1. Quantitative Assessment of Tissue-based IHC Biomarkers
25 March 2017
Quantitative Assessment of Tissue-based IHC Biomarkers
Next Generation Pharmaceutical Summit
David Young Apr 09
New Targets Committee

2. Digital Pathology
25 March 2017
Digital Pathology – Research and Clinical Possibilities
Quantitative Digital pathology
IHC – Traditional evaluation vs Image analysis
Tools not limited to pathologists
New Targets Committee

3. Digital Pathology – Where Are We Headed?
25 March 2017
Digital Pathology – Where Are We Headed?
New Targets Committee

4. Digital Pathology
25 March 2017
Digital Pathology – Research and Clinical Possibilities
Archival of pathology specimens
Diagnosis
Digital slide conferencing
Consultation
Help from Development Teams
putting the power in the hands of the people who know it best
New Targets Committee

5. Quantitative Digital Pathology - The Next Step
25 March 2017
Quantitative Digital Pathology - The Next Step
New Targets Committee

6. Quantitative Digital Pathology
25 March 2017
Pathologist opinions
Good enough for government work, or
Close, but no cigar
X number of pathologists = Y number of results
Diagnoses
IHC analysis
subjective; based on familiarity of tissue and experience
New Targets Committee

7. IHC Assessment of Tissue-based Biomarkers
25 March 2017
IHC Assessment of Tissue-based Biomarkers
New Targets Committee

8. Immunohistochemistry Analyses and Quantitative Digital Pathology
25 March 2017
Not an exact science
Basis of many aspects of drug development and drug selection
New Targets Committee

9. Biomarker Scoring Consensus
25 March 2017
Biomarker Scoring Consensus
Clark (2006) – ‘there is no consensus in the literature about how to summarize these scoring assessments into a single determination of EGFR protein expression status as EGFR positive or EGFR negative.’
‘Evaluation of the clinical significance of EGFR expression by IHC has been complicated by the use of different antibodies, different scoring systems, and different clinical endpoints.’
Clark, et al: J Thorac Oncol 2006
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10. Importance of Standardized Scoring
25 March 2017
Prevalence and tumor surveillance
Prognostic factors
Predictive factors
Comparing study results from a recognized baseline of analysis
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11. IHC Scoring Concordance – Pathologists Variability
25 March 2017
Concordance
Total scoring = 78%
Cut point <100 = 92%
Concordance
Total scoring = 75%
Cut point <100 = 100%
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12. Pathologist Variation
25 March 2017
Legend:
Red – Pathologist 1
Blue – Pathologist 2
Pathologist 1 Scores:
Y = 0.96X
R = 0.987
Pathologist 2 Scores:
Y = 0.97X -2.72
R = 0.974
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13. Image Analysis – Lessens Subjectivity of Scoring
25 March 2017
Quantify:
Size (area)
Positive cells
Negative cells
Intensity levels
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14. Tissue-based Biomarkers – Case Study
25 March 2017
E-Cadherin
Marker of epithelial phenotype
Associated with cell-to-cell adhesion
Membrane protein
Vimentin
Marker of mesenchymal phenotype
Associated with cellular skeleton
Cytoplasmic protein
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15. Experimental Xenograft model
25 March 2017
H&E
E-cad
Vim
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16. Heterogeneity in Tumor Tissue – E-cad
25 March 2017
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17. Heterogeneity in Tumor Tissue – Vim
25 March 2017
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18. Traditional IHC Score (H-Score)
25 March 2017
Traditional IHC Score (H-Score) 1%
10%
30%
75%
100%
Proportion
Score (PS)
0 – 100%
Immunostaining was scored using a previously established scoring system developed by Dr. Craig Allred in our group. The proportion of stained tumor cells was estimated on a scale of 0 to 5: 0 represents no staining; 1 is less than 1/100 cells; 2 is 1/100 to 1/10 cells; 3 is 1/10 to 1/3; 4 is 1/3 to 2/3; and 5 indicates staining in more than 2/3 of the tumor cells.
Staining intensity was rated as negative, weak, intermediate, or strong.
A total IHC score was calculated by adding the proportion score and the intensity score. The range of values is 0, and 2 to 8.
Intensity
Score (IS)
0 = negative
1 = weak
2 = intermed
3 = strong
Score range: 0-300
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19. Factors Affecting IHC Analysis – Not Just the Pathologist
25 March 2017
Tumor acquisition (pre-analytical factors)
Tumor size
Tumor type (Tumor tissue and host response)
Antibodies
Processing factors
Individual variation in evaluation
New Targets Committee

20. Cell Culture - E-cadherin
25 March 2017
Algorithm - Membrane v9
Default
Min Nuclear Size (um^2) 10 85
Background Intensity Threshold
240
Weak (1+) Intensity Threshold
200
Moderate (2+) Intensity Threshold
170
Strong (3+) Intensity Threshold
105
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21. NSCLC Criteria setup
25 March 2017
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22. Cell Culture - Vimentin
25 March 2017
Algorithm - Color Deconvolution v9
Default
Weak Postive Threshold
220
180
Medium Postive Threshold
175
120
Strong Positive Threshold
100 60
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23. Xenograft model - E-cadherin
25 March 2017
Entire Specimen
IHC
Test box
(3+) Percent Cells
71.83 50
65.67
(2+) Percent Cells
9.61 40
8.17
(1+) Percent Cells
18.53 10
26.16
(0+) Percent Cells
0.03
0.00
SCORE
253.24
240
239.51
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24. Xenograft model - Vimentin
25 March 2017
Entire Specimen
IHC
Test box
(3+) Percent
41.28 25
24.70
(2+) Percent
46.02 50
56.80
(1+) Percent 20
17.51
(0+) Percent
0.26 5
1.00
SCORE
228.32
195
205.21
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25. NSCLC – example 1
25 March 2017
New Targets Committee

26. NSCLC – example 1 (higher mag)
25 March 2017
E-Cad
Vim
Aperio
IHC
(3+) Percent Cells
41.28 25
(3+) Percent
1.10 1
(2+) Percent Cells
46.02 50
(2+) Percent
0.96
(1+) Percent Cells 20
(1+) Percent
3.03 3
(0+) Percent Cells
0.26 5
(0+) Percent
94.90 95
SCORE
228.32
195
8.25 8
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27. NSCLC – example 2 25 March 2017 New Targets Committee E-Cad Vim Aperio
IHC
(3+) Percent cells
61.77 35
(3+) Percent
6.93
(2+) Percent cells
17.73 60
(2+) Percent
30.51 10
(1+) Percent cells
20.00 5
(1+) Percent
43.15 30
(0+) Percent cells
0.50
(0+) Percent
19.41
SCORE
240.77
230
124.96 50
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28. NSCLC – example 3 25 March 2017 New Targets Committee E-Cad Vim Aperio
IHC
(3+) Percent Cells
65.28 15
(3+) Percent
3.80
(2+) Percent Cells
9.88
(2+) Percent
2.21 10
(1+) Percent Cells
24.80 50
(1+) Percent
6.05
(0+) Percent Cells
0.04 20
(0+) Percent
87.94 75
SCORE
240.40
125
21.87 35
New Targets Committee

29. NSCLC – example 4 (Whole tumor; E-Cadherin)
25 March 2017
E-Cad
Aperio
IHC
(3+) Percent Cells
68.60 50
(2+) Percent Cells
6.25 25
(1+) Percent Cells
24.54 20
(0+) Percent Cells
0.60 5
SCORE
242.84
220
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30. NSCLC – example 4 (Vimentin)
25 March 2017
Vim
Aperio
IHC
(3+) Percent
0.44
(2+) Percent
0.96
(1+) Percent
2.50
(0+) Percent
96.11
100
SCORE
5.74
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31. Pancreas – Xenograft 1 H&E E-cad Vim 25 March 2017
New Targets Committee

32. Pancreas – Xenograft 1 25 March 2017 New Targets Committee E-Cad Vim
Aperio
IHC
(3+) Percent Cells
71.59 50
(3+) Percent
0.40
(2+) Percent Cells
7.48 40
(2+) Percent
1.26
(1+) Percent Cells
20.93 10
(1+) Percent
24.36
(0+) Percent Cells
(0+) Percent
73.98
100
SCORE
250.66
240
28.08
New Targets Committee

33. Pancreas – Xenograft 2 25 March 2017 New Targets Committee E-Cad Vim
Aperio box
Aperio whole
IHC
(3+) Percent Cells
0.76
(3+) Percent
50.82
51.80 70
(2+) Percent Cells
10.65
(2+) Percent
34.35
34.72 30
(1+) Percent Cells
22.22
49.27
(1+) Percent
13.26
12.42
(0+) Percent Cells
77.78
39.32
100
(0+) Percent
1.58
1.06
SCORE
72.85
234.42
237.26
270
New Targets Committee

34. Summary – What have we learned so far?
25 March 2017
Selection of site for IHC evaluation is important; may or may not be reflective of whole tumor
Tumor heterogeneity affects tissue-based biomarker assessment and analysis
IA correlates well with traditional IHC scoring methods.
Validation removes pathologists scoring variability
‘Tweaking’ of algorithms required prior to universal deployment
New Targets Committee

35. Putting the Power in the Hands of the People
25 March 2017
Putting the Power in the Hands of the People
New Targets Committee

36. Investigator Asks the Questions
25 March 2017
New Targets Committee

37. 25 March 2017
Thank you!
New Targets Committee