Practical Approaches to Tumor
Xenograft Analysis
Frank Voelker, Flagship Biosciences LLC
Trevor Johnson, Flagship Biosciences LLC
Veronica Traviglone, Infinity Pharmaceuticals
Igor Deyneko, Infinity Pharmaceuticals
Outline
Introduction
Anatomy of a Xenograft
Defining the Approach to the Analysis
Analytical Strategies
Examples of Cases
Presenting FACTS for Target Tissue Analysis
www.flagshipbio.com
General Anatomy of a Xenograft
CD-31 Stain for Microvessels
www.flagshipbio.com
Chronic Inflammation and Peripheral Adipose Tissue
Adjacent tissue frequently contains host responses such as inflammation,
adipose tissue or adnexal structures that need to be excluded from the analysis
www.flagshipbio.com
Extensive Necrosis and Degeneration
CD31 Immunostain
Necrosis and neoplastic cells in various stages of
degeneration are common features of a xenograft.
www.flagshipbio.com
Host Response of Vascular Ingrowth Demonstrated
with CD31 Immunostain
Even the smallest microvessels may be enclosed in adventitial
tissue as an extension of stromal ingrowths
www.flagshipbio.com
Compare H&E and IHC Stains
H&E
www.flagshipbio.com
CD31
Compare Corresponding Areas of H&E and CD31 Stains
H&E
CD31
Compare microscopic
characteristics of an
H&E- stained section
with comparable
regions of an IHC
CD31-stained section
This will provide
valuable perspective
regarding IHC target
tissue staining and will
allow more accurate
identification of tissue
classes.
www.flagshipbio.com
Significant Xenograft Tissue Components
Neoplastic Cells
Tissue Biomarker
Connective Tissue Stroma
Necrosis and Degeneration
Cystic or Secretory Vacuoles
 Artifactual Space
Which of these do you want to include in
your analysis?
www.flagshipbio.com
Some Examples of Analytical Endpoints
Neoplastic Cell Area
Total Xenograft Area
A function of neoplastic cell
abundance versus necrosis and/or
stromal prominence
Marker Area or Score
Neoplastic Cell Area
Immunohistochemistry expression
of marker metabolism within
neoplastic cell population
Number of Neoplastic Nuclei
Neoplastic Cell Area
Targeted Cell Number
Total Xenograft Area
Number of Microvessels
Neoplastic Cell + Stromal Area
www.flagshipbio.com
An indication of mean neoplastic
cell size
Cell frequency within measured
area
Microvessel analysis
What aspects of a marker determine treatment effect?
Staining variation in tumors or
other tissues frequently raises
the question of whether to
measure either percent area or
average intensity of an
immunostain.
In some cases, a solution to
this problem is to measure
score as an output convention
encompassing both percent
area and stain intensity.
(Nwp/Ntotal)x(100) + Np/Ntotal)x(200) + Nsp/Ntotal)x(300) = “H Score”
(For a maximum of 300)
www.flagshipbio.com
Manual Use of Positive and Negative Pen Tools
Similar IHC staining of fibronectin and
secretion droplets in this xenograft
tumor with subsequent poor
differentiation by the Genie™ classifier
required the use of the negative pen
tool to assist in quantitating fibronectin
using the IHC deconvolution algorithm.
12
www.flagshipbio.com
Manual Use of Positive and Negative Pen Tools
Use of a 21UX Cintiq
Wacom drawing board
facilitates the use of
positive and negative
pen tools in manually
delineating critical
features of the
xenograft.
www.flagshipbio.com
Using Genie™ to Segregate Neoplasm from Nontarget
Tissue in a Xenograft Stained for Phospho-Histone 3
Central regions of the xenograft
contain an interdigitating pattern of
necrosis and connective tissue
trabeculae too complex for manual
exclusion .
Accurate segregation of
neoplasm (green) from
necrosis and connective
tissue (red) was
accomplished using Genie™
www.flagshipbio.com
The Rationale Behind Histology Feature Recognition
Using software to preprocess an image with the purpose of
segregating target tissue components from nontarget tissue.
Aperio Genie™
Primary Image
Genie Preprocessing
Analytical Algorithm
Analytical Result
Visiopharm
Primary Image
Preprocessing
Feature Recognition
Postprocessing
www.flagshipbio.com
Subsequent analysis yields
accurate data only from the
target tissue component, and
omits erroneous nonspecific
results from nontarget tissue.
Feature recognition is valuable
in xenograft analysis when
target and nontarget regions
are too intricately interwoven
for manual exclusion.
Strategy for Analyzing Successive Samples
Xenograft neoplasms within a study are surprisingly heterogeneous
even though derived from the same source, and it is difficult and
time consuming to derive a common pattern recognition classifier
appropriate for all neoplasms within a study. It is more expeditious
and also yields more accuracy to develop new classifiers as the
analysis progresses.
Progression of analysis through sample series
*
1
2
3
*
4
5
6
7
*
8
9
10
11
12
13
14
15
16
17
18
19
20
Red = 1st Classifier
Blue = 2nd Classifier
Green = 3rd Classifier
* = Points when a new classifier was developed during the analysis
www.flagshipbio.com
Consistent Analysis of Study Samples Using
Genie™
Even though multiple classifiers are constructed for successive samples, the
final analyses of target tissue components will be accurate and comparable if
the same algorithm threshold values are constantly maintained.
Subsequent Uniform Analysis of Segregated Target Tissue for
area/intensity
www.flagshipbio.com
Using Genie™ to Segregate Neoplasm from Nontarget
Tissue in a Xenograft Stained for Phospho-Histone 3
Higher magnification
reveals accurate
separation of target from
nontarget tissue.
The grayed-out nontarget
tissue class consists of a
mixture of connective
tissue trabeculae and
necrotic tumor cells.
www.flagshipbio.com
Assessing Fibronectin in a Xenograft Using
Several Software Programs
Original IHC Image
Assessing the intensity and
quantity of fibronectin as a
marker in xenograft stroma
Aperio Deconvolution Mark-up
Visiopharm Mark-up
www.flagshipbio.com
Assessing Angiogenesis in a Xenograft Using
Several Software Programs
Original CD31-Stained Image
Use of the microvessel analysis
algorithm to assess angiogenesis in
a xenograft neoplasm in a mouse
Aperio Microvessel Algorithm Mark-up
Visiopharm Mark-up
Microvessel analysis provides
important information regarding
potential antineoplastic effects of
pharmaceutical compounds
20
www.flagshipbio.com
Using the Microvessel Analysis Algorithm to Count
Cyclin B1-Positive Target Cells in a Xenograft
Use of the microvessel analysis
algorithm to assess macrophage
populations in mouse xenograft
neoplasms
Threshold algorithm parameters
are modified to accommodate
the smaller size and shape
characteristics of the cells
www.flagshipbio.com
Use of Visiopharm™ Software to Analyze a Marker
Separately in Cytoplasm and Nuclei of a Neoplasm
Discriminating between nuclear and cytoplasmic regions of a neoplasm allows separate
biomarker intensity measurement for both nuclear and cytoplasmic markers (analysis
with Visiopharm software).
www.flagshipbio.com
Distinctive or Special Staining Facilitates
Target Tissue Pattern Recognition
H&E
H&E Classifier
First pass accuracy is
much greater for the
H&E-stained section than
for the hematoxylincounterstained IHC
section
CD31
CD31 Classifier
Current histology pattern
recognition programs
often have difficulty
distinguishing target
tissue profiles because of
low contrast /nonspecific
counterstaining
www.flagshipbio.com
Feature Analysis on Consecutive
Tissue Sections (FACTS)
1. Consecutive
tissue
sectioning
www.flagshipbio.com
2. Automated
feature
recognition
3. Image
and ROI
registration
4. QC and
pathologist
review
Image and ROI Registration
3. Image
and ROI
registration

Register images with <3% Feature Error Across multiple
consecutive slides
– Not a trivial problem given the potential histological and
biological differences between tissue sections and stains

Several registration techniques currently used throughout
CT/MRI, CT/PET, CT radiology, ultrasound, and multispectral
imaging
– Typically elastic, morphing, because of image warping
– Heavy use of image features or fiducials

Type of registration for best performance in FFPE tissue is
heavily dependent on the application
www.flagshipbio.com
Typical Image Registration Process

Feature detection
– Distinctive objects to be aligned

Feature matching
– Finding the association between the distinct objects

Transform model estimation
– The mapping functions used to align the subsequent image to
the reference image
– May be non-elastic (much simpler) or elastic

Image re-sampling and transformation
– Applying the mapping functions where non-integer
coordinates can be correctly interpolated
www.flagshipbio.com
Non-Elastic Image to Image Registration

Perform color deconvolution to focus on a common Stain, typically
Hematoxylin
– Helps reduce potential errors from strongly stained “positive”
features

Use slide features and image intensities to adjust rotation and
translation of selected images or regions
u(x,y) -> v(x,y)
Rotation:
x’ = x•cos(θ) - y•sin(θ)
y’ = x•sin(θ) + y•cos(θ)
Translation:
x -> x’
y -> y’
www.flagshipbio.com
Example of Slide Registration
www.flagshipbio.com
Annotated Feature to Feature Registration

More complex due to biological and histological differences
between serial sections

Usually Elastic to count for these differences
– Important to note that the actual images are never morphed,
just the annotations

Let the application determine the method
Phase Registration:
℮xp(2 ∏ i (u x’ + v y’)) = ƒ(f) ƒ(g) / | ƒ(f) ƒ(g) |
Mutual Information:
MI(X,Y) = H(Y) – H(Y | X) = H(X) – H(Y) – H(X,Y)
where H(X) = Ex(log(P(X))
www.flagshipbio.com
Annotation Feature to Feature Registration
(cont.)
Wavelet Transform:
Decompose image into collection of appropriate wavelet
(Spline, Haar, Etc.)
Filter image along rows and columns (high and low pass)
Find frequency coefficients and apply differential
measurements
www.flagshipbio.com
Example of Feature Registration
www.flagshipbio.com
Acknowledgments
 Dr.
Steven Potts, Flagship Biosciences LLC
 Dr.
David Young, Flagship Biosciences LLC
 Ms.
Charlotte Aagaard Johnson, Visiopharm Inc.
 Mr.
Rob Diller, Flagship Biosciences LLC
 Mr
Erik Hagendorn, Flagship Biosciences LLC
Questions? Email contact: frank@flagshipbio.com
trevor@flagshipbio.com
www.flagshipbio.com