O câncer de próstata é o segundo câncer mais comum entre homens, uma vez que tanto a incidência como a mortalidade aumentam exponencialmente após a idade de 50 anos. As células Natural Killer (NK) fazem parte do sistema imune inato e reconhecem moléculas de HLA de classe I na célula alvo, através de seus receptores de membrana, chamados killer immunoglobulin-like-receptors (KIR). O objetivo desse estudo foi avaliar a associação entre os genes KIR e HLA em pacientes com câncer de próstata e grupo controle. Genotipamos 200 pacientes com diagnóstico de câncer de próstata e 185 pacientes saudáveis para os genes KIR e HLA classe I por PCR-SSP. Quando comparados os grupos, não foram encontradas diferenças significativas para HLA-C do grupo 1 e do grupo 2, HLA-Bw4, HLA-A3 e A11. Nenhuma diferença foi observada na frequência dos genes KIR nos pacientes com câncer de próstata e nos controles. Esses resultados sugerem que não há potencial papel para o sistema dos genes KIR no câncer de próstata. / Prostate cancer is the second most common cancer among men, since both incidence and mortality exponentially increases in men over fifty years of age. Natural killer cells (NK) are part of the innate immune system recognizing class I HLA molecules on target cells through their membrane receptors, called killer immunoglobulin-like receptors (KIR). The aim of our study was to evaluate the association between the KIR genes and HLA alleles in patients with prostate cancer and healthy controls. Two hundred prostate cancer patients and 185 healthy controls were typed for HLA class I and KIR genes by PCR-SSP. When both groups were compared, no significant differences were found for HLA-C group 1 and group 2, HLA-Bw4, HLA-A3 and A11. No difference was seen either in KIR frequency between patients with prostate cancer and controls. In conclusion, our data suggests no potential role for the KIR gene system in prostate cancer.

O câncer colorretal (CCR) pode ocorrer em qualquer parte do cólon ou do reto e representa o terceiro câncer mais comum no mundo em ambos os sexos. As células Natural Killer (NK) fazem parte do sistema imune inato reconhecendo moléculas de HLA de classe I em células alvo, através de seus receptores de membrana killer cell immunoglobulin-like receptors (KIR). O objetivo deste estudo foi avaliar a associação entre os genes KIR e os ligantes HLA em pacientes com câncer colorretal e controles saudáveis. Examinamos o polimorfismo de 16 genes KIR e seus ligantes HLA em 154 pacientes caucasóides com CCR e 216 controles saudáveis pela técnica de PCR-SSO e PCR-SSP. Quando comparamos os dois grupos, não foram encontradas diferenças significativas para os ligantes HLA e os genes KIR após correção de Bonferroni. Entretanto, o grupo de genótipos Bx (heterozigoto e homozigoto para o haplótipo B) foi mais frequente nos controles, quando comparados com os pacientes. Estes achados sugerem que altos níveis de ativação de sinais KIR aparecem como proteção para o câncer colorretal. / Colorectal cancer (CRC) can occur anywhere in the colon or rectum and represents the third most common cancer in the world in both sexes. Natural killer cells (NK) are part of the innate immune system recognizing class I HLA molecules on target cells through their membrane receptors, called killer cell immunoglobulin-like receptors (KIR). The aim of our study was to evaluate the association between the KIR genes and HLA ligands in patients with colorectal cancer and healthy controls. We examined the polymorphism of 16 KIR genes and their HLA ligands in 154 caucasoid CRC patients and 216 healthy controls by PCR-SSO and PCR-SSP. When both groups were compared, no significant differences were found for HLA ligands and KIR genes after Bonferroni correction. However, the Bx group genotypes (heterozygous and homozygous for the haplotype B) were more frequent in controls, when compared with patients. These findings suggest that individuals with Bx genotypes could have some protection to colorectal cancer. These findings suggest that higher levels of activating KIR signals appear as protective to colorectal cancer.

O câncer de próstata é o segundo câncer mais comum entre homens, uma vez que tanto a incidência como a mortalidade aumentam exponencialmente após a idade de 50 anos. As células Natural Killer (NK) fazem parte do sistema imune inato e reconhecem moléculas de HLA de classe I na célula alvo, através de seus receptores de membrana, chamados killer immunoglobulin-like-receptors (KIR). O objetivo desse estudo foi avaliar a associação entre os genes KIR e HLA em pacientes com câncer de próstata e grupo controle. Genotipamos 200 pacientes com diagnóstico de câncer de próstata e 185 pacientes saudáveis para os genes KIR e HLA classe I por PCR-SSP. Quando comparados os grupos, não foram encontradas diferenças significativas para HLA-C do grupo 1 e do grupo 2, HLA-Bw4, HLA-A3 e A11. Nenhuma diferença foi observada na frequência dos genes KIR nos pacientes com câncer de próstata e nos controles. Esses resultados sugerem que não há potencial papel para o sistema dos genes KIR no câncer de próstata. / Prostate cancer is the second most common cancer among men, since both incidence and mortality exponentially increases in men over fifty years of age. Natural killer cells (NK) are part of the innate immune system recognizing class I HLA molecules on target cells through their membrane receptors, called killer immunoglobulin-like receptors (KIR). The aim of our study was to evaluate the association between the KIR genes and HLA alleles in patients with prostate cancer and healthy controls. Two hundred prostate cancer patients and 185 healthy controls were typed for HLA class I and KIR genes by PCR-SSP. When both groups were compared, no significant differences were found for HLA-C group 1 and group 2, HLA-Bw4, HLA-A3 and A11. No difference was seen either in KIR frequency between patients with prostate cancer and controls. In conclusion, our data suggests no potential role for the KIR gene system in prostate cancer.

O câncer de próstata é o segundo câncer mais comum entre homens, uma vez que tanto a incidência como a mortalidade aumentam exponencialmente após a idade de 50 anos. As células Natural Killer (NK) fazem parte do sistema imune inato e reconhecem moléculas de HLA de classe I na célula alvo, através de seus receptores de membrana, chamados killer immunoglobulin-like-receptors (KIR). O objetivo desse estudo foi avaliar a associação entre os genes KIR e HLA em pacientes com câncer de próstata e grupo controle. Genotipamos 200 pacientes com diagnóstico de câncer de próstata e 185 pacientes saudáveis para os genes KIR e HLA classe I por PCR-SSP. Quando comparados os grupos, não foram encontradas diferenças significativas para HLA-C do grupo 1 e do grupo 2, HLA-Bw4, HLA-A3 e A11. Nenhuma diferença foi observada na frequência dos genes KIR nos pacientes com câncer de próstata e nos controles. Esses resultados sugerem que não há potencial papel para o sistema dos genes KIR no câncer de próstata. / Prostate cancer is the second most common cancer among men, since both incidence and mortality exponentially increases in men over fifty years of age. Natural killer cells (NK) are part of the innate immune system recognizing class I HLA molecules on target cells through their membrane receptors, called killer immunoglobulin-like receptors (KIR). The aim of our study was to evaluate the association between the KIR genes and HLA alleles in patients with prostate cancer and healthy controls. Two hundred prostate cancer patients and 185 healthy controls were typed for HLA class I and KIR genes by PCR-SSP. When both groups were compared, no significant differences were found for HLA-C group 1 and group 2, HLA-Bw4, HLA-A3 and A11. No difference was seen either in KIR frequency between patients with prostate cancer and controls. In conclusion, our data suggests no potential role for the KIR gene system in prostate cancer.

京都大学 / 0048 / 新制・課程博士 / 博士(医科学) / 甲第20758号 / 医科博第81号 / 新制||医科||6(附属図書館) / 京都大学大学院医学研究科医科学専攻 / (主査)教授 江藤 浩之, 教授 三森 経世, 教授 杉田 昌彦 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

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Syfte: Målet med denna studie var att undersöka ett möjligt samband mellan de olika HLA-DRB1*-allelerna med mängden Mutans Streptococci (MS) i saliven, med fokus på HLA DRB1*04, i en grupp förskolebarn i södra Sverige, Skåne.Material och metod: Salivprover från 318 HLA-DRB1*-typade barn odlades på MSB-agarplattor och antalet MS CFU räknades. Resultaten analyserades statistiskt med chi-två-test.Resultat: Inget signifikant samband kunde fastställas mellan någon av DRB1*04-allelerna och mängden MS. Dock var höga MS-värden ungefär dubbelt så vanligt för homozygota DRB1*04 alleler (p = 0,354). Höga MS-värden var vanligare för DRB1*04:01 allelen (p = 0,717). Däremot var höga MS-värden procentuellt mycket mindre förekommande för DRB1*04:04 allelen (p = 0,098). Ett statistisk signifikant samband (p = 0,003) kunde ses för pojkar positiva för DRB1*07:01-allelen. Höga MS-värden var mycket vanligare för DRB1*07:01-allelen.Slutsats: Ett samband mellan HLA-DRB1-alleler och mängden MS i saliven kan finnas. Resultaten indikerar att barn positiva för DRB1*04:01-allelen och homozygota DRB1*04-alleler har en tendens att uppvisa ett högre MS-värde i saliven jämfört med barn negativa för allelen. HLA-typen är antagligen bara en av många faktorer som påverkar mängden MS. Resultaten från denna studie är delvis i linje med tidigare studier och ytterligare studier behövs. / Objective: The aim of the study was to investigate a possible relationship of the different HLA-DRB1* alleles, with focus on HLA-DRB1*04, and the amount of Mutans Streptococci (MS) in saliva from a group of preschool children in the Southern part of Sweden, in the County of Skåne.Material and method: Saliva samples from 318 HLA-DRB1* typed children were cultivated on MSB agar and CFU of MS was counted. The results were statistically analyzed using chi-square tests.Results: No statistical significant relationship could be established between any DRB1*04 allele and the amount of MS. However, high numbers of MS was found to be about twice as common for homozygote DRB1*04 alleles (p = 0.364). High numbers of MS was more common for DRB1*04:01 alleles (p = 0.717). On the contrary, high levels of MS was much less common for DRB1*04:04 alleles (p = 0.098). A statistical significant relationship (p = 0.003) could be seen for boys positive for the DRB1*07:01 allele. High MS count was much more common for DRB1*07:01 alleles.Conclusion: A relationship between HLA-DRB1 alleles and the amount MS in the saliva might exist. The results indicate that children positive for the DRB1*04:01 allele and homozygote DRB1*04 alleles have a tendency to display more MS in their saliva compared to children negative to the alleles. The HLA type might just be one of many factors affecting the amount of MS. The results are partly in line with earlier studies and further studies are needed.

Cytotoxic T-lymphocytes (CTLs) are important components of the adaptive immune system and function by scanning the intracellular environment so as to detect and de-stroy infected cells. CTL responses play a major role in controlling virus-infected cells such as in HIV or influenza and cells infected with intracellular bacteria such as in tuberculosis. To do so they require the antigens to be presented to them, which is fulfilled by the major histocompatibility complex (MHC), commonly known as human leukocyte antigen or HLA molecules in humans. Recognition of antigenic peptides to Class-1 HLA molecules is a prerequisite for triggering CTL immune responses. Individuals differ significantly in their ability to respond to an infection. Among the factors that govern the outcome of an infection, HLA polymorphism in the host is one of the most important. Despite a large body of work on HLA molecules, much remains to be understood about the relationship between HLA diversity and disease susceptibility. High complexity arises due to HLA allele polymorphism, extensive antigen cross-presentability, and host-pathogen heterogeneity. A given allele can recognize a number of different peptides from various pathogens and a given peptide can also bind to a number of different individuals. Thus, given the plurality in peptide-allele pairs and the large number of alleles, understanding the differences in recognition profiles and the implications that follow for disease susceptibilities require mathematical modelling and computational analysis. The main objectives of the thesis were to understand heterogeneity in antigen presentation by HLA molecules at different scales and how that heterogeneity translates to variations in disease susceptibilities and finally the disease dynamics in different populations. Towards this goal, first the variations in HLA alleles need to be characterized systematically and their recognition properties understood. A structure-based classification of all known HLA class-1 alleles was therefore attempted. In the process, it was also of interest to see if understanding of sub-structures at the binding grooves of HLA molecules could help in high confidence prediction of epitopes for different alleles. Next, the goal was to understand how HLA heterogeneity affect disease susceptibilities and disease spread in populations. This was studied at two different levels. Firstly, modelling the HLA genotypes and CTL responses in different populations and assessing how they recognized epitopes from a given virus. The second approach involved modelling the disease dynamics given the predicted susceptibilities in different populations. Influenza H1N1 infection was used as a case study. The specific objectives addressed are: (a) To develop a classification scheme for all known HLA class-1 alleles that can explain epitope recognition profiles and further to dissect the physic-chemical features responsible for differences in peptide specificities, (b) A statistical model has been derived from a large dataset of HLA-peptide complexes. The derived model was used to identify the interdependencies of residues at different peptide and thereby, rationalize the HLA class-I allele binding specificity at a greater detail, (c) To understand the effect of HLA heterogeneity on CTL mediated disease response. A model of HLA genotypes for different populations was required for this, which was constructed and used for estimating disease response to H1N1 via the prediction of epi-topes and (d) To model disease dynamics in different populations with the knowledge of the CTL response-grouping and to evaluate the effect of heterogeneity on different vaccination strategies. Each of the four objectives listed above are described subsequently in chapters 2 to 5, followed by Chapter 6 which summarises the findings from the thesis and presents future directions. Chapter 1 presents an introduction to the importance of the function of HLA molecules, describes structural bioinformatics as a discipline and the methods that are available for it. The chapter also describes different mathematical modelling strategies available to study host immune responses. Chapter 2 describes a novel method for structure-based hierarchical classification of HLA alleles. Presently, more than 2000 HLA class-I alleles are reported, and they vary only across peptide-binding grooves. The polymorphism they exhibit, enables them to bind to a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern due to multiplicity in their associations. Thus, a powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. The study reports a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification with 7 supergroups was derived, each further categorized to yield a total of 72 groups. An independent clustering scheme based only on the similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explains the basis for the observed clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues that contribute to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants. The results are presented in an interactive web- server http://proline.iisc.ernet.in/hlaclassify. In Chapter 3, the knowledge of structural features responsible for generating peptide recognition specificities are first analysed and then utilized for predicting T-cell epi-topes for any class-1 HLA allele. Since identification of epitopes is critical and central to many of the questions in immunology, a study of several HLA-peptide complexes is carried out at the structural level and factors are identified that discriminate good binder peptides from those that do not. T-cell epitopes serve as molecular keys to initiate adaptive immune responses. Identification of T-cell epitopes is also a key step in rational vaccine design. Most available methods are driven by informatics, critically dependent on experimentally obtained training data. Analysis of the training set from IEDB for several alleles indicate that sampling of the peptide space is extremely sparse covering only a tiny fraction of all possible nonamer space, and also heavily skewed, thus restricting the range of epitope prediction. A new epitope prediction method is therefore developed. The method has four distinct modules, (a) structural modelling, estimating statistical pair-potentials and constraint derivation, (b) implicit modelling and interaction profiling, (c) binding affinity prediction through feature representation and (d) use of graphical models to extract peptide sequence signatures to predict epitopes for HLA class I alleles . HLaffy is a novel and efficient epitope prediction method that predicts epitopes for any HLA Class-1 allele, by estimating binding strengths of peptide-HLA complexes which is achieved through learning pair-potentials important for peptide binding. It stands on the strength of mechanistic understanding of HLA-peptide recognition and provides an estimate of the total ligand space for each allele. The method is made accessible through a webserver http://proline.biochem.iisc.ernet.in/HLaffy. In chapter 4, the effect of genetic heterogeneity on disease susceptibilities are investigated. Individuals differ significantly in their ability to respond to an infection. Among the factors that govern the outcome of an infection, HLA polymorphism in the host is one of the most important. Despite a large body of work on HLA molecules, much remains to be understood about how host HLA diversity affects disease susceptibilities. High complexity due to polymorphism, extensive cross-presentability among HLA alleles, host and pathogen heterogeneity, demands for an investigation through computational approaches. Host heterogeneity in a population is modelled through a molecular systems approach starting with mining ‘big data’ from literature. The in-sights derived through this is used to investigate the effect of heterogeneity in a population in terms of the impact it makes on recognizing a pathogen. A case study of influenza virus H1N1 infection is presented. For this, a comprehensive CTL immunome is defined by taking a consensus prediction by three distinct methods. Next, HLA genotypes are constructed for different populations using a probabilistic method. Epidemic incidences in general are observed to correlate with poor CTL response in populations. From this study, it is seen that large populations can be classified into a small number of groups called response-types, specific to a given viral strain. Individuals of a response type are expected to exhibit similar CTL responses. Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity. Overall, the study presents a conceptual advance towards understanding how genetic heterogeneity influences disease susceptibility in individuals and in populations. Lists of top-ranking epitopes and proteins are also derived, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which pro- vide ready short-lists for rational vaccine design (flutope). Next, in Chapter 5, the effect of genetic heterogeneity on disease dynamics has been investigated. A mathematical framework has been developed to incorporate the heterogeneity information in the form of response-types described in the previous chap-ter. The spread of a disease in a population is a complex process, controlled by various factors, ranging from molecular level recognition events to socio-economic causes. The ‘response-typing’ described in the previous chapter allows identification of distinct groups of individuals, each with a different extent of susceptibility to a given strain of the virus. 3 different approaches are used for modelling: (i) an SIR model where different response types are considered as partitions of each S, I and R compartment. Initially SIR models are developed, such that the S compartment is sub-divided into further groups based on the ‘response-types’ obtained in the previous chapter. This analysis shows an effect in infection sweep time, i.e., how long the infection stays in the population. A stochastic model incorporates the environmental noise due to random variation in population influx, due to birth, death or migration. The system is observed to show higher stability in the presence of genetic heterogeneity. As the contagion spreads only through direct host to host contact. The topology of the contact network, plays major role in deciding the extent of disease dynamics. An agent based computational framework has been developed for modelling disease spread by considering spatial distribution of the agents, their movement patterns and resulting contact probabilities. The agent-based model (ABM) incorporates the temporal patterns of contacts. The ABM is based on a city block model and captures movement of individuals parametrically. A new concept of system ‘characteristic time’ has been introduced in context of a time-evolving network. ‘Characteristic time’ is the minimum time required to ensure, every individual is connected to all other individuals, in the time aggregated contact network. For any given temporal system, disease time must exceed ‘characteristic time’ in order to spread throughout the population. Shorter ‘characteristic time’ of the system is suggestive of faster spread of the disease. A disease spread network is constructed which shows how the disease spreads from one infected individual to others in the city, given the contact rules and their relative susceptibilities to that viral strain. A high degree of population heterogeneity is seen to results in longer disease residence time. Susceptible individuals preferentially get infected first thereby exposing more susceptible individuals to the disease. Vaccination strategies are derived from the model, which indicates that vaccinating only 20% of the agents, who are hub nodes or highly central nodes and who also have a high degree to susceptible agents, lead to high levels of herd immunity and can confer protection to the rest of the population. Overall, the thesis has provided biologically meaningful classification of all known HLA class-1 alleles and has unravelled the physico-chemical basis for their peptide recognition specificities. The thesis also presents a new algorithm for estimating pep-tide binding affinities and consequently predicting epitopes for all alleles. Finally the thesis presents a conceptual advance in relating HLA diversity to disease susceptibilities and explains how different populations can respond differently to a given infection. A case study with the influenza H1N1 virus identified populations who are most susceptible and those who are least susceptible, in the process identifying important epitopes and responder alleles, providing important pointers for vaccine design. The influence of heterogeneity and response-typing on disease dynamics is also presented for influenza H1N1 infection, which has led to the rational identification of effective vaccination strategies. The methods and concepts developed here are fairly generic and can be adapted easily for studying other infectious diseases as well. Three new web-resources, a) HLAclassify, b) HLaffy and c) Flutope have been developed, which host pre-computed results as well as allow interactive querying to an user to perform analysis with a specific allele, peptide or a pathogenic genome sequence.

O diabetes mellitus tipo 1A (DM1) é uma doença crônica caracterizada pela destruição imunológica das células ? do pâncreas e pela incapacidade de seu portador produzir insulina. Nas últimas décadas foram descritos vários aspectos sobre a fisiopatologia do DM1 e identificado um aumento de sua incidência mundial. Entretanto, na literatura há lacunas a serem respondidas envolvendo a etiologia e a imunopatologia desta doença. No presente trabalho, foi analisado o impacto de duas moléculas endógenas imunoregulatórias, Antígeno Leucocitário Humano-G (HLA-G) e Galectina-1 (GAL-1), no DM1 humano e experimental. Para tanto, as formas recombinantes de HLA-G (-G5 e -G6) e seus respectivos anticorpos foram produzidos e/ou bioquimicamente caracterizados. A partir de amostras de pacientes diagnosticados com DM1 ou de indivíduos controle foi feita uma análise comparativa envolvendo o perfil de expressão do HLA-G e da GAL-1 e a identificação de microRNAs (miRNAs) associados a estas duas moléculas. Camundongos Lgals-/- ou não para o gene da GAL-1 foram tratados com estreptozotocina (STZ) para indução do DM1 experimental. As duas formas recombinantes do HLA-G foram produzidas, mas apenas o HLA-G6 foi caracterizado como uma solução polidispersa contendo um componente majoritário (99,2%) com massa molecular de 23.603,766 Da, raio hidrodinâmico de 6,0 ± 2,0 nm e imunoreatividade para diferentes anticorpos anti-HLA-G comerciais ou produzidos no laboratório. Os níveis transcricional e proteico do HLA-G e da GAL-1 não foram diferentes entre os grupos de indivíduos estudados. A análise comparativa de miRNAs mostrou que a elevada indução do miRNA modulador negativo da expressão do HLA-G (hsa-miR-16-5p) nos controles em relação aos pacientes foi a única associação robusta com a patogenia do DM1. Curiosamente, os animais selvagens apresentam maior suscetilibilidade à indução de DM1 por STZ, uma vez que os indicadores desta doença como o grau de insulite, a taxa de migração de linfócitos T CD4 e T CD8 para os linfonodos pancreáticos, o nível de redução de insulina no pâncreas e a taxa glicêmica estavam aumentados nesses animais em relação aos nocautes para GAL-1. Finalmente, este conjunto de resultados sugere que possa ocorrer uma regulação positiva da expressão de transcritos do HLA-G em pacientes com DM1 e que a presença de GAL-1 endógena pode favorecer o DM1 experimental. Estes dados abrem novas perspectivas para o melhor entendimento da imunopatologia do DM-1 / Diabetes Mellitus type 1A (DM1) is a chronic disease characterized by the immune destruction of pancreatic beta cells and by the consequent inability of its bearer to produce insulin. For the last decades, several aspects of the pathophysiology of DM1 were described and an increase on its worldwide incidence has been identified.Nevertheless, there are gaps in the literature related to aspects of its etiology and immunopathology to be filled.In the present work, the impact of two endogenous immunoregulatory molecules, Human Leukocyte Antigen-G (HLA-G) and Galectin-1 (GAL-1), was analyzed on human and experimental DM1.To do so, the recombinant forms of HLA-G (-G5 and - G6) and its respective antibodies were produced and/or biochemically characterized. A comparative analysis involving the expression profile of HLA-G and GAL-1 and the identification of microRNAs (miRNAs) associated with these two molecules was made from samples of patients diagnosed with DM1, or control subjects. Mice deficient or not for the GAL-1 gene were treated with streptozotocin (STZ) for the induction of experimental DM1.Both recombinant forms of HLA-G were produced, but only HLA-G6 was characterized as a polydisperse solution containing a major component (99.2%), with molecular mass of 23,603,766 Da, hydrodynamic radius of 6.0 ± 2.0 nm, and immunoreactivity for different commercial or lab produced anti-HLA-G antibodies HLA-G and GAL-1. The transcriptional and protein levels were not different between the groups of subjects studied. High induction of the negative modulator miRNA expression of HLA-G (hsa-miR-16-5p) in the controls compared to the patients was the only robust association found with the pathogenesis of DM1.Interestingly, wild type animals presented more susceptibility to the induction of DM1 by STZ, once the indicators of this disease such as the degree of insulin, the migration rate of CD4 T and CD8 T lymphocytes to pancreatic lymph nodes, the level of insulin reduction in the pancreas and the glycemic rate were increased in wild type mice (Lgals-1+/+) when compared to GAL-1-knock out mice (Lgals-1-/-). Finally, this set of results suggests that a positive regulation of the expression of HLA-G transcripts may occur in patients with DM1 and that the presence of endogenous GAL-1 may favor the experimental DM1. These data open new perspectives for a better understanding of the immunopathology of DM-1

O presente estudo tem como objetivo investigar a frequência dos diversos polimorfismos dos genes KIR (Killer Immunoglobulin-like Receptors) e HLA C1 e C2 em um grupo de pacientes com câncer de mama e comparar com um grupo controle de indivíduos sadios. As células natural killer (NK) são linfócitos que diferem das células T e B e que fazem parte da imunidade natural, reconhecendo as moléculas HLA (Antígenos Leucocitários Humano) de classe I em células infectadas por vírus ou em células tumorais, através de seus receptores de membrana. Os principais receptores das células NK são conhecidos como receptores KIR, sendo codificados por genes localizados no cromossomo 19q13.4 e classificados em grupos funcionais supressores e ativadores. Neste estudo, analisamos 15 genes KIR e alelos do sistema HLA de classe I em 230 pacientes caucasóides e em 278 controles, usando a técnica de PCR com primers específicos (PCR-SSO e PCR-SSP). Nossos resultados demonstraram uma frequência maior do genótipo supressor 2DL2 (P<0,001) em pacientes com câncer de mama, quando comparados ao grupo controle. Os genes HLA-C2 e HLA-BW4 não apresentaram diferenças significantes entre os grupos. Contudo, o gene HLA-C1 foi observado em maior frequência nos pacientes com câncer de mama. Considerando que estes achados sugerem uma potencial associação entre o sistema de genes KIR, HLA classe I e o câncer de mama, estudos adicionais sobre este tema são necessários. / We investigated the frequency of various KIR (Killer Immunoglobulin-like Receptors) and HLA C1 and C2 gene polymorphisms in a group of patients with breast cancer and healthy controls. Natural Killer (NK) cells are lymphocytes that differ from T and B cells and are part of the innate immune system, recognizing class I Human Leukocyte Antigens (HLA) molecules on target cells (virus-infected as well as cancer cells), through specific cell surface receptors. KIR comprises the main class of NK receptors, being encoded by genes located in chromosome 19q13.4. They possess both suppressor and activating functional groups. Fifteen KIR genes and class I HLA alleles obtained from 230 Caucasians patients, as well as 278 controls were studied, using PCR techniques with specific primers (PCR-SSO and PCR-SSP). Our results showed a higher frequency of suppressor genotype 2DL2 (P<0,001) in patients with breast cancer as compared to controls. No significant difference between HLA-C2 and HLA-BW4 alleles were observed between the study groups. Notably, a higher frequency of HLA-C1 gene was noted in patients with breast cancer. Our results suggest a potential association between KIR genes, HLA class I and breast cancer, deserving further investigation.