewal of
cells from basal layer.
Keratinised ‘squame’
cells lost from surface
Increase in basal cell
proliferation. More cells
migrate through to
squamous layer
Unchecked proliferation leads to
many hallmarks of carcinoma.
Tumour is localised with no
metastasis seen.
Microarray
•Features measure one nucleotide
sequence (25mers).
•25mer sequence specifically binds
biotin labelled cDNA.
•Hundreds of identical 25mers per
feature.
•Fluorescence readings give relative
RNA concentration – equivalent to
gene expression.
•11-20 features per gene.
Images courtesy of Affymetrix - www.affymetrix.com
Microarray Hybridization
Total RNA
AAAA
Biotin-labelled
cRNA
cDNA
Reverse
Transcription
In Vitro
Transcription
B
AAAA
B
AAAA
B
AAAA
Fragmentation,
biotin labelling
and hybridization.
Analysis in
Genespring
Cell cycle – Cancer reversal
Cell Death – Cancer reversal
Laser Capture Microscopy
LCM
Ependorf
Tube
Membrane
Slide
Tissue
Laser
Glass Slide
Support
• Tissue section bound to membrane of LCM slide. Glass slide used as support
on LCM platform.
• “Sticky” ependorf tube lid lowered onto membrane. Laser cuts designated
area for dissection. Raising lid lifts cut material from LCM platform for RNA
extraction.
Laser Capture Microscopy
1:
2:
Sweat
gland
3:
Sweat
gland
removed
Path of
laser
4:
Laser
captured
sweat
gland
Problems with pancreatic RNA
A
Control
sample
18s and
28s peaks
similar
heights
B
Fresh
section
C
18s and
28s peaks
different
heights
Airdried
section
18s and
28s peaks
nonexistant
Fixed
section
D
E
18s and
28s peaks
nonexistant
• RNA degraded naturally in cells by the enzyme RNase.
• Pancreas rife with RNase activity.
• Integrity of RNA gradually decreases throughout LCM procedure.
• RNA fully degraded by the time of tissue collection.
Stained
section
18s and
28s peaks
nonexistant
Problems with pancreatic RNA
A
Fresh
Sample
18S and
28S
peaks
different
heights
B
Islet
RNA
18S and
28S
peaks
different
heights
C
Exocrine
RNA
Large
unknown
peak
• RNA integrity in islets is good compared to RNA integrity in exocrine
tissue.
• Implies that islet RNA is not subject to same degradation as that in the
exocrine.
• Possible that structure of islets protects islet cell RNA from ductal RNases.
Network Analysis
•Empirical Bayesian
approach estimates
gene network structure
from microarray data.
•Problems – Sample
size small for number of
nodes (genes).
•Allows estimation of
gene interactions in
complex system.
Image from Schäfer et al., 2005.
Generalised Linear Models
• Unsupervised linear regression technique.
• Models data as a linear combination of variables:
y  a  b x  b2 x2  b3 x3  ...
n1
1 1
n2
n3
• Gives the most statistically relevant variables.
• Implementation in Genespring for public use.
• Makes no assumptions of data and works with
unbalanced experiments – Useful for clinical data.
Conclusion
• c-Myc known to be very important in cancer
formation.
• c-Myc function in cancer onset still not fully
understood.
• In vivo analysis of early c-Myc activity will help to
disentangle the web of c-Myc functionality.
• Understanding of the route of tumourigenesis
will hopefully aid in development of gene specific
cancer therapies.
Acknowledgements
Project Supervisors:
Group members:
Mike Khan
Sylvie Abouna
David Epstein
Linda Cheung
Stella Pelengaris
Vicky Ifandi
Special thanks:
Göran Mattson
Helen Bird, Sue Davis, Lesley Ward, David
Pritlove, Sean James, Paul Anderson