基于HLA三维结构模建预测GVHD的基础与临床应用研究
|
摘要
异基因造血干细胞移植(allo-HSCT)在临床中应用于对多种恶性血液病的治疗,同时对部分实体瘤、遗传代谢性疾病及自身免疫性疾病等疾患有显著疗效,但受多种因素的影响,不同个体allo-HSCT术后疗效迥异。移植供受者间主要组织相容性复合体(MHC,人类又称为HLA)的错配所引发的急重度移植物抗宿主病(GVHD)是影响allo-HSCT预后的最关键因素之一。2008年美国国家骨髓库(NMDP)制订的allo-HSCT配型手册提出:HLA-A、-B、-Cw、-DRBl四个位点8/8高分辨匹配是allo-HSCT供者选择的最佳标准;无全相合供者时,建议接受HLA-A,-B,-Cw,-DRB1位点中有一个等位基因错配的供者。但对于何种HLA错配是具有相容性的或何种HLA错配不引发急重度GVHD这一问题目前仍没有明确答案。因此,随着HLA不全相合allo-HSCT移植病例的增多,如何评估任意两个不同HLA分子的相容性程度就成为临床移植免疫学与基础医学研究都非常关注和亟待解决的关键问题。
无法判断不完全相合供受者间HLA相容程度时,人们用HLA的功能匹配、序列匹配、结构匹配等评价方式来进行相容性评估。传统的混合淋巴细胞培养(MLC)及群体反应性T细胞(PRT)试验等都依赖体外细胞学实验,结果不稳定且不适于高通量供者筛选,不能评估所有HLA分子间的相容性。目前亦有根据HLA氨基酸序列分析其功能差异的理论,及根据HLA-Pep-TCR复合体间的结合能来分析HLA相似性的报道,遗憾的是这些理论假设大都缺乏临床数据支持而遭到质疑。
针对上述现状,本课题根据蛋白质的结构决定其功能的理论基础,提出基于HLA分子空间结构差异优化选择allo-HSCT最佳供者的设想并进行了如下研究。
鉴于MHC极具多态性、连锁不平衡性及地区民族差异性,我们首先研究了本地区、本民族的HLA基因遗传特征。我们统计了1014例汉族人群HLA-I、-II类经典基因座位的基因频率及单倍型频率,并分析了HLA基因的连锁不平衡、人群及地区分布等群体遗传学特征。结果显示:汉族人群中较为常见的HLA-I、-II类基因有A*02(0.33),B*15(0.14),Cw*03(0.25),DRB1*15(0.170),DQB1*06(0.218)等。HLA-I类基因较为常见的单倍型是A*02-B*46(0.071),A*02-Cw*01 (0.084),B*46-Cw*01 (0.095)等,并且部分单倍型还呈现出显著的连锁不平衡。HLA-II类基因较为常见的单倍型有DRB1*15-DQB1*06-DRB5(0.137)、DRB1*09-DQB1*03 -DRB4(0.129)等,HLA-II类基因单倍型大都高度连锁,但单倍型种类远少于HLA-I类基因。汉族人群与世界其它人种间的HLA基因频率分布存在差异显著,且不同地区的汉族人群HLA基因频率分布亦差异显著。这些资料较系统地分析了我国汉族人群的HLA基因分布特征,为后续有重点的分析HLA分子空间结构差异与GVHD的关系等研究提供了可靠的遗传学资料。
在获得汉族人群HLA-I、-II类基因多态性分布的基础上,我们从HLA分子空间结构差异的角度研究HLA结构与功能相容性。首先用SWISS-MODEL服务器对IMGT/HLA 2010年1月之前公布的HLA-A、-B、-Cw、-DRB1、-DPB1、-DQB1位点4556个HLA分子逐一构建其空间结构;随后用计算机软件VMD计算各位点HLA分子两两间整体均方根偏差(RMSD),以此衡量HLA分子间空间结构差异的大小;并根据HLA分子结构特征,剔除非功能结构区域氨基酸残基差异对计算结果的影响,计算修正后分子间均方根偏差(RMSD-revised)。整理汇总160余万条数据后,我们编制了数据库管理工具,即人类白细胞抗原三维结构匹配打分系统-HLAStrucmark (v1.0),并于2007年获得国家计算机软件著作权登记证书。该打分系统不仅涵盖所有HLA分子间结构差异数据,而且融入了HLA序列比对功能及氨基酸残基特征展示功能,为HLA分子间结构与功能差异的分析提供了丰富、翔实和直观的数据。
随后我们结合16例HLA不完全相合的临床HSCT资料进行分析,结果显示:RMSD或RMSD-revised值均同移植后排斥反应强度呈正相关;也就是说,供受者间错配抗原的结构差异较大,移植后将发生较为强烈的移植排斥反应;反之,错配抗原结构差异较小,移植排斥反应程度则较为轻微。但受限于现有临床病例数量,如果要获得可靠结论还需更大样本资料来进行回顾性分析。
为进一步从分子生物学角度研究HLA分子空间结构差异大小与GVHD发生程度的联系,我们用CTL细胞的交叉识别格局来评价不同HLA分子间的相容性。我们成功设计并构建了中国汉族人群中常见的HLA-B*1502、HLA-B*1518、HLA-B*3503及HLA-B*4403分子重链的真核表达载体,并转染入HLA-I类分子缺陷性细胞株Hmy2.CIR。用转染后的Hmy2.CIR细胞分别体外负载低亲合力结合的EBNA肽,诱导活化T细胞使其成为具有相对抗原特异性的CTL。流式细胞术结果显示,刺激后CD8+T细胞亚群较诱导前显著增多,诱导前CD8+/CD4+比值为4:10,而经诱导后该比例倒置为10:7;TCR Vβ基因扫描显示,T细胞诱导前TCR Vβ各亚群呈典型高斯分布,诱导后T细胞有明显单克隆化形成。这说明经过低亲和力结合的HLA-EBNA肽复合体诱导,体外培养的T细胞出现了特异性CTL的增殖。
随后采用T细胞增殖试验及细胞毒性试验鉴定异基因HLA-肽复合体诱导CTL的交叉识别能力。实验数据显示:HLA-B*4403诱导的CTL对B*1502、B*1518、B*3503诱导的CTL相互间交叉识别能力极弱,但B*1502、B*1518、B*3503诱导的CTL相互间却具有明显交叉识别现象,这说明HLA-B*4403相对于B*1502、B*1518及B*3503具有结构与功能不相容性。
研究还分析了HLA-B*4403、B*1502、B*1518以及B*3503分子间结构差异,HLA-B*4403与B*1502、B*1518、B*3503分子在F抗原结合槽处存在多个氨基酸残基差异,这一方面佐证了F抗原结合槽对抗原呈递以及TCR识别有重要作用,另一方面也说明体外异基因诱导CTL的交叉识别格局可以用于HLA结构与功能差异的评价。以修正均方根偏差(RMSD-revised)表示分子间整体结构差异,结果表明,HLA-B*4403与B*1502、B*1518、B*3503的结构差异值比B*1502、B*1518、B*3503相互间的结构差异值大,表现出结构与功能上的独特性,进一步说明通过HLA三维结构差异评价HLA分子相容性有科学的实验基础支持。
综上所述,本研究在国际上原创性地提出并完善了基于HLA空间结构差异评价HLA相容性,以优化选择最佳HSCT移植供者的新理论,并在临床HSCT患者中得到了初步证实;建立并完善了一种以CTL对异基因HLA交叉识别格局来分析HLA功能相似性的体外评价模式,该评价模式对研究HLA相容性提供了有效手段,为HLA相容性的理论研究与应用研究搭建一个科学、可行的体外技术平台,为今后HLA相容性研究提供可靠的量化数据。相信通过实验数据与临床移植病例资料的不断累积,定能绘制出完整的HLA分子相容性图谱,为异基因造血干细胞移植以及器官移植筛选最佳供者提供新思路和技术支撑。
Allogeneic haematopoietic stem cell transplantation (allo-HSCT) is a safe and effective method to cure a range of acute leukemia, and has a significant effectiveness for solid tumors, inherited metabolic diseases, and autoimmune diseases, et al. Allo-HSCT has widely applied prospect in clinical practice., while the curative effect of it is various for different individuals because of many factors. The most important factor is the severe acute graft-versus-host disease (GVHD) induced by major histocompatibility complex (MHC, HLA in human) mismatching of donor-recipient. The guidelines for unrelated adult donor hematopoietic cell transplants, based on retrospective analysis of large-sample clinical data, revised by the National Marrow Donor Program (NMDP) 2008 recommend that when possible, patients and unrelated donors should be matched at high resolution for HLA-A, -B, -C, and -DRB1 locus, and the eight alleles should be defined using DNA-based testing. When no perfect match donor was available, NMDP accept one allele mismatch at HLA-A, -B, -Cw, or -DRB1 locus as well. But there are no explicit answers to date about what specifical kind of HLA mismatch should be accepted, or what kind of HLA mismatch do not induce severe acute GVHD. It has always been the concerned issue in both clinical medicine and basic research fields how to assess the matching degree of any two HLA molecules, with HLA mismatch allo-HSCT becoming popular.
When we couldn’t predict the compatibility between the transplant recipient and the HLA mismatched donor based on the results of HLA gene typing, we had to resort to other evaluation methods, such as HLA functional matching, sequence matching, and structural matching, et al. The traditional mixed lymphocyte culture (MLC) assay and panel-reactive T cells (PRT) assay are individual assessment of the compatibility between HSCT recipients and the potential donors pre-transplant. And the cytology experiments results in vitro, on which those assessments are dependent, are variable. Therefore, neither assay is suitable for high-throughput screening of HSCT donors and for evaluating the compatibility of all HLA molecules. There’s a rating system of HLA similarity based on differences of sequence, which is still not supported by retrospective clinical analysis very well. Recently there’s another hypothesis to evaluate the compatibility of HLA molecules, which is awaited to predict the impact of HLA mismatch on HSCT outcomes based on HLA-Pep-TCR binding energy. Regretfully, lacking of clinical supports has aroused fierce opposition.
According to the basic concept that the protein structure determines its function, a novel strategy to optimize allo-HSCT donor selecting based on differences of HLA molecules three-dimensional structure was proposed. We analyzed the functional compatibility of allogeneic HLA molecules through the differences of structure.
Because of the extremely polymorphism, linkage disequilibrium, and national/regional diversity of MHC, the genetic polymorphism features of HLA in our own area and our own nation must be made clear firstly. HLA-A, -B, -Cw, -DRB1, -DQB1 and DRB3/4/5 loci were genotyped in 1014 Chinese Han population. Their gene frequencies, haplotype frequencies and linkage disequilibrium were also analyzed. The genetic distances between different populations were analyzed to evaluate their genetic relationships.Among all the detected HLA genes, A*02(0.33), B*15(0.14), Cw*03(0.25), DRB1*15(0.170), DQB1*06(0.218) are the popular gene groups distributing in Chinese Han population. A*02-B*46(0.071), A*02-Cw*01 (0.084), and B*46-Cw*01(0.095) are the predominant haplotypes in HLA I genes. Additionally, some of those haplotypes are statistically significant with strong linkage disequilibrium. In addition, DRB1*15 -DQB1*06 -DRB5 (0.137), DRB1*09 -DQB1*03 -DRB4 (0.129) are the main haplotypes in HLA II genes. Almost all HLA II gene haplotypes are in strong linkage disequilibrium, but the numbers of the varieties of HLA II gene haplotypes are less then HLA I genes. There were significant differences of HLA genetic distribution between different local Han populations, and similarly, the identical results were also found in the different ethnic populations of the world. With respect to genetic distance, distances within Han population of different areas were obviously smaller than that of different ethnic groups. All of these results reveal systemically the genetic polymorphism feature of Chinese Han population, which will be the basic reference data for the analysis of HLA structure differences and GVHD in following studies.
Based on the HLA genes distribution results of Chinese Han population, we evaluated HLA molecule differences from the point of HLA structures, and discussed the relationship of HLA structure differences of donor-recipient and GVHD after allo-HSCT according to clinical data. Firstly, structures of all the 4556 molecules including HLA-A, -B, -Cw, -DRB1, -DPB1 and -DQB1 released from IMGT/HLA database up to Jan 2010 were modeled one by one with SWISS-MODEL server. And then the overall root mean square deviations (RMSD), which were used to evaluate the degree of structure differences of HLA molecules pairs in each locus, were calculated by Visual Molecular Dynamics (VMD) software aided with computer programming. The parameters of RMSD calculation were revised according to HLA molecular structure feature, and the amino acids residues located inα1/α2 domain (HLA I) orα1 domain (HLA II) interacting with neither peptide nor TCR were excluded in the calculation of RMSD-revised. A database management system integrating with HLA sequence alignment can also show the features of mutation amino acid residues was built to collect and sort out all the 1.6 million data. This system has been registered as HLA structure matching system (HLAStrucmark, v1.0), and obtained certificate for the registration of computer software in 2007.
Then 16 HSCT data with HLA mismatches between related donor-recipient show that RMSD or RMSD-revised values is positive correlate to the degree of allograft rejection. That is, the more differences of HLA structure between donor-recipient are, the more severe rejection occurs after HSCT. In contrast, the more similar mismatched HLA molecules between donor-recipient are, the less rejection happens. However, retrospective case-control studies of large samples are better to draw more reliable conclusions when more samples are available.
To validate that the level of HLA structure difference is correlated with the degree of GVHD with biology experiment data,we evaluated the compatibility of different HLA molecules with the cross reaction patterns of allogeneic reaction CTLs induced by different HLA-Pep complex. Firstly, a series of eukaryotic expression vectors inserted with full-length HLA-B cDNA gene were constructed, including HLA-B*1502, HLA-B*1518, HLA-B*3503 and HLA-B*4403 ,the popular gene type in Chinese Han population. The HLA I deficient cells Hmy2.CIR was transduced with HLA-B expression vectors using Amaxa Nucleofection system. Hmy2.CIR cells expressing HLA-B*1502, HLA-B*1518, HLA-B*3503 or HLA-B*4403 molecules pulsed with a nonameric consensus peptide (FLRGRAYGL) derived from Epstein-Barr virus, were used as APC cells to induce antigen specific CTLs respectively in vitro. And there were low binding affinity between the nonameric peptide and HLA-B molecules expressed on membrane of Hmy2.CIR. The FACS results indicated that percentage of CD8+ T lymphocytes subgroups up-regulated significantly after Hmy2.CIR inducing, and CD8+/CD4+ ratio converted to 10:7 compared with 4:10 before induction. Genes of T cell receptorβvariable region (TCRBV) families were scanned to observe the clonal changes of T cells before and after the induction and cultivation of T lymphocytes. The gene scan results showed that the 24 TCRBV families remained polyclonal before Hmy2.CIR inducing, while presented as oligoclonal distribution after inducing. These FACS and gene scan results suggested that HLA-B molecules pulsed with low binding affinity epitope peptide could induce clonal CTLs activation in vitro.
The activated CTL cells induced in vitro exhibited various cross reactions while co-culturing with target cells expressing HLA-B*1502, HLA-B*1518, HLA-B*3503, HLA-B*4403 molecules pulsed with EBNA epitope peptide respectively. The cross-reaction patterns of different CTLs were distinctive in proliferation test and cytotoxicity test. The activated CTLs induced by Hmy2.CIR-B*4403-Pep exhibited unique HLA restriction, while CTLs induced by HLA-B*1502, B*1518 or B*3503 exhibited significant cross-reaction to each target cells. According to these data, HLA-B*4403 was un-compatibility with HLA-B*1502, B*1518, B*3503 in aspect of HLA restriction to TCR.
The sequence alignment analysis show that there are many amino acid residue difference in the position of F epitope binding pocket between HLA-B*4403 and HLA-B*1502, B*1518, B*3503. The F pocket located in antigen binding groove contributes a lot to epitope anchoring and TCR recognition, and this point of view has been emphasized here. On the other hand, these results confirm the feasibility of the evaluation method which analyze HLA compatibility based on the CTLs cross-reaction patterns. The value of RMSD-revised between B*4403 and the other three HLA-B molecules were larger than the value of RMSD-revised within B*1502, B*1518, and B*3503. Data above suggested that HLA-B*4403 show somewhat unique feature comparing with the other three HLA-B molecules, and the results confirm the feasibility of the HLA compatibility evaluation method based on the HLA 3D structure analysis.
In present study, we first explored and improved a novel strategy for evaluating HLA compatibility based on analysis of three-dimensional structure of HLA, which could optimize allo-HSCT donor selecting. This evaluating strategy has been affirmed by clinical data primarily. In addtion, we also created a pattern for HLA functional compatibility evaluation in vitro based on the cross-reaction scheme of CTLs, which could provid a scientific and effective platform for studying HLA compatibility in vitro. With the accumulation or collection of such research data, a complex relationship map of HLA similarity or compatibility could be built in the future, which would be helpful for the optimization allo-HSCT or organ donor selecting.
无法判断不完全相合供受者间HLA相容程度时,人们用HLA的功能匹配、序列匹配、结构匹配等评价方式来进行相容性评估。传统的混合淋巴细胞培养(MLC)及群体反应性T细胞(PRT)试验等都依赖体外细胞学实验,结果不稳定且不适于高通量供者筛选,不能评估所有HLA分子间的相容性。目前亦有根据HLA氨基酸序列分析其功能差异的理论,及根据HLA-Pep-TCR复合体间的结合能来分析HLA相似性的报道,遗憾的是这些理论假设大都缺乏临床数据支持而遭到质疑。
针对上述现状,本课题根据蛋白质的结构决定其功能的理论基础,提出基于HLA分子空间结构差异优化选择allo-HSCT最佳供者的设想并进行了如下研究。
鉴于MHC极具多态性、连锁不平衡性及地区民族差异性,我们首先研究了本地区、本民族的HLA基因遗传特征。我们统计了1014例汉族人群HLA-I、-II类经典基因座位的基因频率及单倍型频率,并分析了HLA基因的连锁不平衡、人群及地区分布等群体遗传学特征。结果显示:汉族人群中较为常见的HLA-I、-II类基因有A*02(0.33),B*15(0.14),Cw*03(0.25),DRB1*15(0.170),DQB1*06(0.218)等。HLA-I类基因较为常见的单倍型是A*02-B*46(0.071),A*02-Cw*01 (0.084),B*46-Cw*01 (0.095)等,并且部分单倍型还呈现出显著的连锁不平衡。HLA-II类基因较为常见的单倍型有DRB1*15-DQB1*06-DRB5(0.137)、DRB1*09-DQB1*03 -DRB4(0.129)等,HLA-II类基因单倍型大都高度连锁,但单倍型种类远少于HLA-I类基因。汉族人群与世界其它人种间的HLA基因频率分布存在差异显著,且不同地区的汉族人群HLA基因频率分布亦差异显著。这些资料较系统地分析了我国汉族人群的HLA基因分布特征,为后续有重点的分析HLA分子空间结构差异与GVHD的关系等研究提供了可靠的遗传学资料。
在获得汉族人群HLA-I、-II类基因多态性分布的基础上,我们从HLA分子空间结构差异的角度研究HLA结构与功能相容性。首先用SWISS-MODEL服务器对IMGT/HLA 2010年1月之前公布的HLA-A、-B、-Cw、-DRB1、-DPB1、-DQB1位点4556个HLA分子逐一构建其空间结构;随后用计算机软件VMD计算各位点HLA分子两两间整体均方根偏差(RMSD),以此衡量HLA分子间空间结构差异的大小;并根据HLA分子结构特征,剔除非功能结构区域氨基酸残基差异对计算结果的影响,计算修正后分子间均方根偏差(RMSD-revised)。整理汇总160余万条数据后,我们编制了数据库管理工具,即人类白细胞抗原三维结构匹配打分系统-HLAStrucmark (v1.0),并于2007年获得国家计算机软件著作权登记证书。该打分系统不仅涵盖所有HLA分子间结构差异数据,而且融入了HLA序列比对功能及氨基酸残基特征展示功能,为HLA分子间结构与功能差异的分析提供了丰富、翔实和直观的数据。
随后我们结合16例HLA不完全相合的临床HSCT资料进行分析,结果显示:RMSD或RMSD-revised值均同移植后排斥反应强度呈正相关;也就是说,供受者间错配抗原的结构差异较大,移植后将发生较为强烈的移植排斥反应;反之,错配抗原结构差异较小,移植排斥反应程度则较为轻微。但受限于现有临床病例数量,如果要获得可靠结论还需更大样本资料来进行回顾性分析。
为进一步从分子生物学角度研究HLA分子空间结构差异大小与GVHD发生程度的联系,我们用CTL细胞的交叉识别格局来评价不同HLA分子间的相容性。我们成功设计并构建了中国汉族人群中常见的HLA-B*1502、HLA-B*1518、HLA-B*3503及HLA-B*4403分子重链的真核表达载体,并转染入HLA-I类分子缺陷性细胞株Hmy2.CIR。用转染后的Hmy2.CIR细胞分别体外负载低亲合力结合的EBNA肽,诱导活化T细胞使其成为具有相对抗原特异性的CTL。流式细胞术结果显示,刺激后CD8+T细胞亚群较诱导前显著增多,诱导前CD8+/CD4+比值为4:10,而经诱导后该比例倒置为10:7;TCR Vβ基因扫描显示,T细胞诱导前TCR Vβ各亚群呈典型高斯分布,诱导后T细胞有明显单克隆化形成。这说明经过低亲和力结合的HLA-EBNA肽复合体诱导,体外培养的T细胞出现了特异性CTL的增殖。
随后采用T细胞增殖试验及细胞毒性试验鉴定异基因HLA-肽复合体诱导CTL的交叉识别能力。实验数据显示:HLA-B*4403诱导的CTL对B*1502、B*1518、B*3503诱导的CTL相互间交叉识别能力极弱,但B*1502、B*1518、B*3503诱导的CTL相互间却具有明显交叉识别现象,这说明HLA-B*4403相对于B*1502、B*1518及B*3503具有结构与功能不相容性。
研究还分析了HLA-B*4403、B*1502、B*1518以及B*3503分子间结构差异,HLA-B*4403与B*1502、B*1518、B*3503分子在F抗原结合槽处存在多个氨基酸残基差异,这一方面佐证了F抗原结合槽对抗原呈递以及TCR识别有重要作用,另一方面也说明体外异基因诱导CTL的交叉识别格局可以用于HLA结构与功能差异的评价。以修正均方根偏差(RMSD-revised)表示分子间整体结构差异,结果表明,HLA-B*4403与B*1502、B*1518、B*3503的结构差异值比B*1502、B*1518、B*3503相互间的结构差异值大,表现出结构与功能上的独特性,进一步说明通过HLA三维结构差异评价HLA分子相容性有科学的实验基础支持。
综上所述,本研究在国际上原创性地提出并完善了基于HLA空间结构差异评价HLA相容性,以优化选择最佳HSCT移植供者的新理论,并在临床HSCT患者中得到了初步证实;建立并完善了一种以CTL对异基因HLA交叉识别格局来分析HLA功能相似性的体外评价模式,该评价模式对研究HLA相容性提供了有效手段,为HLA相容性的理论研究与应用研究搭建一个科学、可行的体外技术平台,为今后HLA相容性研究提供可靠的量化数据。相信通过实验数据与临床移植病例资料的不断累积,定能绘制出完整的HLA分子相容性图谱,为异基因造血干细胞移植以及器官移植筛选最佳供者提供新思路和技术支撑。
Allogeneic haematopoietic stem cell transplantation (allo-HSCT) is a safe and effective method to cure a range of acute leukemia, and has a significant effectiveness for solid tumors, inherited metabolic diseases, and autoimmune diseases, et al. Allo-HSCT has widely applied prospect in clinical practice., while the curative effect of it is various for different individuals because of many factors. The most important factor is the severe acute graft-versus-host disease (GVHD) induced by major histocompatibility complex (MHC, HLA in human) mismatching of donor-recipient. The guidelines for unrelated adult donor hematopoietic cell transplants, based on retrospective analysis of large-sample clinical data, revised by the National Marrow Donor Program (NMDP) 2008 recommend that when possible, patients and unrelated donors should be matched at high resolution for HLA-A, -B, -C, and -DRB1 locus, and the eight alleles should be defined using DNA-based testing. When no perfect match donor was available, NMDP accept one allele mismatch at HLA-A, -B, -Cw, or -DRB1 locus as well. But there are no explicit answers to date about what specifical kind of HLA mismatch should be accepted, or what kind of HLA mismatch do not induce severe acute GVHD. It has always been the concerned issue in both clinical medicine and basic research fields how to assess the matching degree of any two HLA molecules, with HLA mismatch allo-HSCT becoming popular.
When we couldn’t predict the compatibility between the transplant recipient and the HLA mismatched donor based on the results of HLA gene typing, we had to resort to other evaluation methods, such as HLA functional matching, sequence matching, and structural matching, et al. The traditional mixed lymphocyte culture (MLC) assay and panel-reactive T cells (PRT) assay are individual assessment of the compatibility between HSCT recipients and the potential donors pre-transplant. And the cytology experiments results in vitro, on which those assessments are dependent, are variable. Therefore, neither assay is suitable for high-throughput screening of HSCT donors and for evaluating the compatibility of all HLA molecules. There’s a rating system of HLA similarity based on differences of sequence, which is still not supported by retrospective clinical analysis very well. Recently there’s another hypothesis to evaluate the compatibility of HLA molecules, which is awaited to predict the impact of HLA mismatch on HSCT outcomes based on HLA-Pep-TCR binding energy. Regretfully, lacking of clinical supports has aroused fierce opposition.
According to the basic concept that the protein structure determines its function, a novel strategy to optimize allo-HSCT donor selecting based on differences of HLA molecules three-dimensional structure was proposed. We analyzed the functional compatibility of allogeneic HLA molecules through the differences of structure.
Because of the extremely polymorphism, linkage disequilibrium, and national/regional diversity of MHC, the genetic polymorphism features of HLA in our own area and our own nation must be made clear firstly. HLA-A, -B, -Cw, -DRB1, -DQB1 and DRB3/4/5 loci were genotyped in 1014 Chinese Han population. Their gene frequencies, haplotype frequencies and linkage disequilibrium were also analyzed. The genetic distances between different populations were analyzed to evaluate their genetic relationships.Among all the detected HLA genes, A*02(0.33), B*15(0.14), Cw*03(0.25), DRB1*15(0.170), DQB1*06(0.218) are the popular gene groups distributing in Chinese Han population. A*02-B*46(0.071), A*02-Cw*01 (0.084), and B*46-Cw*01(0.095) are the predominant haplotypes in HLA I genes. Additionally, some of those haplotypes are statistically significant with strong linkage disequilibrium. In addition, DRB1*15 -DQB1*06 -DRB5 (0.137), DRB1*09 -DQB1*03 -DRB4 (0.129) are the main haplotypes in HLA II genes. Almost all HLA II gene haplotypes are in strong linkage disequilibrium, but the numbers of the varieties of HLA II gene haplotypes are less then HLA I genes. There were significant differences of HLA genetic distribution between different local Han populations, and similarly, the identical results were also found in the different ethnic populations of the world. With respect to genetic distance, distances within Han population of different areas were obviously smaller than that of different ethnic groups. All of these results reveal systemically the genetic polymorphism feature of Chinese Han population, which will be the basic reference data for the analysis of HLA structure differences and GVHD in following studies.
Based on the HLA genes distribution results of Chinese Han population, we evaluated HLA molecule differences from the point of HLA structures, and discussed the relationship of HLA structure differences of donor-recipient and GVHD after allo-HSCT according to clinical data. Firstly, structures of all the 4556 molecules including HLA-A, -B, -Cw, -DRB1, -DPB1 and -DQB1 released from IMGT/HLA database up to Jan 2010 were modeled one by one with SWISS-MODEL server. And then the overall root mean square deviations (RMSD), which were used to evaluate the degree of structure differences of HLA molecules pairs in each locus, were calculated by Visual Molecular Dynamics (VMD) software aided with computer programming. The parameters of RMSD calculation were revised according to HLA molecular structure feature, and the amino acids residues located inα1/α2 domain (HLA I) orα1 domain (HLA II) interacting with neither peptide nor TCR were excluded in the calculation of RMSD-revised. A database management system integrating with HLA sequence alignment can also show the features of mutation amino acid residues was built to collect and sort out all the 1.6 million data. This system has been registered as HLA structure matching system (HLAStrucmark, v1.0), and obtained certificate for the registration of computer software in 2007.
Then 16 HSCT data with HLA mismatches between related donor-recipient show that RMSD or RMSD-revised values is positive correlate to the degree of allograft rejection. That is, the more differences of HLA structure between donor-recipient are, the more severe rejection occurs after HSCT. In contrast, the more similar mismatched HLA molecules between donor-recipient are, the less rejection happens. However, retrospective case-control studies of large samples are better to draw more reliable conclusions when more samples are available.
To validate that the level of HLA structure difference is correlated with the degree of GVHD with biology experiment data,we evaluated the compatibility of different HLA molecules with the cross reaction patterns of allogeneic reaction CTLs induced by different HLA-Pep complex. Firstly, a series of eukaryotic expression vectors inserted with full-length HLA-B cDNA gene were constructed, including HLA-B*1502, HLA-B*1518, HLA-B*3503 and HLA-B*4403 ,the popular gene type in Chinese Han population. The HLA I deficient cells Hmy2.CIR was transduced with HLA-B expression vectors using Amaxa Nucleofection system. Hmy2.CIR cells expressing HLA-B*1502, HLA-B*1518, HLA-B*3503 or HLA-B*4403 molecules pulsed with a nonameric consensus peptide (FLRGRAYGL) derived from Epstein-Barr virus, were used as APC cells to induce antigen specific CTLs respectively in vitro. And there were low binding affinity between the nonameric peptide and HLA-B molecules expressed on membrane of Hmy2.CIR. The FACS results indicated that percentage of CD8+ T lymphocytes subgroups up-regulated significantly after Hmy2.CIR inducing, and CD8+/CD4+ ratio converted to 10:7 compared with 4:10 before induction. Genes of T cell receptorβvariable region (TCRBV) families were scanned to observe the clonal changes of T cells before and after the induction and cultivation of T lymphocytes. The gene scan results showed that the 24 TCRBV families remained polyclonal before Hmy2.CIR inducing, while presented as oligoclonal distribution after inducing. These FACS and gene scan results suggested that HLA-B molecules pulsed with low binding affinity epitope peptide could induce clonal CTLs activation in vitro.
The activated CTL cells induced in vitro exhibited various cross reactions while co-culturing with target cells expressing HLA-B*1502, HLA-B*1518, HLA-B*3503, HLA-B*4403 molecules pulsed with EBNA epitope peptide respectively. The cross-reaction patterns of different CTLs were distinctive in proliferation test and cytotoxicity test. The activated CTLs induced by Hmy2.CIR-B*4403-Pep exhibited unique HLA restriction, while CTLs induced by HLA-B*1502, B*1518 or B*3503 exhibited significant cross-reaction to each target cells. According to these data, HLA-B*4403 was un-compatibility with HLA-B*1502, B*1518, B*3503 in aspect of HLA restriction to TCR.
The sequence alignment analysis show that there are many amino acid residue difference in the position of F epitope binding pocket between HLA-B*4403 and HLA-B*1502, B*1518, B*3503. The F pocket located in antigen binding groove contributes a lot to epitope anchoring and TCR recognition, and this point of view has been emphasized here. On the other hand, these results confirm the feasibility of the evaluation method which analyze HLA compatibility based on the CTLs cross-reaction patterns. The value of RMSD-revised between B*4403 and the other three HLA-B molecules were larger than the value of RMSD-revised within B*1502, B*1518, and B*3503. Data above suggested that HLA-B*4403 show somewhat unique feature comparing with the other three HLA-B molecules, and the results confirm the feasibility of the HLA compatibility evaluation method based on the HLA 3D structure analysis.
In present study, we first explored and improved a novel strategy for evaluating HLA compatibility based on analysis of three-dimensional structure of HLA, which could optimize allo-HSCT donor selecting. This evaluating strategy has been affirmed by clinical data primarily. In addtion, we also created a pattern for HLA functional compatibility evaluation in vitro based on the cross-reaction scheme of CTLs, which could provid a scientific and effective platform for studying HLA compatibility in vitro. With the accumulation or collection of such research data, a complex relationship map of HLA similarity or compatibility could be built in the future, which would be helpful for the optimization allo-HSCT or organ donor selecting.
引文
1. Shlomchik WD. Graft-versus-host disease. Nat Rev Immunol, 2007, 7:340-52.
2. Jacobsohn DA, Vogelsang GB. Acute graft versus host disease. Orphanet J Rare Dis, 2007, 35:1-9.
3. Morris ES, Hill GR. Advances in the understanding of acute graft-versus-host disease. Br J Haematol, 2007, 137(1):3-19.
4. Morishima Y, Sasazuki T, Inoko H, et al. The clinical significant of human leukocyte antigen (HLA) allele compatibility in patients receiving a marrow transplant from serologically HLA-A, HLA-B, and HLA-DR matched unrelated donors. Blood, 2002, 99:4200-4206.
5. Flomenberg N, Baxter LA, Confer D, et a1. Impact of HLA class I and II high resolution matching on outcomes of unrelated donor bone marrow transplantation: HLA-C mismatching is associated with a strong adverse effect on transplantation outcome. Blood, 2004, 104(7):1923-1930.
6. Bray AR, Hurley KC, Kamani RN, et al. National marrow donor program HLA matching guidelines for unrelated adult donor hematopoietic cell transplantation. Biol Blood Marrow Tr, 2008, 14: 45-53
7. Kawase T, Matsuo K, Kashiwase K, et al. HLA mismatch combinations associated with decreased risk of relapse: implications for the molecular mechanism. Blood. 2009, 113(12):2851-8.
8. Oudshoorn M, Doxiadis II, Berg PM et al. Functional vs structural matching: can the CTLp test be replaced by HLA allele typing? Hum Immunol 2002; 63:176–184.
9. Spencer A, Brookes PA, Kaminski E et al. Cytotoxic T lymphocyte precursor frequency analyses in bone marrow transplantation with volunteer unrelated donors. Value in donor selection. Transplantation 1995; 59: 1302–1308.
10. Keeve CA, Passweg J, Kawanishi Y et al. Association of donor-derivedhost-reactive cytolytic and helper T cells with outcome following alternative donor T cell-depleted bone marrow transplantation. Bone Marrow Transpl. 1997;19: 1001–1009.
11. Meer A, Joosten I, Schattenberg AV. et al. Cytotoxic T-lymphocyte precursor frequency (CTLp-f) as a tool for distinguishing permissible from non-permissible class I mismatches in T-cell-depleted allogeneic bone marrow transplantation. Br J Haematol. 2000, 111:685–694.
12. Dolezalova L, Vrana M, Dobrovolna M, et al. Cytotoxic T lymphocyte precursor frequency analysis in the selection of HLA matched unrelated donors for hematopoietic stem cell transplantation: the correlation of CTLp frequency with HLA class I genotyping and aGVHD development. Neoplasma. 2002, 49:26–32.
13. Iacomini J, Sayegh MH. Measuring T cell alloreactivity to predict kidney transplant outcomes: are we there yet? J Am Soc Nephrol. 2006.17(2):328-30.
14. Andree H, Nickel P, Nasiadko C, et al. Identification of dialysis patients with panel-reactive memory T cells before kidney transplantation using an allogeneic cell bank. J Am Soc Nephrol. 2006, 17(2):573-80.
15. Poggio ED, Clemente M, Hricik DE, et al. Panel of reactive T cells as a measurement of primed cellular alloimmunity in kidney transplant candidates. J Am Soc Nephrol. 2006, 17(2):564-72.
16. Oudshoorn M, Doxiadis II, Berg PM et al. Functional vs structural matching: can the CTLp test be replaced by HLA allele typing? Hum Immunol 2002; 63:176–184.
17. Elsner HA. Blasczyk R. Sequence similarity matching: proposal of a structure-based rating system for bone marrow transplantation. Eur J Imm. 2002. 29:229–236.
18. Elsner HA, DeLuca D, Strub J. et al. HistoCheck: rating of HLA class I and II mismatches by an internet-based software tool. Bone Marrow Transpl. 2004. 33:165–169.
19. Shaw BE, Barber LD, Madrigal JA. et al. Scoring for HLA matching? A clinical test of HistoCheck. Bone Marrow Transplantation. Bone Marrow Transpl. 2004. 34:367–368.
20. Sijpkens YW, Doxiadis II, De JW, et al. Sharing cross-reactive groups of MHC class I improves long-term graft survival. Kidney Int. 1999, 56(5):1920-7.
21. Hwang SH, Oh HB, Shin ES, et al. Influence of mismatching of HLA cross-reactive groups on cadaveric kidney transplantation. Transplant Proc. 2005, 37(10):4194-8.
22. Wade J A, Hurley CK, Takemoto SK, et al. HLA mismatching within or outside of cross-reactive groups (CREGs) is associated with similar outcomes after unrelatedhematopoietic stem cell transplantation. Blood, 2007, 109(9):4064-70.
23. Duquesnoy RJ, Marrari M. Correlations between Terasaki's HLA class I epitopes and HLAMatchmaker-defined eplets on HLA-A, -B and -C antigens. Tissue Antigens. 2009, 74(2):117-33.
24. Silva E, Alba A, Castro A, et al. Evaluation of HLA Matchmaker Compatibility as Predictor of Graft Survival and Presence of Anti-HLA Antibodies.Transplant Proc. 2010,42(1):266-269
25. Matthias S, Robert S, Hans GP, et al. Graft-versus-host disease after allogeneic hematopoietic stem cell transplantation induces a CD8+ T cell-mediated graft-versus-tumor effect that is independent of the recognition of alloantigenic tumor targets. Blood, 2004, 104 (4):1210-1216.
26. Dudkiewicz M, Malanowski P, Czerwin J, et al. An Approach to Predicting Hematopoietic Stem Cell Transplantation Outcome Using HLA-Mismatch Information Mapped on Protein Structure Data. Biol Blood Marrow Tr. 2009. 15(9):1014-1025.
27. Hurley CK, Oudshoorn M, and Setterholm M. et al. Re: An Approach to Predicting HSCT Outcome Using HLA-Mismatch Information Mapped on Protein Structure Data. Biol Blood Marrow Tr. 2010. In press.
28. Armstrong KM, Piepenbrink KH, Baker BM. Conformational changes and flexibility in T-cell receptor recognition of peptide-MHC complexes. Biochem J. 2008. 415(2):183-96.
29. Lee JK, Stewart JG, Dong T, et al. T cell cross-reactivity and conformational changes during TCR engagement. J Exp Med. 2004. 200(11):1455-66.
30. Baker BM, Turner RV, Gagnon SJ, et al. Identification of a crucial energetic footprint on the alpha1 helix of human histocompatibility leukocyte antigen (HLA)-A2 that provides functional interactions for recognition by tax peptide/HLA-A2-specific T cell receptors. J Exp Med. 2001. 193(5):551-62.
31.孙玉英,奚永志.防治移植物抗宿主病的新策略.中国输血杂志. 2003.16(5):364-8.
32.韩红星,孔繁华,奚永志,等.利用供受体HLA三维结构差异快速预测GVHD.中国输血杂志.2003.16(3):154-6.
33. Lim DG, Slavik JM, Bourcier K, et al. Allelic variation of MHC structure alters peptide ligands to induce atypical partial agonistic CD8+ T cell function. J Exp Med. 2003. 198(1):99-109.
34. Fleur ET, Diah E, Anthony W. et al. The immunogenicity of a viral cytotoxic T cellepitope is controlled by its MHC-bound conformation. J Exp Med. 2005. 202(9):1249–1260.
1. Beck S, Geraghty D, Inoko H, Rowen L. Complete sequence and gene map of a human major histocompatibility complex. Nature, 1999, 401:921-923.
2.谢毓滨,王赤林,李双,等.实用预防医学.湖南地区人群HLA_ABDRB1等位基因多态性的研究. 2006 ,13: 4-8
3.李彩丽,唐朝晖,方丽华,等.兰州地区汉族人群HLA-A、-B和DRB1等位基因多态性分析.中华医学遗传学杂志. 2006, 23: 89-91
4.陈阳,李剑平.辽宁汉族人群HLA-B等位基因多态性的分布.中华医学遗传学杂志. 2006, 23: 461-462
5.戴云鹏,阎文英,沈柏均,等.山东地区汉族脐血供者HLA_I等位基因多态性研究.中国小儿血液与肿瘤杂志. 2006. 11: 244-248
6.兰涛,张德梅,王桂琴.山西汉族人群HLA-A、-B、-DRB1基因多态性研究.中华医学遗传学杂志. 2005, 22: 583-584
7.梁文飚,薛敏,潘芹芹,等.中华江苏骨髓库人群HLA--I类抗原的PCR-SSP分型.中国输血杂志. 2005. 18: 199-201
8.吴国光,邓志辉,高素青,等. 6965名汉族骨髓供者HLA多态性分析.中国血液学杂志. 2004, 25: 473-477
9. Shaw CK, Chang TK, Chen SN, et al. HLA polymorphism and probability of finding HLA-matched unrelated marrow donors for Chinese in Taiwan. Tissue Antigens. 1997, 50: 610-619
10.谭建明,周永昌,唐孝达主编.组织配型技术与临床应用.人民卫生出版社, 2002, 62-131
11.吴国光,邓志辉,高素青,等. 6965名汉族骨髓供者HLA多态性分析.中华血液学杂志. 2004, 25:473-477.
12.马红京,尹晓林,郭坤元,等.广东汉族人群HLA-I、II基因多态性及单倍型分析.中华医学遗传学杂志. 2005,22:467-469.
13.高素青,吴国光,李兴茂,等.安徽汉族HLA-A、-B、-DRB1基因多态性和单倍型的分布特征.临床输血与检验. 2005,7:161-169.
14.林琳,高小江,祝文华,等.用DNA分型研究中国人HLA-A、-C、-B的部分单倍型.中华微生物学和免疫学杂志.1999,19:152.
15.杜若甫,肖春杰, Cavalli LL.用38个基因座的基因频率计算中国人群间遗传距离.中国科学:C辑. 1998, 28: 83-89
16. Guethlein LA, Older AM, Abi-Rached L, et al. Evolution of killer cell Ig-like receptor (KIR) genes: definition of an orangutan KIR haplotype reveals expansion of lineage III KIR associated with the emergence of MHC-C. J Immunol. 2007. 179: 491-504
17. Morishima Y, Sasazuki T, Inoko H, et al. The clinical significance of human leukocyte antigen allele compatibility in patients receiving a marrow transplant from serologically HLA-A, HLA-B, and HLA-DR matched unrelated donors. Blood, 2002, 99: 4200-6
1. Heemskerk MB, Roelen DL, Dankers MK, et al. M. Allogeneic MHC class I molecules with numerous sequence differences do not elicit a CTL response. Hum Immunol. 2005.66(9):969-76.
2. Robinson J, Waller MJ, Parham P, et al. IMGT/HLA and IMGT/MHC: sequence databases for the study of the major histocompatibility complex. Nucleic Acids Research. 2003.31:311-314.
3. Arnold K, Bordoli L, Kopp J, et al.The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics. 2006.22:195-201.
4. Humphrey W, Dalke A, Schulten K. VMD - Visual Molecular Dynamics. J Molec Graphics. 1996. 14(1):33-8.
5. Saper MA, Bjorkman PJ, Wiley DC. Refined structure of the human histocompatibility antigen HLA-A2 at 2.6A resolution. J Mol Biol. 1991. 219: 277–319.
6. Garboczi DN, Ghosh P, Utz U, et al. Structure of the complex between human T-cell receptor, viral peptide and HLA-A2. Nature. 1996. 384:134–141.
7. Thomas E, Storb R, Clift RA, et al. Bone-marrow transplan-tation. N Engl J Med, 1975, 292:832-843.
8. Przepiorka D, Weisdorf D, Martin P ,et al . 1994 Consensus conference on acute GVHD grading.Bone Marrow Transplant ,1995 ,15 :8252828.
9. Dehn J, Arora M, Spellman S, et al. Unrelated Donor Hematopoietic Cell Transplantation: Factors Associated with a Better HLA Match. Biology of Blood and Marrow Transplantation. 2008. 14(12):1334-1340.
10. Nicola G, Renate A, Angelika B, et al. Treatment of Adult ALL According to Protocols of the German Multicenter Study Group for Adult ALL (GMALL). Acute Leukemias.2008.14(6):167-176.
11. Lee SJ, Klein J, Haagenson M,et al. High-resolution donor-recipient HLA matching contributes to the success of unrelated donor marrow transplantation. Blood. 2007. 110(13):4576-83.
12. Davis J, Buck K, Dorr L, et al. Evaluation of unrelated donor search strategy proficiencies. Biology of Blood and Marrow Transplantation. 2006. 12(2)31-31.]
13. Petemdorf EW, Malkki M, Cooley TA, et al. MHC haplotype matching for unrelated hematopoietic cell transplantation. PloS Med. 2007.4(1):59-68.
14. Baker BM, Turner RV, Gagnon SJ, et al. identification of a crucial energetic footprint on the alpha1 helix of human histocompatibility leukocyte antigen (HLA)-A2 that provides functional interactions for recognition by tax peptide/HLA-A2-specific T cell receptors. J Exp Med. 2001.193:551-562.
15. Garcia K, Adams J, Feng D, et al. The molecular basis of TCR germline bias for MHC is surprisingly simple. Nature Immunology. 2009. 10(2):143-147.147.
1. Shlomchik WD. Graft-versus-host disease. Nat Rev Immunol. 2007. 7:340-52.
2. Jacobsohn DA, Vogelsang GB. Acute graft versus host disease. Orphanet J Rare Dis, 2007. 35:1-9.
3. Morris ES, Hill GR. Advances in the understanding of acute graft-versus-host disease. Br J Haematol. 2007. 137(1):3-19.
4. Salomon BL, Sudres M, Cohen JL. Regulatory T cells in graft-versus-host disease. Springer Semin Immun. 2006. 28:25-29.
5. Armstrong MK, Piepenbrink HK, Baker B. Conformational changes and flexibilityinT-cell receptor recognition of peptide–MHC complexes. Journal of Biochem. 2008. 415:183–196.
6. Buus S, Lauemoller SL, Worning P, et al. Sensitive quantitative predictions of peptide-MHC binding by a“Query by Committee”artificial neural network approach. Tissue Antigens. 2003.62:378-84.
7. Bhasin M, Raghava GP. Prediction of promiscuous and high-affinity mutated MHC binders. Hybrid Hybridomics. 2003.22:229-34.
8. Rammensee H, Bachmann J, Emmerich NP,et al. SYFPEiTHi: database for MHC ligands and peptide motifs. Immunogenetics. 1999.50:213-219.
9.房崇芸,吴雄文,龚非力.人类白细胞抗原-抗原肽复合体特异性细胞毒性T细胞的诱生及克隆.同济医科大学学报.2001.5:407-411.
10.刘岩,顾江英,欧媛,等.白血病过继免疫治疗时外周血T淋巴细胞诱导培养后的克隆性变化.中国实验血液学杂志. 2009.17:621-628.
11. Kjer NL, Clements CS, Brooks AG, et al. The structure of HLA-B8 complexed to an immunodominant viral determinant: peptide-induced conformational changes and a mode of MHC class i dimerization. J Immunol. 2002. 169:5153-60.
12. Rudd BD, Venturi V, Smithey MJ, et al. Diversity of the CD8+ T cell repertoire elicited against an immunodominant epitope does not depend on the context of infection. J immunol. 2010. 184(6):2958-65.
13. Mealey RH, Littke MH, Leib SR, et al. Cloning and large-scale expansion of epitope-specific equine cytotoxic T lymphocytes using an anti-equine CD3 mono- clonal antibody and human recombinant iL-2. Vet Immunol Immunop. 2007.4.
14. Lim DG, Slavik JM, Bourcier K, et al. Allelic variation of MHC structure alters peptide ligands to induce atypical partial agonistic CD8+ T cell function. Exp Med. 2003, 198(1):99-109.
15. Zemmour J, Little AM, Schendel DJ. et al. The HLA-A, B "negative" mutant cell line C1R expresses a novel HLA-B35 allele, which also has a point mutation in the translation initiation codon. J Immunol. 1992.148(6):1941-8
16. Zichun W, Richard T, Brian M. et al. MHC allele-specific molecular features determine Peptide/HLA-A2 conformations that are recognized by HLA-A2 -Restricted T cell receptors. J Immunol. 2002.169:3146-54.
17. Whitelegg AM, Oosten LE, Jordan S, et al. investigation of peptide involvement in T cell allorecognition using recombinant HLA class I multimers. J Immunol. 2005,175:1706-14.
18. Amir AL, D'Orsogna LJ, Roelen DL, et al. Allo-HLA reactivity of virus-specific memory T-cells is common. Blood. 2010. 115(15):3146-57
19. Mimura K, Kono K, Southwood S,et al. Substitution analog peptide derived from HER-2 can efficiently induce HER-2-specific, HLA-A24 restricted CTLs. Cancer immunol immunother. 2006. 55:1358-66
20. Ohno S, Moriya O, Yoshimoto T, et al. immunogenic variation between multiple HLA-A*0201-restricted, Hepatitis C Virus-derived epitopes for cytotoxic T lymphocytes. Viral immunology. 2006.19:458-467.
21. Appel H, Kuon W, Kuhne M, et al. The solvent-inaccessible Cys67 residue of HLA-B27 contributes to T cell recognition of HLA-B27/peptide complexes. J immunol. 2004. 173(11):6564-73.
22. Fleur ET, Diah E, Anthony WP, et al. The immunogenicity of a viral cytotoxic T cell epitope is controlled by its MHC-bound conformation 2005. 202:1249-1260.
23. Dai S, Huseby ES, Rubtsova K, et al. Crossreactive T Cells spotlight the germline rules forαβT cell-receptor interactions with MHC molecules. Immunity. 2008. 28:324-34.
24. Lim DG, KB Bourcier, Freeman GJ, et al. Examination of CD8+ T cell function in humans using MHC class I tetramers: similar cytotoxicity but variable proliferation and cytokine production among sifferent clonal CD8+ T Cells specific to a single viral epitope. J Immunol. 2000. 165: 6214-6220.
25. Hong JJ, Reynolds MR, Mattila TL, et al. Localized populations of CD8 MHC class I tetramer SiV-specific T cells in lymphoid follicles and genital epithelium. PLoS One. 2009. 4(1):e4131..
26. Frison S, Crivello P, Longhi E, et al. Description and molecular modeling of 2 novel HLA alleles: HLA-A*0343 and A*0345. Hum immunol. 2010.
27. Jacqueline M, Katherine K, Fleur E, et al. The impact of HLA-B micro -polymorphism outside primary peptide anchor pockets on the CTL response to CMV. Eur J Immunol. 2007.37:946–953.
2. Jacobsohn DA, Vogelsang GB. Acute graft versus host disease. Orphanet J Rare Dis, 2007, 35:1-9.
3. Morris ES, Hill GR. Advances in the understanding of acute graft-versus-host disease. Br J Haematol, 2007, 137(1):3-19.
4. Morishima Y, Sasazuki T, Inoko H, et al. The clinical significant of human leukocyte antigen (HLA) allele compatibility in patients receiving a marrow transplant from serologically HLA-A, HLA-B, and HLA-DR matched unrelated donors. Blood, 2002, 99:4200-4206.
5. Flomenberg N, Baxter LA, Confer D, et a1. Impact of HLA class I and II high resolution matching on outcomes of unrelated donor bone marrow transplantation: HLA-C mismatching is associated with a strong adverse effect on transplantation outcome. Blood, 2004, 104(7):1923-1930.
6. Bray AR, Hurley KC, Kamani RN, et al. National marrow donor program HLA matching guidelines for unrelated adult donor hematopoietic cell transplantation. Biol Blood Marrow Tr, 2008, 14: 45-53
7. Kawase T, Matsuo K, Kashiwase K, et al. HLA mismatch combinations associated with decreased risk of relapse: implications for the molecular mechanism. Blood. 2009, 113(12):2851-8.
8. Oudshoorn M, Doxiadis II, Berg PM et al. Functional vs structural matching: can the CTLp test be replaced by HLA allele typing? Hum Immunol 2002; 63:176–184.
9. Spencer A, Brookes PA, Kaminski E et al. Cytotoxic T lymphocyte precursor frequency analyses in bone marrow transplantation with volunteer unrelated donors. Value in donor selection. Transplantation 1995; 59: 1302–1308.
10. Keeve CA, Passweg J, Kawanishi Y et al. Association of donor-derivedhost-reactive cytolytic and helper T cells with outcome following alternative donor T cell-depleted bone marrow transplantation. Bone Marrow Transpl. 1997;19: 1001–1009.
11. Meer A, Joosten I, Schattenberg AV. et al. Cytotoxic T-lymphocyte precursor frequency (CTLp-f) as a tool for distinguishing permissible from non-permissible class I mismatches in T-cell-depleted allogeneic bone marrow transplantation. Br J Haematol. 2000, 111:685–694.
12. Dolezalova L, Vrana M, Dobrovolna M, et al. Cytotoxic T lymphocyte precursor frequency analysis in the selection of HLA matched unrelated donors for hematopoietic stem cell transplantation: the correlation of CTLp frequency with HLA class I genotyping and aGVHD development. Neoplasma. 2002, 49:26–32.
13. Iacomini J, Sayegh MH. Measuring T cell alloreactivity to predict kidney transplant outcomes: are we there yet? J Am Soc Nephrol. 2006.17(2):328-30.
14. Andree H, Nickel P, Nasiadko C, et al. Identification of dialysis patients with panel-reactive memory T cells before kidney transplantation using an allogeneic cell bank. J Am Soc Nephrol. 2006, 17(2):573-80.
15. Poggio ED, Clemente M, Hricik DE, et al. Panel of reactive T cells as a measurement of primed cellular alloimmunity in kidney transplant candidates. J Am Soc Nephrol. 2006, 17(2):564-72.
16. Oudshoorn M, Doxiadis II, Berg PM et al. Functional vs structural matching: can the CTLp test be replaced by HLA allele typing? Hum Immunol 2002; 63:176–184.
17. Elsner HA. Blasczyk R. Sequence similarity matching: proposal of a structure-based rating system for bone marrow transplantation. Eur J Imm. 2002. 29:229–236.
18. Elsner HA, DeLuca D, Strub J. et al. HistoCheck: rating of HLA class I and II mismatches by an internet-based software tool. Bone Marrow Transpl. 2004. 33:165–169.
19. Shaw BE, Barber LD, Madrigal JA. et al. Scoring for HLA matching? A clinical test of HistoCheck. Bone Marrow Transplantation. Bone Marrow Transpl. 2004. 34:367–368.
20. Sijpkens YW, Doxiadis II, De JW, et al. Sharing cross-reactive groups of MHC class I improves long-term graft survival. Kidney Int. 1999, 56(5):1920-7.
21. Hwang SH, Oh HB, Shin ES, et al. Influence of mismatching of HLA cross-reactive groups on cadaveric kidney transplantation. Transplant Proc. 2005, 37(10):4194-8.
22. Wade J A, Hurley CK, Takemoto SK, et al. HLA mismatching within or outside of cross-reactive groups (CREGs) is associated with similar outcomes after unrelatedhematopoietic stem cell transplantation. Blood, 2007, 109(9):4064-70.
23. Duquesnoy RJ, Marrari M. Correlations between Terasaki's HLA class I epitopes and HLAMatchmaker-defined eplets on HLA-A, -B and -C antigens. Tissue Antigens. 2009, 74(2):117-33.
24. Silva E, Alba A, Castro A, et al. Evaluation of HLA Matchmaker Compatibility as Predictor of Graft Survival and Presence of Anti-HLA Antibodies.Transplant Proc. 2010,42(1):266-269
25. Matthias S, Robert S, Hans GP, et al. Graft-versus-host disease after allogeneic hematopoietic stem cell transplantation induces a CD8+ T cell-mediated graft-versus-tumor effect that is independent of the recognition of alloantigenic tumor targets. Blood, 2004, 104 (4):1210-1216.
26. Dudkiewicz M, Malanowski P, Czerwin J, et al. An Approach to Predicting Hematopoietic Stem Cell Transplantation Outcome Using HLA-Mismatch Information Mapped on Protein Structure Data. Biol Blood Marrow Tr. 2009. 15(9):1014-1025.
27. Hurley CK, Oudshoorn M, and Setterholm M. et al. Re: An Approach to Predicting HSCT Outcome Using HLA-Mismatch Information Mapped on Protein Structure Data. Biol Blood Marrow Tr. 2010. In press.
28. Armstrong KM, Piepenbrink KH, Baker BM. Conformational changes and flexibility in T-cell receptor recognition of peptide-MHC complexes. Biochem J. 2008. 415(2):183-96.
29. Lee JK, Stewart JG, Dong T, et al. T cell cross-reactivity and conformational changes during TCR engagement. J Exp Med. 2004. 200(11):1455-66.
30. Baker BM, Turner RV, Gagnon SJ, et al. Identification of a crucial energetic footprint on the alpha1 helix of human histocompatibility leukocyte antigen (HLA)-A2 that provides functional interactions for recognition by tax peptide/HLA-A2-specific T cell receptors. J Exp Med. 2001. 193(5):551-62.
31.孙玉英,奚永志.防治移植物抗宿主病的新策略.中国输血杂志. 2003.16(5):364-8.
32.韩红星,孔繁华,奚永志,等.利用供受体HLA三维结构差异快速预测GVHD.中国输血杂志.2003.16(3):154-6.
33. Lim DG, Slavik JM, Bourcier K, et al. Allelic variation of MHC structure alters peptide ligands to induce atypical partial agonistic CD8+ T cell function. J Exp Med. 2003. 198(1):99-109.
34. Fleur ET, Diah E, Anthony W. et al. The immunogenicity of a viral cytotoxic T cellepitope is controlled by its MHC-bound conformation. J Exp Med. 2005. 202(9):1249–1260.
1. Beck S, Geraghty D, Inoko H, Rowen L. Complete sequence and gene map of a human major histocompatibility complex. Nature, 1999, 401:921-923.
2.谢毓滨,王赤林,李双,等.实用预防医学.湖南地区人群HLA_ABDRB1等位基因多态性的研究. 2006 ,13: 4-8
3.李彩丽,唐朝晖,方丽华,等.兰州地区汉族人群HLA-A、-B和DRB1等位基因多态性分析.中华医学遗传学杂志. 2006, 23: 89-91
4.陈阳,李剑平.辽宁汉族人群HLA-B等位基因多态性的分布.中华医学遗传学杂志. 2006, 23: 461-462
5.戴云鹏,阎文英,沈柏均,等.山东地区汉族脐血供者HLA_I等位基因多态性研究.中国小儿血液与肿瘤杂志. 2006. 11: 244-248
6.兰涛,张德梅,王桂琴.山西汉族人群HLA-A、-B、-DRB1基因多态性研究.中华医学遗传学杂志. 2005, 22: 583-584
7.梁文飚,薛敏,潘芹芹,等.中华江苏骨髓库人群HLA--I类抗原的PCR-SSP分型.中国输血杂志. 2005. 18: 199-201
8.吴国光,邓志辉,高素青,等. 6965名汉族骨髓供者HLA多态性分析.中国血液学杂志. 2004, 25: 473-477
9. Shaw CK, Chang TK, Chen SN, et al. HLA polymorphism and probability of finding HLA-matched unrelated marrow donors for Chinese in Taiwan. Tissue Antigens. 1997, 50: 610-619
10.谭建明,周永昌,唐孝达主编.组织配型技术与临床应用.人民卫生出版社, 2002, 62-131
11.吴国光,邓志辉,高素青,等. 6965名汉族骨髓供者HLA多态性分析.中华血液学杂志. 2004, 25:473-477.
12.马红京,尹晓林,郭坤元,等.广东汉族人群HLA-I、II基因多态性及单倍型分析.中华医学遗传学杂志. 2005,22:467-469.
13.高素青,吴国光,李兴茂,等.安徽汉族HLA-A、-B、-DRB1基因多态性和单倍型的分布特征.临床输血与检验. 2005,7:161-169.
14.林琳,高小江,祝文华,等.用DNA分型研究中国人HLA-A、-C、-B的部分单倍型.中华微生物学和免疫学杂志.1999,19:152.
15.杜若甫,肖春杰, Cavalli LL.用38个基因座的基因频率计算中国人群间遗传距离.中国科学:C辑. 1998, 28: 83-89
16. Guethlein LA, Older AM, Abi-Rached L, et al. Evolution of killer cell Ig-like receptor (KIR) genes: definition of an orangutan KIR haplotype reveals expansion of lineage III KIR associated with the emergence of MHC-C. J Immunol. 2007. 179: 491-504
17. Morishima Y, Sasazuki T, Inoko H, et al. The clinical significance of human leukocyte antigen allele compatibility in patients receiving a marrow transplant from serologically HLA-A, HLA-B, and HLA-DR matched unrelated donors. Blood, 2002, 99: 4200-6
1. Heemskerk MB, Roelen DL, Dankers MK, et al. M. Allogeneic MHC class I molecules with numerous sequence differences do not elicit a CTL response. Hum Immunol. 2005.66(9):969-76.
2. Robinson J, Waller MJ, Parham P, et al. IMGT/HLA and IMGT/MHC: sequence databases for the study of the major histocompatibility complex. Nucleic Acids Research. 2003.31:311-314.
3. Arnold K, Bordoli L, Kopp J, et al.The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics. 2006.22:195-201.
4. Humphrey W, Dalke A, Schulten K. VMD - Visual Molecular Dynamics. J Molec Graphics. 1996. 14(1):33-8.
5. Saper MA, Bjorkman PJ, Wiley DC. Refined structure of the human histocompatibility antigen HLA-A2 at 2.6A resolution. J Mol Biol. 1991. 219: 277–319.
6. Garboczi DN, Ghosh P, Utz U, et al. Structure of the complex between human T-cell receptor, viral peptide and HLA-A2. Nature. 1996. 384:134–141.
7. Thomas E, Storb R, Clift RA, et al. Bone-marrow transplan-tation. N Engl J Med, 1975, 292:832-843.
8. Przepiorka D, Weisdorf D, Martin P ,et al . 1994 Consensus conference on acute GVHD grading.Bone Marrow Transplant ,1995 ,15 :8252828.
9. Dehn J, Arora M, Spellman S, et al. Unrelated Donor Hematopoietic Cell Transplantation: Factors Associated with a Better HLA Match. Biology of Blood and Marrow Transplantation. 2008. 14(12):1334-1340.
10. Nicola G, Renate A, Angelika B, et al. Treatment of Adult ALL According to Protocols of the German Multicenter Study Group for Adult ALL (GMALL). Acute Leukemias.2008.14(6):167-176.
11. Lee SJ, Klein J, Haagenson M,et al. High-resolution donor-recipient HLA matching contributes to the success of unrelated donor marrow transplantation. Blood. 2007. 110(13):4576-83.
12. Davis J, Buck K, Dorr L, et al. Evaluation of unrelated donor search strategy proficiencies. Biology of Blood and Marrow Transplantation. 2006. 12(2)31-31.]
13. Petemdorf EW, Malkki M, Cooley TA, et al. MHC haplotype matching for unrelated hematopoietic cell transplantation. PloS Med. 2007.4(1):59-68.
14. Baker BM, Turner RV, Gagnon SJ, et al. identification of a crucial energetic footprint on the alpha1 helix of human histocompatibility leukocyte antigen (HLA)-A2 that provides functional interactions for recognition by tax peptide/HLA-A2-specific T cell receptors. J Exp Med. 2001.193:551-562.
15. Garcia K, Adams J, Feng D, et al. The molecular basis of TCR germline bias for MHC is surprisingly simple. Nature Immunology. 2009. 10(2):143-147.147.
1. Shlomchik WD. Graft-versus-host disease. Nat Rev Immunol. 2007. 7:340-52.
2. Jacobsohn DA, Vogelsang GB. Acute graft versus host disease. Orphanet J Rare Dis, 2007. 35:1-9.
3. Morris ES, Hill GR. Advances in the understanding of acute graft-versus-host disease. Br J Haematol. 2007. 137(1):3-19.
4. Salomon BL, Sudres M, Cohen JL. Regulatory T cells in graft-versus-host disease. Springer Semin Immun. 2006. 28:25-29.
5. Armstrong MK, Piepenbrink HK, Baker B. Conformational changes and flexibilityinT-cell receptor recognition of peptide–MHC complexes. Journal of Biochem. 2008. 415:183–196.
6. Buus S, Lauemoller SL, Worning P, et al. Sensitive quantitative predictions of peptide-MHC binding by a“Query by Committee”artificial neural network approach. Tissue Antigens. 2003.62:378-84.
7. Bhasin M, Raghava GP. Prediction of promiscuous and high-affinity mutated MHC binders. Hybrid Hybridomics. 2003.22:229-34.
8. Rammensee H, Bachmann J, Emmerich NP,et al. SYFPEiTHi: database for MHC ligands and peptide motifs. Immunogenetics. 1999.50:213-219.
9.房崇芸,吴雄文,龚非力.人类白细胞抗原-抗原肽复合体特异性细胞毒性T细胞的诱生及克隆.同济医科大学学报.2001.5:407-411.
10.刘岩,顾江英,欧媛,等.白血病过继免疫治疗时外周血T淋巴细胞诱导培养后的克隆性变化.中国实验血液学杂志. 2009.17:621-628.
11. Kjer NL, Clements CS, Brooks AG, et al. The structure of HLA-B8 complexed to an immunodominant viral determinant: peptide-induced conformational changes and a mode of MHC class i dimerization. J Immunol. 2002. 169:5153-60.
12. Rudd BD, Venturi V, Smithey MJ, et al. Diversity of the CD8+ T cell repertoire elicited against an immunodominant epitope does not depend on the context of infection. J immunol. 2010. 184(6):2958-65.
13. Mealey RH, Littke MH, Leib SR, et al. Cloning and large-scale expansion of epitope-specific equine cytotoxic T lymphocytes using an anti-equine CD3 mono- clonal antibody and human recombinant iL-2. Vet Immunol Immunop. 2007.4.
14. Lim DG, Slavik JM, Bourcier K, et al. Allelic variation of MHC structure alters peptide ligands to induce atypical partial agonistic CD8+ T cell function. Exp Med. 2003, 198(1):99-109.
15. Zemmour J, Little AM, Schendel DJ. et al. The HLA-A, B "negative" mutant cell line C1R expresses a novel HLA-B35 allele, which also has a point mutation in the translation initiation codon. J Immunol. 1992.148(6):1941-8
16. Zichun W, Richard T, Brian M. et al. MHC allele-specific molecular features determine Peptide/HLA-A2 conformations that are recognized by HLA-A2 -Restricted T cell receptors. J Immunol. 2002.169:3146-54.
17. Whitelegg AM, Oosten LE, Jordan S, et al. investigation of peptide involvement in T cell allorecognition using recombinant HLA class I multimers. J Immunol. 2005,175:1706-14.
18. Amir AL, D'Orsogna LJ, Roelen DL, et al. Allo-HLA reactivity of virus-specific memory T-cells is common. Blood. 2010. 115(15):3146-57
19. Mimura K, Kono K, Southwood S,et al. Substitution analog peptide derived from HER-2 can efficiently induce HER-2-specific, HLA-A24 restricted CTLs. Cancer immunol immunother. 2006. 55:1358-66
20. Ohno S, Moriya O, Yoshimoto T, et al. immunogenic variation between multiple HLA-A*0201-restricted, Hepatitis C Virus-derived epitopes for cytotoxic T lymphocytes. Viral immunology. 2006.19:458-467.
21. Appel H, Kuon W, Kuhne M, et al. The solvent-inaccessible Cys67 residue of HLA-B27 contributes to T cell recognition of HLA-B27/peptide complexes. J immunol. 2004. 173(11):6564-73.
22. Fleur ET, Diah E, Anthony WP, et al. The immunogenicity of a viral cytotoxic T cell epitope is controlled by its MHC-bound conformation 2005. 202:1249-1260.
23. Dai S, Huseby ES, Rubtsova K, et al. Crossreactive T Cells spotlight the germline rules forαβT cell-receptor interactions with MHC molecules. Immunity. 2008. 28:324-34.
24. Lim DG, KB Bourcier, Freeman GJ, et al. Examination of CD8+ T cell function in humans using MHC class I tetramers: similar cytotoxicity but variable proliferation and cytokine production among sifferent clonal CD8+ T Cells specific to a single viral epitope. J Immunol. 2000. 165: 6214-6220.
25. Hong JJ, Reynolds MR, Mattila TL, et al. Localized populations of CD8 MHC class I tetramer SiV-specific T cells in lymphoid follicles and genital epithelium. PLoS One. 2009. 4(1):e4131..
26. Frison S, Crivello P, Longhi E, et al. Description and molecular modeling of 2 novel HLA alleles: HLA-A*0343 and A*0345. Hum immunol. 2010.
27. Jacqueline M, Katherine K, Fleur E, et al. The impact of HLA-B micro -polymorphism outside primary peptide anchor pockets on the CTL response to CMV. Eur J Immunol. 2007.37:946–953.