Quantitative Assessment of Tissuebased IHC Biomarkers

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Quantitative Assessment of Tissue-based IHC
Biomarkers

• Pathology Visions
• David Young Sept 09

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Digital Pathology

• Digital Pathology Research and Clinical
  Possibilities
• Quantitative Digital pathology
• IHC Traditional evaluation vs Image analysis
• Tools not limited to pathologists

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Digital Pathology Where Are We Headed?
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Digital Pathology

• 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

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Quantitative Digital Pathology - The Next Step
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Quantitative Digital Pathology

• Pathologist opinions
• X number of pathologists Y number of results
• Diagnoses
• IHC analysis
• subjective based on familiarity of tissue and
  experience

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IHC Scoring Concordance Pathologists
Variability
Concordance Total scoring 78 Cut point lt100
92
Concordance Total scoring 75 Cut point lt100
100
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Pathologist and Assay Variability
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IHC Assessment of Tissue-based Biomarkers
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Immunohistochemistry Analyses and Quantitative
Digital Pathology

• Not an exact science
• Basis of many aspects of drug development and
  drug selection

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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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Importance of Standardized Scoring

• Prevalence and tumor surveillance
• Prognostic factors
• Predictive factors
• Comparing study results from a recognized
  baseline of analysis

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Image Analysis Lessens Subjectivity of Scoring
Quantify Size (area) Positive cells
Negative cells Intensity levels
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Tissue-based Biomarkers Case Study

• 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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Experimental Xenograft model
HE
E-cad
Vim
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Traditional IHC Score (H-Score)
100
30
10
1
75
0
Proportion Score (PS)
0 100

Intensity Score (IS)

1 weak
0 negative
2 intermed
3 strong













Score range 0-300
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Heterogeneity in Tumor Tissue E-cad
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Heterogeneity in Tumor Tissue Vim
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Factors Affecting IHC Analysis Not Just the
Pathologist

• Tumor acquisition (pre-analytical factors)
• Tumor size
• Tumor type (Tumor tissue and host response)
• Antibodies
• Processing factors
• Individual variation in evaluation

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Cell Culture - E-cadherin
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NSCLC Criteria setup
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Cell Culture - Vimentin
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Xenograft model - E-cadherin
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Xenograft model - Vimentin
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NSCLC example 1
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NSCLC example 1 (higher mag)
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NSCLC example 2
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NSCLC Whole tumor E-Cadherin
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Pancreas Xenograft 1
HE
E-cad
Vim
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Pancreas Xenograft 1
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Pancreas Xenograft 2
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Summary What have we learned so far?

• 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

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Putting the Power in the Hands of the People
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Investigator Asks the Questions
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Thank you!