BACKGROUND: Acute rejection is still a significant barrier to long-term survival of the allograft. Current acute rejection diagnostic methods are not specific enough or are invasive. There have been a number of studies that have explored the blood or the biopsy to discover genomic biomarkers of acute rejection; however, none of the studies to date have used both. METHODS: We analyzed endomyocardial biopsy tissue and whole blood-derived messenger RNA from 11 acute rejection and 20 nonrejection patients using Affymetrix Human Genome U133 Plus 2.0 chips. We used a novel approach and gained insight into the biology of rejection based on gene expression in the biopsy, and applied this knowledge to the blood analysis to identify novel blood biomarkers. RESULTS: We identified probesets that are differentially expressed between acute rejection and nonrejection patients in the biopsy and blood, and developed three biomarker panels: (1) based on biopsy-only (area under the curve=0.85), (2) based on biopsy-targeted whole blood (area under the curve=0.83), and (3) based on whole blood-only (area under the curve=0.60) analyses. CONCLUSIONS: Most of the probesets replicated between biopsy and blood are regulated in opposite direction between the two sources of information. We also observed that the biopsy-targeted blood biomarker discovery approach can improve performance of the biomarker panel. The biomarker panel developed using this targeted approach is able to diagnose acute cardiac allograft rejection almost as well as the biopsy-only based biomarker panel.
BACKGROUND: Acute rejection is still a significant barrier to long-term survival of the allograft. Current acute rejection diagnostic methods are not specific enough or are invasive. There have been a number of studies that have explored the blood or the biopsy to discover genomic biomarkers of acute rejection; however, none of the studies to date have used both. METHODS: We analyzed endomyocardial biopsy tissue and whole blood-derived messenger RNA from 11 acute rejection and 20 nonrejection patients using Affymetrix Human Genome U133 Plus 2.0 chips. We used a novel approach and gained insight into the biology of rejection based on gene expression in the biopsy, and applied this knowledge to the blood analysis to identify novel blood biomarkers. RESULTS: We identified probesets that are differentially expressed between acute rejection and nonrejection patients in the biopsy and blood, and developed three biomarker panels: (1) based on biopsy-only (area under the curve=0.85), (2) based on biopsy-targeted whole blood (area under the curve=0.83), and (3) based on whole blood-only (area under the curve=0.60) analyses. CONCLUSIONS: Most of the probesets replicated between biopsy and blood are regulated in opposite direction between the two sources of information. We also observed that the biopsy-targeted blood biomarker discovery approach can improve performance of the biomarker panel. The biomarker panel developed using this targeted approach is able to diagnose acute cardiac allograft rejection almost as well as the biopsy-only based biomarker panel.
Authors: Erick Romero; Eleanor Chang; Esteban Tabak; Diego Pinheiro; Jose Tallaj; Silvio Litovsky; Brendan Keating; Mario Deng; Martin Cadeiras Journal: Transplant Direct Date: 2020-10-19
Authors: R C Starling; J Stehlik; D A Baran; B Armstrong; J R Stone; D Ikle; Y Morrison; N D Bridges; P Putheti; T B Strom; M Bhasin; I Guleria; A Chandraker; M Sayegh; K P Daly; D M Briscoe; P S Heeger Journal: Am J Transplant Date: 2015-08-10 Impact factor: 8.086
Authors: Casey P Shannon; Zsuzsanna Hollander; Janet Wilson-McManus; Robert Balshaw; Raymond T Ng; Robert McMaster; Bruce M McManus; Paul A Keown; Scott J Tebbutt Journal: Bioinform Biol Insights Date: 2012-04-10
Authors: Heesun Shin; Casey P Shannon; Nick Fishbane; Jian Ruan; Mi Zhou; Robert Balshaw; Janet E Wilson-McManus; Raymond T Ng; Bruce M McManus; Scott J Tebbutt Journal: PLoS One Date: 2014-03-07 Impact factor: 3.240
Authors: Casey P Shannon; Robert Balshaw; Raymond T Ng; Janet E Wilson-McManus; Paul Keown; Robert McMaster; Bruce M McManus; David Landsberg; Nicole M Isbel; Greg Knoll; Scott J Tebbutt Journal: PLoS One Date: 2014-04-14 Impact factor: 3.240