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Gene expression testing in cardiac and lung transplantation

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

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Gene expression testing in cardiac and lung transplantation

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

  2. 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

  3. The transplant patient management challenge

  4. 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

  5. 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 > 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

  6. 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 • Algorithm development • Sensitive and reproducible real-time PCR methods • Development of a 20-gene algorithm to distinguish rejection from quiescence (AlloMap) Phase II Development • Validation • Prospective, blinded, statistically-powered clinical study (n = 270) • Additional samples were tested to further define performance (n > 1000) Phase III Validation Study

  7. 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 • 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

  8. Naïve T cell Primed T cell Dendritic cell Monocyte 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 Rejection Rx IL1R2, ITGAM, FLT3

  9. Q R 0 + 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 40 AlloMap Diagnostic Algorithm

  10. 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

  11. 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

  12. 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

  13. 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 Hemotopoietic cell lines FLT3 fms-related lymphoid/myeloid tyr kinase progenitors ITGA4 integrin, alpha 4 Monos, PMN, lymphocytes

  14. Individual Patients Have Varied Responses to Steroids:Steroid Resistant Rejection and Steroid Sensitivity Gene expression based estimate of steroid dose Quiescent gold Rejection blue

  15. Identification of Quiescence • Samples below threshold are unlikely to have 3A or higher biopsy NPV > 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)

  16. Molecular Testing: Correlation to Biopsy and Graft Dysfunction Humoral Rejection Molecular Rejection Cellular Rejection Graft Dysfunction Biopsy (late) AlloMap Test (early) Graft Failure (too late)

  17. Risk of graft dysfunction with high score, negative biopsy • Risk of graft dysfunction (PCW >20) within 45 days RR = 6.8 p = 0.03 Low High

  18. 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

  19. 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

  20. Local Pathologist: Rejection

  21. Consensus: Quilty B

  22. 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?

  23. AlloMap Scores by ISHLT Grade 472 samples ≥ 6 months post-transplant • Grade 1B sample scores were significantly higher than Grades 0 (p=0.02) and 1A (p=0.002) • 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

  24. Molecular response to rejection therapy

  25. 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

  26. CARGO – Ongoing Studies, CARGO II Study • Prediction of clinical outcomes • Immunosuppression / Rejection Rx monitoring • Humoral rejection • Vasculopathy • Pediatrics • Infection

  27. 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

  28. Thank You

  29. 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)

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