Syngeneic Models
Progress immunotherapeutic development with CrownBio’s panel of over 30
syngeneic models
Discover the benefits of using our fully
characterized and checkpoint inhibitor
benchmarked syngeneic models to accelerate
your immuno-oncology drug discovery
programs.
The development of novel immunotherapeutics presents many
challenges, including the need for immunocompetent preclinical
models. Syngeneic mouse models are undergoing a resurgence
as an accessible platform to evaluate the efficacy and MOA of
novel agents and combination strategies.
CrownBio provides an extensive syngeneic platform of over 30
models covering more than 15 cancer types for immunotherapeutic assessment.
•• Select the most appropriate models for checkpoint
inhibitor novel agent/combination studies using a vast
array of benchmarking data (e.g. anti-PD-1, PD-L1, CTLA-4
antibodies) complemented by immunoprofiling and NGS.
Historical origins of
in vitro cell line: murine tumor
Implant into original
inbred mouse strain
Syngeneic Models for I/O
Research
Standard subcutaneous models
for I/O agent evaluation
Advanced orthotopic, bioluminescent,
and metastic modeling
•• Choose the right model for bacterial, viral, and vaccine
immunotherapy research based on baseline immunophenotyping at the subcutaneous or orthotopic site.
•• Evaluate efficacy quickly with standard subcutaneous
Checkpoint inhibitor
benchmarking
models, alongside disease relevant tumor microenviroment
in orthotopic and metastatic sites with bioluminescent
imaging.
Combination therapy
strategies
•• Assess immunomodulatory effects through post-treatment
Immune cell profiling
immunoprofiling including T cell infiltration.
•• Fast track new immuno-oncology agents using the first
large-scale in vivo syngeneic screening platform.
Large scale in vivo
screening
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Syngeneic Models Key Facts
CrownBio provides a well characterized Syngeneic Model Panel:
• Over 30 models covering 15 cancer types, with further models undergoing validation.
• Standard subcutaneous models for efficacy evaluation, complemented by orthotopic models to better recapitulate the
tumor microenvironment, and metastatic models allowing targeting of clinically relevant metastatic invasion.
• Bioluminescent metastatic models to monitor in-life disease progression, and primary to end stage disease.
• Full validation data (baseline and post-treatment immunoprofiling, immunotherapy, standard of care, and NGS data) easily
searchable through MuBase®, CrownBio’s online collated immuno-oncology model database.
• Checkpoint inhibitor benchmarking data including anti-PD-1, PD-L1, and CTLA-4 antibodies to select the appropriate
models for single agent and combination studies, including combination immunotherapy and immunotherapy +
chemotherapy (including inducer of ICD) strategies.
• Validated immunoprofiling including treatment induced T cell infiltration assessment to characterize immunomodulatory
effects of novel agents and treatment regimens.
• Microbiome analysis to correlate gut microbiomes across our syngeneic models with response to therapy.
• CrownBio’s large-scale, in vivo syngeneic screening platform MuScreen™, the first screening platform of its type, to fast track
immunotherapy compounds.
Syngeneic Model Use in Preclinical ImmunoOncology Research
CrownBio Provides a Large and Well Profiled
Panel of Syngeneic Models
Evaluating immunotherapeutic agents brings many challenges,
including the need for preclinical models within immunocompetent
hosts. Syngeneic mouse models have seen a resurgence in use as a
straightforward platform enabling efficacy testing and elucidation of
the mechanism of action of new immuno-oncology treatments.
Our large panel of well validated syngeneic models covers over 15
cancer types and more than 30 individual models (summarized in
Table 1, availability site by site is covered within our In Vivo Cancer
Pharmacology Model catalogs available on request). CrownBio are
constantly improving and expanding the syngeneic collection, and
our pipeline of models currently undergoing validation includes:
Syngeneic mouse tumors are allografts derived from immortalized
mouse cancer cell lines which originate from the same inbred strain
of mice. The recipient mice have fully competent mouse immunity
and are histocompatible to the allografted tumors. Models have now
been extensively profiled genomically and immunologically (both
pre- and post-treatment), and for agent efficacy to allow simple and
rapid model selection for preclinical studies.
Agents commonly tested using syngeneics include checkpoint
inhibitors such as anti-PD-1 and PD-L1 antibodies in proof of
concept studies. Syngeneics can also be utilized for evaluating a
wide range of other immunotherapeutics, including bacterial, viral,
and vaccine therapies, all of which have driven syngeneics to
become one of the most commonly utilized immuno-oncology
models in preclinical investigations.
•
•
•
•
•
•
breast C127I model
chondrogenic ATDC5 model
colon CMT-93 model
liver Hepa1c1c7 model
lung LA-4 model
kidney RAG model.
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Syngeneic Models Factsheet
Table 1: Summary of Syngeneic Immunotherapy Models
X = data available; *bioluminescent models established with further validation ongoing.
Cancer Type
Cell Line
Model Type
Anti-PD-1
Anti-PD-L1
Anti-CTLA-4
RNAseq
Immune Cell Profiling
Bladder
MBT-2*
Subcutaneous
X
X
X
X
X
Breast
4T1*
Subcutaneous, orthotopic, metastatic, bioluminescent
X (s.c., ortho)
X (s.c., ortho)
X (s.c., ortho*)
X (s.c., ortho*)
X (ortho) Ongoing (s.c.)
EMT6*
Subcutaneous, orthotopic, bioluminescent
X (s.c.)
X (s.c.)
X (s.c.)
X (s.c.)
X (s.c.)
JC
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
X
Colon26
Subcutaneous
X
X
X
Ongoing
X
CT-26.WT*
Subcutaneous
X
X
X
X
X
Fibrosarcoma
WEHI-164
Subcutaneous
X
Ongoing
Ongoing
Ongoing
Ongoing
Glioma
GL261
Subcutaneous, orthotopic
Ongoing (s.c., ortho)
Ongoing (s.c., ortho)
Ongoing (s.c., ortho)
X (s.c.) Ongoing (ortho)
Ongoing (s.c., ortho)
Kidney
Renca*
Subcutaneous
X
X
X
X
X
Leukemia
C1498
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
X
L1210
Subcutaneous
X
X
X
X
X
H22*
Subcutaneous, orthotopic, bioluminescent
X
X
X
X
X
Hepa 1-6*
Subcutaneous, orthotopic, bioluminescent
X (s.c.)
X (s.c.)
X (s.c.)
Ongoing (s.c.)
X (s.c.)
KLN205
Subcutaneous
X
X
X
X
X
LL/2 (LLC1)*
Subcutaneous, metastatic
X
X
X
X
X
A20
Subcutaneous
X
X
X
X
X
E.G7-OVA
Subcutaneous
X
Ongoing
Ongoing
Ongoing
Ongoing
EL4
Subcutaneous
X
X
X
X
X
L5178-R (LY-R)
Subcutaneous
X
X
X
Ongoing
X
Colon
Liver
Lung
Lymphoma
P388D1
Subcutaneous
X
X
X
X
X
Mastocytoma
P815*
Subcutaneous
Ongoing
X
Ongoing
Ongoing
Ongoing
Melanoma
B16-BL6
Subcutaneous
X
X
X
X
X
B16-F0
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
Ongoing
B16-F1
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
Ongoing
B16-F10*
Subcutaneous, metastatic, bioluminescent
X
X
X
X
X
Clone M-3
(Cloudman S91)
Subcutaneous
Ongoing
X
Ongoing
Ongoing
Ongoing
J558
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
X
MPC-11
Subcutaneous
X
X
X
X
X
P3X63Ag8U.1
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
Ongoing
N1E-115
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
Ongoing
Myeloma
Neuroblastoma
Neuro-2a
Subcutaneous
Ongoing
Ongoing
Ongoing
Ongoing
Ongoing
Pancreatic
Pan02*
Subcutaneous, orthotopic, bioluminescent
X (s.c.)
X (s.c.)
X (s.c.)
X (s.c.)
X (s.c.)
Prostate
RM-1*
Subcutaneous
X
X
X
X
X
Standard Subcutaneous Models to Evaluate Novel Immunotherapies
CrownBio standard syngeneic models shown in Table 1 are fully validated with growth, standard of care (SoC) and/or immunotherapy treatment
data available. Complete background information, growth, and treatment data on models are included within MuBase our easy to use, proprietary online database. Models can be quickly searched and compared to find those appropriate for indivdual studies.
Models with baseline immune cell profiling data are also highlighted in Table 1. CrownBio research has shown that baseline immune cell
populations in untreated syngeneic models (T cells and the Teff/Treg ratio) may predict efficacy of anti-CTLA-4 and anti-PD-L1 antibodies,
respectively(1). Example FACS analysis baseline data are included within Figure 1 for T cells (CD3+, CD4+, CD8+, CD4+/FOXP3+) and ratio of CD8+
Teffect/Treg cells, with further NK, MDSC, and macrophage data available in MuBase.
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Syngeneic Models Factsheet
Figure 1: Basal Level of Immune Cells in Syngeneic Tumors
A: T cell mean % of CD3+, CD4+, CD8+, CD4+/FOXP3+ in TIL. B: Ratio of
CD8+ Teffect cells to Treg cells in total cell. Data generated at Crown
Bioscience Taicang site.
60
40
As checkpoint inhibitors continue to be approved for a variety of
cancer types, preclinical evaluation via syngeneic models can be
used to identify their potential indications and combination therapy
strategies.
30
20
P388D1
L5178-R
A20
Pan02
EMT6
B16-F10
H22
L1210
RM-1
B16-BL6
CT-26.WT
LL/2
ortho 4T1
MBT-2
Fold Change
35
30
25
20
Figure 2: Anti-PD-1 Antibody Efficacy Benchmarking in
Syngeneic Models
Antibody: RMP1-14. All data mean + SD. Data generated at Crown
Bioscience Beijing and Taicang sites.
15
10
Renca
EL4
MBT-2
LL/2
ortho 4T1
CT-26.WT
B16-BL6
RM-1
H22
L1210
B16-F10
EMT6
A20
Pan02
P388D1
5
0
CrownBio has extensively profiled our syngeneic panel in vivo
response to a variety of checkpoint inhibitors, providing clients with
the information necessary to select models and the correct doses
for combination therapy (available data shown in Table 1). Waterfall
plots for our models tested with anti-PD-1, anti-PD-L1, and antiCTLA-4 antibodies are shown in Figure 2 through Figure 4.
Table 1 also shows the availability of RNAseq data for our
syngeneic models, which has been used to identify biomarkers to
predict treatment response. Through generating detailed expression
maps and mutational profiles, we have identified alternative gene
splicing transcripts and gene fusions within our models. Further
mutational analysis has indicated a number of our syngeneic models
harbor mutations that may be useful for combination studies of
targeted agents and immunotherapy, and we have identified a set of
biomarkers that may be useful to predict immunotherapeutic agent
response(2).
We also provide syngeneic tumor samples for ex vivo research uses
including tumor tissue histology (H&E staining), and frozen and
formalin-fixed, paraffin-embedded tumor samples as required.
100
50
TGI (%)
0
Renca
EL4
10
0
-50
He
pa
16
H2 10
2 mg
or EM 10m /kg
th T6 g
o
/k
4
L5 T1 5mg g
1 1
CT 78 0m /kg
26 -R g/k
5
.W m g
M T 1 g/
BT 0 kg
E.G
7- L1 - 2 mg/
O 21 5 kg
V 0 m
A
g
20 10m /kg
0u g
su A2 g/m /kg
bq 0 1 ou
4T 0m se
1 g
B1 LL / 10m /k g
6 2 g
B1 -F1 10m /kg
6- 0 1 g/
B 0 k
KL L 6 mg g
N2 10 /kg
m
RM 05 g/k
-1 5m g
P 1 g/
P3 an0 0m kg
88 2 g/k
D1 5m g
g
E 10 /k
M L 4 mg g
PC 10 /k
W -1 m g
EH 1 g/
I-1 5m k g
Re 64 g/
Co nca 5m kg
lo 10 g/k
n2 m g
6 g/
5m kg
g/
kg
Mean (%)
Examine a Vast Array of Checkpoint Inhibitor
Benchmarking Data including Anti-PD1, PD-L1,
and CTLA-4 Agents
CD3+
CD3+CD4+
CD3+CD8+
Treg
50
For more information on these models and our pipeline of
developing bioluminescent syngeneics please request our Optical
Imaging FactSheet.
Figure 3: Anti-PD-L1 Antibody Efficacy Benchmarking in
Syngeneic Models
Antibody: 10F.9G2. All data mean + SD. Data generated at Crown
Bioscience Beijing and Taicang sites.
100
Advanced Orthotopic and Metastatic Disease
Models, and Syngeneic Imaging Modalities
and microenvironment
• clinically relevant metastatic models of disease
• bioluminescent metastatic models to study clinically relevant
metastatic invasion, metastatic lesions in secondary organs, and
the evaluation of agents to target this metastasis.
TGI (%)
• orthotopic models to more closely recapitulate the tumor situation
60
40
20
0
-20
-40
He
p
CT a 1
26 -6
.W 5m
T g
A2 10 /kg
EM 0 1 mg/
T6 0m kg
1 g/k
Cl L5 H2 0mg g
ou 17 2 5 /k
dm 8 m g
an -R 5 g/k
S m g
RM 9 1 g/k
- 5m g
M 1 1 g/k
BT 0m g
-2 g
or P8 5m /k g
th 15 g
/
o
4T 5m kg
Re 1 5 g/k
P3 nca mg g
88 5 /kg
D1 mg
B1 EL 5m /kg
6- 4 g/k
F1 5m g
0 g
su Pan 10m /kg
bq 02 g/
4 5 k
M T-1 mg g
P C 5 /k
g
L1 - 11 mg/
21 5 kg
KL 0 1 mg
N2 0m /kg
0
LL 5 5 g/k
Co /2 mg g
l 1 /
B1 on2 0m kg
6- 6 5 g/k
BL m g
6 g/k
5m g
g/
kg
CrownBio also provides advanced syngeneic modeling options
(model availability detailed in Table 1):
80
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Syngeneic Models Factsheet
Figure 4: Anti-CTLA-4 Antibody Efficacy Benchmarking in
Syngeneic Models
A: 9D9, data mean + SD; B: 9H10. Data generated at Crown
Bioscience Beijing and Taicang sites.
B.
100
50
80
40
40
TGI (%)
TGI (%)
60
20
1200
Tumor Voume (mm3)
A.
B.
IgG2a 3mg/kg b.i.w.
1000
800
600
400
200
0
30
3
20
5
7
11
13
15
17
19
21
23
25
10
-20
0
L5178-R 10mg/kg
MPC-11 10mg/kg
KLN205 10mg/kg
Individual control and treated spider plots are available for each
model on request, to evaluate model response variability, example
data for the liver syngeneic Hepa 1-6 model is included in Figure 5.
900
700
1000
800
600
400
200
0
3
5
7
9
11 13 15 17 19 21 23 25
Days post Tumor Inoculation
1200
D.
IgG2a 3mg/kg b.i.w.
Anti-PD-1 (RMP1-14) 10mg/kg b.i.w.
Anti-PD-L1 (10F.9G2) 5mg/kg b.i.w.
Anti-CTLA-4 (9D9) 5mg/kg b.i.w.
800
Anti-PD-1 (RMP1-14) 10mg/kg b.i.w.
Anti-PD-L1 (10F.9G2) 5mg/kg b.i.w.
Tumor Volume (mm3)
Figure 5: Variability of Hepa 1-6 Response: Control and
Treatment Spider Plots
A: Mean tumor volume ± SEM. B-E: Individual reponse following
treatment with IgG2a or checkpoint inhibitor shown. Statistical analysis on Day 25 post inoculation. Data generated at Crown Bioscience
Taicang site.
1200
C.
Tumor Volume (mm3)
H2
2
EM 10
T m
He 6 1 g/k
pa 0m g
su
bq 1-6 g/k
4T 5m g
-1
g
M
10 /kg
B
m
g/
CT T-2
26 10 kg
or .WT mg/k
th
1
0 g
o
4T mg
1
/k
g
RM 10
m
g
Pa 1 10 /k g
n0 m
2 g/k
10 g
A2 m
g
L1 0 10 /kg
21 m
B1 0 1 g/k g
6- 0m
F
B1
g
1
6- 0 5 /kg
BL m
6 g/k
LL 10m g
P3 /2 g/k
1
88 0m g
D
Co 1 1 g/k
lo 0m g
n2
6 g/kg
EL 5mg
4
Re 10 /kg
nc mg
a 1 /k
0m g
g/
kg
-40
Tumor Volume (mm3)
9
Days post Tumor Inoculation
0
600
500
400
300
1000
800
600
400
200
0
3
200
5
7
9
11
13
15
17
19
21
23
25
Days post Tumor Inoculation
100
0
5
7
9
11
13
15
17
19
21
23
Days post Tumor Inoculation
Treatment
T/C (%)
TGI (%)
p Value
Anti-PD-1 (RMP1-14)
15
85
<0.001
Anti-PD-L1 (10F.9G2)
32
68
0.042
Anti-CTLA-4 (9D9)
13
87
<0.001
25
1200
E.
Tumor Volume (mm3)
3
Anti-CTLA-4 (9D9) 5mg/kg b.i.w.
1000
800
600
400
200
0
3
5
7
9
11 13 15 17 19 21 23 25
Days post Tumor Inoculation
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Syngeneic Models Factsheet
As researchers discover that chemotherapy, radiotherapy, and
targeted therapies may interact or change the tumor immune
environment, suitable models are required to evaluate combinations
of these agents with immunotherapy.
CrownBio is utilizing our syngeneic panel to investigate combination therapy strategies. Example data treating the H22 liver cancer
syngeneic model with a combination of doxorubicin and anti-PD-L1
antibody showed that combined treatment had a greater effect than
either treatment alone (Figure 6).
Figure 7: Cyclophosphamide and Checkpoint Inhibitor Combined
Treatment of A20 Model Elicits a Range of Responses
Data generated at Crown Bioscience Taicang site.
2800
2400
2000
1600
1200
800
400
A range of checkpoint inhibitors have been trialed in combination
with cyclophosphamide on the A20 B lymphoma model (Figure 7).
Response to combination therapy varied, with the greatest tumor
growth inhibition observed for cyclophosphamide combined with
anti-GITR antibody.
Figure 6: Combination Doxorubicin and Anti-PD-L1 Antibody
Induces TGI of H22 Model Greater than Either Agent Alone
Data generated at Crown Bioscience Taicang site.
Tumor Volume (mm3)
2800
Vehicle q.w.
2400
Doxorubicin 5mg/kg q.4.d.
2000
Anti-PD-L1 (10F.9G2) 5mg/kg b.i.w.
1600
Doxorubicin 5mg/kg q.4.d. + Anti-PD-L1
(10F.9G2) 5mg/kg b.i.w.
PBS
CTX 20mg/kg
CTX 20mg/kg + Anti-CTLA-4 (9D9) 75μg/mouse
CTX 20mg/kg + Anti-PD-1 (RPM1-14) 75μg/mouse
CTX 20mg/kg + Anti-OX40 (OX-86) 75μg/mouse
CTX 20mg/kg + Anti-GITR (DTA-1) 75μg/mouse
CTX 20mg/kg + Anti-CD20 (AISB12) 50μg/mouse
3200
Tumor Volume (mm3)
Evaluate Combination Checkpoint Inhibitor and
Chemotherapy Regimens
0
10
12
14
16
18
20
22
24
Days post Tumor Inoculation
Treatment
Tumor Volume
(mm3)
T/C Value (%)
on Day 24
p Value
PBS
2752 ± 240
--
--
Cyclophosphamide (CTX)
776 ± 238
28
<0.001
CTX + Anti-CTLA-4 (9D9)
601 ±154
22
<0.001
CTX + Anti-PD1 (RMP1-14)
1016 ± 363
37
0.004
CTX + Anti-OX40 (OX-86)
538 ± 348
20
0.001
CTX + Anti-GITR (DTA-1)
151 ± 91
5
<0.001
CTX + Anti-CD20 (AISB12)
895 ± 110
33
<0.001
1200
800
Combining Inducers of Immunogenic Cell Deacth
(ICD) with Immunotherapy
400
0
3
5
7
9
11
13
15
17
19
21
Days post Tumor Inoculation
Treatment
Tumor Volume
(mm3)
T/C Value (%)
on Day 21
p Value
Vehicle
2291 ± 231
--
--
Anti-PD-L1 (10F.9G2)
519 ± 65
23
<0.001
Anti-CTLA-4 (9D9)
1436 ± 383
63
0.072
Anti-PD-L1 (10F.9G2)
268 ± 28
12
<0.001
A number of anticancer treatment strategies such as chemotherapeutic agents (e.g. oxaliplatin, doxorubicin, bortezomib, and
mitoxantrone), radiotherapy, and oncolytic viruses have been highlighted as potential inducers of ICD. These treatments are known to
increase the presentation of cell-associated antigens to CD4+ and
CD8+ T lymphocytes by dendritic cells.
Combination strategies of ICDs with immunotherapies could therefore provide opportunities to harness the immune system to extend
survival, even among metastatic and heavily pretreated cancer
patients, and may increase the efficacy of immunotherapy in cancer
types with low immunogenic status.
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Syngeneic Models Factsheet
Figure 9: Continuation..
CrownBio has combined the ICD oxaliplatin with anti-CTLA-4 in
treating the CT26 colon cancer syngeneic model. Combination of
anti-CTLA-4 immunotherapy with oxaliplatin resulted in an additive
40
tumor growth inhibition (Figure 8), and also induced a statistically
+
significant increase in CD8 TILs compared with oxaliplatin or
*
30
anti-CTLA-4 antibody alone (p<0.05,
Figure 9)(3). These results effectively demonstrate the applicability for further exploring combination ICD inducer strategies involving
immunotherapy.
20
15
Ratio of CD8+ : CD4+/FoxP3+
CD3+CD8+/Viable Single Lymphocytes
B.
Figure 8: ICD Oxaliplatin and Anti-CTLA-4
Combination Results in
10
Additive TGI
TGI reduction: Anti-CTLA-4 vs vehicle p<0.05. Oxaliplatin vs vehicle
0
p<0.01. Combination therapy is additive
over single
agent
therapy
Vehicle
Anti-CTLA-4
Oxaliplatin Anti-CTLA-4 +
alone. Data generated at CrownBio UK.
Oxaliplatin
10
5
0
Vehicle
Tumor Volume (mm3)
Oxaliplatin
Anti-CTLA-4 +
Oxaliplatin
Treatment
Treatment
Vehicle b.i.w. + vehicle q.w.
Anti-CTLA-4 10mg/kg b.i.w. ( ) + vehicle q.w.
Oxaliplatin 6mg/kg q.w. ( )+ vehicle q.w.
Anti-CTLA-4 10mg/kg b.i.w. ( )+ oxaliplatin 6mg/kg q.w. ( )
1750
Anti-CTLA-4
Microbiome Analysis of Responder vs
Non-Responder Animals
1500
Microbiota play an important role in determining an organism’s
response to anticancer treatment, even in tumors far from the
gastrointestinal tract, possibly because of their pro-inflammatory
properties which activate the immune system.
1250
1000
750
In order to gain insights into the complex interaction between the
microbiome and cancer therapy, CrownBio performs fecal collection
and microbiome profiling (16S rRNA sequencing) to compare gut
microbiomes across our syngeneic models, which we can correlate
with response to therapy.
500
250
0
0
5
10
15
20
25
30
Example data is shown in Figure 10 for animals implanted with
either CT-26 or 4T1 models, and treated with anti-PD-1 antibody or
isotype control. Efficacy studies revealed varying response across
different tumor models and within tumor models. Gut microbiome
sequencing was performed post dosing and showed that:
Study Day
Figure 9: ICD Oxaliplatin and Anti-CTLA-4 Combination Results in
CD8+ TIL Increase
Treatment dosing and regimens as per Figure 8. A: % CD3+/CD8+
T cells, *p<0.05 vs single agent anti-CTLA-4 and oxaliplatin. B: Ratio
Teff:Treg. Data generated at CrownBio UK.
• the gut microbiome of animals that were responsive to anti-PD-1
treatment differed from animals that were treated with isotype
control
40
*
30
20
10
0
Ratio of CD8+ : CD4+/FoxP3+
A.
CD3+CD8+/Viable Single Lymphocytes
• the gut microbiome of animals that were unresponsive to
15
anti-PD-1 treatment clustered closely with animals that were
treated with isotype control (Figure 10)(4).
10
5
0
Vehicle
Anti-CTLA-4
Oxaliplatin
Treatment
Anti-CTLA-4 +
Oxaliplatin
Vehicle
Anti-CTLA-4
Oxaliplatin
Anti-CTLA-4 +
Oxaliplatin
Treatment
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ingSyngeneic
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Figure
10: Gut Microbiome
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aves,
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to
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Fig. 1.Fig.
Immune
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Fig. 2.Fig.
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sequencing
seque
CrownCrown
Bios
Syngeneic Models Factsheet
Assess Immunotherapy Induced T Cell Infiltration
and Immunomodulatory Effects
Example FACS immunophenotyping data for the H22 liver model,
and IHC immunophenotyping for the A20 lymphoma model are
detailed below.
Following checkpoint inhibitor or immunotherapy evaluation,
CrownBio can perform immune cell profiling to evalute induced T
cell infiltration and immuno-modulatory effects. Our techniques
include FACS and IHC immunophenotyping, which have been validated with a range of our syngeneic models following checkpoint
inhibitor treatment:
The H22 model was treated with anti-PD-1 and anti-CTLA-4
antibodies, with response to treatment correlating with an increase
in selected tumor infiltrating lymphocytes (TIL) (Figure 11 and
Figure 12). T cell infiltration into A20 tumors was analyzed via IHC
and immunofluorescence (Figure 13).
• FACS immunophenotyping: MBT-2, 4T1, EMT6, CT-26.WT, L1210,
H22 ,B16-F10, and Pan02 models
• IHC immunophenotyping: A20
Tumor Volume (mm3)
Figure 11: H22 Liver Syngeneic Model Responds to Checkpoint Inhibitors: Mean and Individual Response
T/C values on Day 21: anti-PD-1 (RMP1-14) 16% (p=0.020); anti-CTLA-4 (9D9) 5% (p=0.012). B, C, D: Individual responses to PBS control, anti-PD-1,
and anti-CTLA-4, respectively. Data generated at Crown Bioscience Taicang site.
3000
PBS b.i.w.
Anti-PD-1 (RMP1-14) 10mg/kg b.i.w.
2500
Anti-CTLA-4 (9D9) 10mg/kg b.i.w.
2000
1500
1000
500
0
5
7
9
11
13
15
17
19
21
Days post Tumor Inoculation
3000
2000
1000
0
5
7
9
11
13
15
17
Days post Tumor Inoculation
19
21
3000
Anti-PD-1 (RMP1-14) 10mg/kg b.i.w.
Anti-CTLA-4 (9D9) 10mg/kg b.i.w.
Tumor Volume (mm3)
PBS b.i.w.
Tumor Volume (mm3)
Tumor Volume (mm3)
3000
2000
1000
0
2000
1000
0
5
7
9
11
13
15
17
Days post Tumor Inoculation
19
21
5
7
9
11
13
15
17
19
21
Days post Tumor Inoculation
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Syngeneic Models Factsheet
Figure 12: H22 Liver Syngeneic Model: Response to Checkpoint
Abs Correlates with an Increase in Selected TILs
FACS result on Day 21: 2 days post the 5th dose. Data generated at
Crown Bioscience Taicang site. *p<0.05, **p<0.01, ***p<0.001.
25
20
aPD-1 10mg/kg b.i.w., i.p.
IHC (images 20x) of CD4, CD8, CD335, FOXP3, and neutrophils (Ly6G/C) was
used to label helper T-cells, cytotoxic T cells, NK, Treg, and neutrophil cells. All IHC
assays were run with BondRX Autostainer (Leica) and stained on 4µm FFPE sections of A20 without treatment. IF (image 40x) of CD4 (red) and FOXP3 (green)
was stained on frozen sections of the A20 model to label Treg cells (run on Bond
RX). DAPI (blue) is used to label the nucleus.
aCTLA-4 10mg/kg b.i.w., i.p.
30
*
***
***
***
***
15
10
***
5
*
*
***
0
CD4
CD8
CD335
FOXP3
Neutrophil
CD4 FOXP3 DAPI
XP
3+
+
C
D
4+
FO
+
+
+
Tumor Infiltrating Immune Cells
(% in CD45+ Population)
PBS b.i.w., i.p.
Figure 13: A20 Tumor T-Cell Infiltration
p Value vs
Control
CD45+
CD3+
CD3+
CD4+
CD3+
CD8+
CD4+FOXP3+
NK
MDSC
Macrophage
Anti-PD-1 10mg/kg
0.082
<0.001
<0.001
<0.001
0.145
0.506
0.056
0.343
Anti-CTLA-4
10mg/kg
0.179
<0.001
<0.001
0.046
<0.001
0.758
0.017
0.028-
Standard of Care and Experimental Treatment Data also Available
A range of SoC agents, experimental treatments, and combination chemotherapies have been trialed with our syngeneic models (results shown
in Table 2).
Table 2: Syngeneic Model Standard of Care and Experimental Treatment Data
Day: days post-tumor inoculation.
Cancer Type
Syngeneic Model
Treatment
T/C (%)
p Value
Breast
4T1
Paclitaxel
Day 27: 75
0.042
Colon
CT-26
VEGF-TRAP
Day 15: 50
0.007
Cisplatin
Day 20: 52
0.002
Oxaliplatin
Day 23: 50
<0.01
Doxorubicin
Day 21: 23
<0.001
Sorafenib
Day 28: 52
0.047
Liver
H22
Lymphoma
A20
Cyclophosphamide
Day 20: 6.4
<0.001
Melanoma
B16-BL6
Cisplatin
Day 35: 43
0.016
Melanoma
B16-F10
Cisplatin
Day 28: 30
0.006
Pancreatic
Pan02
Gemcitabine
Day 21: 58
<0.001
Gemcitabine + cisplatin
Day 21: 40
<0.001
Gemcitabine + paclitaxel
Day 45: 33
<0.001
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Syngeneic Models Factsheet
Fast-Track the In Vivo Screening of Immunotherapy Compounds
Full characterization including immunoprofiling, NGS, and checkpoint inhibitor benchmarking allows rapid selection of appropriate
models for client studies. Immunomodulatory effects of novel
agents can be evaluated through assessment of immunotherapy
induced T cell infiltration, validated for a range of models. Our
models are also available for a wide variety of agent assessment
from checkpoint inhibitors to other immnunotherapeutics including
bacterial, viral, and vaccination research.
For immunotherapeutic agents, in vitro screening is not the
optimum approach for evaluating PD effect and/or efficacy across
multiple cancer types. However, as an alternative, large-scale,
parallel, in vivo screening of syngeneic models can provide a cost
effective approach.
CrownBio are therefore utilizing our syngeneic platform to offer a
unique large scale MuScreen to fast track immunotherapy treatment
strategies, the first platform of its type. MuScreen can be used for
both single agent and combination studies, reducing variability and
improving screening efficiency. We provide a syngeneic efficacy
screening panel and tumor microarrays to fit your research needs.
For further information please consult the MuScreen FactSheet
available from the CrownBio website: www.crownbio.com/
publications/factsheets/.
Conclusions
Immunotherapy research and agents such as anti-PD-1 antibodies
are showing considerable success in oncology; providing both
patient benefits and commercial success for the pharmaceutical
industry. However, progress in the field is hindered through a lack of
experimental immunotherapy models featuring a fully competent
immune system.
Syngeneic models (allografts derived from immortalized mouse
cancer cell lines, which originated from the same inbred strain of
mice) are a simple way to evaluate novel immunotherapy treatments through eliciting an immune response, in fully immunocompetent mice.
CrownBio has validated a large panel of syngeneic models, covering
a variety of cancer types, with a commitment to further extend this
model selection. Alongside subcutaneous models, bioluminescent
imaging of orthotopic and metastatic tumous allows more clinically
relevant stromal interactions to be modeled and investigated.
Contact Sales
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As immunotherapies are combined with chemotherapy and targeted agents, in an effort to extend patient survival, CrownBio is also
utilizing its wide ranging Syngeneic Panel to interrogate different
combinations including with inducers of ICD and can offer a large
scale MuScreen to fast-track strategies.
References
Zhang L, Zhang J, Guo S et al. RNAseq and immune profiling analysis of syngeneic mouse
models treated with immune checkpoint inhibitors enable biomarker discovery and model
selection for cancer immunotherapy. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA.
Philadelphia (PA): AACR; Molecular Cancer Therapeutics 2015;14(12 Suppl 2): Abstract nr A6.
2
Zhang L, Zhang J, Guo S et al. RNAseq and FACS profiling of syngeneic mouse models treated
with immune checkpoint inhibitors enable biomarker discovery and model selection for cancer immunotherapy [abstract]. In: Proceedings of the 107th Annual Meeting of the American
Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR;
Cancer Research 2016;76(14 Suppl): Abstract nr5177.
3
Mckenzie A, Kumari R, Shi Q et al. Immune competent syngeneic models demonstrate
additive effects of combination strategies using checkpoint immunotherapy and inducers of
immunogenic cell death (ICD). [abstract]. In: Proceedings of the 107th Annual Meeting of the
American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia
(PA): AACR; Cancer Research 2016;76(14 Suppl): Abstract nr 3994.
4
Kato Maves Y, Izadi H, Talaoc EC et al. Characterizing the effect of immune checkpoint
inhibitors on syngeneic tumor models through gut microbiome sequencing and immunophenotyping [abstract].. In: Proceedings of the 28th EORTC-NCI-AACR Symposium: Molecular
Targets and Cancer Therapeutics; 2016 Nov 29 – Dec 02; Munich, Germany: European Journal
of Cancer 2016;69: S111.
1
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