Precision Subtypes of T Cell-Mediated Rejection Identified by Molecular Profiles.
Precision Subtypes of T Cell-Mediated Rejection Identified by Molecular Profiles.
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DOI：
10.3389/fimmu.2015.00536
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发表时间：
2015
影响因子：
7.3
通讯作者：
Perkins DL
中科院分区：
文献类型：
--
作者：
Kadota PO;Hajjiri Z;Finn PW;Perkins DL
在肾移植受者中，采用脉冲类固醇或抗体方案治疗急性T细胞介导的排斥反应（TCMR）具有不同的结局。一些排斥反应对最初的类固醇脉冲有抵抗力，但对随后的抗体方案有反应。引起不同治疗反应的生物学机制目前尚不清楚。移植肾的组织学检查被认为是诊断急性排斥反应的金标准。建立了Banff分类系统，以规范组织病理学诊断和指导治疗。虽然被广泛使用，但它在病理学家中表现出变异性，并且缺乏指导精确个体化治疗的标准。我们在本研究中分析的同种异体移植物活检中的转录组分析提供了一种开发分子诊断的策略，可以提高诊断精度并有助于个体化治疗的发展。我们的假设是，TCMR的组织学分类包含多种亚型的排斥反应。使用R语言算法来确定统计学显著性、多维标度和分层，我们基于来自分类为TCMR的活检组织的微阵列数据来分析差异基因表达。接下来，我们确定了KEGG功能，蛋白质-蛋白质相互作用网络，基因调控网络，并使用集成数据库ConsesnsusPathDB（CPDB）预测治疗靶点。根据我们的分析，确定了两个不同的活检集群，称为TCMR 01和TCMR 02。尽管有相同的班夫分类，我们确定了1933差异表达的基因之间的两个集群。这些基因进一步分为三大类：TCMR 01和TCMR 02亚型中包含的核心组，以及TCMR 01或TCMR 02特有的基因。TCMR的亚型利用不同的生物学途径，不同的调节网络，并预测对不同的治疗药物的反应。我们的研究结果提出了确定更精确的TCMR分子诊断的方法，这可能成为个性化治疗的基础。
Among kidney transplant recipients, the treatment of choice for acute T cell-mediated rejection (TCMR) with pulse steroids or antibody protocols has variable outcomes. Some rejection episodes are resistant to an initial steroid pulse, but respond to subsequent antibody protocols. The biological mechanisms causing the different therapeutic responses are not currently understood. Histological examination of the renal allograft is considered the gold standard in the diagnosis of acute rejection. The Banff Classification System was established to standardize the histopathological diagnosis and to direct therapy. Although widely used, it shows variability among pathologists and lacks criteria to guide precision individualized therapy. The analysis of the transcriptome in allograft biopsies, which we analyzed in this study, provides a strategy to develop molecular diagnoses that would have increased diagnostic precision and assist the development of individualized treatment. Our hypothesis is that the histological classification of TCMR contains multiple subtypes of rejection. Using R language algorithms to determine statistical significance, multidimensional scaling, and hierarchical, we analyzed differential gene expression based on microarray data from biopsies classified as TCMR. Next, we identified KEGG functions, protein–protein interaction networks, gene regulatory networks, and predicted therapeutic targets using the integrated database ConsesnsusPathDB (CPDB). Based on our analysis, two distinct clusters of biopsies termed TCMR01 and TCMR02 were identified. Despite having the same Banff classification, we identified 1933 differentially expressed genes between the two clusters. These genes were further divided into three major groups: a core group contained within both the TCMR01 and TCMR02 subtypes, as well as genes unique to TCMR01 or TCMR02. The subtypes of TCMR utilized different biological pathways, different regulatory networks and were predicted to respond to different therapeutic agents. Our results suggest approaches to identify more precise molecular diagnoses of TCMR, which could form the basis for personalized treatments.