OBJECTIVE: The rapid diagnosis of acute graft-versus-host disease (GVHD) following allogeneic hematopoietic cell transplantation (HCT) is important for optimizing the management of this life-threatening complication. Current diagnostic techniques are time-consuming and require invasive tissue sampling. We investigated serum protein pattern analysis using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry as a tool to diagnose GVHD. PATIENTS AND METHODS: Eighty-eight serum samples were obtained from 34 patients undergoing HCT either pretransplant (n = 28 samples) or at various time points posttransplant (n = 60 samples), including 22 samples obtained on the day of onset of acute GVHD symptoms. Serum proteomic spectra generated from a "training set" of known samples were used to identify distinct proteomic patterns that best categorized a sample as either pretransplant, posttransplant non-GVHD, or GVHD; these distinct proteomic signatures were subsequently used to classify samples from a masked "test" sample set into the appropriate diagnostic category. RESULTS: Proteomic pattern analysis accurately distinguished GVHD samples from both posttransplant non-GVHD samples and pretransplant samples (100% specificity and 100% sensitivity in both cases). Furthermore, distinct serum proteomic signatures were identified that distinguished pretransplant from posttransplant non-GVHD samples (100% specificity and 94% sensitivity). CONCLUSION: These preliminary data suggest a potential application of SELDI-TOF-based proteomic analysis as a rapid and accurate method to diagnose acute GVHD.
OBJECTIVE: The rapid diagnosis of acute graft-versus-host disease (GVHD) following allogeneic hematopoietic cell transplantation (HCT) is important for optimizing the management of this life-threatening complication. Current diagnostic techniques are time-consuming and require invasive tissue sampling. We investigated serum protein pattern analysis using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry as a tool to diagnose GVHD. PATIENTS AND METHODS: Eighty-eight serum samples were obtained from 34 patients undergoing HCT either pretransplant (n = 28 samples) or at various time points posttransplant (n = 60 samples), including 22 samples obtained on the day of onset of acute GVHD symptoms. Serum proteomic spectra generated from a "training set" of known samples were used to identify distinct proteomic patterns that best categorized a sample as either pretransplant, posttransplant non-GVHD, or GVHD; these distinct proteomic signatures were subsequently used to classify samples from a masked "test" sample set into the appropriate diagnostic category. RESULTS: Proteomic pattern analysis accurately distinguished GVHD samples from both posttransplant non-GVHD samples and pretransplant samples (100% specificity and 100% sensitivity in both cases). Furthermore, distinct serum proteomic signatures were identified that distinguished pretransplant from posttransplant non-GVHD samples (100% specificity and 94% sensitivity). CONCLUSION: These preliminary data suggest a potential application of SELDI-TOF-based proteomic analysis as a rapid and accurate method to diagnose acute GVHD.
Authors: Matin M Imanguli; Jane C Atkinson; Kristen E Harvey; Gerard T Hoehn; Ok Hee Ryu; Tianxia Wu; Albert Kingman; A John Barrett; Michael R Bishop; Richard W Childs; Daniel H Fowler; Steven Z Pavletic; Thomas C Hart Journal: Exp Hematol Date: 2007-02 Impact factor: 3.084
Authors: Sophie Paczesny; Thomas M Braun; John E Levine; Jason Hogan; Jeffrey Crawford; Bryan Coffing; Stephen Olsen; Sung W Choi; Hong Wang; Vitor Faca; Sharon Pitteri; Qing Zhang; Alice Chin; Carrie Kitko; Shin Mineishi; Gregory Yanik; Edward Peres; David Hanauer; Ying Wang; Pavan Reddy; Samir Hanash; James L M Ferrara Journal: Sci Transl Med Date: 2010-01-06 Impact factor: 17.956
Authors: Andrew R Rezvani; Barry E Storer; Rainer F Storb; Marco Mielcarek; David G Maloney; Brenda M Sandmaier; Paul J Martin; George B McDonald Journal: Biol Blood Marrow Transplant Date: 2011-07-30 Impact factor: 5.742
Authors: Bin Xiao; Yu Wang; Wei Li; Megan Baker; Jian Guo; Kelly Corbet; Ephraim L Tsalik; Qi-Jing Li; Scott M Palmer; Christopher W Woods; Zhiguo Li; Nelson J Chao; You-Wen He Journal: Blood Date: 2013-09-16 Impact factor: 22.113