BACKGROUND: Gene expression profiling distinguishes the absence or presence of moderate to severe grades of acute cellular rejection in cardiac allograft recipients using a 20-gene classifier. We explored the hypothesis that the rejection classifier also differentiates various forms of mild rejection and we performed sub-analyses based on time post-transplant and confirmatory pathology interpretations. METHODS: A post hoc analysis of 265 CARGO study patients and 714 clinical encounters focused on the correlation of rejection classifier-derived gene expression (GE) scores for blood samples accompanying endomyocardial biopsies. Biopsy grades assigned by a study center pathologist (center) were re-interpreted by three pathologists (panel) in a blinded manner. RESULTS: Mean GE scores not only differentiated Grades >or=3A from Grade 0 (p < 0.00001, center or panel), but also from Grades 1A or 2 (p < 0.05, center or panel), based on mild rejection sub-groups defined by the ISHLT 1990 grading system. In contrast, mean GE scores for Grades 1B and >or=3A were indistinguishable, using either center or panel interpretation. Sub-group analyses of encounters from 2 to 6 months or >6 months post-transplant showed similar results for the classifier's ability to discriminate moderate to severe rejection from Grades 1A and 2 mild rejection, but indistinguishable mean GE scores for Grades >or=3A and the Grade 1B sub-group. Of the classifier's 11 informative genes, expression of MIR and WDR40 showed statistically significant increases for both Grade 1B and Grade >or=3A rejection, while expression of PDCD1 or SEMA7A showed similar directional patterns without achieving statistical significance. CONCLUSIONS: These data demonstrate that GE scores discriminate moderate to severe rejection from Grades 1A and 2 mild rejection. However, a sub-group of mild rejection cases, defined as Grade 1B according to the 1990 grading system, share a molecular signature more consistent with moderate to severe rejection. The clinical relevance of these data remains to be defined.
BACKGROUND: Gene expression profiling distinguishes the absence or presence of moderate to severe grades of acute cellular rejection in cardiac allograft recipients using a 20-gene classifier. We explored the hypothesis that the rejection classifier also differentiates various forms of mild rejection and we performed sub-analyses based on time post-transplant and confirmatory pathology interpretations. METHODS: A post hoc analysis of 265 CARGO study patients and 714 clinical encounters focused on the correlation of rejection classifier-derived gene expression (GE) scores for blood samples accompanying endomyocardial biopsies. Biopsy grades assigned by a study center pathologist (center) were re-interpreted by three pathologists (panel) in a blinded manner. RESULTS: Mean GE scores not only differentiated Grades >or=3A from Grade 0 (p < 0.00001, center or panel), but also from Grades 1A or 2 (p < 0.05, center or panel), based on mild rejection sub-groups defined by the ISHLT 1990 grading system. In contrast, mean GE scores for Grades 1B and >or=3A were indistinguishable, using either center or panel interpretation. Sub-group analyses of encounters from 2 to 6 months or >6 months post-transplant showed similar results for the classifier's ability to discriminate moderate to severe rejection from Grades 1A and 2 mild rejection, but indistinguishable mean GE scores for Grades >or=3A and the Grade 1B sub-group. Of the classifier's 11 informative genes, expression of MIR and WDR40 showed statistically significant increases for both Grade 1B and Grade >or=3A rejection, while expression of PDCD1 or SEMA7A showed similar directional patterns without achieving statistical significance. CONCLUSIONS: These data demonstrate that GE scores discriminate moderate to severe rejection from Grades 1A and 2 mild rejection. However, a sub-group of mild rejection cases, defined as Grade 1B according to the 1990 grading system, share a molecular signature more consistent with moderate to severe rejection. The clinical relevance of these data remains to be defined.
Authors: Santanu Guha; S Harikrishnan; Saumitra Ray; Rishi Sethi; S Ramakrishnan; Suvro Banerjee; V K Bahl; K C Goswami; Amal Kumar Banerjee; S Shanmugasundaram; P G Kerkar; Sandeep Seth; Rakesh Yadav; Aditya Kapoor; Ajaykumar U Mahajan; P P Mohanan; Sundeep Mishra; P K Deb; C Narasimhan; A K Pancholia; Ajay Sinha; Akshyaya Pradhan; R Alagesan; Ambuj Roy; Amit Vora; Anita Saxena; Arup Dasbiswas; B C Srinivas; B P Chattopadhyay; B P Singh; J Balachandar; K R Balakrishnan; Brian Pinto; C N Manjunath; Charan P Lanjewar; Dharmendra Jain; Dipak Sarma; G Justin Paul; Geevar A Zachariah; H K Chopra; I B Vijayalakshmi; J A Tharakan; J J Dalal; J P S Sawhney; Jayanta Saha; Johann Christopher; K K Talwar; K Sarat Chandra; K Venugopal; Kajal Ganguly; M S Hiremath; Milind Hot; Mrinal Kanti Das; Neil Bardolui; Niteen V Deshpande; O P Yadava; Prashant Bhardwaj; Pravesh Vishwakarma; Rajeeve Kumar Rajput; Rakesh Gupta; S Somasundaram; S N Routray; S S Iyengar; G Sanjay; Satyendra Tewari; Sengottuvelu G; Soumitra Kumar; Soura Mookerjee; Tiny Nair; Trinath Mishra; U C Samal; U Kaul; V K Chopra; V S Narain; Vimal Raj; Yash Lokhandwala Journal: Indian Heart J Date: 2018-06-08
Authors: Jane P F Bai; Robert Bell; ShaAvhree Buckman; Gilbert J Burckart; Hans-Georg Eichler; Kenneth C Fang; Federico M Goodsaid; William J Jusko; Lawrence L Lesko; Bernd Meibohm; Scott D Patterson; Oscar Puig; Jeffrey B Smerage; Barbara J Snider; John A Wagner; Jingsong Wang; Marc K Walton; Russell Weiner Journal: AAPS J Date: 2011-03-30 Impact factor: 4.009
Authors: Cécile T J Holweg; Luciano Potena; Helen Luikart; Tianwei Yu; Gerald J Berry; John P Cooke; Hannah A Valantine; Edward S Mocarski Journal: Circulation Date: 2011-05-09 Impact factor: 29.690
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