BACKGROUND: Chronic allograft rejection (CR) is the major cause of failure of long-term graft survival and is so far irreversible. Early prognosis of CR by molecular markers before overt histologic manifestation would be a valuable aid for the optimization of treatment regimens and the design of clinical CR trials. Oligonucleotide microarray-based approaches have proven to be useful for the diagnosis and prognosis of a variety of diseases and were chosen for the unbiased identification of prognostic biomarkers. METHODS: Renal allograft biopsies were taken at month 6 posttransplantation (PT) from two groups who were, at that time, healthy recipients: one group developed CR at month-12 PT, the other group remained healthy. Gene expression profiles from the two groups at month-6 PT biopsies were analyzed to identify differentially expressed genes with prognostic value for CR development at month 12. RESULTS: A set of 10 genes was identified that showed differential expression profiles between the two patient groups and had a complete separation of the 15% to 85% quantile range for each individual gene. This set of genes was sufficient to allow the correct prediction of the occurrence or nonoccurrence of CR in 15 of 17 (88%) patients using cross-validation (occurrence for a patient was predicted on the basis of the other patients' data only). In addition, a correct prediction could be made that a recipient with a normal biopsy 12 months PT developed CR within the following 6 months. CONCLUSIONS: Identified expression patterns seem to be highly prognostic of the development of renal CR.
BACKGROUND: Chronic allograft rejection (CR) is the major cause of failure of long-term graft survival and is so far irreversible. Early prognosis of CR by molecular markers before overt histologic manifestation would be a valuable aid for the optimization of treatment regimens and the design of clinical CR trials. Oligonucleotide microarray-based approaches have proven to be useful for the diagnosis and prognosis of a variety of diseases and were chosen for the unbiased identification of prognostic biomarkers. METHODS: Renal allograft biopsies were taken at month 6 posttransplantation (PT) from two groups who were, at that time, healthy recipients: one group developed CR at month-12 PT, the other group remained healthy. Gene expression profiles from the two groups at month-6 PT biopsies were analyzed to identify differentially expressed genes with prognostic value for CR development at month 12. RESULTS: A set of 10 genes was identified that showed differential expression profiles between the two patient groups and had a complete separation of the 15% to 85% quantile range for each individual gene. This set of genes was sufficient to allow the correct prediction of the occurrence or nonoccurrence of CR in 15 of 17 (88%) patients using cross-validation (occurrence for a patient was predicted on the basis of the other patients' data only). In addition, a correct prediction could be made that a recipient with a normal biopsy 12 months PT developed CR within the following 6 months. CONCLUSIONS: Identified expression patterns seem to be highly prognostic of the development of renal CR.
Authors: Federico M Goodsaid; Shashi Amur; Jiri Aubrecht; Michael E Burczynski; Kevin Carl; Jennifer Catalano; Rosane Charlab; Sandra Close; Catherine Cornu-Artis; Laurent Essioux; Albert J Fornace; Lois Hinman; Huixiao Hong; Ian Hunt; David Jacobson-Kram; Ansar Jawaid; David Laurie; Lawrence Lesko; Heng-Hong Li; Klaus Lindpaintner; James Mayne; Peter Morrow; Marisa Papaluca-Amati; Timothy W Robison; John Roth; Ina Schuppe-Koistinen; Leming Shi; Olivia Spleiss; Weida Tong; Sharada L Truter; Jacky Vonderscher; Agnes Westelinck; Li Zhang; Issam Zineh Journal: Nat Rev Drug Discov Date: 2010-06 Impact factor: 84.694
Authors: Maarten Naesens; Purvesh Khatri; Li Li; Tara K Sigdel; Matthew J Vitalone; Rong Chen; Atul J Butte; Oscar Salvatierra; Minnie M Sarwal Journal: Kidney Int Date: 2011-08-31 Impact factor: 10.612