HLA Genotypes Research Articles

Class I HLA Alleles are associated with an increased risk of osimertinib-induced hypersensitivity

BackgroundOsimertinib, a third-generation epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), shows superior lung cancer treatment efficacy. However, osimertinib-induced severe hypersensitivity, including Stevens–Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN), is frequently observed in Asian populations and hinders cancer treatment. ObjectiveWe investigated the genetic HLA predisposition and immune pathomechanism of osimertinib-induced hypersensitivity. MethodsWe enrolled 17 patients with osimertinib-induced delayed hypersensitivity (7 with severe SJS/TEN and 10 with mild maculopapular exanthema [MPE]), 98 osimertinib-tolerant subjects, and 2123 general population controls. HLA genotyping, drug-induced lymphocyte activation test (LAT), and surface plasmon resonance (SPR) assay were performed. ResultsHLA-B*51:02 was present in 83.3% of osimertinib-induced SJS/TEN patients but only in 3.3% of the general population controls (P = 2.8×10−7, Pc=6.9×10−6, odds ratio [OR]=146), and 0% of osimertinib-tolerant controls (P = 6.5×10−8, Pc=1.6×10−6, OR=707). The association of HLA-B*51:01 and HLA-A*24:02 with osimertinib-induced MPE patients, rather than with osimertinib-tolerant subjects (P = 0.002, OR=15.7 for HLA-B*51:01; P = 0.003, OR=9.5 for HLA-A*24:02), was identified as a phenotype-specific association. Granulysin—the SJS/TEN-specific cytotoxic protein—was significantly higher in SJS/TEN patients’ plasma (39.8±4.5 ng/ml, P<0.001) and in in vitro LAT (sensitivity=83.3%, P<0.01) compared to the tolerant controls. Patients with osimertinib-induced hypersensitivity appeared to tolerate alternative EGFR-TKIs. SPR results also confirmed that HLA-B*51:02 protein has a higher binding affinity for osimertinib and lower or no affinity for other EGFR-TKIs. ConclusionsHLA-B*51:02 frequently occurs in Asian populations and is strongly associated with osimertinib-induced SJS/TEN. Our findings suggest HLA-B*51:02 screening as a preemptive test to reduce osimertinib-induced severe hypersensitivity.

Sequence analysis and identification of a novel HLA-DPB1*02:01:69 allele by third-generation sequencing

To analyze the sequence of a novel HLA-DPB1 allele in an individual. A individual identified from the database of blood donors for matched platelet transfusion at the Blood Center of Zhejiang Province in May 2022 was selected as the study subject. HLA genotype of the individual was determined by next-generation sequencing (NGS) on an Ion Torrent S5 platform. The sequence of the HLA-DPB1 locus was also determined by NGS on an Illumina Miseq platform and third-generation sequencing using Oxford Nanopore MinION. This study was approved by the Blood Center of Zhejiang Province (Ethics No. 2021-001). A novel HLA-DPB1*02 allele was identified in the specimen, for which the closest genotype was HLA-DPB1*02:new,17:01:01G, with the variant located in exon 3. Meanwhile, the NGS also revealed a novel HLA-DPB1*17 allele, with the closest genotype being HLA-DPB1*02:01,17:new. Both the HLA-DPB1*17:01:01:01 and HLA-DPB1*02 alleles were identified by third-generation sequencing. Compared with the HLA-DPB1*02:01:02:01 allele, the novel allele had a G>A variation at position 369 in the exon 3, which however did not result in amino acid change. A novel HLA-DPB1 allele has been identified and validated by both NGS and TGS, which has been named as HLA-DPB1*02:01:69 by the World Health Organization Committee on Nomenclature of Factors of the HLA System.

Revolutionising High Resolution HLA Genotyping for Transplant Assessment: Validation, Implementation and Challenges of Oxford Nanopore Technologies' Q20+ Sequencing.

The advent of third-generation sequencing (TGS) represents a significant shift in the field of genetic sequencing, enabling single-molecule sequencing to overcome limitations of short-read NGS platforms. Several studies have assessed the utilisation of TGS in HLA genotyping, though many of these studies have described the high error rate as an obstacle to achieving a robust and highly accurate HLA typing assay. In 2021, Oxford Nanopore Technologies (ONT) released the high-accuracy sequencing Kit 14 and the MinION flow cell model R10.4.1, which were reported to achieve sequencing accuracies up to 99%. The aim of this study was to validate this novel high-accuracy sequencing kit for HLA genotyping coupled with a full-gene HLA PCR assay. Comparison with historical data obtained using legacy flow cell models such as R9.4, R10.3 and R10.4 was also done to assess progressive improvement in sequencing performance with each sequential release. The workflow was validated based on data throughput, sequence quality and accuracy, and HLA genotyping resolution. An initial validation was performed using an internal reference panel of 42 samples representing common HLA allele groups, followed by an analysis of data obtained from 111 sequencing batch runs since the implementation, to assess assay performance and define quality control metrics to assess inter-run variability and monitor quality. Furthermore, challenges arising from MinION flow cell stability and use, and assessment of barcode contamination are discussed. The findings of this study highlight advantages of ONT sequencing kit 14/R10.4.1 for HLA genotyping and the implementation considerations for the routine diagnostic HLA laboratory.

Quantifying uncertainty of molecular mismatch introduced by mislabeled ancestry using haplotype-based HLA genotype imputation.

Modern histocompatibility algorithms depend on the comparison and analysis of high-resolution HLA protein sequences and structures, especially when considering epitope-based algorithms, which aim to model the interactions involved in antibody or T cell binding. HLA genotype imputation can be performed in the cases where only low/intermediate-resolution HLA genotype is available or if specific loci are missing, and by providing an individuals' race/ethnicity/ancestry information, imputation results can be more accurate. This study assesses the effect of imputing high-resolution genotypes on molecular mismatch scores under a variety of ancestry assumptions. We compared molecular matching scores from "ground-truth" high-resolution genotypes against scores from genotypes which are imputed from low-resolution genotypes. Analysis was focused on a simulated patient-donor dataset and confirmed using two real-world datasets, and deviations were aggregated based on various ancestry assumptions. We observed that using multiple imputation generally results in lower error in molecular matching scores compared to single imputation, and that using the correct ancestry assumptions can reduce error introduced during imputation. We conclude that for epitope analysis, imputation is a valuable and low-risk strategy, as long as care is taken regarding epitope analysis context, ancestry assumptions, and (multiple) imputation strategy.

Differential modulation of mutant CALR and JAK2 V617F-driven oncogenesis by HLA genotype in myeloproliferative neoplasms.

It has been demonstrated previously that human leukocyte antigen class I (HLA-I) and class II (HLA-II) alleles may modulate JAK2 V617F and CALR mutation (CALRmut)-associated oncogenesis in myeloproliferative neoplasms (MPNs). However, the role of immunogenetic factors in MPNs remains underexplored. We aimed to investigate the potential involvement of HLA genes in CALRmut+ MPNs. High-resolution genotyping of HLA-I and -II loci was conducted in 42 CALRmut+ and 158 JAK2 V617F+ MPN patients and 1,083 healthy controls. A global analysis of the diversity of HLA-I genotypes revealed no significant differences between CALRmut+ patients and controls. However, one HLA-I allele (C*06:02) showed an inverse correlation with presence of CALR mutation. A meta-analysis across independent cohorts and healthy individuals from the 1000 Genomes Project confirmed an inverse correlation between the presentation capabilities of the HLA-I loci for JAK2 V617F and CALRmut-derived peptides in both patients and healthy individuals. scRNA-Seq analysis revealed low expression of TAP1 and CIITA genes in CALRmut+ hematopoietic stem and progenitor cells. In conclusion, the HLA-I genotype differentially restricts JAK2 V617F and CALRmut-driven oncogenesis potentially explaining the mutual exclusivity of the two mutations and differences in their presentation latency. These findings have practical implications for the development of neoantigen-based vaccines in MPNs.

Harmonisation of the HLA tests for the diagnosis of coeliac disease: experiences from the Czech external proficiency testing program.

Coeliac disease (CD) is an autoimmune disorder caused by the ingestion of gluten-containing grains. One of the prerequisites for the development of the disease is the presence of specific combinations of HLA alleles at the DQA1 and DQB1 loci. The HLA test is a supportive diagnostic test. In the Czech Republic, approximately 3,500 HLA tests for CD diagnosis are performed annually in almost three dozen laboratories. The HLA Department of the Institute of Haematology and Blood Transfusion in Prague has been offering the EPT "Detection of HLA Alleles Associated with Diseases" for more than 10years. The results are evaluated in terms of the correct determination of predisposing alleles/allelic groups and clinical interpretation. Every year, we notice some problems with the detection of CD-associated alleles and the interpretation of results. Annual workshops are part of this EPT, and they also include recommendations for the interpretation of results. This interpretation is evolving based on the current knowledge in the field. The current recommendation for interpretation was adopted in 2023, dividing HLA-DQA1/DQB1 genotypes into three categories: 1) detected HLA genotype is associated with predisposition to coeliac disease; 2) coeliac disease could not be excluded based on the detected HLA genotype; 3) coeliac disease could be excluded with high probability based on the detected HLA genotype. The quality of examination is increasing but still needs improvement. Correct results and accurate interpretation can inform clinicians' decisions about the diagnosis of coeliac disease in appropriate patients.

Telomere Length, HLA, and Longevity-Results from a Multicenter Study.

Aging is an exceptionally complex process that depends on genetic, environmental, and lifestyle factors. Previous studies within the International HLA and Immunogenetics Workshop (IHIWS) component "Immunogenetics of Ageing" showed that longevity is associated with positive selection of HLA-DRB1*11- and DRB1*16-associated haplotypes, shown to be protective against diseases. Within the 18th IHIWS, we aimed to investigate the relevance of telomere length for successful aging and its association with classical HLAs. In total 957 individuals from Bulgaria, Turkey, Romania, and Poland in two age groups, elderly individuals (age 65-99 years) and ethnically matched young group (age 18-64 years), were investigated. The obtained results confirmed interpopulation differences in the distribution of HLA alleles, documented the lengths of telomeres in analyzed populations, and demonstrated significant associations of telomere length with aging as well as with the presence of some HLA class I or class II alleles. They suggest that telomere length assessment combined with HLA genotyping may help identify immunogenetic profiles associated with longevity. The associations between HLA and telomeres support the theory that HLA genes influence the aging process. However, further research is needed to clarify the biological basis of the observed relationships.

Description and first insights on a large genomic biobank of lung transplantation.

The main limitation to long-term lung transplant (LT) survival is chronic lung allograft dysfunction (CLAD), which leads to irreversible lung damage and significant mortality. Individual factors can impact CLAD, but no large genetic investigation has been conducted to date. We established the multicentric Genetic COhort in Lung Transplantation (GenCOLT) biobank from a rich and homogeneous sub-part of COLT cohort. GenCOLT collected DNA, high-quality GWAS (genome-wide association study) genotyping and robust HLA data for donors and recipients to supplement COLT clinical data. GenCOLT closely mirrors the global COLT cohort without significant variations in variables like demographics, initial disease and survival rates (P > 0.05). The GenCOLT donors were 45 years-old on average, 44% women, and primarily died of stroke (54%). The recipients were 48 years-old at transplantation on average, 45% women, and the main underlying disease was chronic obstructive pulmonary disease (45%). The mean follow-up time was 67 months and survival at 5 years was 57.3% for the CLAD subgroup and 97.4% for the non-CLAD subgroup. After stringent quality controls, GenCOLT gathered more than 7.3 million SNP and HLA genotypes for 387 LT pairs, including 91% pairs composed of donor and recipient of European ancestry. Overall, GenCOLT is an accurate snapshot of LT clinical practice in France and Belgium between 2009 and 2018. It currently represents one of the largest genetic biobanks dedicated to LT with data available simultaneously for donors and recipients. This unique cohort will empower to run comprehensive GWAS investigations of CLAD and other LT outcomes.

High Resolution HLA-A, HLA-B, and HLA-C Allele Frequencies in Romanian Hematopoietic Stem Cell Donors.

The HLA genes are associated with various autoimmune pathologies, with the control of the immune response also being significant in organs and cells transplantation. The aim of the study is to identify the HLA-A, HLA-B, and HLA-C alleles frequencies in the analyzed Romanian cohort. We performed HLA typing using next-generation sequencing (NGS) in a Romanian cohort to estimate class I HLA allele frequencies up to a six-digit resolution. A total of 420 voluntary donors from the National Registry of Voluntary Hematopoietic Stem Cell Donors (RNDVCSH) were included in the study for HLA genotyping. Peripheral blood samples were taken and brought to the Fundeni Clinical Institute during 2020-2021. HLA genotyping was performed using the Immucor Mia Fora NGS MFlex kit. A total of 109 different alleles were detected in 420 analyzed samples, out of which 31 were for HLA-A, 49 for HLA-B, and 29 for HLA-C. The most frequent HLA-A alleles were HLA-A*02:01:01 (26.11%), HLA-A*01:01:01 (12.5%), HLA-A*24:02:01 (11.67%), HLA-A*03:01:01 (9.72%), HLA-A*11:01:01, and HLA-A*32:01:01 (each with 8.6%). For the HLA-B locus, the most frequent allele was HLA-B*18:01:01 (11.25%), followed by HLA-B*51:01:01 (10.83%) and HLA-B*08:01:01 (7.78%). The most common HLA-C alleles were HLA-C*07:01:01 (17.36%), HLA-C*04:01:01 (13.47%), and HLA-C*12:03:01 (10.69%). Follow-up studies are ongoing for confirming the detected results.

The characteristic of HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DRB3/4/5, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1 alleles in Zhejiang Han population.

The Zhejiang Han population, a subgroup of the Southern Han ethnic group, resides in Zhejiang Province, situated on the southeast coast of China. In this study, we conducted HLA genotyping for 813 voluntary umbilical cord blood donors from the Zhejiang Han population, targeting 11 HLA loci, namely HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DRB3/4/5, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1, using the next-generation sequencing method. Our analysis of the alleles and haplotypes revealed a high degree of polymorphism within these loci. A total of 289 unique HLA alleles were identified, with the HLA-B locus exhibiting the most significant diversity, while HLA-DRB4 displayed the lowest variation. Due to the inherent limitations of the sequencing method, some unresolvable alleles in the specific loci, such as HLA-DRB1, HLA-DPA1, and HLA-DPB1, were assigned as G group designation. In our comprehensive analysis across all 11 HLA loci, a total of 1204 haplotypes were estimated. The distribution of these alleles was similar to those of the Chinese Southern Han population while highly different from the Caucasian population. These findings contribute to a deeper understanding of the genetic characteristics of HLA loci within the Chinese Southern Han population.

High resolution HLA genotyping with third generation sequencing technology-A multicentre study.

Molecular HLA typing techniques are currently undergoing a rapid evolution. While real-time PCR is established as the standard method in tissue typing laboratories regarding allocation of solid organs, next generation sequencing (NGS) for high-resolution HLA typing is becoming indispensable but is not yet suitable for deceased donors. By contrast, high-resolution typing is essential for stem cell transplantation and is increasingly required for questions relating to various disease associations. In this multicentre clinical study, the TGS technique using nanopore sequencing is investigated applying NanoTYPE™ kit and NanoTYPER™ software (Omixon Biocomputing Ltd., Budapest, Hungary) regarding the concordance of the results with NGS and its practicability in diagnostic laboratories. The results of 381 samples show a concordance of 99.58% for 11 HLA loci, HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1 and -DPB1. The quality control (QC) data shows a very high quality of the sequencing performed in each laboratory, 34,926 (97.15%) QC values were returned as 'passed', 862 (2.4%) as 'inspect' and 162 (0.45%) as 'failed'. We show that an 'inspect' or 'failed' QC warning does not automatically lead to incorrect HLA typing. The advantages of nanopore sequencing are speed, flexibility, reusability of the flow cells and easy implementation in the laboratory. There are challenges, such as exon coverage and the handling of large amounts of data. Finally, nanopore sequencing presents potential for applications in basic research within the field of epigenetics and genomics and holds significance for clinical concerns.

Early appearance of thyroid autoimmunity in children followed from birth for type 1 diabetes risk.

Autoantibodies to thyroid peroxidase (TPOAb) and thyroglobulin (TgAb) define pre-clinical autoimmune thyroid disease (AITD) which can progress to either clinical hypo- or hyperthyroidism. We determined the age at seroconversion in children genetically at risk for type 1 diabetes. TPOAb and TgAb seropositivity were determined in 5066 healthy children with HLA DR3 or DR4 containing haplogenotypes from The Environmental Determinants of Diabetes in the Young (TEDDY) Study. Children seropositive on the cross-sectional initial screen at 8-13 years of age had longitudinally collected samples (from 3.5 months of age) screened retrospectively and prospectively for thyroid autoantibodies to identify the age at seroconversion. First-appearing autoantibody was related to sex, HLA genotype, family history of AITD, and subsequent thyroid dysfunction and disease. The youngest appearance of TPOAb and TgAb was 10 and 15 months of age, respectively. Girls had higher incidence rates of both autoantibodies. Family history of AITD was associated with a higher risk of TPOAb hazard ratio [HR] 1.90, 95% confidence interval [CI] 1.17, 3.08; and TgAb HR 2.55, 95% CI 1.91, 3.41. The risk of progressing to hypo- or hyperthyroidism was not different between TgAb and TPOAb, but children with both autoantibodies appearing at the same visit had a higher risk compared to TPOAb appearing first (HR 6.34, 95% CI 2.72, 14.76). Thyroid autoantibodies may appear during the first years of life, especially in girls, and in children with a family history of AITD. Simultaneous appearance of both autoantibodies increases the risk for hypo- or hyperthyroidism.

Genomic variants associated with age at diagnosis of childhood-onset type 1 diabetes.

Age at diagnosis (AAD) of Type 1 diabetes (T1D) is determined by the age at onset of the autoimmune attack and by the rate of beta cell destruction that follows. Twin studies found that T1D AAD is strongly influenced by genetics, notably in young children. In young UK, Finnish, Sardinian patients AAD-associated genomic variants were previously identified, which may vary across populations and with time. In 1956 children of European ancestry born in mainland France in 1980-2008 who declared T1D before 15 years, we tested 94 T1D-associated SNPs for their association with AAD using nonparametric Kruskal-Wallis test. While high-risk HLA genotypes were not found to be associated with AAD, fourteen SNPs located in 12 non-HLA loci showed a strong association (2.9 × 10-12 < P < 1.4 × 10-3 after FDR correction). Four of these loci have been associated with AAD in previous cohorts (GSDMB, IL2, TNFAIP3, IL1), supporting a partially shared genetic influence on AAD of T1D in the studied European populations. In contrast, the association of 8 new loci CLEC16A, TYK2, ERBB3, CCR7, FCRL3, DNAH2, FGF3/4, and HPSE2 with AAD is novel. The 12 protein-coding genes located within these loci are involved in major immune pathways or in predisposition to other autoimmune diseases, which suggests a prominent role for these genes in the early immune mechanisms of beta cell destruction.

Effect of peptide-binding motif on survival of HLA-haploidentical transplantation with post-transplant cyclophosphamide.

Peptide-binding motif (PBM) model, a hierarchical clustering of HLA class I based on their binding specificity, was developed to predict immunopeptidome divergence. The effect of PBM mismatches on outcomes is unknown in HLA-haploidentical haematopoietic cell transplantation with post-transplant cyclophosphamide (PTCy-haplo). We therefore conducted a retrospective study using national registry data in PTCy-haplo. Overall, 1352 patients were included in the study. PBM-A bidirectional mismatch was associated with an increased risk of overall mortality in multivariable analysis (hazard ratio, 1.26; 95% confidence interval, 1.06 to 1.50; p = 0.010). None of relapse, non-relapse mortality (NRM) and graft-versus-host disease showed significant differences according to PBM-A bidirectional mismatch status in the entire cohort. The impact of PBM-A bidirectional mismatch on overall survival (OS) was preserved within the HLA-A genotype bidirectional mismatch population, and their lower OS stemmed from higher relapse rate in this population. The worse OS due to high NRM with PBM-A bidirectional mismatch was prominent in lymphoid malignancies receiving reduced-intensity conditioning. The PBM model may predict outcomes more accurately than HLA genotype mismatches. In conclusion, this study demonstrated that the presence of PBM-A bidirectional mismatch elevated the risk of mortality of PTCy-haplo. Avoiding PBM-A bidirectional mismatch might achieve better outcomes in PTCy-haplo.

HLA-DQA1*01:03 and DQB1*06:01 are risk factors for severe COVID-19 pneumonia.

The clinical spectrum of COVID-19 includes a wide range of manifestations, from mild symptoms to severe pneumonia. HLA system plays a pivotal role in immune responses to infectious diseases. The purpose of our study was to investigate the association between HLA and COVID-19 severity in a Japanese population. The study included 209 Japanese COVID-19 patients aged ≥20 years. Saliva samples were collected and used to determine the HLA genotype by HLA imputation through genome-wide association analyses. The association between HLA genotype and COVID-19 severity was then evaluated. The allele frequency was compared between patients with respiratory failure (severe group: 91 cases) and those without respiratory failure (non-severe group: 118 cases), categorising the data into three time periods: pre-Omicron epidemic period, Omicron epidemic period, and total period of this study (from January 2021 to May 2023). In comparing the severe and non-severe groups, the frequencies of the HLA-DQA1*01:03 (35.1% vs. 10.5%, odds ratio [OR] = 4.57, corrected p [pc] = 0.041) and -DQB1*06:01 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) alleles were significantly higher in the severe group during the pre-Omicron epidemic period. During the Omicron epidemic period, HLA-DQB1*06 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) was significantly higher in the severe group. During total period of this study, HLA-DQA1*01:03 (30.2% vs. 14.4%, OR = 2.57, corrected pc = 0.0013) and -DQB1*06:01 (44.5% vs. 26.7%, OR = 2.20, pc = 0.013) alleles were significantly higher in the severe group. HLA-DQB1*06:01 and -DQA1*01:03 were in strong linkage disequilibrium with each other (r2 = 0.91) during total period of this study, indicating that these two alleles form a haplotype. The frequency of the HLA-DQA1*01:03-DQB1*06:01 in the severe group was significantly higher than in the non-severe group during pre-Omicron epidemic period (32.4% vs. 7.9%, OR = 5.59, pc = 0.00072), and total period of this study (28.6% vs. 13.1%, OR = 2.63, pc = 0.0013). During Omicron epidemic period, the haplotype did not demonstrate statistical significance, although the odds ratio indicated a value greater 1. Frequencies of the HLA-DQA1*01:03 and -DQB1*06:01 alleles were significantly higher in severe COVID-19 patients, suggesting that these alleles are risk factors for severe COVID-19 pneumonia in the Japanese population.

Linkage between HLA genotypes and COVID-19 susceptibility, severity and mortality-A Systematic Review

HLA is vital for effective immune responses against viruses. The virus responsible for COVID-19, SARS-CoV-2, highlights the significance of this immune response. The unpredictable nature of COVID-19 prompts investigation into how HLA, a component of host genetics, impacts disease susceptibility and outcomes. Understanding HLA variants' influence on COVID-19 susceptibility and severity can aid in identifying at-risk individuals. Significant HLAs that had been previously investigated for their association with COVID-19 were sought. Articles from January 2001 to February 2022 were reviewed in 2 databases: Science Direct and PubMed, employing the search terms "COVID-19" AND "HLA." Studies of genetic association measuring the severity or susceptibility to COVID-19 were analyzed in accordance with PRISMA guidelines. A total of 1326 studies related to the novel coronavirus and HLA conducted between the first month of 2001 and the second month of 2022 were identified in our search. Following the screening process, 15 relevant publications were selected. With the exception of one publication that did not demonstrate any connection, significant correlations between the incidence and mortality due to COVID-19 were found in all investigations. In severe cases, HLA class II, DRB113, was notably more prevalent. Among Black hospitalized patients positive for HLA-B53, there was an observed 7.4-fold higher risk of mortality, while HLA-B51:01 and HLA-A*26:01 were indicative of protective effects. HLAs play an essential role in immunological responses, potentially contributing to varying COVID-19 infection rates and outcomes across populations. These findings underscore the need for national networks to collect patient samples for HLA typing, identifying HLA genotypes associated with disease vulnerability.

HLA Gene Polymorphism in Patients with Chronic HBV Infection. Fundeni Clinical Institute Experience

Introduction: Hepatitis B virus (HBV) infection is a serious health problem for the public health systems in many countries worldwide. According to the European Society for the Liver Study, more than 350 million people are diagnosed with hepatitis B virus infection. Chronic viral HBV infection could be caused by the inability of both the cellular and humoral immune systems to eliminate HBV. HLA genes control cellular and humoral immune responses and present the viral antigens to CD8+ (cytotoxic T cells) and CD4+ T (T helper cells). Aim: To look at the HLA allele polymorphisms in chronic hepatitis B-infected patients to search for significant HLA allele associations. Methods: We have included 240 patients with HBV infection from the Gastroenterology and Hepatology ward, at Fundeni Clinical Institute. As a control group, 300 unrelated healthy people with no hepatitis B infection were also included. We have genotyped the HLA class I and class II genes for both patients and the control group with Next Generation Sequencing Illumina (Immucor, Mia Fora NGS Flex, Norcross, GA, USA). Results: Our preliminary data showed that HLA-DQA1*01:02:02 and HLADRB5*02:02:01 alleles are associated with the risk of HBV infection persistence. Conclusions: Our study showed that a specific HLA genotype profile is associated with chronic HBV infection in our Romanian patients.

HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups.

Biomarkers that predict posttransplant alloimmunity could lead to improved long-term graft survival. Evaluation of the number of mismatched epitopes between donor and recipient HLA proteins, termed molecular mismatch analysis, has emerged as an approach to classify transplant recipients as having high, intermediate, or low risk of graft rejection. When high-resolution genotypes are unavailable, molecular mismatch analysis requires algorithmic assignment, or imputation, of a high-resolution genotyping. Although imputation introduces inaccuracies in molecular mismatch analyses, it is unclear whether these inaccuracies would impact the clinical risk assessment for graft rejection. Using renal transplant patients and donors from our center, we constructed cohorts of surrogate donor-recipient pairs with high-resolution and low-resolution HLA genotyping that were racially concordant or discordant. We systemically assessed the impact of imputation on molecular mismatch analysis for cohorts of 180-200 donor-recipient pairs for each of 4 major racial groups. We also evaluated the effect of imputation for a racially diverse validation cohort of 35 real-world renal transplant pairs. In the surrogate donor-recipient cohorts, imputation preserved the molecular mismatch risk category for 90.5%-99.6% of racially concordant donor-recipient pairs and 92.5%-100% of racially discordant pairs. In the validation cohort, which comprised 72% racially discordant pairs, we found that imputation preserved the molecular mismatch risk category for 97.1% of pairs. Overall, these data demonstrate that imputation preserves the molecular mismatch risk assessment in the vast majority of cases and provides evidence supporting imputation in the performance of molecular mismatch analysis for clinical assessment.

Individualized neoantigen therapy mRNA-4157 (V940) plus pembrolizumab in resected melanoma: 3-year update from the mRNA-4157-P201 (KEYNOTE-942) trial.

LBA9512 Background: mRNA-4157 is a novel, mRNA-based individualized neoantigen therapy designed to increase endogenous antitumor T-cell responses by targeting unique patient (pt) tumor mutations. In the primary analysis of the Ph 2 mRNA-4157-P201 (KEYNOTE-942) trial (median planned follow-up, 23 mo), pts with completely resected high-risk stage IIIB–IV cutaneous melanoma receiving mRNA-4157 + pembrolizumab (pembro; combo) had prolonged recurrence-free survival (RFS) and distant metastasis-free survival (DMFS) vs pembro alone (Weber JS, et al. Lancet. 2024). Methods: Pts were assigned 2:1 to mRNA-4157 (1 mg IM, max 9 doses) + pembro (200 mg IV, max 18 cycles) or pembro alone. The primary endpoint was investigator-assessed RFS; secondary endpoints were DMFS and safety. This planned supportive analysis was triggered when the last randomized pt had ≥2 y follow-up. Translational subgroup analyses were also reported. HLA genotypes were analyzed by exome sequencing of DNA from PBMC. RFS and DMFS were not formally tested; nominal 2-sided p-values are descriptive. Results: With an additional year follow-up (data cutoff, 03 Nov 2023; median [range], 34.9 [25.1–51.0] mo) after primary analysis, minimal new events occurred. RFS benefit in the combo vs pembro arm was maintained with 49% risk reduction in recurrence and/or death (HR [95% CI], 0.510 [0.288–0.906]; 2-sided nominal p-value 0.019). The 2.5-yr RFS rate of combo treatment (tx) vs pembro alone was 74.8% vs 55.6%. Combo tx also produced clinically meaningful, sustained improvement in DMFS vs pembro alone (HR [95% CI], 0.384 [0.172–0.858], 2-sided nominal p-value 0.0154). OS favored combo vs pembro alone; 2.5-y OS rate was 96.0% vs 90.2% (HR [95% CI], 0.425 [0.114–1.584]). RFS benefit of combo vs pembro was maintained in TMB high (HR [95% CI], 0.564 [0.253–1.258]), TMB non-high (0.571 [0.245–1.331]), PD-L1 positive (0.471 [0.226–0.979]), PD-L1 negative (0.147 [0.034–0.630]), and ctDNA negative (0.207 [0.091–0.470]) subgroups; ctDNA positive HR was not estimable. No significant associations between individual HLA alleles and RFS were observed in either tx arm. Maximal heterozygosity at HLA class I genotype loci (A, B, C) improved RFS vs homozygosity for ≥1 locus in the pembro arm (HR [95% CI], 0.425 [0.179–1.01]) but not combo arm (1.252 [0.498–3.146]). mRNA-4157 was well tolerated and combo tx had a safety profile consistent with previous analysis with no potentiation of immune-related AEs. Conclusions: The current analysis with ∼3 y median follow-up showed durable and meaningful long-term RFS and DMFS benefit with mRNA-4157 + pembro vs pembro alone. A trend for improved OS with combo tx was also observed. HLA and translational subgroup results suggest mRNA-4157 + pembro may benefit a broader pt population vs pembro alone. Clinical trial information: NCT03897881 .

Characterization of T-cell receptor repertoire and correlation with tumor mutational landscape in lung cancer.

2577 Background: T-cell receptor (TCR) repertoire represents an overall immune condition which is closely related to pathogens- or tumor-associated T cell responses. Increasing evidence suggests that TCR repertoire is expected to undergo cancer-specific changes during tumorigenesis, supporting that TCR characteristics can serve as novel markers to indicate early cancer progression. Here, we performed a systematic T cell repertoire analysis in lung cancer. We identified cancer-enriched TCR signatures and constructed a comprehensive lung cancer database integrating TCR diversity, tumor mutational profiles, immune markers expression and HLA genotypes. Methods: A total of 988 tissue samples and 3,360 blood samples were obtained from patients with lung cancer, in addition to 2,699 blood samples from healthy individuals. Multiplex-PCR-based sequencing of the CDR3 regions of TCR-β chains was applied to the tissue and blood samples. TCR repertoires were analyzed using MiXCR and VDJtools. Whole exome sequencing was performed on partial tumor tissues to profile the mutational landscape and HLA genotypes. An in-house pipeline, considering the frequency and distribution of CDR3, was utilized to identify cancer-enriched CDR3 sequences. The PD-L1 expression was evaluated and quantified using CPS. Furthermore, an enrich score was developed to measure the content of cancer-related TCRs by aligning against the built cancer-enriched CDR3 dataset. Spearman's rank correlation was used to assess relationships between variables. Results: Lung cancer exhibited significantly lower Shannon index, Simpson index and evenness index in TCR repertoire (p&lt;0.001), both in tissue and blood samples, when compared with healthy blood samples. Approximate 3% T-cell clonotypes within lung tissues were detected in blood TCR repertoires. A correlation was observed between the decreased TCR diversity and a higher tumor mutational burden (TMB)(r = -0.15, p &lt; 0.01), as well as a higher variant allele frequency (VAF) (r = -0.19, p &lt; 0.01). In this study, 3,652 and 3,840 CDR3 sequences were identified to be enriched in lung cancer tissue and blood respectively. A significant difference in cancer-enriched score was observed between cancer and healthy TCR repertoires (p &lt; 0.001). The cancer-enriched score showed a significant positive correlation with TMB, particularly in TP53- mutant tumors (r = 0.27, p &lt; 0.001). A higher CPS (PD-L1) was associated with a higher cancer-enriched score (r = 0.18 ,p &lt; 0.01). Conclusions: Cancer-related T-cell clonotypes in the tumor microenvironment and peripheral blood informs the changes in anti-tumor responses, supporting the potential application of TCR signatures in early cancer detection. This study identified the lung cancer-related TCR signatures and provided a comprehensive lung cancer TCR database, revealing the relationship between TCR characteristics and mutational profiles. Clinical trial information: ChiCTR2200055761.