Transcript cybernephrology.ualberta.ca

Gene expression testing in cardiac
and lung transplantation
Banff Congress
Jay Wohlgemuth MD
July 16, 2005
Scientific assumptions
 Gene expression profiling of the immune system
may anticipate tissue injury
 Multiple genes from multiple pathways are required
to overcome complexity and variability
 Complex multi-pathway signals can be reduced to
simple, clinically actionable test result(s)
 Use of genomic information may enable proactive
therapy, reduction in un-necessary
immunosuppression and monitoring procedures
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The transplant patient management challenge
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Clinical need for molecular testing in cardiac transplantation
 Monitoring for rejection
 Rejection rates are very low (2-3% for Grade 3A)
 Biopsy has limitations for patients and physicians
 Reduction in burden of immunosuppression
 Complications of IS are a major cause of M & M beyond the 1st
year post-transplant
 Minimization may be facilitated with molecular testing
 Clarification of uncertain clinical and pathological cases
 Mild rejection
 Need for augmentation or change in Rx
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CARGO Clinical Study
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Goal: discover, develop and validate gene
expression testing for rejection and
quiescence in cardiac transplant recipients

Multi-center observational study initiated in
2001 (centers represent 22% of US cardiac
transplants)
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Followed 650 patients during > 5500 posttransplant encounters
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Microarrays used for gene discovery, realtime PCR for development and validation of
a multi-gene, multi-pathway molecular test
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Prospective, blinded validation study of 20
gene algorithm demonstrated ability to
distinguish rejection from quiescence
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CARGO Study Overview
Phase I
Exploratory
Phase II
Development
Phase III
Validation Study
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 Candidate gene selection
 Leukocyte microarray derived from 25K cDNAs and
human genome information
 285 CARGO samples used in microarray experiments
 Database and literature mining
 Identification of 252 candidate genes
 Algorithm development
 Sensitive and reproducible real-time PCR methods
 Development of a 20-gene algorithm to distinguish
rejection from quiescence (AlloMap)
 Validation
 Prospective, blinded, statistically-powered
clinical study (n = 270)
 Additional samples were tested to further define
performance (n > 1000)
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Rejection Associated Gene Expression Pathways

Of 252 PCR-assayed
genes, 68 genes
correlated with rejection (p
< 0.01) and/or have a
median ratio more than
±25%.

Measuring both gene
expression and shifts of
cell populations
T lymphocyte

CD8 T cell and NK
markers
B lymphocyte
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Markers of hematopoiesis
up-regulated with rejection
Activated Macrophage / PMN
Steroid responsive
Megakaryocyte
Hematopoiesis
Cytokines, IFN induced
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Monitoring Multiple Pathways Associated with Rejection
Inflammation
Platelet Activation
PF4, G6B
IL-6
T cell Priming
PDCD-1, ITGA4
Lymph node
Mobilization of
Hematopoietic
precursors
WDR40A, MIR
Lymph and
Lymphocytes
Naïve T cell
Rejection Rx
Primed T cell
IL1R2, ITGAM, FLT3
Dendritic cell
Monocyte
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AlloMap Diagnostic Algorithm
0
Q
R
+ 1 x Metagene 1
– 2 x Metagene 2
– 3 x Metagene 3
4 x Gene 1
+ 5 x Gene 2
+ 6 x Gene 3
+ 7 x Gene 4
0
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CARGO Study Results Summary
 AlloMap distinguishes grade ≥3A rejection from
grade 0 at all times post-transplant (p <0.0001)
 Grade 1B samples have high algorithm scores on
average, grades 0, 1A and 2 are indistinguishable
 Patients with low scores have very low risk of
moderate-severe acute rejection
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CARGO Study Results Summary
 AlloMap correlates more closely to centralized than
local pathology
 Algorithm predicts future rejection and graft
dysfunction in grade 0 cases
 Pediatric samples look qualitatively similar
 CMV signature identified which does not confound
the AlloMap test result
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AlloMap Score Increases with Decreased Steroid Dose
AlloMap
Prednisone
Days post transplant
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Prednisone dose [mg/day]
AlloMap score, quiescent samples
AlloMap score and steroid dose vs. days post transplant
Steroid Responsive Genes and Pathways
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5 of 11 informative algorithm genes significantly correlate with steroids
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Steroid and rejection gene expression responses are opposite
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Predominance of monocyte and PMN expressed genes
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ITGAM and IL1R2 are most responsive to steroid dose
Gene
Description
Cell Type
ITGAM
Integrin, alpha M
Monos, PMN, NK
IL1R2
Interleukin 1
receptor
Monos, PMN
G6b
lg superfamily
Hemotopoietic
cell lines
FLT3
fms-related
tyr kinase
lymphoid/myeloid
progenitors
integrin, alpha 4
Monos, PMN,
lymphocytes
ITGA4
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Rejection
Steroid
Response
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Individual Patients Have Varied Responses to Steroids:
Steroid Resistant Rejection and Steroid Sensitivity
Gene expression based estimate of steroid dose
Quiescent gold
Rejection blue
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Identification of Quiescence
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Samples below threshold are unlikely to have 3A or higher biopsy NPV > 99%
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Samples above threshold are enriched for concurrent biopsy ≥3A
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12X increased risk for 3A rejection vs. low scores
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Still, low PPV relative to biopsy – Why?
Below threshold
(high NPV)
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Above threshold
(moderate PPV)
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Molecular Testing: Correlation to Biopsy and Graft Dysfunction
Humoral Rejection
Molecular
Rejection
Cellular
Rejection
AlloMap Test
(early)
Biopsy
(late)
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Graft
Dysfunction
Graft Failure
(too late)
Risk of graft dysfunction with high score, negative biopsy

Risk of graft dysfunction (PCW >20) within 45 days
% Graft Dysfunction (45 days)
30
25
20
15
RR = 6.8
p = 0.03
10
5
0
Low
Rejection
High
Quiescent
Algorithm score
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Cardiac biopsy interpretation variability contributes to
discordance between molecular and pathological results

Pathology panel (Billingham, Marboe and Berry) re-read all biopsy slides
for the study (n = 827) Marboe et al., JHLT 2005
 The maximum concordance between two central pathologists for grade
≥3A rejection was 77%
 The average concordance between the local and central pathologists
grade ≥3A rejection was 40%
 Local pathologists call grade ≥3A rejection 50% more frequently than
central pathologists
 Quilty lesions cause significant uncertainty and overcalls for rejection
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Quilty lesions cause over diagnosis of ISHLT Grade 2 and 3A
rejection

Serial sections of 18 cases performed
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All cases involved local Grade 2 or 3A

All cases had been identified as likely
Grade 0-1 and Quilty B by centralized
panel
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17 of 18 confirmed to be Grade 0-1
 12/12 Local Grade 2s
 5/6 Local Grade 3As
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Re-read with
Local Grade sections
2
2
2
2
2
2
2
2
2
2
2
2
3A
3A
3A
3A
3A
3A
1A
0
1A
1A
0-1A
1A
0
0
1A
0
1A
1A
1A
1A
1A
0
3A/3B
0
Local Pathologist: Rejection
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Consensus: Quilty B
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Discordance between molecular and pathological results
 Positive biopsy, low molecular score
 >50% of Grade 3As after year 1 may resolve without therapy
 Quilty lesions or other causes of over diagnosis by biopsy
 Molecular test and biopsy measure different processes which may be
discordant
 Negative biopsy, high molecular score
 Early, focal rejection, negative on biopsy
 Sensitivity of test for humoral rejection?
 Patients may have peripheral alloimmune activity, no cellular rejection
 Risk of vasculopathy?
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AlloMap Scores by ISHLT Grade
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36
34
32
30
Grade 1B scores were
not significantly
different than grade ≥3
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Grades 0, 1A and 2
scores were not
significantly different
Mild rejection (0-2) with
high scores have
significant increased
risk of progression to
grade 3A on next
biopsy (p = 0.0015)
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20
18
0
1A
1B
Local ISHLT grade
23
2
≥3A
AlloMap Score

472 samples ≥ 6 months post-transplant
Grade 1B sample
scores were
significantly higher than
Grades 0 (p=0.02) and
1A (p=0.002)
Molecular response to rejection therapy
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Clinical uses of molecular testing in cardiac transplantation
 Rejection surveillance
 Stable outpatients with low scores are low risk: biopsy reduction
 Access issues
 Immunosuppression titration
 Guide weaning of immunosuppression
 Follow after rejection therapy
 Risk stratification
 Mild rejection or possible Quilty on biopsy
 Uncertain clinical picture
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CARGO – Ongoing Studies, CARGO II Study
 Prediction of clinical
outcomes
 Immunosuppression /
Rejection Rx monitoring
 Humoral rejection
 Vasculopathy
 Pediatrics
 Infection
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LARGO Study
 Ongoing 14 center international study of
molecular testing in Lung transplantation
 Endpoints: Acute rejection, BOS, infection
 Infectious complications may be addressed with
development of new molecular information
 Common relevant pathways for multiple solid
organ transplant settings will be sought
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Thank You
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CARGO Centers and Collaborators
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Transplant cardiology programs:
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Cleveland Clinic
Columbia University
Columbia University (peds)
Ochsner Clinic
Stanford University, PAVAMC
Stanford University (peds)
Temple University
UCLA Medical Center
University of Florida
University of Pittsburgh
University of Pittsburgh (peds)
Randall Starling, MD, MPH
Mario Deng, MD, Helen Baron, MD
Seema Mital MD, Linda Addonizio, MD
Mandeep Mehra, MD
Sharon Hunt, MD, Fran Johnson MD
Daniel Bernstein, MD
Howard Eisen, MD
Jon Kobashigawa, MD
James Hill,MD, Dan Pauly, MD, PhD
Srinivas Murali, MD, Adrianna Zeevi, PhD
Steven Webber, MBChB
Centralized reading of biopsy pathology:
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Gerald Berry, MD (Stanford)
Margaret Billingham, MD (Stanford)
Charles Marboe, MD (Columbia)
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