| |
|
|
|
|
|
|
|||
|
TRANSPLANTATION
From Laboratorio di Immunogenetica, Servizio di
Epidemiologia Clinica and Laboratorio di Biologia Strutturale, Istituto
Nazionale per la Ricerca sul Cancro; Dipartimento di Ematologia,
Ospedale San Martino; Medicina IV UO Oncoematologia Pediatrica,
Ospedale Gaslini; Registro Italiano Donatori di Midollo Osseo, Ospedali
Galliera; Dipartimento di Oncologia, Biologia e Genetica,
Università di Genova; Genoa, Italy; Istituto di Ematologia e
Oncologia Clinica, L. e A. Seragnoli; Servizio di Medicina
Trasfusionale, Policlinico S. Orsola, Bologna, Italy.
The hypothesis was tested that amino acid substitutions in specific
positions within human leukocyte antigen class I heavy chain would have
different impacts on transplant-related mortality (TRM) in patients
receiving transplanted bone marrow from unrelated donors. One hundred
patients and their unrelated donors were typed by sequence-based typing
for the human leukocyte antigen (HLA)-A, -B, and -C loci. All pairs
were matched for DRB1, DRB3, DRB4, DRB5, DQA1, and DQB1 loci. Forty
pairs were also matched at class I, and 60 pairs had one or more
mismatches at class I loci. It was found that substitutions at
positions 116 and 114 of class I heavy chain significantly increased
the risk for TRM in univariate and bivariate Cox analyses. Conversely,
no association between number of multiple mismatches or number of amino
acid substitutions and TRM was seen when positions 116 and 114 were
adjusted for. Variables predictive of TRM in multivariate Cox analysis
were number of cells infused, diagnosis (chronic myeloid leukemia
[CML] or non-CML), and amino acid substitution at position 116 or
152. The only variable predictive of severe acute graft-versus-host disease (GVHD) in multivariate Cox analysis was substitution at position 116. Actuarial risk for acute GVHD grade III-IV, TRM, and
relapse in pairs with substitutions at position 116 (n = 37) compared
to other pairs (n = 63) was, respectively, 36% versus 14%
(P = .01), 59% versus 28% (P = .001), and
25% versus 31% (P = .4). In conclusion these data
suggest that substitutions at position 116 of class I heavy chain
increase the risk for acute GVHD and TRM in patients who receive
transplanted bone marrow from unrelated donors.
(Blood. 2001;98:3150-3155) Graft-versus-host disease (GVHD), graft rejection,
and delayed immune recovery are more severe and frequent after
unrelated donor bone marrow transplantation (UD-BMT) than after human
leukocyte antigen (HLA)-identical sibling
transplantation.1 One interpretation is that siblings
matched by serology are likely to be genotypic matches, whereas
unrelated persons with the same serotype may have different alleles.
This has suggested the need for molecular matching of most HLA loci in
UD-BMT. The outcome is improved when donor and recipient are matched
for DRB1 and DQA-DQB,2 whereas the role of DP is
less well defined.3
As to class I antigens, the general agreement is that multiple
mismatches have a negative impact on survival but that a single mismatch does not modify the outcome significantly.3,4
However, we do not know whether different class I mismatches have
a different influence on transplant-related mortality
(TRM).2,3 In organ transplantation there are so-called
taboo combinations,5 associated with a high risk for
graft rejection, and so-called permissive mismatches,6-8
that will not reduce graft survival. This phenomenon probably
depends on the functional relevance of the amino acid differences
between the mismatched alleles. We reasoned that permissive and
nonpermissive combinations could be relevant in bone marrow transplantation, especially because the immune reaction is directed in
2 directions, the graft-versus-host (GVH) and the host-versus-graft (HVG) vectors. We have, therefore, studied the role of class I loci
mismatches in patients who have undergone UD-BMT to identify specific
amino acid substitutions increasing the risk for TRM.
Patients
Transplantation procedures
HLA high-resolution typing Donor-recipient pairs were retrospectively typed by polymerase chain reaction-sequence-based typing (PCR-SBT) for the HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, and -DQB1 loci, starting from genomic DNA or frozen samples of peripheral blood. When peripheral blood was used as the DNA source, genomic DNA was isolated with the salting-out technique. Amplification and sequencing protocols for typing by PCR-SBT of class I loci were described in previous reports.11-13 Briefly, for HLA-B and -C loci, only one locus-specific amplification of exons 2 and 3 was performed using primers located in introns 1 and 3, near the polymorphic exons. For HLA-A locus, the amplification spanned exon 1 to exon 4. Four sequencing reactions covering exons 2 and 3 allowed complete HLA-A typing in most samples. Additional sequencing of exons 1 and 4 led to complete resolution of all HLA-A polymorphisms.11 The ambiguous heterozygous patterns were solved through allele-specific amplification followed by direct sequencing of the product. An analogous approach was used for the DR and DQ loci typed according to previously described techniques.14 For HLA-DRB1, 7 group-specific amplifications of exon 2 were performed. All group-specific primers were designed with a fluorescently labeled 5' end tail of a -21M13 sequence (-21M13 Big-dye Primer cycle-sequencing reaction kit (Perkin Elmer, Foster City, CA). For HLA-DRB3, -DRB4, and -DRB5 loci, 2 specific primers at the 5' and 3' regions of exon 2 were designed to selectively amplify exon 2 of each locus, intron 1 and exon 3 of the DRB4 locus, and exon 3 for the DRB5 locus. Positive PCR mixes were sequenced in both directions using the same amplification primers and the standard AmpliTaq FS Big Dye Terminator cycle-sequencing protocol. HLA-DQA1 exon 2 was amplified using 5 group-specific PCRs that allowed the separation of deleted from nondeleted DQA1 alleles. To increase typing resolution, DQA1 exons 1, 3, and 4 and DQB1 exon 3 also were eventually analyzed by PCR sequence-specific primers.15 HLA-DQB1 exon 2 was amplified using 2 group-specific amplifications. PCR products were purified and then used for cycle-sequencing reactions (Big Dye Terminator cycle-sequencing kit; Perkin Elmer) followed by automated analysis (ABI Prism 377 DNA Automatic Sequencer; Perkin Elmer). Sequence analysis and allele assignment were performed using MatchTools and MTNavigator software (Perkin Elmer).14Evaluation of amino acid substitution Amino acid sequences of HLA class I molecules were obtained from the Anthony Nolan site on the World Wide Web (www.anthonynolan.org.uk/HIG/seq/pep/text/). Visual analysis was carried out by using program O16 on an SGI workstation.Statistical analysis The effect of the number and position of amino acid substitutions on TRM and on acute GVHD was evaluated in univariate and multivariate analyses (including other clinical variables) using a Cox model with a backward selection procedure based on the likelihood ratio test. Kaplan-Meier actuarial survival estimates were calculated for acute GVHD, TRM, relapses, disease-free survival (DFS), and overall survival (OS) and were compared among different patient categories using the log-rank test. In tests of significance, no correction for multiple comparisons was made because of the exploratory nature of these analyses. As a consequence, all P values should be considered with caution. Cumulative incidence rates, based on the competing risks method, were also calculated for TRM and relapses.17
Effect of position of amino acid substitution on transplant-related mortality All 100 donor-recipient pairs were matched for DRB1, DRB3, DRB4, DRB5, DQA1, and DQB1 loci. Forty pairs were also matched for A, B, and C loci, whereas 60 had one or more mismatches at class I. In detail, 16 pairs had 2 mismatches, always at different loci, and 44 had only one.Step 1. The occurrence of a single mismatch slightly increased the risk for TRM (hazard ratio [HR] = 1.54; P = .27), whereas the occurrence of multiple mismatches significantly increased the risk for TRM (HR = 3.38; P = .004). A single mismatch occurred 4 times at the HLA-A allele, 8 times at the B allele, and 32 times at the C allele. Step 2.
We then evaluated whether there was any difference in the risk for TRM
in mismatches at different loci (A, B, or C). No statistically significant heterogeneity was seen
( Step 3.
We then analyzed the impact on TRM of number and position of amino acid
substitutions. The frequency of substitutions at each amino acid
position of the class I heavy chain is detailed in Table
1: some positions were rarely involved,
such as position 10 with 1 of 60 (2%) patients, and some were
frequently involved, such as position 156 with 38 of 60 (63%)
patients. Table 2 reports the results of
univariate analysis on the association between TRM and total number and
the position of amino acid substitutions. The latter association was
evaluated only for the most frequently involved positions, that is,
substitutions present in 20 or more pairs. Total number of amino acid
substitutions (HR = 1.06; P = .02) and substitutions at
position 116 (HR = 2.75; P = .002) and 114 (HR = 2.30;
P = .01) were significantly associated with the risk for
TRM, whereas substitutions at position 9, 156, 24, and 152 showed a
weak and nonsignificant association (HR = 1.5-2; P = .05-.10). Because the total number of substitutions
and the presence of a substitution at any position are highly
correlated variables, bivariate Cox analysis was performed for each
amino acid position correcting also for the number of other
substitutions (Table 2). When the number of other substitutions was
included in the model, using a stepwise procedure, substitutions at
positions 116 and 114 were the only ones that excluded the
number of other substitutions from the model. Conversely, no
association between number of amino acid substitutions and TRM was seen
when positions 116 and 114 were adjusted for.
Step 4.
Multivariate Cox analysis was then carried out that included all
the positions examined at univariate analysis and several clinical
variables affecting risk for TRM
Effect of position of amino acid substitution on graft-versus-host disease The same analysis carried out on TRM was performed on GVHD (Table 3). Total number of amino acid substitutions (HR = 1.07; P = .02) and substitutions at positions 116 (HR = 2.79; P = .01) and 114 (HR = 2.88; P = .01) were significantly associated with the risk for GVHD, whereas substitutions at positions 77, 80, 156, and 152 showed weak and nonsignificant association (HR = 1.5-2; P = .05-.10). In addition, after adjusting for the number of other substitutions, bivariate analysis for GVHD indicated that substitutions at positions 116 and 114 excluded from the model the number of other substitutions. No association between number of other amino acid substitutions and GVHD resulted when positions 116 and 114 were adjusted for. Multivariate Cox analysis was carried out that included all the positions examined at univariate analysis and all the clinical variables in the model for TRM. Only substitution at position 116 was included in the final model (HR = 2.79; P = .01).Table 4 shows the clinical data of
patients, grouped by absence or presence of amino acid substitution at
position 116. There appeared to be no difference in the way each
parameter was distributed in the 2 groups.
Effect of amino acid substitutions at position 116 on outcome Actuarial risk estimates of severe (grade III-IV) acute GVHD, TRM, relapse, DFS, and OS were then calculated, comparing mismatched pairs with substitutions at position 116 with all the other pairs. As shown in Table 5, the risk for acute GVHD at 100 days was higher in donor-recipient pairs with an amino acid substitution at position 116 than in pairs with no substitution at the same position (36% vs 14%; P = .01); risk for relapse was not statistically different between the 2 groups (25% vs 31%; P = .41), whereas both DFS and OS were higher in donor-recipient pairs with no substitution at position 116. Kaplan-Meier estimates of TRM and severe acute GVHD for pairs with a substitution at position 116 and pairs without such a substitution are shown in Figure 1. Because relapse and TRM are mutually exclusive events, we calculated the cumulative incidence rates based on the competing risks method17; it is known, in fact, that Kaplan-Meier estimates tend to overestimate the proportion of patients in whom each event taken separately develops. Figure 2 outlines the cumulative incidence curves, which sum up the cumulative incidence of events in the 2 patient groups. Risks for relapse and TRM at 3 years were estimated as 25% and 26%, respectively, for donor-recipient pairs with no substitution at position 116 and as 12% and 57% for pairs with a substitution at position 116 (Table 5).
These results suggest that a molecular mismatch involving position 116 of the HLA class I heavy chain can influence the outcome of unrelated BMT in donor-recipient pairs, otherwise matched for DRB and DQ loci. Patients with substitution at position 116 are at increased risk for TRM, primarily because of the concomitant increased risk for severe acute GVHD. In these patients, a nonsignificant reduction of relapse was also observed. The resultant net effect for patients with a mismatch involving position 116 was a decrease in DFS and OS. These findings are not in contrast with the correlation between postgraft events and total number of amino acid substitutions or frequency of multiple mismatches; in fact, the higher the number of substitutions or mismatches, the higher the chance position 116 will be involved. Our results may also explain the controversy about the relevance of locus-specific class I mismatches in transplants from unrelated donors18,19; it is possible that the effect of mismatches involving position 116 is diluted by the null effect of mismatches not involving this position. Based on the available class I crystal structures, some considerations on the peculiar behavior of position 116 may be discussed. The overall structure of different class I molecules is similar, diverging only at the polymorphic residues, which are relatively few and located mostly in the peptide-binding groove.20,21 Bound peptides interact with class I molecules, in human and in mouse, through specific pockets in the groove.22,23 Of particular relevance are the B and F pockets, which harbor, respectively, the N- and C-terminal common motifs of the peptides bound by class I molecules. A slight structural variation affecting one of these pockets can dramatically change the requirements for binding peptides and may result in a different set of bound peptides. Amino acid 116 forms the floor of the F pocket, selecting the size of the peptide C-terminal residue.22,24 Analysis of the different crystal structures indicates that amino acid 116 specifically interacts with residue P9 of the bound peptide.22,24,25 It also shows that at the level of the F pocket, the cleft for the peptide is tight, restricting the requirements for P9 residue accommodation.20 In this regard it has been reported that the different specificities of the same pocket in the different alleles depend primarily on steric, rather than chemical, changes within the pocket.26 Analysis of the 6 Protein Data Bank27 entries representing 5 distinct HLA class I molecules displaying different residues at position 116 (Ser, Tyr, Asp) shows that residue replacement at position 116 is likely to affect steric conformation of the F pocket, changing the requirements for the common motif located at the peptide C-terminus and modifying the set of bound peptides. This is confirmed by the analysis of peptide binding and by the study of T-cell reactivity.28-30 The substitution of Tyr for Ser at position 116 in HLA-B3501 reduces the affinity of peptides carrying Tyr at P9 while it enhances that of peptides with Ile or Leu at P9.28 Furthermore, changes in the sole C-terminal residue of a peptide are sufficient to produce heterogeneity in the responses of different CTL clones with the same peptide specificity.29 In contrast, mutations in the F pocket involving residues other than 116 have no effect on CTL recognition.30 The possibility that differences at position 116 could select for binding of peptide residues other than P9 should also be taken into account. Differences in the residues at positions 114 and 116 modify the conformation outside the F pocket of a peptide that binds with similar efficiency to different B35 alleles and contribute to allele-specific recognition by different CTL clonotypes.31 In addition, the occurrence of indirect allorecognition, with peptides including the substituted residue 116 presented here, cannot be ruled out. If amino acid substitution at position 116 affects the outcome of BMT, it would be difficult to prove the effect of the different amino acid substitutions at this position. The replacement of Tyr with Phe induces less dramatic changes in bulkiness or charge of the side chain than the replacement of Tyr with Ser or the replacement of His with Asp, respectively. Therefore, the type of amino acid substitution occurring at position 116 may have an additional impact on transplantation outcome. A much larger cohort is required to verify this hypothesis. Conflicting results of substitutions at positions 114 and 152, statistically significant in univariate or multivariate analysis, respectively, suggest that an association caused by pure chance cannot entirely be ruled out. Indeed, the small sample size of the current study is a limiting factor for the power of the analysis. In terms of TRM, with 38 events we have a power of 80% (at a significance level of 5%) to detect a hazard ratio equal to 2.65. A lower HR could be not significant because of insufficient statistical power. The large number of statistical comparisons and the high number of variables included in the multivariate models should be also considered. Exploratory analyses on the robustness of the statistical models suggest caution in interpreting these results and warrant further studies in larger, independent data sets.
We thank our nursing staff for their great work. We thank the Italian Bone Marrow Donor Registry for giving us the pretransplantation typing of patients and donors and for supplying us with blood samples for the SBT typing. We also thank the Centro Ricerche Immunoematologiche AVIS di Bergamo for supplying us with blood samples for the set-up of molecular typing.
Submitted November 27, 2000; accepted July 19, 2001.
Supported by Associazione Italiana Ricerca contro il Cancro, Associazione Ricerca Trapianto Midollo Osseo, CNR Target Project on Biotechnology 1999, Ministero della Sanità R.F. 1998, MURST National Research Programs 1998, and Regione Liguria 1999 and 2000. S.P. is a recipient of an FIRC grant 1999-2000.
The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked "advertisement" in accordance with 18 U.S.C. section 1734.
Reprints: Giovanni B. Ferrara, Servizio di Immunogenetica, IST, c/o CBA torre A2, Largo Rosanna Benzi 10, 16132 Genova, Italy, e-mail: ferrara{at}cba.unige.it.
1. Marks DI, Cullis JO, Ward KN, et al. Allogeneic bone marrow transplantation for chronic myeloid leukemia using siblings and volunteer unrelated donors: a comparison in complication in the first 2 years. Ann Intern Med. 1993;119:204-214. 2. Hansen JA, Yamamoto K, Petersdorf E, Sasazuki T. The role of HLA matching in hematopoietic cell transplantation. Rev Immunogenet. 1999;1:359-373[Medline] [Order article via Infotrieve].
3.
Sasazuki T, Juji T, Morishima I, et al.
Effect of matching of class I HLA alleles on clinical outcome after transplantation of hematopoietic stem cells from an unrelated donor.
N Engl J Med.
1998;339:1177-1185
4.
Petersdorf EW, Gooley TA, Anasetti C, et al.
Optimizing outcome after unrelated bone marrow transplantation by comprehensive matching of HLA class I and II alleles in the donor and recipient.
Blood.
1998;92:3515-3520 5. Doxiadis II, Smits JMA, Schreuder GMT, et al. Association between specific HLA combinations and probability of kidney allograft loss: the taboo concept. Lancet. 1996;348:850-853[CrossRef][Medline] [Order article via Infotrieve]. 6. Maruya E, Takemoto S, Terasaki PI. HLA matching: identification of permissible HLA mismatches. In: Terasaki PI,Cecka JM, eds. Clinical Transplants. Los Angeles, CA: UCLA Tissue Typing Laboratory; 1993:511-520. 7. Van Rood JJ, Lagaay EL, Doxiadis II, Roelen D, Perijn G, Claas FHJ. Permissible mismatches, acceptable mismatches and tolerance: new trends in decision making. In: Terasaki PI,Cecka JM, eds. Clinical Transplants. Los Angeles, CA: UCLA Tissue Typing Laboratory; 1993:285-293. 8. Takemoto S, Cecka JM, Terasaki PI. Permissible class I mismatches identified from 7 years kidney transplant successes with 4 AB mismatches [abstract]. Hum Immunol. 1994;40:17[Medline] [Order article via Infotrieve]. 9. Terasaki PI, McClelland JD. Microdoplet assay of human serum cytotoxins. Nature. 1964;204:998-1000[Medline] [Order article via Infotrieve].
10.
Kernan NA, Bartsch G, Ash RC, et al.
Analysis of 462 transplantations from unrelated donors facilitated by the National Marrow Donor Program.
N Engl J Med.
1993;328:593-602 11. Pera C, Delfino L, Morabito A, et al. HLA-A typing: comparison between serology, the amplification refractory mutation system with polymerase chain reaction and sequencing. Tissue Antigens. 1997;50:372-379[Medline] [Order article via Infotrieve]. 12. Delfino L, Morabito A, Longo A, Ferrara GB. HLA-C high resolution typing: exons 2-3 analysis by sequence based typing (SBT) and exons 1-5 polymorphisms detection by sequence specific primers (PCR-SSP). Tissue Antigens. 1998;52:251-259[Medline] [Order article via Infotrieve]. 13. Pozzi S, Longo A, Ferrara GB. HLA-B locus sequence based typing. Tissue Antigens. 1999;53:275-281[CrossRef][Medline] [Order article via Infotrieve]. 14. Morabito A, Pera C, Longo A, Delfino L, Ferrara GB. Identification of a new DRB3*02 allelic variant (DRB3*0209) by high resolution sequence based typing. Tissue Antigens. 2000;56:90-94[CrossRef][Medline] [Order article via Infotrieve]. 15. Pera C, Delfino L, Longo A, Pistillo MP, Ferrara GB. Novel association among HLA-DQA1 and -DQB1 alleles, revealed by high resolution sequence based typing (SBT) of these loci. Tissue Antigens. 2000;55:275-279[CrossRef][Medline] [Order article via Infotrieve]. 16. Jones TA, Zou J-Y, Cowan SW, Kjeldgaard M. Improved methods for building protein models in electron density maps and the location of errors in these models. Acta Cristallgr. 1991;47:110-119[CrossRef]. 17. Gooley TA, Leisering W, Crowley J, Storer BE. Estimation of failure probabilities in the presence of competing risks: new representations of old estimators. Stat Med. 199;18:695-706.
18.
Davies SM, Shu XO, Blazar BR, et al.
Unrelated donor bone marrow transplantation: influence of HLA A and B incompatibility on outcome.
Blood.
1995;86:1636-1642 19. Petersdorf EW, Mickelson EM, Anasetti C, Martin PJ, Woolfrey AE, Hansen JA. Effect of HLA mismatches on the outcome of hematopoietic transplants. Curr Opin Immunol. 1999;11:521-526[CrossRef][Medline] [Order article via Infotrieve]. 20. Madden RD, Garboczi DN, Wiley DC. The antigenic identity of peptide-MHC complexes: a comparison of the conformations of five viral peptides presented by HLA-A2. Cell. 1993;75:693-708[CrossRef][Medline] [Order article via Infotrieve]. 21. Garrett TPJ, Saper MA, Bjorkman PJ, Strominger JL, Wiley DC. Specificity pockets for the side chains of peptide antigens in HLA-Aw68. Nature. 1989;342:692-696[CrossRef][Medline] [Order article via Infotrieve]. 22. Saper MA, Bjorkman PJ, Wiley DC. Refined structure of the human histocompatibility antigen HLA-A2 at 2.6 A resolution. J Mol Biol. 1991;219:277-319[CrossRef][Medline] [Order article via Infotrieve].
23.
Matsumura M, Fremont DH, Peterson PA, Wilson IA.
Emerging principles for the recognition of peptide antigens by MHC class I molecules.
Science.
1992;257:927-934 24. Silver ML, Guo H, Strominger JL, Wiley DC. Atomic structure of a human MHC molecule presenting an influenza virus peptide. Nature. 1992;360:367-369[CrossRef][Medline] [Order article via Infotrieve].
25.
Smith KJ, Reid SW, Stuart DI, McMichael AJ, Yvonne Jones E, Bell JI.
An altered position of the 26. Guo H, Jardetzky TS, Garrett TPJ, Lane WS, Strominger JL, Wiley DC. Different length peptides bind to HLA-Aw68 similarly at their ends but bulge out in the middle. Nature. 1992;360:364-366[CrossRef][Medline] [Order article via Infotrieve]. 27. Bernstein FC, Koetzle TF, Williams GJB, et al. The Protein Data Bank: a computer based archival file for macromolecular studies. J Mol Biol. 1977;112:535-542[Medline] [Order article via Infotrieve]. 28. Kubo H, Ikeda-Moore Y, Kikuchi A, et al. Residue 116 determines the C-terminal anchor residue of HLA-B*3501 and -B*5101 binding peptides but does not explain the general affinity difference. Immunogenetics. 1998;47:256-263[CrossRef][Medline] [Order article via Infotrieve]. 29. Dong T, Boyd D, Rosenberg W, et al. An HLA-B35-restricted epitope modified at an anchor residue results in an antagonist peptide. Eur J Immunol. 1996;26:335-339[Medline] [Order article via Infotrieve].
30.
Latron F, Pazmany L, Morrison J, et al.
A critical role for conserved residues in the cleft of HLA-A2 in presentation of a nonapeptide to T cells.
Science.
1992;257:964-967 31. Khanna R, Silins SL, Weng Z, Gatchell D, Burrows SR, Cooper L. Cytotoxic T cell recognition of allelic variants of HLA B 35 bound to an Epstein-Barr virus epitope: influence of peptide conformation and TCR-peptide interaction. Eur J Immunol. 1999;29:1587-1597[CrossRef][Medline] [Order article via Infotrieve].
© 2001 by The American Society of Hematology.
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
![]() |
D. Narzi, K. Winkler, J. Saidowsky, R. Misselwitz, A. Ziegler, R. A. Bockmann, and U. Alexiev Molecular Determinants of Major Histocompatibility Complex Class I Complex Stability: SHAPING ANTIGENIC FEATURES THROUGH SHORT AND LONG RANGE ELECTROSTATIC INTERACTIONS J. Biol. Chem., August 22, 2008; 283(34): 23093 - 23103. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Kawase, Y. Morishima, K. Matsuo, K. Kashiwase, H. Inoko, H. Saji, S. Kato, T. Juji, Y. Kodera, T. Sasazuki, et al. High-risk HLA allele mismatch combinations responsible for severe acute graft-versus-host disease and implication for its molecular mechanism Blood, October 1, 2007; 110(7): 2235 - 2241. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. Fleischhauer, F. Locatelli, M. Zecca, M. G. Orofino, C. Giardini, P. De Stefano, A. Pession, A. M. Iannone, C. Carcassi, E. Zino, et al. Graft rejection after unrelated donor hematopoietic stem cell transplantation for thalassemia is associated with nonpermissive HLA-DPB1 disparity in host-versus-graft direction Blood, April 1, 2006; 107(7): 2984 - 2992. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. M. E. Whitelegg, L. E. M. Oosten, S. Jordan, M. Kester, A. G. S. van Halteren, J. A. Madrigal, E. Goulmy, and L. D. Barber Investigation of Peptide Involvement in T Cell Allorecognition Using Recombinant HLA Class I Multimers J. Immunol., August 1, 2005; 175(3): 1706 - 1714. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. T. Fiorillo, C. Ruckert, M. Hulsmeyer, R. Sorrentino, W. Saenger, A. Ziegler, and B. Uchanska-Ziegler Allele-dependent Similarity between Viral and Self-peptide Presentation by HLA-B27 Subtypes J. Biol. Chem., January 28, 2005; 280(4): 2962 - 2971. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Pohlmann, R. A. Bockmann, H. Grubmuller, B. Uchanska-Ziegler, A. Ziegler, and U. Alexiev Differential Peptide Dynamics Is Linked to Major Histocompatibility Complex Polymorphism J. Biol. Chem., July 2, 2004; 279(27): 28197 - 28201. [Abstract] [Full Text] [PDF] |
||||
![]() |
E. Zino, G. Frumento, S. Marktel, M. P. Sormani, F. Ficara, S. D. Terlizzi, A. M. Parodi, R. Sergeant, M. Martinetti, A. Bontadini, et al. A T-cell epitope encoded by a subset of HLA-DPB1 alleles determines nonpermissive mismatches for hematologic stem cell transplantation Blood, February 15, 2004; 103(4): 1417 - 1424. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Hulsmeyer, M. T. Fiorillo, F. Bettosini, R. Sorrentino, W. Saenger, A. Ziegler, and B. Uchanska-Ziegler Dual, HLA-B27 Subtype-dependent Conformation of a Self-peptide J. Exp. Med., January 20, 2004; 199(2): 271 - 281. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. S. Block, M. J. Hansen, V. P. Van Keulen, and L. R. Pease MHC Class I Gene Conversion Mutations Alter the CD8 T Cell Repertoire J. Immunol., October 15, 2003; 171(8): 4006 - 4010. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. Park, S. Lee, E. Kim, and K. Ahn A Single Polymorphic Residue Within the Peptide-Binding Cleft of MHC Class I Molecules Determines Spectrum of Tapasin Dependence J. Immunol., January 15, 2003; 170(2): 961 - 968. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Hulsmeyer, R. C. Hillig, A. Volz, M. Ruhl, W. Schroder, W. Saenger, A. Ziegler, and B. Uchanska-Ziegler HLA-B27 Subtypes Differentially Associated with Disease Exhibit Subtle Structural Alterations J. Biol. Chem., November 27, 2002; 277(49): 47844 - 47853. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Copyright © 2001 by American Society of Hematology Online ISSN: 1528-0020 | |||||||||