RNA-sequencing of Human Kidney Allografts and Delineation of T-Cell Genes, Gene Sets, and Pathways Associated With Acute T Cell–mediated Rejection

基因 核糖核酸 生物 细胞 计算生物学 遗传学
作者
Franco B. Mueller,Hua Yang,Carol Li,Darshana Dadhania,Jenny Xiang,Steven Salvatore,Surya V. Seshan,Vijay K. Sharma,Manikkam Suthanthiran,Thangamani Muthukumar
出处
期刊:Transplantation [Ovid Technologies (Wolters Kluwer)]
标识
DOI:10.1097/tp.0000000000004896
摘要

Background. Delineation of T-cell genes, gene sets, pathways, and T-cell subtypes associated with acute T cell–mediated rejection (TCMR) may improve its management. Methods. We performed bulk RNA-sequencing of 34 kidney allograft biopsies (16 Banff TCMR and 18 no rejection [NR] biopsies) from 34 adult recipients of human kidneys. Computational analysis was performed to determine the differential intragraft expression of T-cell genes at the level of single-gene, gene set, and pathways. Results. T-cell signaling pathway gene sets for plenary T-cell activation were overrepresented in TCMR biopsies compared with NR biopsies. Heightened expression of T-cell signaling genes was validated using external TCMR biopsies. Pro- and anti-inflammatory immune gene sets were enriched, and metabolism gene sets were depleted in TCMR biopsies compared with NR biopsies. Gene signatures of regulatory T cells, Th1 cells, Th2 cells, Th17 cells, T follicular helper cells, CD4 tissue-resident memory T cells, and CD8 tissue-resident memory T cells were enriched in TCMR biopsies compared with NR biopsies. T-cell exhaustion and anergy were also molecular attributes of TCMR. Gene sets associated with antigen processing and presentation, and leukocyte transendothelial migration were overexpressed in TCMR biopsies compared with NR biopsies. Cellular deconvolution of graft infiltrating cells by gene expression patterns identified CD8 T cell to be the most abundant T-cell subtype infiltrating the allograft during TCMR. Conclusions. Our delineation of intragraft T-cell gene expression patterns, in addition to yielding new biological insights, may help prioritize T-cell genes and T-cell subtypes for therapeutic targeting.
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