Gene expression testing in cardiac and lung transplantation

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Gene expression testing in cardiac and lung
transplantation
Banff Congress Jay Wohlgemuth MD July 16, 2005
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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

• 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)
• Followed 650 patients during gt 5500
  post-transplant encounters
• Microarrays used for gene discovery, real-time
  PCR for development and validation of a
  multi-gene, multi-pathway molecular test
• Prospective, blinded validation study of 20 gene
  algorithm demonstrated ability to distinguish
  rejection from quiescence

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CARGO Study Overview

• 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

Phase I Exploratory

Phase II Development

• 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 gt 1000)

Phase III Validation Study
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Rejection Associated Gene Expression Pathways

• Of 252 PCR-assayed genes, 68 genes correlated
  with rejection (p lt 0.01) and/or have a median
  ratio more than 25.
• Measuring both gene expression and shifts of cell
  populations
• CD8 T cell and NK markers
• Markers of hematopoiesis up-regulated with
  rejection

Activated Macrophage / PMN
Steroid responsive
Megakaryocyte
Hematopoiesis
Cytokines, IFN induced
T lymphocyte
B lymphocyte
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Monitoring Multiple Pathways Associated with
Rejection
Inflammation
Platelet Activation
IL-6
PF4, G6B
T cell Priming
PDCD-1, ITGA4
Lymph node
Mobilization of Hematopoietic precursors
WDR40A, MIR
Lymph and Lymphocytes
Rejection Rx
IL1R2, ITGAM, FLT3
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AlloMap Diagnostic Algorithm
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CARGO Study Results Summary

• AlloMap distinguishes grade 3A rejection from
  grade 0 at all times post-transplant (p lt0.0001)
• 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 score and steroid dose vs. days post
transplant
AlloMap
AlloMap score, quiescent samples
Prednisone dose mg/day
Prednisone
Days post transplant
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Steroid Responsive Genes and Pathways

• 5 of 11 informative algorithm genes significantly
  correlate with steroids
• Steroid and rejection gene expression responses
  are opposite
• Predominance of monocyte and PMN expressed genes
• ITGAM and IL1R2 are most responsive to steroid
  dose

SteroidGene Rejection Response Description Cell
Type ITGAM Integrin, alpha M Monos, PMN,
NK IL1R2 Interleukin 1 Monos,
PMN receptor G6b lg superfamily Hemotopoiet
ic cell lines FLT3 fms-related lymphoid/m
yeloid tyr kinase progenitors ITGA4
integrin, alpha 4 Monos, PMN, lymphocytes
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Individual Patients Have Varied Responses to
SteroidsSteroid Resistant Rejection and Steroid
Sensitivity
Gene expression based estimate of steroid dose
Quiescent gold Rejection blue
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Identification of Quiescence

• Samples below threshold are unlikely to have 3A
  or higher biopsy NPV gt 99
• Samples above threshold are enriched for
  concurrent biopsy 3A
• 12X increased risk for 3A rejection vs. low
  scores
• Still, low PPV relative to biopsy Why?

Below threshold (high NPV)
Above threshold (moderate PPV)
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Molecular Testing Correlation to Biopsy and
Graft Dysfunction
Humoral Rejection
Cellular Rejection
Molecular Rejection
Graft Dysfunction
Biopsy (late)
AlloMap Test (early)
Graft Failure (too late)
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Risk of graft dysfunction with high score,
negative biopsy

• Risk of graft dysfunction (PCW gt20) within 45
  days

RR 6.8 p 0.03
High
Low
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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
• All cases involved local Grade 2 or 3A
• All cases had been identified as likely Grade 0-1
  and Quilty B by centralized panel
• 17 of 18 confirmed to be Grade 0-1
• 12/12 Local Grade 2s
• 5/6 Local Grade 3As

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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
• gt50 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
472 samples 6 months post-transplant

• Grade 1B sample scores were significantly higher
  than Grades 0 (p0.02) and 1A (p0.002)
• Grade 1B scores were not significantly different
  than grade 3
• 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)

AlloMap Score
Local ISHLT grade
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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

• Transplant cardiology programs
• Cleveland Clinic Randall Starling, MD, MPH
• Columbia University Mario Deng, MD, Helen Baron,
  MD
• Columbia University (peds) Seema Mital MD, Linda
  Addonizio, MD
• Ochsner Clinic Mandeep Mehra, MD
• Stanford University, PAVAMC Sharon Hunt, MD,
  Fran Johnson MD
• Stanford University (peds) Daniel Bernstein, MD
• Temple University Howard Eisen, MD
• UCLA Medical Center Jon Kobashigawa, MD
• University of Florida James Hill,MD, Dan Pauly,
  MD, PhD
• University of Pittsburgh Srinivas Murali, MD,
  Adrianna Zeevi, PhD
• University of Pittsburgh (peds) Steven Webber,
  MBChB
• Centralized reading of biopsy pathology
• Gerald Berry, MD (Stanford)
• Margaret Billingham, MD (Stanford)
• Charles Marboe, MD (Columbia)