1. Ariel Kaluzhny
Muniba Iqbal
Katherine Kyman

2.  Amplicon- the source or product of DNA or
RNA amplification or replication events
◦ Amplicome- set of all amplicons
 Mutacon- the site of mutation
◦ Mutacome- set of all mutacons
 Synergy- multiple elements in a system
working together to produce an effect greater
than the sum of their individual effects
 GO process- a series of molecular events or
functions with a defined beginning and end
(often disrupted by mutant phenotypes)

3.  “multiple genetic events, including copy
number gains and somatic mutations, are
necessary for establishing the malignant cell
phenotype”

4.  “to characterize copy number alterations in
primary breast cancer carcinomas and to
define functional interactions among
genetically altered genes in breast cancer”
 “to lay the groundwork for future
translational studies exploring the potential
therapeutic targeting of key regulators of the
malignant cellular phenotype”

5.  The most frequent amplicons were found on
chromosomes 1q, 8p12, 8q24, 11q13,
12p13, 16p13, 17q11-q21, 17q22-q23, and
20q13
◦ Nomenclature: p is the short arm, q is the long arm
and the numbers are the map units
 Previous studies show that breast tumor
subtypes correlate with the types and
numbers of amplicons

6.  specific gene combinations are rarely the
same in two different tumors, but “very few
genes are mutated in a high fraction of
tumors”
 A single amplicon does not encode any
processes and pathways, but is highly
synergistic for encoding for genes with roles
in tumorigenisis

7.  Collected from multiple universities and
hospitals using protocols approved by the
Institutional Review Boards
 Only immunomagnetic bead purified or
microdissected tumor samples
 Snap frozen and stored at -80°C

8.  Synthesis of 24-40
different oligomers of 25
bases per locus
◦ There are 3-5 groups of
probes
◦ Each group has:
 a perfect match for one allelic
state
 A single-based mismatch for
one allele
 A perfect match for the other
allelic state
 A single-based mismatch for
the second allele
 Also has the complementary
sequences for each of the
above
http://www-microarrays.u-strasbg.fr/base.php?page=affySNPsE.php

9.  Subtypes of tumors: Luminal, Basal-
like (triple negative), and HER2 type
◦ The subtypes were based on the
expression of ER (Estrogen Receptors) and
HER2

10.  173 out of 191
samples had at least
one gained
chromosomal
region or gene
 Observed an
enrichment of
specific amplicons:
◦ Luminal - 16p13
◦ Basal-like - 8p11-12
and 8q
◦ HER2+ - 17q

11.  Total of 15,145 genes gained in at least one sample
 Narrowed it down to 1,747 genes that were amplified at least
five-fold in at least seven cases of the 191 samples
◦ Organized into 30 amplicons distributed over 16 chromosomes =
amplicome
 Number of genes in individual amplicons ranged from 4 to
336 and are not equally distrubed throughout the
chromosomes
Supplementary Figure 1

12.  All the of the amplicons found had different
outcomes in terms of protein functions
◦ Encoded for transcription factors
(TF), receptors, secreted
proteins, kinases, phosphates, proteases, and
metabolic enzymes
◦ Ex: amplicon 7p15 was made up of TFs
encompassing the HOXA homebox genes whereas
amplicon 20p13 had enrichment in receptors
 Some amplicons had unrelated TFs but
included for similar function
◦ Ex. 20q12-13

13.  Looked for 5 functional ontologies
◦ GO processes, GO molecular functions, canonoical
pathway maps, cellular process networks, and
disease biomarkers
 The amplicons all encoded multiple pathways
and processes without showing distinct
specialization for them
 Individual amplicons were highly synergistic
for encoding for tumorigenisis

14. IGF-RI signaling
canonocial
pathway map
composed of
genes derived
from 11
amplicons shows
synergy in
tumorigenisis
Figure 2
Supplementary Figure S5

15.  Individual amplicons did not form concise
networks
◦ Calculated by comparison with the global
interactome which was used as a control
◦ Only 6 of the 30 displayed any significant amount
of intraamplicon connectivity but was still
significantly lower than the global human
interactome
 Most amplicons were regulated (received
signal in) rather than regulating
◦ Although four of them send more signal out

16.  Used the Analyze Networks (AN) algorithms
to further evaluate functional interactions
among 1,360 amplified genes
◦ AN Transciption Factors (ANTF) algorithm
 JUN oncogene is the central hub although it wasn’t
amplified itself but has amplified targets
◦ AN Receptors (ANR) algorithm
 Highest scored ANR subnetwork is centered at ESR1
nuclear hormone receptor (not amplified in this data
set but had many direct targets of amplified genes)

17. Figure 3

18.  Connectivity- protein interaction
 Intraconnections and interconnections of the
amplicons were evaluated compared with the
expected number of connection based on the
size of the data
Supplementary Figure 6

19. r= number of transcription interaction of the transcription factor in
the set of interest
R= number of regulation interactions of the transcription factor in the
whole network
n= number of transcription targets in the sample of interest
N= number of transcriptional targets in the global network

20.  Largest number of interactions in the
overconnected pair 8q12-q22 and 17q11-
q21 (15 links) and the underconnected pair
8q23-q24 and 17q21-q25 (39 links)
◦ c-Myc, a transcription fator, had the most outgoing
TR links in 8q23-q24 (which is the amplicon with
the most outgoing interactions)
 In general, interconnectivity was higher than
intraconnectivity
 Among 17 interactions tested, they were
particularly enriched in transcription
regulation (TR) links

21.  Defined as the nonredundant union of 1,188
somatically mutated genes
 Also analyzed 140 CAN (candidate cancer)
genes that likely play a role in tumorigenesis
 Mutated genes were randomly distributed
through the genome (unlike the amplicons)

22.  Only 94 genes were part of both the mutome
and the amplicome
◦ Statistically smaller than expected
◦ Maybe because mutational analysis was conducted on
a smaller set of tumors
◦ Maybe some gene categories are preferentially
affected by copy number gain versus mutation
 Mutome was closely interlinked with individual
amplicons
 More interactions were from the mutome to the
amplicome
◦ Most prominent and statistically significant is 15q26
with 8 interactions from mutome to amplicome targets

23. Figure S7. Interconnectivity between mutome and individual amplicons. The
length of the line representing each amplicon reflects the number of genes in
each amplicon. The thickness of arrows is proportional to the number of
outgoing and incoming interactions between mutome and amplicons.

24.  The mutome was enriched for TF’s and the
amplicome for their targets
◦ Applied Transcription Target Modeling (TTM) algorithm
to investigate
 Mutated genes were always upstream of the
amplified ones
 23 mutated TFs were overconnected with
amplicome genes
 Seven of the CAN TFs had targets on amplified
genes
◦ Mutated genes BRAC1 and HDAZ4 had the highest
number of interactions with mutated genes

25.  Both show higher connectivity than the global
human interactome
◦ Both had higher connectivity for outgoing links
◦ CAN genes especially had many outgoing
interactions (2.6 times more than expected)
 Evaluated specific types of proteins
◦ Mutome had fewer ligands but more kinases and
receptors
◦ Amplicome had fewer receptors
◦ TFs similar in both

26.  Most important trascription hub for the
amplicome but underconnected with the
mutome
◦ Could be due to the distribution of ER+ or ER-
tumors within the amplicome and mutome
 Amplicome enriched in ESR1 target genes but
not binding sites

27.  Used enrichment analysis in the five functional
ontologies
 Both enriched for processes and genes involved
in tumorigenesis
 Mutome enriched for cell-adhesion, cell cycle,
and DNA damage pathways
◦ CAN genes were especially enriched in DNA damage
pathways
◦ Suprisingly, 15 top disease markers were not cancer
causing except leukemia
 Amplicome enriched for developmental pathways
◦ Enriched for disease biomarkers of breast cancer and
skin disease

28.  Analyzed synergy in ontology enrichment
pathways to deterine if the mutome and
amplicome were working cooperatively to
change certain pathways or networks
 Found synergy in some funtional ontologies
canonoical pathways and processes networks
◦ Suggest close interactions between mutated and
amplified genes

29. Figure 4
Some of the highest
synergy found in
pathways involving:
• Cell adhesion
• Cytoskeloton
remodeling
• Cell Cycle
regulation of the
G1-S checkpoint
Red rectangles are
amplified genes and
Blue boxes are
mutated genes

30.  The fact that the amplicome had more
disease biomarkers for cancer suggests that
gene amplification events are more
significant in activating tumorigenenises than
somatic mutations
 Combination of multiple genetic alterations
(both amplification and somatic mutation)
necessary for multiple tumorigenetic
signaling pathways in breast cancer
 Further research can be done to explore
therapeutic targeting of synergystic pathways

31.  Is there selection for or against amplification
in certain places in the genome? Is there
something about the sequence or gene that
allows amplification to occur?
 Why do you think that the mutated genes
were always found to be upstream of the
amplified genes? What effect does this have
on their roles in pathways?

32.  http://cancerres.aacrjournals.org/content/68
/22/9532.full
 http://cancerres.aacrjournals.org/content/68
/22/9532/suppl/DC1
 http://macf-
web.dfci.harvard.edu/index.php?option=com
_content&task=viewid=20&ltemid=88
 http://media.affymetrix.com/support/technic
al/appnotes/microarrays_cancer_research_ap
pnote.pdf