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Structurally based epitope analysis of major histocompatibility complex class I-related chain A (MICA) antibody specificity patterns.

ABSTRACT: Recent studies have suggested a clinical significance to the detection of anti-major histocompatibility complex class I-related chain A (MICA) antibodies in transplantation. We have developed an eplet-based version of the HLAMatchmaker algorithm to assess the epitope specificity of these antibodies. Molecular viewing of the MICA structure and the determination of amino acid sequence differences between MICA alleles has yielded a repertoire of 38 potentially immunogenic MICA eplets. These eplets are based on the functional epitope structure that considers a configuration of amino acids within a 3-Angstrom radius of an antibody-accessible polymorphic residue on the molecular surface. In this study MICA-reactive sera were screened in Luminex assays with single MICA allele panels and analyzed with HLAMatchmaker. We identified reactivity patterns that correspond to eplet-specific antibodies to identify of unacceptable MICA mismatches including those alleles that have not been tested with the serum. In conclusion, HLAMatchmaker is a useful algorithm to analyze the reactivity patterns of anti-MICA antibodies and the determination of MICA mismatch acceptability at the structural level.

SUBMITTER: Duquesnoy RJ

PROVIDER: S-EPMC2636556 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

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Structurally based epitope analysis of major histocompatibility complex class I-related chain A (MICA) antibody specificity patterns.

Duquesnoy Rene J RJ Mostecki Justin J Hariharan Jayasree J Balazs Ivan I

Human immunology 20081026 12

Recent studies have suggested a clinical significance to the detection of anti-major histocompatibility complex class I-related chain A (MICA) antibodies in transplantation. We have developed an eplet-based version of the HLAMatchmaker algorithm to assess the epitope specificity of these antibodies. Molecular viewing of the MICA structure and the determination of amino acid sequence differences between MICA alleles has yielded a repertoire of 38 potentially immunogenic MICA eplets. These eplets ...[more]

PMID: 18957310

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Project description:An ever growing number of reports on graft rejection and/or failure even with good HLA matches have highlighted an important role of non-HLA antigens in influencing allograft immunity. The list of non-HLA antigens that have been implicated in graft rejection in different types of organ transplantation has already grown long. Of these, the Major Histocompatibility Complex class I chain-related molecule A (MICA) is one of the most polymorphic and extensively studied non-HLA antigenic targets especially in the kidney transplantation. Humoral response to MICA antigens has repeatedly been associated with lower graft survival and an increased risk of acute and chronic rejection following kidney and liver transplantation with few studies showing conflicting results. Although there are clear indications of MICA antibodies being associated with adverse graft outcome, a definitive consensus on this relationship has not been arrived yet. Furthermore, only a few studies have dealt with the impact of MICA donor-specific antibodies as compared to those that are not donor specific on graft outcome. In addition to the membrane bound form, a soluble isoform of MICA (sMICA), which has the potential to engage the natural killer cell-activating receptor NKG2D resulting in endocytosis and degradation of receptor-ligand interaction complex leading to suppression of NKG2D-mediated host innate immunity, has been a subject of intense discussion. Most studies on sMICA have been directed toward understanding their influence on tumor growth, with limited literature focusing its role in transplant biology. Furthermore, a unique dimorphism (methionine to valine) at position 129 in the α2 domain categorizes MICA alleles into strong (MICA-129 met) and weak (MICA-129 val) binders of NKG2D receptor depending on whether they have methionine or valine at this position. Although the implications of MICA 129 dimorphism have been highlighted in hematopoietic stem cell transplantation, its role in solid organ transplantation is yet to be explored. This review summarizes the currently available information on MICA antibodies, soluble MICA, and MICA-129 dimorphism in a setting of solid organ transplantation.

Project description:Gastric cancer (GC) is the fifth most prevalent type of cancer worldwide. Gastric tumor cells express MICA protein, a ligand to NKG2D receptor that triggers natural killer (NK) cells effector functions for early tumor elimination. MICA gene is highly polymorphic, thus originating alleles that encode protein variants with a controversial role in cancer. The main goal of this work was to study MICA gene polymorphisms and their relationship with the susceptibility and prognosis of GC. Fifty patients with GC and 50 healthy volunteers were included in this study. MICA alleles were identified using Sanger sequencing methods. The analysis of MICA gene sequence revealed 13 MICA sequences and 5 MICA-short tandem repeats (STR) alleles in the studied cohorts We identified MICA*002 (*A9) as the most frequent allele in both, patients and controls, followed by MICA*008 allele (*A5.1). MICA*009/049 allele was significantly associated with increased risk of GC (OR: 5.11 [95% CI: 1.39-18.74], p = 0.014). The analysis of MICA-STR alleles revealed a higher frequency of MICA*A5 in healthy individuals than GC patients (OR = 0.34 [95% CI: 0.12-0.98], p = 0.046). Survival analysis after gastrectomy showed that patients with MICA*002/002 or MICA*002/004 alleles had significantly higher survival rates than those patients bearing MICA*002/008 (p = 0.014) or MICA*002/009 (MICA*002/049) alleles (p = 0.040). The presence of threonine in the position MICA-181 (MICA*009/049 allele) was more frequent in GC patients than controls (p = 0.023). Molecular analysis of MICA-181 showed that the presence of threonine provides greater mobility to the protein than arginine in the same position (MICA*004), which could explain, at least in part, some immune evasion mechanisms developed by the tumor. In conclusion, our findings suggest that the study of MICA alleles is crucial to search for new therapeutic approaches and may be useful for the evaluation of risk and prognosis of GC and personalized therapy.

Dataset Information

Structurally based epitope analysis of major histocompatibility complex class I-related chain A (MICA) antibody specificity patterns.

Publications

Structurally based epitope analysis of major histocompatibility complex class I-related chain A (MICA) antibody specificity patterns.

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