Sheyla Velasques Paladini1,2, Graziela Hünning Pinto1,2, Rodrigo Haas Bueno1, Raquel Calloni3, Mariana Recamonde-Mendoza4,5,6. 1. Experimental and Molecular Cardiovascular Laboratory, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil. 2. Post-Graduate Program in Cardiology and Cardiovascular Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil. 3. Instituto Federal de Educação, Ciência e Tecnologia Sul-Rio Grandense-Campus Gravataí, Gravataí, RS, Brazil. 4. Post-Graduate Program in Cardiology and Cardiovascular Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil. mrmendoza@inf.ufrgs.br. 5. Institute of Informatics, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, Setor IV, Building 43424, Office 225, Porto Alegre, RS, 91501-970, Brazil. mrmendoza@inf.ufrgs.br. 6. Bioinformatics Core, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil. mrmendoza@inf.ufrgs.br.
Abstract
BACKGROUND: Traditional methods for rejection control in transplanted patients are considered invasive, risky, and prone to sampling errors. Using molecular biomarkers as an alternative protocol to biopsies, for monitoring rejection may help to mitigate some of these problems, increasing the survival rates and well-being of patients. Recent advances in omics technologies provide an opportunity for screening new molecular biomarkers to identify those with clinical utility. OBJECTIVE: This systematic literature review (SLR) aimed to summarize existing evidence derived from large-scale expression profiling regarding differentially expressed mRNA and miRNA in graft rejection, highlighting potential molecular biomarkers in transplantation. METHODS: The study was conducted following PRISMA methodology and the BiSLR guide for performing SLR in bioinformatics. PubMed, ScienceDirect, and EMBASE were searched for publications from January 2001 to January 2018, and studies (i) aiming at the identification of transplant rejection biomarkers, (ii) including human subjects, and (iii) applying methodologies for differential expression analysis from large-scale expression profiling were considered eligible. Differential expression patterns reported for genes and miRNAs in rejection were summarized from both cross-organ and organ-specific perspectives, and pathways enrichment analysis was performed for candidate biomarkers to interrogate their functional role in transplant rejection. RESULTS: A total of 821 references were collected, resulting in 604 studies after removal of duplicates. After application of inclusion and exclusion criteria, 33 studies were included in our analysis. Among the 1517 genes and 174 miRNAs identifed, CXCL9, CXCL10, STAT1, hsa-miR-142-3p, and hsa-miR-155 appeared to be particularly promising as biomarkers in transplantation, with an increased expression associated with transplant rejection in multiple organs. In addition, hsa-miR-28-5p was consistently decreased in samples taken from rejected organs. CONCLUSION: Despite the need for further research to fill existing knowledge gaps, transcriptomic technologies have a relevant role in the discovery of accurate biomarkers for transplant rejection diagnostics. Studies have reported consistent evidence of differential expression associated with transplant rejection, although issues such as experimental heterogeneity hinder a more systematic characterization of observed molecular changes. Special attention has been giving to large-scale mRNA expression profiling in rejection, whereas there is still room for improvements in the characterization of miRnome in this condition. PROSPERO REGISTRATION NUMBER: CRD42018083321.
BACKGROUND: Traditional methods for rejection control in transplanted patients are considered invasive, risky, and prone to sampling errors. Using molecular biomarkers as an alternative protocol to biopsies, for monitoring rejection may help to mitigate some of these problems, increasing the survival rates and well-being of patients. Recent advances in omics technologies provide an opportunity for screening new molecular biomarkers to identify those with clinical utility. OBJECTIVE: This systematic literature review (SLR) aimed to summarize existing evidence derived from large-scale expression profiling regarding differentially expressed mRNA and miRNA in graft rejection, highlighting potential molecular biomarkers in transplantation. METHODS: The study was conducted following PRISMA methodology and the BiSLR guide for performing SLR in bioinformatics. PubMed, ScienceDirect, and EMBASE were searched for publications from January 2001 to January 2018, and studies (i) aiming at the identification of transplant rejection biomarkers, (ii) including human subjects, and (iii) applying methodologies for differential expression analysis from large-scale expression profiling were considered eligible. Differential expression patterns reported for genes and miRNAs in rejection were summarized from both cross-organ and organ-specific perspectives, and pathways enrichment analysis was performed for candidate biomarkers to interrogate their functional role in transplant rejection. RESULTS: A total of 821 references were collected, resulting in 604 studies after removal of duplicates. After application of inclusion and exclusion criteria, 33 studies were included in our analysis. Among the 1517 genes and 174 miRNAs identifed, CXCL9, CXCL10, STAT1, hsa-miR-142-3p, and hsa-miR-155 appeared to be particularly promising as biomarkers in transplantation, with an increased expression associated with transplant rejection in multiple organs. In addition, hsa-miR-28-5p was consistently decreased in samples taken from rejected organs. CONCLUSION: Despite the need for further research to fill existing knowledge gaps, transcriptomic technologies have a relevant role in the discovery of accurate biomarkers for transplant rejection diagnostics. Studies have reported consistent evidence of differential expression associated with transplant rejection, although issues such as experimental heterogeneity hinder a more systematic characterization of observed molecular changes. Special attention has been giving to large-scale mRNA expression profiling in rejection, whereas there is still room for improvements in the characterization of miRnome in this condition. PROSPERO REGISTRATION NUMBER: CRD42018083321.
Authors: Zsuzsanna Hollander; David Lin; Virginia Chen; Raymond Ng; Janet Wilson-McManus; Andrew Ignaszewski; Gabriela Cohen Freue; Rob Balshaw; Alice Mui; Robert McMaster; Paul A Keown; Bruce M McManus Journal: Transplantation Date: 2010-12-27 Impact factor: 4.939
Authors: Alexandre Loupy; Jean Paul Duong Van Huyen; Luis Hidalgo; Jeff Reeve; Maud Racapé; Olivier Aubert; Jeffery M Venner; Konrad Falmuski; Marie Cécile Bories; Thibaut Beuscart; Romain Guillemain; Arnaud François; Sabine Pattier; Claire Toquet; Arnaud Gay; Philippe Rouvier; Shaida Varnous; Pascal Leprince; Jean Philippe Empana; Carmen Lefaucheur; Patrick Bruneval; Xavier Jouven; Philip F Halloran Journal: Circulation Date: 2017-02-01 Impact factor: 29.690
Authors: Xiaoyou Liu; Changgui Dong; Zhengyao Jiang; William K K Wu; Matthew T V Chan; Jie Zhang; Haibin Li; Ke Qin; Xuyong Sun Journal: Exp Cell Res Date: 2015-02-07 Impact factor: 3.905
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: Daniel Baron; Gérard Ramstein; Mélanie Chesneau; Yann Echasseriau; Annaick Pallier; Chloé Paul; Nicolas Degauque; Maria P Hernandez-Fuentes; Alberto Sanchez-Fueyo; Kenneth A Newell; Magali Giral; Jean-Paul Soulillou; Rémi Houlgatte; Sophie Brouard Journal: Kidney Int Date: 2015-01-28 Impact factor: 10.612
Authors: Ihdina Sukma Dewi; Zsuzsanna Hollander; Karen K Lam; Janet-Wilson McManus; Scott J Tebbutt; Raymond T Ng; Paul A Keown; Robert W McMaster; Bruce M McManus; Olof Gidlöf; Jenny Öhman Journal: PLoS One Date: 2017-01-26 Impact factor: 3.240