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PRESENTER: Sean T. Glenn
Unique Tumor Immune Microenvironments
Of Potentially PD-L1/TGF-β Trap Responsive Tumors
Sean T. Glenn1,2, Sarabjot Pabla1, Erik Van Roey1, Jonathan Andreas1, BlakeBurgher1, Jeffrey M. Conroy1,2, Mary Nesline1, Antonios Papanicolau-Sengos1, Vincent Giamo1, Felicia L. Lenzo1, Yirong Wang1, Carl Morrison1,2,*
1Omniseq Inc., 700 Ellicott Street, Buffalo, NY2 Center for Personalized Medicine, Roswell Park Comprehensive Cancer Center, Elm Street, Buffalo, NY*[email protected]
700 Ellicott Street | Buffalo NY, 14203
INTRODUCTIONTumors often do not respond to PD-1/PD-L1 axis inhibitors dueto immune escape mechanisms present in the tumormicroenvironment. Bi-functional antibody-basedimmunotherapies that simultaneously target immunecheckpoints and immunosuppressive cells are being developedto slow tumor growth.
Anti-PD-L1/TGF-β trap fusion proteins are one approach beingdeveloped to counter the traditional immune checkpointinhibition via PD-1/PD-L1 axes and simultaneously inhibit thepro-tumor/anti-inflammatory effects of TGF-β. In this study, wenot only describe the tumor immune microenvironment oftumors expressing PD-L1 and TGF-β, but also describe potentialpatient selection strategies based on gene expressionmeasurements of these tumor immune microenvironments inclinical samples.
METHODSRNA-seq was performed for 395 immune transcripts1 on 1323FFPE tumors of diverse histologies. To find true TGF-β highexpressing tumors, TGFb1 gene expression was normalized by atumor inflammatory score (average expression rank of 161inflammation genes derived from a co-expression signature of>1000 tumors spanning 35 histologies). Proportion of PD-L1 IHCpositive, inflamed, tumor mutational burden (TMB) high and cellproliferation2 categories was estimated for TGFb1 highexpressing tumors. Inclusion and exclusion criteria weredeveloped based on PD-L1 and normalized TGFb1 expression..
CONCLUSION• Evaluation of a 1323 patient cohort suggests an immune
phenotype of potentially PD-L1/TGF-β trap responsivetumors exists across multiple histologies.
• PD-L1/TGF-β high tumors have distinct immune profilescompared to PD-L1/TGF-β low tumors.
• A clinical immune gene expression assay described in thisstudy could not only improve patient selection for anti-PD-L1/TGF-β trap treatment, but for other bi-specific fusionprotein-based immunotherapies.
Tumor mutational burden estimated as
number of non-synonymous mutation
per Mb of exonic DNA
TMB
• RNA-seq expression profiling of 395
immune transcripts1
• PD-L1 IHC1
• Cell Proliferation2
• Inflammation
Immune Profiling
FFPE
REFERENCES1. Conroy JM, Pabla S, Glenn ST. Analytical validation of a next
generation sequencing assay to monitor immune responsesin solid tumors. J Mol Diagn. 2018;20:95–109.
2. Pabla S, Conroy JM, et. al. Proliferative potential andresistance to immune checkpoint blockade in lung cancerpatients. J Immunotherapy Cancer. 2019;7(1):27.
Figure 1: Dual extraction of DNA and RNA from FFPE tissue followed by comprehensiveimmune profiling (RNA-Seq), PD-L1 (IHC) and TMB (DNA-Seq).
Figure 3: Unsupervised clustering (Kmeans) of 395 immune transcripts depicting three tumor phenotypes (Inflamed, borderline and non-inflamed), and three gene clusters (Cancer Tests Antigens (CTA), Inflammation, and Other Immune genes).
SITC 2019 – P90
Infl
amm
atio
n N
orm
aliz
ed
TG
FB1
TGFB1PD-L1
TGFB1PD-L1
11% (n=147)
15.12% (n=200) Inclusion
Exclusion
No
rmal
ize
d T
GFb
1 E
xpre
ssio
n
PD-L1 Expression
TGFb1 PD-L1
11% (n=147)
TGFb1 PD-L1
15.12% (n=200)
TGFb1 PD-L1
11.72% (n=155)
Inclusion
Exclusion
Figure 6: PD-L1 expression vs normalized TGFβ1expression showing candidate PD-L1/TGF-β trap responsive tumors. TGFβ1 cutoff ≥1.5 and PD-L1 expression cutoff of<33 (low), 33-66 (moderate) and ≥66 used to derive inclusion and exclusion criteria.
TGFβ1 Cutoff ≥ 1.5
Figure 7: Proportion of inflamed and borderline tumors per PD-L1/TGF-β expression groups.
Figure 8: Proportion of TMB high tumors per PD-L1/TGF-β expression groups.
Figure 5: Frequency of PD-L1+, TMB high, and cell proliferation in TGFb1 high tumors
35%
25%
16%
44%49%
62%
34%
0%
20%
40%
60%
80%
100%
Pro
po
rtio
n o
f TG
Fβh
igh
cas
es
41%
28%
47%
35%
18%
0%
20%
40%
60%
80%
100%
PD-L1 IHC+ TMB High High Prol. Mod. Prol. Poor Prol.
Pro
po
rtio
n in
TG
Fβh
igh
cas
es
Figure 4: TGFb1 high expression prevalence in top 7 histologies of 1323 tumor cohort
Figure 2: Distribution of TGFβ1 compared to immune gene expression distribution of IFNG, LAG3 and TIM3 in 1323 clinical cases.
Selection
Patient selection based on
gene expression
biomarkersThis clinical assay could improve
patient selection for anti-PD-
L1/TGF-β trap treatment, and
potentially other bi-specific fusion
protein-based immunotherapies.
TMB
Tumor Mutational
Burden
High TMB cases were
enriched in potentially PD-
L1/TGF-β trap responsive
tumors.
Immune
Profile
Tumor Immune
Microenvironment
PD-L1/TGF-β high tumors
have distinct immune profiles
compared to PD-L1/TGF-β low
tumors.
Pan-Cancer
This large clinically tested tumor
cohort suggests an immune
phenotype of potentially PD-L1/TGF-β
trap responsive tumors exists across
multiple histologies.
Multiple histologies
TGFb1 High Expression in Multiple Tumor Types Frequency of Immune Oncology Biomarkers in TGFb1 High Tumors
46.9%
9.5%
25.8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
High-High High-Low Low-Low
Pro
po
rtio
n o
f in
flam
ed
/bo
rde
rlin
e t
um
ors
TGFβ & PD-L1 Group
p = 0.0002138
p = 6.39E-15 p = 7.83E-05
40.8%
21.0%25.8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
High-High High-Low Low-Low
Pro
po
rtio
n o
f TM
B H
igh
tu
mo
rs
TGFβ & PD-L1 Group
p = 0.0001p = 0.0001 p = 0.3479
Tum
or
ph
eno
typ
esGenes
