Authors: J.R. Mansfield (1), C.M. van der Loos (2), L.S. Nelson (3), C. Rose (3), H.E. Sandison (3), S. Usher (3), J.A. Radford (3), K. M. Linton (3) and R.J. Byers (3). Affiliations: 1 - PerkinElmer, Hopkinton, MA 2 - Academic Medical Center, Amsterdam, Netherlands 3 - University of Manchester, UK For further information on the Microscopy Imaging Systems and Software (PerkinElmer) presented in this poster, please visit http://bit.ly/15hJz6D

1. Phenotyping TILs in situ: Automated Enumeration of Intra- and Extra-Follicular
FOXP3+ Regulatory T Cells in Follicular Lymphoma
J.R. Mansfield,1 C.M. van der Loos,2 , L.S. Nelson,3 C. Rose,3 H.E. Sandison,3 S. Usher,3 J.A. Radford,3 K. M. Linton,3 R.J. Byers3
1) PerkinElmer, Hopkinton, MA; 2) Academic Medical Center, Amsterdam, Netherlands; 3) University of Manchester, UK
Summary Automated tissue and cellular segmentation Clinical correlation of results
Outcome Outcome Outcome
In many cancers, tumor-infiltrating lymphocytes (TILs) indicate levels of tumor CD3 positivity, identifying T-cells, was
immunogenicity and are a strong predictor of survival. In particular, increased levels of
Sample 1 Sample 2 used to identify CD3 rich and poor
100
FOXP3 Tregs in CD3 poor areas
100 100
FOXP3 Tregs in CD3 poor areas FOXP3 Tregs in CD3 poor areas
regulatory T cells (Tregs) are associated with poorer prognosis in some cancers. An areas, approximating to extra-follicular 90 less than 25% centile less than median 90 less than 75% centile
=/> 25% centile =/> median =/> 75% centile
understanding of the phenotype and spatial distribution of TILs in situ within tumor regions (green) and intra-follicular (pink) 80 80 80
Survival probability (%)
Survival probability (%)
Survival probability (%)
would be advantageous. However, visual TIL assessment cannot easily determine the type areas, respectively. Thresholding of
70
70
of lymphocyte in situ and multimarker quantitation is difficult with standard methods. Here CD3 (membrane) and FOXP3
P=0.04 60
P=0.00
we present a multi-marker, computer-aided event-counting method for determining the (nuclear) was used to identify double 60
31 36 60
phenotypes of lymphocytes in follicular lymphoma sections using a multispectral imaging FOXP3+/CD3+ Treg cells (shown as 50
50
(MSI) and automated tissue segmentation and counting approach. A tissue microarray yellow cells), FOXP3-/CD3+ cells
40 40
P=0.017
containing follicular lymphoma cores from 70 patients was stained for CD3, FOXP3 and (green) and other cells (blue) in both 40
hematoxylin, of which 40 cores were informative for both triple staining and clinical follow- compartments. 30 3
20 30
up. Each core was imaged using MSI and the individual staining of each marker separated 20
from each other using spectral unmixing. The images were analyzed using software which 20
10
had been trained to recognize the follicular areas based on the tissue morphology, 0 50 100 150 200 0 10
specifically based on CD3 rich (extra-follicular) and poor (intra-follicular) areas. The Sample 1 Sample 2 Time
Outcome
0 50 100
Outcome
150 200 0 50 100
Outcome
150 200
FOXP3 status of each CD3+ TIL was then determined and the number of each Treg Time Time
100 100 100
(FOXP3+/CD3+) counted for both the intra- and extra-follicular tissue compartments. FOXP3 Tregs in CD3 rich areas FOXP3 Tregs in CD3 rich areas FOXP3 Tregs in CD3 rich areas
Results indicate that machine-learning software can be trained to accurately recognize less than 25% centile less than median 90 less than 75% centile
=/> than 25% centile =/> than median =/> than 75% centile
follicular and non-follicular regions within each core, in this instance based on abundance 80 80 80
Survival probability (%)
Survival probability (%)
Survival probability (%)
of CD3 cells. MSI enabled the accurate quantitation of two immunostains in the sample
70
without crosstalk. The number of Tregs were determined for each core and used in Kaplan- 60
Meier survival analysis, which demonstrated association of FOXP3+/CD3+ Tregs with
60
P=0.21 60
favourable outcome in both the intra- and extra-follicular areas. Understanding the number 79 50
40
and location (intra- and extra-follicular) of Tregs is an assay with potentially important 40
40
clinical prognostic implications. Thus study shows that an automated method for counting P=0.03
P=0.003
Tregs can be developed for follicular lymphoma. This multimarker phenotyping and 20
30
43
counting approach shows the potential for broad applicability in the enumeration of a wide
20
4
20
range of specifically phenotyped TILs in situ in many solid tumors.
0 10
0
0 50 100 150 200 0 50 100 150 200
0 50 100 150 200
Time Time
Time
Sample 1 Sample 2
Extra-follicular cells:1473 Extra-follicular cells: 1917
53 samples from 40 patients were automatically analyzed using this methodology and the number of FOXP3+/CD3+ Treg cells in each determined, in both T-cell (CD3+) rich
Multispectral imaging technology Morphologic and cellular segmentation CD3+/FOXP3-: 13.9% CD3+/FOXP3-: 19.66% and poor areas. The number of Tregs cells were used in Kaplan-Meier survival analysis, demonstrating association of higher numbers of Tregs with favourable outcome in
CD3+/FOXP3+: 12.3% CD3+/FOXP3+: 0.66%
Spectrum from Survival: 171+ months Survival: 54 months
both T-cell rich (extra-follicular) and poor (intra-follicular) areas (data shown with data split at 25th percentile, median & 75th percentiles for CD3+/FOXP3+ Treg score). This
• Images at different
nucleus with both
hematoxylin and
Breast cancer ER/PR meant patients were divided into groups determined by their Treg numbers using these three statistics as a threshold; . Kaplan-Meier demonstrated that patients with Treg
DAB
wavelengths
co-expression assay numbers in the top 75%, 50% and 25% all had significant survival advantages over those with lower numbers when divided into two groups based on these proportions
• Assemble the images
into a data “cube”
• Spectrum at every (x,y)
pixel RGB representation Multispectral imaging of triplex-
Conclusions
of spectral cube
stained follicular lymphoma
Spectrum from Spectrum from With cancer mask
• Multispectral imaging enabled the quantitation of two immunostains (CD3
Nuance® and Vectra™
membrane with
just red stain
stroma with just
hematoxylin
RGB representation of multispectral dataset & FOXP3) in intra- and extra-follicular compartments in follicular
Multispectral Imaging
FOXP3 lymphoma
RGB Representation of Spectral Cube
Systems
With cancer mask and
• FOXP3+ Tregs were automatically counted and used in Kaplan-Meier
nuclear segmentation
survival analysis, demonstrating association with good outcome
Unmixed DAB
• Automated multiplexed tissue cytometry analyses are feasible for routine
Component 1) Automated user-trained
morphologic segmentation
clinical studies and work with many multiplexed IHC staining
Spectra of pure chromogens
using inForm™ Tissue Finder
collected from single- stained
sections
Unmixed Red
Component Once unmixed, methodologies.
• The enumeration of FOXP3 +’ve T cells in these clinical samples was
Unmixed Hematoxylin stains can be 2) Cellular segmentation
Component Red = cancer mask
measured (nuclear, cytoplasmic or
CD3
Green = cancer nuclei
accurately. membrane)
Blue = background
effective and easy to perform.
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