Transcript Sarcomas with Aberrant Transcription Factors: Biology and Expression Profiling Marc Ladanyi

Sarcomas with Aberrant Transcription Factors:
Biology and Expression Profiling
Marc Ladanyi
Memorial Sloan-Kettering Cancer Center
New York, NY, USA
Translocation-associated
sarcomas
1. General biological features and
comparison to sarcomas with non-specific
cytogenetic alterations
2. Insights from microarray-based expression
profiling of translocation-associated
sarcomas
Pathologic genetic rearrangements
in human cancers: a family tree
Translocations
Balanced
Promoter Substitution
Unbalanced
Gene Fusion
Chimeric
Transcription Factor
Deregulated
gene expression
Loss of Tumor Suppressor
Chimeric
Tyrosine Kinase
Deregulated
growth signaling
Gain of Oncogene
Molecular pathology of sarcomas: two major classes
1. Sarcomas with specific
reciprocal translocations and
relatively simple karyotypes
•
•
•
•
approx. 1/3 of all sarcomas
15 different sarcoma types
with over 25 different
translocations
fusion genes: aberrant
chimeric transcription factors
(most) or aberrant kinases
(some)
biology: transcriptional
deregulation or aberrant
signaling
2. Sarcomas with complex
unbalanced karyotypes
and no specific translocations
•
•
approx. 2/3 of all sarcomas
biology: genetic gains &
losses, chromosomal
instability, telomere
dysfunction
Molecular pathology of sarcomas: two major classes
Sarcomas with specific
translocations
Sarcomas with
non-specific genetic
alterations
Usually complex
Karyotypes
Usually simple
Translocations
Reciprocal & specific,
producing fusion genes
Telomere maintenance
mechanisms
Telomerase common,
ALT mechanism rare
Relatively rare, but strong
More frequent, but limited
Evidence
of “alternative
prognostic impact*
or no prognostic
impact
lengthening
Not observed
Commonof telomeres”
P53 pathway alterations
Incidence in P53-mutant
or knockout mice
Non-reciprocal & nonspecific, causing gene copy
number changes
ALT mechanism more
common than telomerase
(ALT) telomere maintenance
Common
mechanism:
Incidence in bilateral
retinoblastoma and
Li-Fraumeni syndrome
Rare
Global gene expression
profiles
Robust clustering
Ewing sarcoma (0/30) vs
osteosarcoma
(38/60)
Looser clustering
(P<0.0001)*
* MSKCC study: Genes Chromos Cancer 2004
Molecular pathology of sarcomas: two major classes
Sarcomas with specific
translocations
Sarcomas with
non-specific genetic
alterations
Usually complex
Karyotypes
Usually simple
Translocations
Reciprocal & specific,
producing fusion genes
Telomere maintenance
mechanisms
Telomerase common,
ALT mechanism rare
Relatively rare, but strong
More frequent, but limited
Evidence
of “alternative
prognostic impact*
or no prognostic
impact
lengthening
Not observed
Commonof telomeres”
P53 pathway alterations
Incidence in P53-mutant
or knockout mice
Incidence in bilateral
retinoblastoma and
Li-Fraumeni syndrome
Rare
Global gene expression
profiles
Robust clustering
Non-reciprocal & nonspecific, causing gene copy
number changes
ALT mechanism more
common than telomerase
(ALT) telomere maintenance
Common
mechanism:
Translocation sarcomas (0/9)
vs other
sarcomas
Looser
clustering (7/9)
(P=0.002)*
* Hopkins study: AJP 2004
Molecular pathology of sarcomas: two major classes
Sarcomas with specific
translocations
Usually simple
Translocations
Reciprocal & specific,
producing fusion genes
Telomere maintenance
mechanisms
Telomerase common,
ALT mechanism rare
Relatively rare, but strong
prognostic impact
Not observed
Rare
Global gene expression
profiles
Robust clustering
Common
 No P53 mutation
(n=52)
0.6
Incidence in bilateral
retinoblastoma and
Li-Fraumeni syndrome
0.8
Incidence in P53-mutant
or knockout mice
More frequent, but limited
or no prognostic impact
Common
P53 in Ewing sarcoma*
Looser clustering
p<0.0001
* MSKCC study: JCO in press
0.0
0.2
0.4
P53 pathway alterations
Non-reciprocal & nonspecific, causing gene copy
number changes
ALT mechanism more
common than telomerase
1.0
Karyotypes
Sarcomas with
non-specific genetic
alterations
Usually complex
0
 P53 mutated (n=8)
20
40
60
80
100
120
Molecular pathology of sarcomas: two major classes
Sarcomas with specific
translocations
Karyotypes
Usually simple
Translocations
Reciprocal & specific,
producing fusion genes
Telomere maintenance
mechanisms
Telomerase common,
ALT mechanism rare
Relatively rare, but strong
prognostic impact
Not observed
P53 pathway alterations
Incidence in P53-mutant
or knockout mice
Sarcomas with
non-specific genetic
alterations
Usually complex
Non-reciprocal & nonspecific, causing gene copy
number changes
ALT mechanism more
common than telomerase
More frequent, but limited
or no prognostic impact
Common
Incidence in bilateral
retinoblastoma and
Li-Fraumeni syndrome
Rare
Common
Global gene expression
profiles
Robust clustering
Looser clustering
Major fusion genes in sarcomas: biological overview
Sarcoma type
Translocation
Fusion gene
Transcriptional
Deregulation
Aberrant
Signaling
Ewing sarcoma
t(11;22)
EWS-FLI1
X
t(21;22)
EWS-ERG
X
Clear cell sarc.
t(12;22)
EWS-ATF1
X
Myxoid LPS
t(12;16)
TLS-CHOP
X
Alveolar
rhabdomyosarcoma
t(2;13)
PAX3-FKHR
X
t(1;13)
PAX7-FKHR
X
DSRCT
t(11;22)
EWS-WT1
X
Extr. myx. CS
t(9;22)
EWS-CHN
X
Synovial sarc.
t(X;18)
SYT-SSX1,2
X
DFSP
t(17;22)
COL1A1-PDGFB
X
Cong. FS
t(12;15)
ETV6-NTRK3
X
IMT
t(2p23)
ALK fusions
X
End. str. sarc.
t(7;17)
JAZF1-JJAZ1
X
ASPS
t(X;17)
ASPL-TFE3
X
Low grade MFS
t(7;16)
FUS-BBF2H7
X
Pericytoma
t(7;12)
ACTB-GLI
X
Target Genes of Chimeric Transcription Factors
in Sarcomas
• Slow progress in identifying genuine biologically
critical target genes of chimeric transcription factors
– e.g. well-established targets:
• EWS-FLI1 <15
• EWS-WT1, PAX3-FKHR <5 each
– Low throughput gene-by-gene studies
– False leads generated by assays using exogenous target
promoters and/or heterologous cells
– Most representative cellular background for inducible
systems still subject of active investigation
– Need for more alternative higher throughput approaches
Target Genes of Chimeric Transcription Factors
in Selected Sarcomas
Tumor
Fusion protein
Type of
DNA BD
Direct or indirect targets
Ewing sarcoma / EWS-FLI1
PNET
EWS-ERG
ETS
TGFBR2 (), p57KIP2 (), MYC,
PDGF-C, ID2, CCND1, UBE2C,
IGFBP3()
DSRCT
EWS-WT1
Zn finger
PDGF-A, IL-2/15R, TALLA1,
BAIAP3
Alveolar RMS
PAX3-FKHR
PAX7-FKHR
Paired box
MET, CXCR4
Synovial
Sarcoma
SYT-SSX1
SYT-SSX2
(none)
XRCC4, TLE1
Alveolar Soft
Part Sarcoma
ASPL-TFE3
bHLH-LZ
CYP17A1, UPP1
Sarcomas with Aberrant
Transcription Factors
1. General biological features and
comparison to sarcomas with non-specific
cytogenetic alterations
2. Insights from microarray-based expression
profiling of translocation-associated
sarcomas
Expression Profiling of Sarcomas with
Chimeric Transcription Factors
Why is it interesting?
1. Translocation-associated sarcomas already
have an objective molecular classification
(detection of specific translocation) that can
be used to evaluate unsupervised clustering
based on expression profiles
2. Transcriptional deregulation is likely to be
central to the pathogenesis of translocationassociated sarcomas with chimeric
transcription factors
Expression profiling of sarcomas with
chimeric transcription factors
• 137 tumor samples from MSKCC and U.Penn. (F. Barr)
• + 4 xenografts + 12 cell lines = 153 total samples
• Classification of all samples confirmed by fusion transcript RT-PCR
Alveolar Rhabdomyosarcoma
(ARMS)
Desmoplastic Small Round Cell
Tumor (DSRCT)
Synovial Sarcoma (SS)
23
Ewing Sarcoma/PNET
(ES)
38
Alveolar Soft Part Sarcoma
(ASPS)
14
32
46
16 PAX3-FKHR
7 PAX7-FKHR
32 EWS-WT1
25 SYT-SSX1
21 SYT-SSX2
22 EWS-FLI1 type 1
11 EWS-FLI1 type 2
5 EWS-ERG
11 ASPL-TFE3 type 1
3 ASPL-TFE3 type 2
Gene expression data analysis
• Hybridization to Affymetrix U133A GeneChip
(22215 probe sets, 18500 transcripts, 14500 genes)
• Unsupervised Hierarchical Clustering
Raw data
processing
Clustering
Number of genes
MAS v5.0
Cluster/Treeview
RMA method
Pearson correlation
Subsets
All probe sets
(22215)
• Selection of differentially expressed genes
Two-tailed t-tests; p<0.01 after Bonferroni correction
Unsupervised hierarchical clustering n°1
MAS v5.0, Cluster/Treeview, different subsets of most variable probe sets
7200 probe sets
ARMS
SS
ES
DSRCT
SS
ES
ASPS
3200 probe sets
ASPS
DSRCT
ARMS
ES
SS ES
SS
2200 probe sets
DSRCT
ASPS
SS ARMS
SS
ES
ARMS
 Variability of clustering results according to number of probe sets selected
Unsupervised Hierarchical Clustering n°2
RMA method, Pearson correlation, all 22215 probe sets
n=153
ES ASPS
cell
lines
DSRCT
ARMS
ES
SS
Unsupervised hierarchical clustering n°2
RMA method, Pearson correlation, all 22215 probe sets
ES/PNET
orphan
case
n=137
tumors
only
ASPS
ES
SS
DSRCT
ARMS
Unsupervised hierarchical clustering
Multi-dimensional scaling analysis
3 different views of same data
Ewing’s sarcoma
Alveolar rhabdomyosarcoma
Alveolar soft part sarcoma
Synovial sarcoma
Desmoplastic small round cell tumor
n=137
Distribution of tumor types and numbers of
differentially expressed genes by sarcoma type
Samples Genes
significantly
over- or underexpressed*
Subset with
 2 fold
overexpression*
SS
46
6816
638
ARMS
23
1518
282
DSRCT
28
3163
554
ASPS
12
1590
531
ES/PNET
28
2157
294
* all significant at Bonferroni p<0.01 relative to 4 other
sarcoma types
 Numbers of differentially expressed genes “inflated” by comparison to reference
group of remaining four sarcomas, each with strong distinctive expression profile
The gene expression profiles of translocation sarcomas contain
many previously reported differentially expressed genes
“Literature validation”
Sarcoma
Gene
P-value
Fold change
ARMS
MyoD1
10-18
12
FGFR4
10-11
7.7
Myogenin
MIC2
10-9
10-18
4.5
2.8
MYC
10-17
5.2
CCND1
10-12
4.5
PRAME
10-39
5.6
TLE1
10-33
8.5
FZD1
10-24
8.4
ES
SS
• Differentially expressed genes in sarcomas with chimeric transcription factors
– Target genes regulated by fusion protein (direct or indirect)
– Genes reflecting pre-existing phenotype of host cell
– Genes reflecting secondary genetic or epigenetic alterations
Use of microarray data to predict
classification of translocation sarcomas
Multiple-class Prediction using Supervised Methods
Support Vector Machine Prediction Rule
90%
Training set
10%
Validation set
Selection of a subset of informative
genes for each class
Creation of a Prediction Model
Predictor/Classifier
Assess accuracy on the validation set
10 fold
Cross
validation
Performance of microarray-based predictor
136/137 sarcomas were accurately predicted
Model Prediction
ARMS
23
0
0
0
0
Histological
ASPS
and
Molecular DSRCT
Diagnosis
SS
0
12
0
0
0
0
0
28
0
0
0
0
0
46
0
ES
1
0
0
0
27
Similar results with other predictions methods
Single misclassified case = orphan case in unsupervised clustering
 ES with EWS-FLI1 type 1 fusion + p16 deletion and no PAX-FKHR
Expression Profiling of Sarcomas with
Chimeric Transcription Factors
– Global analyses / Microarray-based classifier
• Translocation sarcomas are associated with very
distinctive gene expression profiles
– can be used to classify these sarcomas as accurately
as translocation detection
• Parameters for raw data processing and clustering
can have strong effects on unsupervised analyses
– Contribution of chimeric transcription factor
target genes to specific expression profiles
Contribution of chimeric transcription factor target genes
to specific expression profiles of translocation sarcomas
Approaches
1. Differential expression of known target genes
2. Cross-referencing of profiles from microarray
experiments using inducible cell lines
3. Identification of candidates for target gene
analyses based on expression profiling data
from primary tumors
The expression profiles of translocation
sarcomas contain known target genes
of their chimeric transcription factors
ES: EWS-FLI1 targets
Differential expression in ES/PNET
(n=38 vs 115)
P-value
Fold change
Proposed
Target Gene
Reported Effect
of EWS-FLI1
MYC

10-17
5.2
ID2

10-9
3.2
CCND1

10-12
4.5
UBE2C

10-8
2.7
PDGFC

10-9
3.5
The expression profiles of translocation
sarcomas contain known target genes
of their chimeric transcription factors
DSRCT: EWS-WT1 targets
Proposed
Target Gene
Reported
Effect of
EWS-WT1
Differential expression in
DSRCT (n=32 vs 121)
P-value
Fold change
TALLA-1

10-15
5.5
PDGFA

10-14
2.7
IL2RB

10-13
4.6
BAIAP3

10-9
4
EWS-WT1 target genes defined in a
heterologous cell line are over-represented
among genes differentially expressed in DSRCTs
•
•
•
Induction of EWS-WT1
protein expression in U2OS
human osteosarcoma cells
with tetracycline-inducible
EWS-WT1 construct
Hybridized to U133A chips
W. Gerald Lab, MSKCC
• 102 genes demonstrated at least a 3 fold alteration in expression
level at 24h following induction of EWS-WT1
– 22 down-regulated, 80 upregulated
EWS-WT1 target genes defined in a
heterologous cell line are over-represented
among genes differentially expressed in DSRCTs
U2OS cell experiment
80 genes upregulated
at least 3 fold
Expression profiles of DSRCT tumors
35 genes in common
553 genes that were 2 fold overexpressed
in DSRCT relative to other translocation
sarcomas
• 17-fold enrichment for EWS-WT1 target genes among genes in
the DSRCT expression profile (Chi-square p<0.0001)
• include several previously validated EWS-WT1 targets:
– BAIAP3, PDGFA, TALLA1, IL2RB
EWS-WT1 target genes defined in a
heterologous cell line are over-represented
among genes differentially expressed in DSRCTs
• 44% of genes upregulated by induction of EWS-WT1 in the U2OS
human osteosarcoma cell line were also significantly
overexpressed in DSRCTs
• 6% of the DSRCT expression profile corresponds to genes
induced by EWS-WT1 in the model system
EWS-WT1 target genes defined in a
heterologous cell line are over-represented
among genes differentially expressed in DSRCTs
• 44% of genes upregulated by induction of EWS-WT1 in the U2OS
human osteosarcoma cell line were also significantly
overexpressed in DSRCTs
• 6% of the DSRCT expression profile corresponds to genes
induced by EWS-WT1 in the model system
• Comparison with similar data in Ewing’s sarcoma
•
Lessnick SL, Dacwag CS, Golub TR. Cancer Cell 1:393-401, 2002
• 46% of the EWS-FLI1-upregulated genes appeared in the
ES/PNET expression profile obtained from primary tumors
• 8% of the ES/PNET expression profile corresponded to genes
induced by EWS-FLI1 in the model system
Alveolar Soft Part Sarcoma
Top 20 significantly overexpressed genes
Fold change
P-value
Gene
121
10-11
CYP17A1
86
10-24
INHBE
75
10-9
MIBP
62
10-37
GPNMB
52
10-28
GOS2
51
10-34
Hs.57548
49
10-9
DEFB1
47
10-11
SULT1C1
47
10-10
UPP1
43
10-11
SULT1C1
43
10-15
SV2B
42
10-9
GPR56
41
10-7
NTSR2
40
10-19
Hs.37189
36
10-7
AGXT2L1
30
10-14
CLI
29
10-16
CLI
27
10-2 3
PTDGS
25
10-29
PTDGS
24
10-39
PTDGS
Can we use this list to identify
new target genes of sarcoma
fusion proteins?
Ranked by
fold-change
Makoto Nagai, MD PhD
Alveolar Soft Part Sarcoma
Top 20 significantly overexpressed genes
Fold change
P-value
Gene
121
10-11
CYP17A1
86
10-24
INHBE
75
10-9
MIBP
62
10-37
GPNMB
52
10-28
GOS2
51
10-34
Hs.57548
45000
49
10-9
DEFB1
47
10-11
SULT1C1
40000
35000
47
10-10
UPP1
43
10-11
SULT1C1
20000
15000
43
10-15
SV2B
42
10-9
GPR56
10000
5000
41
10-7
NTSR2
40
10-19
Hs.37189
36
10-7
AGXT2L1
30
10-14
CLI
29
10-16
CLI
27
10-2 3
PTDGS
25
10-29
PTDGS
24
10-39
PTDGS
Cytochrome P450 subfamily 17A1
(CYP17A1)
30000
25000
0
1
11 21 31 41 51 61 71 81 91 101 111 121 131 141 151
Ranked by
fold-change
Identification of CYP17A1 as a direct target of
ASPL-TFE3 based on its strong differential overexpression
in the expression profile of ASPS
• Promoter region of CYP17A1
contains 3 potential TFE3 sites
• CYP17A1 promoter strongly
activated by ASPL-TFE3, but not
native TFE3
• Strong physical binding of ASPLTFE3 to sites #1 and #3 by EMSA
• In vivo presence of ASPL-TFE3 at
CYP17A1 promoter in model cell
line (293) by chromatin IP
• Induction of ASPL-TFE3 in model
cell line (293) results in
upregulation of endogenous
CYP17A1 by real-time Q-RT-PCR
Alveolar Soft Part Sarcoma
Top 20 significantly overexpressed genes
Fold change
P-value
Gene
121
10-11
CYP17A1
86
10-24
INHBE
75
10-9
MIBP
62
10-37
GPNMB
52
10-28
GOS2
51
10-34
Hs.57548
49
10-9
DEFB1
47
10-11
SULT1C1
47
10-10
UPP1
43
10-11
SULT1C1
43
10-15
SV2B
42
10-9
GPR56
41
10-7
NTSR2
40
10-19
Hs.37189
36
10-7
AGXT2L1
30
10-14
CLI
29
10-16
CLI
27
10-2 3
PTDGS
25
10-29
PTDGS
24
10-39
PTDGS
Can we do this with another
gene from the list?
Ranked by
fold-change
Alveolar Soft Part Sarcoma
Top 20 significantly overexpressed genes
Fold change
P-value
Gene
121
10-11
CYP17A1
86
10-24
INHBE
75
10-9
MIBP
62
10-37
GPNMB
52
10-28
GOS2
51
10-34
Hs.57548
49
10-9
DEFB1
47
10-11
SULT1C1
47
10-10
UPP1
43
10-11
SULT1C1
43
10-15
SV2B
42
10-9
GPR56
41
10-7
NTSR2
40
10-19
Hs.37189
36
10-7
AGXT2L1
30
10-14
CLI
29
10-16
CLI
27
10-2 3
PTDGS
25
10-29
PTDGS
24
10-39
PTDGS
203234_at gb:NM_003364.1 Uridine
Uridine Phosphorylase
(UPP1)
phosphorylase (UP)
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
1
11 21 31 41 51 61 71 81 91 101 111 121 131 141 151
Ranked by
fold-change
Identification of UPP1 as a direct target of
ASPL-TFE3 based on its strong differential overexpression
in the expression profile of ASPS
• UPP1 promoter more strongly
activated by ASPL-TFE3 than by
native TFE3
• Induction of ASPL-TFE3 in model
cell line (293) results in
upregulation of endogenous
UPP1, as measured by real-time
quantitative RT-PCR
Identification of UPP1 as a direct target of
ASPL-TFE3 based on its strong differential overexpression
in the expression profile of ASPS
• UPP1 promoter more strongly
activated by ASPL-TFE3 than by
native TFE3
• Induction of ASPL-TFE3 in model
cell line (293) results in
upregulation of endogenous
UPP1, as measured by real-time
quantitative RT-PCR
Identification of UPP1 as a direct target of ASPLTFE3 based on its strong differential
overexpression in the expression profile of ASPS
• UPP1 promoter more strongly
activated by ASPL-TFE3 than by
native TFE3
• Induction of ASPL-TFE3 in model
cell line (293) results in
upregulation of endogenous
UPP1, as measured by real-time
quantitative RT-PCR
• Potential therapeutic interest
of uridine phosphorylase
– converts the pyrimidine
analogue, 5'-deoxy5'fluorouridine, to 5-FU
– allows administration of 5'deoxy-5'fluorouridine as a
prodrug with low toxicity to
non-neoplastic cells
expressing only basal levels of
uridine phosphorylase
Identification of potential target genes of
SYT-SSX based on strong differential overexpression in the
expression profile of synovial sarcoma
Top 5 ranked by p-value
Probe set
Fold T test p-value Gene Symbol
203221_at
10.9
2.68E-43 TLE1
205031_at
6.1
4.54E-40 EFNB3
206315_at
14.0
8.98E-38 CRLF1
204086_at
11.2
1.82E-37 PRAME
58780_s_at
3.2
6.66E-36 FLJ10357
203131_at
14.5
6.87E-36 PDGFRA
221004_s_at
5.1
1.17E-35 ITM2C
213479_at
28.2
1.61E-35 NPTX2
202575_at
7.4
1.27E-33 CRABP2
220326_s_at
2.6
1.72E-33 FLJ10357
204724_s_at 18.4
1.38E-32 COL9A3
209806_at
4.7
3.71E-32 HIST1H2BK
218502_s_at 15.3
1.97E-31 TRPS1
203222_s_at
8.2
3.56E-31 TLE1
210497_x_at
5.2
5.40E-31 SSX2
204735_at
3.8
5.56E-31 PDE4A
217957_at
2.4
1.06E-30 GTL3
214761_at
4.2
1.61E-30 OAZ
212599_at
6.8
2.27E-30 AUTS2
221447_s_at
6.1
2.67E-30 LOC83468
213194_at
5.4
2.95E-30 FLJ10539
Tsuyoshi
Saito,
218397_at
2.7
3.23E-30
PHF9M.D. Ph.D.
213698_at
3.1
3.66E-30 MGC14276
200975_at
2.2
4.52E-30 PPT1
203180_at
10.7
1.45E-29 ALDH1A3
See Pathology Poster # 5
(not in printed program)
TLE1 (transducin-like enhancer of split 1)
a transcriptional repressor of
Wnt/-catenin signaling
Expression Profiling of Sarcomas with
Chimeric Transcription Factors
– Global analyses / Microarray-based classifier
– Contribution of chimeric transcription factor
target genes to specific expression profiles
• Significant subsets of genes in specific expression
profiles may be chimeric transcription factor target
genes
• Specific expression profiles can be used to identify
new candidates for target gene analyses
Kinases as therapeutic targets in sarcomas
with chimeric transcription factors
• kinases or signaling pathways directly activated by the
specific aberrant transcription factor
Tumor
Fusion protein
Signaling proteins
confirmed or proposed
to be upregulated
Ewing sarcoma /
PNET
EWS-FLI1
EWS-ERG
PIM3
Alveolar RMS
PAX3-FKHR
PAX7-FKHR
MET
Desmoplastic
small round cell
tumor
EWS-WT1
PDGF-A, FGFR4
Kinases as therapeutic targets in sarcomas
with chimeric transcription factors
• kinases or signaling pathways directly activated by the
specific aberrant transcription factor
• kinases or signaling pathways overexpressed in
specific sarcomas apparently unrelated to direct action
of aberrant transcription factor
• ERBB2/Her2/neu in synovial sarcoma
• EGFR in synovial sarcoma
• KIT in Ewing’s sarcoma
• kinases activated by mutations as secondary or
cooperating events in sarcomas with aberrant
transcription factors (like FLT3 mutations in leukemias)
• none identified so far
• chimeric transcription factors regulated by
phosphorylation
• EWS-WT1
Expression profiling of sarcomas with aberrant
transcription factors and related studies
MSKCC
• Ladanyi Lab
–
–
–
–
–
–
•
Tsuyoshi Saito
Makoto Nagai
Marick Laé
Violetta Barbashina
Man Yee Lui
Zhiquan Zhao
W. Gerald Lab
– William Gerald
– Lishi Chen
•
– Pete Argani
• U. Pennsylvania
– Fred Barr
Biostatistics
– Adam Olshen
– Shannon Chuai
•
• Johns Hopkins
• U. Michigan
– Larry Baker
– Dafydd Thomas
Other MSKCC collaborators
– Cristina Antonescu
– John Healey, Murray Brennan, Sam Singer
– Paul Meyers, Len Wexler, Robert Maki