Download www.flcmidatlantic.org

BIOMARKER STUDIES IN CLINICAL TRIALS
Vicki Seyfert-Margolis, PhD
CLINICAL DATA (Ontologies)
MECHANISM
DISCOVERY
• Flow Cytometry
• Autoantibody
• ELISPOT
• Cytokine Measures
• Gene Expression
• SNP/Haplotype
• Proteomics
ITN Transplant Trial Model
ONE YEAR
DAY 0
Start of
Study
SERIES OF DAYS
Baseline
Screening
Drug Administration
• Drug Levels
• Drug Effects
• Serum Cytokines
• Cell Populations
• Gene Expressions
Transplant
• Graft Assessment
• Time 0 Biopsy and Gene Expression
• Drug Levels
• Drug Effects
2-5 YEARS
ONE YEAR
WEANING PERIOD
IS Withdrawal
• Immune Response
• Cell Populations - Flow
• T Cell Function - IS Effects
• Rejection- Gene Expression
Immediate Post Withdrawal
• Rejection - Gene Expression
• Cell Populations - Flow
• T Cell Function
End of
Study
Follow Up: 2-5 years
• Tolerance Marker ID
• Gene Expression
• Regulatory Cells - Flow Cytometry
• Th1/Th2 Shift
• Serum Profiles
• Other Assays
Integration of domain-specific information
Antigen Expression
Cytokine Secretion
Gene Expression
Flow Cytometry
EliSPOT
Microarray
High Level Analysis Plan
Original Biopsy Designation
Counts by visit
Classification
On left column
AR = Acute Rejection
HEP = Mild
HEP-MOD = Moderate
To Severe
Gene Expression Statistical Framework
Design
Comparisons of interest
Biological replicates
Pre-processing
Normalization
Quality Assurance
Inference
Mechanism of Action
Statistic that incorporates variability
Fold Change (FC) and p-value cutoff
False Discovery Rate (FDR) estimation
to handle multiple testing comparisons
Gene class testing, enrichment analysis
to facilitate interpretation
Validation
Follow-up study
Alternate assay
(SI)
(CAN)
(TOL)
(HC)
Classification
Biomarker
Supervised and supervised approaches
Support Vector Machines (SVM),
K-means, Random Forests
Issues with with over fitting data
Using test set, training set approaches
Hierarchical Clustering (All Samples, V0, V6)
Hierarchical Clustering
(Pearson correlation)
All visits
Transcripts filtered for those differentially
expressed between V6 and Baseline (V0) at
FC >2 and FDR correction
4, 041 transcripts
Blue = baseline
Yellow = V6
Red = FCLB
Baseline = 27
FCLB = 21
V6 = 12
Hierarchical Clustering (V6 vs. FCLB)
Hierarchical Clustering
(Pearson correlation)
V6 vs. FCLB
Transcripts filtered for those differentially
expressed between FCLB and V6 at FC >1.5
and NO FDR correction
629 transcripts
Blue = V6
Red = FCLB
FCLB = 21
V6 = 12
Hierarchical Clustering – AR and Non AR FCLB
Hierarchical Clustering
(Pearson correlation)
FCLB No AR vs.
FCLB with AR
Transcripts filtered for those differentially
expressed between FCLB NO AR and FCLB
with AR at FC >1.5 and NO FDR correction
580 transcripts
Blue = FCLB No AR
Red = FCLB with AR
FCLB = 21
V6 = 12
ITN Standard Flow Panel
Cell type/function
FITC
DCs
CD11c
DCs/costimulation
CD11c
PerCP
PECy7
APC
dump*
HLA-Dr
CD123
CD80
dump*
HLA-Dr
CD123
CD11c
CD86
dump*
HLA-Dr
CD123
CD11c
IFN alpha
dump*
HLA-Dr
CD123
Antigen presentation, activation and
costimulation
CD14
CD4
CD19
CD3
HLA-Dr
monocytes, B cells
CD14
CD80
CD19
CD3
CD86
T cells/activation/naïve vs memory
CD45RA
CD45RO
CD8
CD4
CD62L
T cells/activation
CD8
CD69
CD4
CD3
CD122
CD8
IL-12R
CD4
CD3
HLA-Dr
CD8
CD25
CD4
CD3
CD62L
Th1/Th2 profiles
IFNgamma
IL-4
CD8
CD3
CD4
Cytotoxic T cells
perforin
granzyme B
CD8
Th1 cells
CD4
CXCR3
CD8
CD3
CCR5
Th2 cells
CD4
CCR3
CD8
CD3
CCR4
Precursors,germinal center, plasma
CD38
IgD
CD138
CD19
CD10
B cells, immature/mature, naïve
CD27 or CD1d
IgD
CD38 or CD20
CD19
IgM
B cells, mature, naïve
CD44
IgD
CD38
CD19
CD10
B cells, mature, naïve
CD23
IgD
CD38
CD19
CD77
B1 cells
CD1d
CD21
CD5
CD19
CD23
Apoptosis
Annexin V
CD95
CD20
CD19
CD27
mature, costimulation, Ag. presn.
CD27
CD80
HLA-DR
CD19
CD86
NK cells
CD57
CD56, CD16
CD14
CD3
CD8
T regulatory cells
PE
Cytokines/chemokines
CD3
B cells
Thistlethwaite – Activated CD3CD4 T Cells (CD62L)
Regulatory T cells
Associations across assays and trials
Operationally
Tolerant Individuals
Microarray
CD19 IgG1 CD79A CD79B IgJ genes
Urine
RT - PCR
CD20
B cells- CD19
Naïve B cells- CD27
IgD+ IgMlo
Flow
Cytometry
Data Flow
Raw
Data
Data Center
- Validated
Raw Data
Analysis
Pipeline
TADA
- Participant Annotation
- Assay review,
annotation
- Quality Assurance
- Normalization
Biostatistical
Repository
TADA
- R or SAS scripting
- Analysis Reports
- Experimental design,
Hypothesis, statistical
modeling
- Exploratory analyses
Curated
‘Results’
(Published)
Communications & TADA
- Camera ready figures
- Analysis revised or
directed for manuscript,
presentation, abstract
etc.
Funded by:
National Institute of Allergy & Infectious Diseases
Juvenile Diabetes Research Foundation
National Institute of Diabetes &
Digestive & Kidney Diseases