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Introduction While patients with advanced urothelial bladder cancer (UBC) and non-small cell lung cancer (NSCLC) have shown significantly improved outcomes to anti-PD-L1 therapies, PD-L1 IHC alone does not predict all patients that may benefit. A further understanding of the tumor microenvironment may improve the prediction of patients who will respond to this class of treatment. To this end, we characterized the tumor microenvironment for PD-L1, CD3, CD8, CD68 and FoxP3 in a cohort of 44 advanced UBC and 43 NSCLC samples using a robust and reproducible automated 5-plex immune-fluorescence (IF) IHC assay and whole slide image (WSI) analysis. Materials & Methods All biomarkers were assessed via fully automated 5-plex IF IHC staining (Fig. 1) and analyzed via automated WSI analysis. We classified the stained cells into different phenotypes and generated a heat map overview of their distribution in addition to a quantitative analysis of their spatial relationships. Fig. 1: Automated 5-Plex Fluorescence IHC with Sequential Detection Cycle 1 Cycle 2 Cycle 3 Cycle 4 Cycle 5
The staining was automated on BenchMark ULTRA automated slide stainer with total run time of ~10 hours for up to 30 slides.
Whole Slide Imaging Workflow
Quantitative Image Analysis of PD-L1, CD8, CD3, CD68 and FoxP3 Protein Expression in Lung and Bladder Cancer
Specimens by Fully Automated Multiplex Fluorescence Immunohistochemistry
www.roche.com www.ventana.com © 2016 Ventana Medical Systems, Inc., the BENCHMARK logo is the trademark of Roche. All other trademarks are the property of their respective owners.
CD3
DAPI PDL1 CD68 FoxP3 CD8 CD3
Wenjun Zhang1, Mehrnoush Khojasteh1a, Joerg Bredno1a, Antony Hubbard1, Nick Cummins1, John Hurley1, Liping Zhang1, Ehab Elgabry1, Xiaoling Xia1, Dustin Harshman1, Frank Ventura1, Jorge Lozano1, Bill Day1, Marcin Kowanetz2, Sanjeev Mariathasan2, Dustin Smith2, J.
Andrew Williams2, Lidija Pestic-Dragovich1, Larry E. Morrison1, Lei Tang1 1Ventana Medical Systems, Inc., Tucson, AZ; 1a Ventana Medical Systems, Inc., Mountain View, CA; 2Genentech, Inc., South San Francisco, CA
Spatial Characterization of Tumor Microenvironment
IMS20136, VMAS1136AH, VT0000123662
Conclusion A cohort of archived lung and bladder cancer specimens was evaluated
for PD-L1, CD3, CD8, FoxP3 and CD68 using a novel, fully automated
fluorescent 5-Plex IHC assay and whole slide digital image analysis.
We observed a wide range of TIL densities in the tumor (107-2672
cells/mm2 for lung and 123-2250 cells/mm2 for bladder), and peritumor
(221-3731 cells/mm2 for lung and 403-1919 cells/mm2 for bladder)
regions. In both lung and bladder samples, the tumor regions had higher
PD-L1+ TIL densities than peritumor regions.
This technology incorporating fully automated fluorescent multiplex IHC
together with automated whole slide image analysis is extendable to
different panels of biomarkers. This novel approach represents a more
holistic method for cancer characterization including the tumor
microenvironment and may lead to a better understanding of patient
responses to cancer immune monotherapies and combinations.
WSI of 5-plex IF IHC slides were acquired on a
Zeiss Axio Scan.Z1 in 6 acquisition channels
corresponding to the six fluorophores (DAPI,
DCC/CD3, FAM/PD-L1, R6G/CD8, Red610/CD68,
and Cy5/FoxP3).
For each sample, adjacent sections were stained
with H&E and WSIs were acquired on a
VENTANA iScan HT scanner.
Using the Roche research software platform for
digital pathology image management and
visualization, two pathologists identified and
delineated tumor and peritumor regions on the
H&E images.
The annotated regions were automatically
transferred onto the IF WSIs using deformable
image registration. The annotations were then
used to define distinct tumor and peritumor
regions on each WSI. The peritumor region is
defined as a region that includes all tissue from
0.5 mm inside to 1mm outside of the tumor
delineation. The tumor region is defined as all
other tissue delineated as tumor.
An automated image analysis algorithm creates a
cell-by-cell read-out from image data at high
resolution. Following spectral unmixing and auto-
fluorescence and red blood cell suppression, a set
of image channels representing the presence of
DAPI, CD3, CD8, FoxP3, CD68, and PD-L1 were
used for analysis.
Given the model panel presented here, the
analysis algorithm identified 9 different
phenotypes of cells on WSIs:
1 and 2) CD3+, CD8-, FoxP3-, and PD-L1- or PD-
L1+
3 and 4) CD3+, CD8+, and PD-L1- or PD-L1+
5 and 6) CD3+, FoxP3+, and PD-L- or PD-L1+
7 and 8) CD68+, and PD-L1- or PD-L1+
9) PD-L1+ tumor
Fig. 3A: WSI Heat Maps of a NSCLC Case (Red circled region: Tumor; Green circled region: Peritumor)
Fig. 2A: WSI Heat Maps of a UBC Case (Red circled region: Tumor; Green circled region: Peritumor)
CD3+, FoxP3+, PD-L1-
CD68+, PD-L1-
CD3+, FoxP3+, PD-L1+
CD68+, PD-L1+
PD-L1+ Tumor
CD3+, CD8-, FoxP3-, PD-L1-
CD3+, CD8-, FoxP3-, PD-L1+
CD3+, CD8+, PD-L1-
CD3+, CD8+, PD-L1+
Map of phenotypes surfaces Map of phenotypes point cloud
Map of phenotypes surfaces Map of cell phenotypes point cloud
Automated transfer of region annotations from
H&E to IF WSI using Roche digital pathology
image management and visualization platform
Descriptive Features of Immune Status in Tumor Microenvironment
3000/m
m2
CD3
3000/m
m2
CD8
1000/m
m2
FoxP3
3000/m
m2
CD68
3000/m
m2
PD-L1
300
0/m
m2
300
0/m
m2
100
0/m
m2
300
0/m
m2
300
0/m
m2
PD-L1 CD68 CD3 CD8 FoxP3
Composed 6-channel image
Composed 6-channel image
Fig. 4: Example UBC and NSCLC cases illustrated in Figs. 2 and 3.
Tumor Type
TIL density
(#/mm2)
PD-L1+/TIL
density
(#/mm2)
CD3+All
density
(#/mm2)
CD8
density
(#/mm2)
CD68
density
(#/mm2)
FoxP3
density
(#/mm2)
Mean Distance
CD8 to closest
PD-L1+ TC (um)
Mean PD-L1+ TC
count in 10um
radius of CD8
Mean PD-L1+ TC
count in 30um
radius of CD8
UBC tumor area 872.48 177.79 609.02 495.22 350.60 7.26 52.20 0.18 1.38
UBC peritumor 1959.00 0.10 1162.00 904.00 797.00 7.15 114.35 0.15 1.25
NSCLC tumor area 2672.21 1122.79 2175.32 676.76 1264.36 90.71 35.93 0.12 1.38
NSCLC peritumor 2206.84 232.33 1453.32 462.41 753.52 84.88 60.88 0.07 0.82
Figs. 5-8: 44 UBC and 43 NSCLC cases
UBC
Peritumor areaTumor area
600
500
400
300
200
100
0
Mean
Dis
tan
ce
(um
)
CD8 Mean Distance to Closest PD-L1+ TC
NSCLC
Peritumor areaTumor area
800
700
600
500
400
300
200
100
0
Mean
Dis
tan
ce (
um
)
CD8 Mean Distance to Closest PD-L1+ TC
UBC
30um
rad
ius
10um
rad
ius
30um
rad
ius
10um
rad
ius
5
4
3
2
1
0
-1
Cell c
ou
nt
Mean PD-L1+ TC Count in the Proximity of CD8
Tumor area Peritumor area
NSCLC
30um
rad
ius
10um
rad
ius
30um
rad
ius
10um
rad
ius
5
4
3
2
1
0
Cell c
ou
nt
Mean PD-L1+ TC Count in the Proximity of CD8
Tumor area Peritumor area
UBC
Peritumor areaTumor area
140
120
100
80
60
40
20
0
Rati
o
CD8/FoxP3 Ratio
NSCLC
Peritumor areaTumor area
60
50
40
30
20
10
0
Rati
o
CD8/FoxP3 Ratio
UBC
* CD3 All: CD3+ cells including CD8+ and FoxP3+
*
Results
CD8
Rb anti-CD8
(SP239)
HRP
TSA-R6G CD3
Rb anti-CD3
(SP162)
Fox
P3
Rb anti-FoxP3
(SP97)
CD68
Rb anti-CD68
(SP251)
PD-L1
Rb anti-PDL1
(SP142)
HD 1°/2°Ab complex HD 1°/2°Ab complex
Goat anti-
rabbit-HRP Goat anti-
rabbit-HRP
HRP Goat anti-
rabbit-HRP
HRP Goat anti-
rabbit-HRP
HRP Goat anti-
rabbit-HRP
HRP
TSA-DCC
TSA-
Red610 TSA-Cy5 TSA-FAM
HD 1°/2°Ab complex HD 1°/2°Ab complex
Red circled
region:
Tumor
Green
circled
region:
Peritumor
Yellow
circled
region:
Excluded
necrotic
region
H&E IF
Heat Map
After the automated WSIs, the coordinates of all detected cells and their
assigned phenotypes were available for post-analysis. The following spatial
features were selected for this presentation:
• Area density of cell phenotypes (demonstrated as heat-maps below) in
tumor and peritumor regions
• Area density of tumor infiltrated lymphocytes (TIL, defined as CD3+,
CD8+, FoxP3+, and CD68+) and PD-L1+ TIL
• Average distance of CD8+ T cells to the closest PD-L1+ tumor cells (TC)
• Average # of PD-L1+ TC within 10 and 30um from CD8+ T cells
Blue region: Tumor
Yellow region: Peritumor
Red dots: CD8+ T cells
Green dots: PD-L1+ tumor cells
Circles: 10 or 30-um neighborhood of the center CD8+ T cells
Arrows: distance of the CD8+ T cells to the closest PD-L1+ tumor cell.
Fig. 2B: Example UBC FOV image (from the red rectangular area shown in the PD-L1 heat map) to show the WSI analysis process
Fig. 3B: Example NSCLC FOV image (from the red rectangular area shown in the PD-L1 heat map) to show the WSI analysis process
Fig. 5
Fig. 6
Fig. 7
Fig. 8
ASCO Abstract No: 11590; Board #287
