B Cell Function in the Tumor Microenvironment.

The tumor microenvironment (TME) is a heterogeneous, complex organization composed of tumor, stroma, and endothelial cells that is characterized by cross talk between tumor and innate and adaptive immune cells. Over the last decade, it has become increasingly clear that the immune cells in the TME play a critical role in controlling or promoting tumor growth. The function of T lymphocytes in this process has been well characterized. On the other hand, the function of B lymphocytes is less clear, although recent data from our group and others have strongly indicated a critical role for B cells in antitumor immunity. There are, however, a multitude of populations of B cells found within the TME, ranging from naive B cells all the way to terminally differentiated plasma cells and memory B cells. Here, we characterize the role of B cells in the TME in both animal models and patients, with an emphasis on dissecting how B cell heterogeneity contributes to the immune response to cancer.

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

Cancer-Germline Antigen Expression Discriminates Clinical Outcome to CTLA-4 Blockade.

CTLA-4 immune checkpoint blockade is clinically effective in a subset of patients with metastatic melanoma. We identify a subcluster of MAGE-A cancer-germline antigens, located within a narrow 75 kb region of chromosome Xq28, that predicts resistance uniquely to blockade of CTLA-4, but not PD-1. We validate this gene expression signature in an independent anti-CTLA-4-treated cohort and show its specificity to the CTLA-4 pathway with two independent anti-PD-1-treated cohorts. Autophagy, a process critical for optimal anti-cancer immunity, has previously been shown to be suppressed by the MAGE-TRIM28 ubiquitin ligase in vitro. We now show that the expression of the key autophagosome component LC3B and other activators of autophagy are negatively associated with MAGE-A protein levels in human melanomas, including samples from patients with resistance to CTLA-4 blockade. Our findings implicate autophagy suppression in resistance to CTLA-4 blockade in melanoma, suggesting exploitation of autophagy induction for potential therapeutic synergy with CTLA-4 inhibitors.

A Functional Genomics Approach to Understand Variation in Cytokine Production in Humans.

As part of the Human Functional Genomics Project, which aims to understand the factors that determine the variability of immune responses, we investigated genetic variants affecting cytokine production in response to ex vivo stimulation in two independent cohorts of 500 and 200 healthy individuals. We demonstrate a strong impact of genetic heritability on cytokine production capacity after challenge with bacterial, fungal, viral, and non-microbial stimuli. In addition to 17 novel genome-wide significant cytokine QTLs (cQTLs), our study provides a comprehensive picture of the genetic variants that influence six different cytokines in whole blood, blood mononuclear cells, and macrophages. Important biological pathways that contain cytokine QTLs map to pattern recognition receptors (TLR1-6-10 cluster), cytokine and complement inhibitors, and the kallikrein system. The cytokine QTLs show enrichment for monocyte-specific enhancers, are more often located in regions under positive selection, and are significantly enriched among SNPs associated with infections and immune-mediated diseases. PAPERCLIP.

A functional genomics approach in Tanzanian population identifies distinct genetic regulators of cytokine production compared to European population.

Humans exhibit remarkable interindividual and interpopulation immune response variability upon microbial challenges. Cytokines play a vital role in regulating inflammation and immune responses, but dysregulation of cytokine responses has been implicated in different disease states. Host genetic factors were previously shown to significantly impact cytokine response heterogeneity mainly in European-based studies, but it is unclear whether these findings are transferable to non-European individuals. Here, we aimed to identify genetic variants modulating cytokine responses in healthy adults of East African ancestry from Tanzania. We leveraged both cytokine and genetic data and performed genome-wide cytokine quantitative trait loci (cQTLs) mapping. The results were compared with another cohort of healthy adults of Western European ancestry via direct overlap and functional enrichment analyses. We also performed meta-analyses to identify cQTLs with congruent effect direction in both populations. In the Tanzanians, cQTL mapping identified 80 independent suggestive loci and one genome-wide significant locus (TBC1D22A) at chromosome 22; SNP rs12169244 was associated with IL-1b release after Salmonella enteritidis stimulation. Remarkably, the identified cQTLs varied significantly when compared to the European cohort, and there was a very limited percentage of overlap (1.6% to 1.9%). We further observed ancestry-specific pathways regulating induced cytokine responses, and there was significant enrichment of the interferon pathway specifically in the Tanzanians. Furthermore, contrary to the Europeans, genetic variants in the TLR10-TLR1-TLR6 locus showed no effect on cytokine response. Our data reveal both ancestry-specific effects of genetic variants and pathways on cytokine response heterogeneity, hence arguing for the importance of initiatives to include diverse populations into genomics research.

GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels.

Cancer initiation and progression are likely caused by the dysregulation of biological pathways. Gene set analysis (GSA) could improve the signal-to-noise ratio and identify potential biological insights on the gene set level. However, platforms exploring cancer multi-omics data using GSA methods are lacking. In this study, we upgraded our GSCALite to GSCA (gene set cancer analysis, http://bioinfo.life.hust.edu.cn/GSCA) for cancer GSA at genomic, pharmacogenomic and immunogenomic levels. In this improved GSCA, we integrated expression, mutation, drug sensitivity and clinical data from four public data sources for 33 cancer types. We introduced useful features to GSCA, including associations between immune infiltration with gene expression and genomic variations, and associations between gene set expression/mutation and clinical outcomes. GSCA has four main functional modules for cancer GSA to explore, analyze and visualize expression, genomic variations, tumor immune infiltration, drug sensitivity and their associations with clinical outcomes. We used case studies of three gene sets: (i) seven cell cycle genes, (ii) tumor suppressor genes of PI3K pathway and (iii) oncogenes of PI3K pathway to prove the advantage of GSCA over single gene analysis. We found novel associations of gene set expression and mutation with clinical outcomes in different cancer types on gene set level, while on single gene analysis level, they are not significant associations. In conclusion, GSCA is a user-friendly web server and a useful resource for conducting hypothesis tests by using GSA methods at genomic, pharmacogenomic and immunogenomic levels.

Comment on 'rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing'.

Transcriptome sequencing has become common in cancer research, resulting in the generation of a substantial volume of RNA sequencing (RNA-Seq) data. The ability to extract immune repertoires from these data is crucial for obtaining information on infiltrating T- and B-lymphocyte clones when dedicated amplicon T-cell/B-cell receptors sequencing (TCR-Seq/BCR-Seq) methods are unavailable. In response to this demand, several dedicated computational methods have been developed, including MiXCR, TRUST and ImRep. In the recent publication in Briefings in Bioinformatics, Peng et al. have conducted an intensive, systematic comparison of the three previously mentioned tools. Although their effort is commendable, we do have a few constructive critiques regarding technical elements of their analysis.

Rigorous benchmarking of T-cell receptor repertoire profiling methods for cancer RNA sequencing.

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.

Therapeutic applications of the cancer immunoediting hypothesis.

Since the late 19th century, the immune system has increasingly garnered interest as a novel avenue for cancer therapy, particularly given scientific breakthroughs in recent decades delineating the fundamental role of the immune system in tumorigenesis. The immunoediting hypothesis has articulated this role, describing three phases of the tumor-immune system interaction: Elimination, Equilibrium, and Escape wherein tumors progress from active immunologic surveillance and destruction through dynamic immunologic stasis to unfettered growth. The primary goals of immunotherapy are to restrict and revert progression through these phases, thereby improving the immune system's ability to control tumor growth. In this review, we detail the development and foundation of the cancer immunoediting hypothesis and apply this hypothesis to the dynamic immunotherapy field that includes checkpoint blockade, vaccine therapy, and adoptive cell transfer.

An integrative genomics approach identifies KDM4 as a modulator of trained immunity.

Innate immune cells are able to build memory characteristics via a process termed "trained immunity." Host factors that influence the magnitude of the individual trained immunity response remain largely unknown. Using an integrative genomics approach, our study aimed to prioritize and understand the role of specific genes in trained immunity responses. In vitro-induced trained immunity responses were assessed in two independent population-based cohorts of healthy individuals, the 300 Bacillus Calmette-Guérin (300BCG; n = 267) and 200 Functional Genomics (200FG; n = 110) cohorts from the Human Functional Genomics Project. Genetic loci that influence cytokine responses upon trained immunity were identified by conducting a meta-analysis of QTLs identified in the 300BCG and 200FG cohorts. From the identified QTL loci, we functionally validated the role of PI3K-Akt signaling pathway and two genes that belong to the family of Siglec receptors (Siglec-5 and Siglec-14). Furthermore, we identified the H3K9 histone demethylases of the KDM4 family as major regulators of trained immunity responses. These data pinpoint an important role of metabolic and epigenetic processes in the regulation of trained immunity responses, and these findings may open new avenues for vaccine design and therapeutic interventions.

Analysis of KIR gene variants in The Cancer Genome Atlas and UK Biobank using KIRCLE.

BACKGROUND: Natural killer (NK) cells represent a critical component of the innate immune system's response against cancer and viral infections, among other diseases. To distinguish healthy host cells from infected or tumor cells, killer immunoglobulin receptors (KIR) on NK cells bind and recognize Human Leukocyte Antigen (HLA) complexes on their target cells. However, NK cells exhibit great diversity in their mechanism of activation, and the outcomes of their activation are not yet understood fully. Just like the HLAs they bind, KIR receptors exhibit high allelic diversity in the human population. Here we provide a method to identify KIR allele variants from whole exome sequencing data and uncover novel associations between these variants and various molecular and clinical correlates. RESULTS: In order to better understand KIRs, we have developed KIRCLE, a novel method for genotyping individual KIR genes from whole exome sequencing data, and used it to analyze approximately sixty-thousand patient samples in The Cancer Genome Atlas (TCGA) and UK Biobank. We were able to assess population frequencies for different KIR alleles and demonstrate that, similar to HLA alleles, individuals' KIR alleles correlate strongly with their ethnicities. In addition, we observed associations between different KIR alleles and HLA alleles, including HLA-B*53 with KIR3DL2*013 (Fisher's exact FDR = 7.64e-51). Finally, we showcased statistically significant associations between KIR alleles and various clinical correlates, including peptic ulcer disease (Fisher's exact FDR = 0.0429) and age of onset of atopy (Mann-Whitney U FDR = 0.0751). CONCLUSIONS: We show that KIRCLE is able to infer KIR variants accurately and consistently, and we demonstrate its utility using data from approximately sixty-thousand individuals from TCGA and UK Biobank to discover novel molecular and clinical correlations with KIR germline variants. Peptic ulcer disease and atopy are just two diseases in which NK cells may play a role beyond their "classical" realm of anti-tumor and anti-viral responses. This tool may be used both as a benchmark for future KIR-variant-inference algorithms, and to better understand the immunogenomics of and disease processes involving KIRs.

Immunologic and immunogenomic aspects of tumor progression.

Tumor progression to metastatic disease is characterized by continuous genetic alterations due to instability of the genome. Immune sensitivity was found to be linked to tumor mutational burden (TMB) and the resulting amount of neoantigens. However, APOBEC activity resulting in increase in TMB causes immune evasion. On the other hand, clonal or acquired genetic loss of HLA class I also hampers immune sensitivity of tumors. Rare amplification of the PD-L1 gene in cancers may render them sensitive to immune checkpoint inhibitors but involvement of broader regions of chromosome 9p may ultimately lead again to immune evasion due to inactivation of the IFN-γ signaling pathway. Such genetic changes may occur not only in the primary tumor but at any phase of progression: in lymphatic as well as in visceral metastases. Accordingly, it is rational to monitor these changes continuously during disease progression similar to target therapies. Moreover, beside temporal variability, genomic features of tumors such as mutation profiles, as well as the tumor immune microenvironment also show considerable inter- and intratumoral spatial heterogeneity, suggesting the necessity of multiple sampling in biomarker studies.

Integrative molecular characterisation of gallbladder cancer reveals micro-environment-associated subtypes.

BACKGROUND & AIMS: Gallbladder cancer (GBC) is the most common type of biliary tract cancer, but the molecular mechanisms involved in gallbladder carcinogenesis remain poorly understood. In this study, we applied integrative genomics approaches to characterise GBC and explore molecular subtypes associated with patient survival. METHODS: We profiled the mutational landscape of GBC tumours (whole-exome sequencing on 92, targeted sequencing on 98, in total 190 patients). In a subset (n = 45), we interrogated the matched transcriptomes, DNA methylomes, and somatic copy number alterations. We explored molecular subtypes identified through clustering tumours by genes whose expression was associated with survival in 47 tumours and validated subtypes on 34 publicly available GBC cases. RESULTS: Exome analysis revealed TP53 was the most mutated gene. The overall mutation rate was low (median 0.82 Mut/Mb). APOBEC-mediated mutational signatures were more common in tumours with higher mutational burden. Aflatoxin-related signatures tended to be highly clonal (present in ≥50% of cancer cells). Transcriptome-wide survival association analysis revealed a 95-gene signature that stratified all GBC patients into 3 subtypes that suggested an association with overall survival post-resection. The 2 poor-survival subtypes were associated with adverse clinicopathologic features (advanced stage, pN1, pM1), immunosuppressive micro-environments (myeloid-derived suppressor cell accumulation, extensive desmoplasia, hypoxia) and T cell dysfunction, whereas the good-survival subtype showed the opposite features. CONCLUSION: These data suggest that the tumour micro-environment and immune profiles could play an important role in gallbladder carcinogenesis and should be evaluated in future clinical studies, along with mutational profiles. LAY SUMMARY: Gallbladder cancer is highly fatal, and its causes are poorly understood. We evaluated gallbladder tumours to see if there were differences between tumours in genetic information such as DNA and RNA. We found evidence of aflatoxin exposure in these tumours, and immune cells surrounding the tumours were associated with survival.

Construction of the optimization prognostic model based on differentially expressed immune genes of lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common pathology subtype of lung cancer. In recent years, immunotherapy, targeted therapy and chemotherapeutics conferred a certain curative effects. However, the effect and prognosis of LUAD patients are different, and the efficacy of existing LUAD risk prediction models is unsatisfactory. METHODS: The Cancer Genome Atlas (TCGA) LUAD dataset was downloaded. The differentially expressed immune genes (DEIGs) were analyzed with edgeR and DESeq2. The prognostic DEIGs were identified by COX regression. Protein-protein interaction (PPI) network was inferred by STRING using prognostic DEIGs with p value< 0.05. The prognostic model based on DEIGs was established using Lasso regression. Immunohistochemistry was used to assess the expression of FERMT2, FKBP3, SMAD9, GATA2, and ITIH4 in 30 cases of LUAD tissues. RESULTS: In total,1654 DEIGs were identified, of which 436 genes were prognostic. Gene functional enrichment analysis indicated that the DEIGs were involved in inflammatory pathways. We constructed 4 models using DEIGs. Finally, model 4, which was constructed using the 436 DEIGs performed the best in prognostic predictions, the receiver operating characteristic curve (ROC) was 0.824 for 3 years, 0.838 for 5 years, 0.834 for 10 years. High levels of FERMT2, FKBP3 and low levels of SMAD9, GATA2, ITIH4 expression are related to the poor overall survival in LUAD (p < 0.05). The prognostic model based on DEIGs reflected infiltration by immune cells. CONCLUSIONS: In our study, we built an optimal prognostic signature for LUAD using DEIGs and verified the expression of selected genes in LUAD. Our result suggests immune signature can be harnessed to obtain prognostic insights.

Genetic variations in medical research in the past, at present and in the future.

As we look so different, our genomic sequences vary enormously. The differences in our genome, genetic variations, have played very significant roles in medical research and have contributed to improvement of medical managements in the last 2-3 decades. Genetic variations include germline variations, somatic mutations, and diversities in receptor genes of rearranged immune cells, T cells and B cells. Germline variants are in some cases causative of genetic diseases, are associated with the risk of various diseases, and also affect drug efficacies or adverse events. Some somatic mutations are causative of tumor development. Recent DNA sequencing technologies allow us to perform single-cell analysis or detailed repertoire analysis of B and T cells. It is critically important to investigate temporal changes in immune environment in various anatomical regions in the next one to two decades. In this review article, we would like to introduce the roles of genetic variations in medical fields in the past, at present and in the future.

Electrostatic Complementarity of T-Cell Receptor-Alpha CDR3 Domains and Mutant Amino Acids Is Associated with Better Survival Rates for Sarcomas.

While sarcoma immunology has advanced with regard to basic, and even some applied topics, this disease has not been subject to more recent immunogenomics approaches. Thus, we assessed the immune receptor recombinations available from the cancer genome atlas (TCGA) sarcoma database via tumor sample exome and RNASeq files. Results indicated that recovery of T-cell receptor-alpha recombination reads (TRA) correlated with a better survival rate, with the expression of T-cell biomarkers, and with tumor sample apoptosis signatures consistent with the longer patient survival times. Furthermore, samples representing TRA complementarity determining region-3 (CDR3) net charge per residue (NCPR) based complementarity with the corresponding sarcoma mutanome had a better survival rate, and more granzyme expression, than samples lacking such complementarity. By specifically using RNASeq-recovered TRA CDR3s and related NCPR assessments, three genes, TP53, ATRX, and RB1, were identified as being key components of the mutanome-based complementarity. Thus, these genes may represent key immune system targets for soft tissue sarcomas. Also, several key results from above were reproduced with a pediatric osteosarcoma dataset, work that led to identification of MUC6 mutations as potentially linked to a strong immune response. In sum, TRA CDR3s are likely to be important prognostic indicators, and possibly a beginning tool for immunotherapy development strategies, for adult and pediatric sarcomas.

Avian Immunome DB: an example of a user-friendly interface for extracting genetic information.

BACKGROUND: Genomic and genetic studies often require a target list of genes before conducting any hypothesis testing or experimental verification. With the ever-growing number of sequenced genomes and a variety of different annotation strategies, comes the potential for ambiguous gene symbols, making it cumbersome to capture the "correct" set of genes. In this article, we present and describe the Avian Immunome DB (AVIMM) for easy gene property extraction as exemplified by avian immune genes. The avian immune system is characterised by a cascade of complex biological processes underlaid by more than 1000 different genes. It is a vital trait to study particularly in birds considering that they are a significant driver in spreading zoonotic diseases. With the completion of phase II of the B10K ("Bird 10,000 Genomes") consortium's whole-genome sequencing effort, we have included 363 annotated bird genomes in addition to other publicly available bird genome data which serve as a valuable foundation for AVIMM. CONSTRUCTION AND CONTENT: A relational database with avian immune gene evidence from Gene Ontology, Ensembl, UniProt and the B10K consortium has been designed and set up. The foundation stone or the "seed" for the initial set of avian immune genes is based on the well-studied model organism chicken (Gallus gallus). Gene annotations, different transcript isoforms, nucleotide sequences and protein information, including amino acid sequences, are included. Ambiguous gene names (symbols) are resolved within the database and linked to their canonical gene symbol. AVIMM is supplemented by a command-line interface and a web front-end to query the database. UTILITY AND DISCUSSION: The internal mapping of unique gene symbol identifiers to canonical gene symbols allows for an ambiguous gene property search. The database is organised within core and feature tables, which makes it straightforward to extend for future purposes. The database design is ready to be applied to other taxa or biological processes. Currently, the database contains 1170 distinct avian immune genes with canonical gene symbols and 612 synonyms across 363 bird species. While the command-line interface readily integrates into bioinformatics pipelines, the intuitive web front-end with download functionality offers sophisticated search functionalities and tracks the origin for each record. AVIMM is publicly accessible at https://avimm.ab.mpg.de .

Immunogenomic pathways associated with cytotoxic lymphocyte infiltration and survival in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the second leading cancer killer in the US today and patients with metastatic disease have only a 14% 5-year survival. One of the most impactful recent advances in cancer therapy, immune checkpoint inhibition, has not been shown to be effective for the majority of these patients. In this study, we use The Cancer Genome Atlas (TCGA) and recently developed informatic-based tools to identify targets for immune based therapy in colorectal cancer patients. METHODS: Open access, pre-processed (level 3) mRNA data and clinical data from colorectal patients from the TCGA was downloaded from FireCloud. Using the Microenvironment Cell Populations-Counter method (MCP-Counter), cytotoxic lymphocyte scores were calculated for all patients. Patients were then grouped by cytotoxic lymphocyte score (High vs Low), pathologic stage, and location to identify differentially expressed genes. Pathway enrichment analysis was performed using Reactome to determine differentially expressed genes associated with immune pathways. Survival analysis was performed with identified differentially expressed genes. RESULTS: In the TCGA dataset, there are 461 colon and 172 rectal cancer patients. After stratifying patients by cytotoxic lymphocyte score, anatomical location, and stage, we found a significant number of differentially expressed genes. We identified one pathway, "immunoregulatory interactions between a lymphoid and non-lymphoid cell", that was highly enriched and included in all tumor locations and stages. Survival analysis performed with differentially expressed genes in this pathway identified 21 different genes associated with survival and cytotoxic lymphocyte infiltration, with ~ 70% of these genes occurring in the metastatic right-sided CRC group. Specifically, all genes associated with survival in the metastatic right-sided colorectal cancer group with low cytotoxic lymphocyte scores positively impacted survival. CONCLUSIONS: Utilizing the TCGA, a publicly available dataset, and informatics-based analyses, we identified potential targets to improve immune based therapy in colorectal cancer. Additionally, we note the most targets in metastatic right-sided CRC patients, the patient group with the worst predicted survival. The results from this study demonstrate the ability of informatics-based analytic techniques to identify new therapeutic targets as well as improve patient selection for intervention, helping us to achieve the goals of precision-based oncology.

Characterization of bovine MHC DRB3 diversity in global cattle breeds, with a focus on cattle in Myanmar.

BACKGROUND: Myanmar cattle populations predominantly consist of native cattle breeds (Pyer Sein and Shwe), characterized by their geographical location and coat color, and the Holstein-Friesian crossbreed, which is highly adapted to the harsh tropical climates of this region. Here, we analyzed the diversity and genetic structure of the BoLA-DRB3 gene, a genetic locus that has been linked to the immune response, in Myanmar cattle populations. METHODS: Blood samples (n = 294) were taken from two native breeds (Pyer Sein, n = 163 and Shwe Ni, n = 69) and a cattle crossbreed (Holstein-Friesian, n = 62) distributed across six regions of Myanmar (Bago, n = 38; Sagaing, n = 77; Mandalay, n = 46; Magway, n = 46; Kayin, n = 43; Yangon, n = 44). In addition, a database that included 2428 BoLA-DRB3 genotypes from European (Angus, Hereford, Holstein, Shorthorn, Overo Negro, Overo Colorado, and Jersey), Zebuine (Nellore, Brahman and Gir), Asian Native from Japan and Philippine and Latin-American Creole breeds was also included. Furthermore, the information from the IPD-MHC database was also used in the present analysis. DNA was genotyped using the sequence-based typing method. DNA electropherograms were analyzed using the Assign 400ATF software. RESULTS: We detected 71 distinct alleles, including three new variants for the BoLA-DRB3 gene. Venn analysis showed that 11 of these alleles were only detected in Myanmar native breeds and 26 were only shared with Asian native and/or Zebu groups. The number of alleles ranged from 33 in Holstein-Friesians to 58 in Pyer Seins, and the observed versus unbiased expected heterozygosity were higher than 0.84 in all the three the populations analyzed. The FST analysis showed a low level of genetic differentiation between the two Myanmar native breeds (FST = 0.003), and between these native breeds and the Holstein-Friesians (FST <  0.021). The average FST value for all the Myanmar Holstein-Friesian crossbred and Myanmar native populations was 0.0136 and 0.0121, respectively. Principal component analysis (PCA) and tree analysis showed that Myanmar native populations grouped in a narrow cluster that diverged clearly from the Holstein-Friesian populations. Furthermore, the BoLA-DRB3 allele frequencies suggested that while some Myanmar native populations from Bago, Mandalay and Yangon regions were more closely related to Zebu breeds (Gir and Brahman), populations from Kayin, Magway and Sagaing regions were more related to the Philippines native breeds. On the contrary, PCA showed that the Holstein-Friesian populations demonstrated a high degree of dispersion, which is likely the result of the different degrees of native admixture in these populations. CONCLUSION: This study is the first to report the genetic diversity of the BoLA-DRB3 gene in two native breeds and one exotic cattle crossbreed from Myanmar. The results obtained contribute to our understanding of the genetic diversity and distribution of BoLA-DRB3 gene alleles in Myanmar, and increases our knowledge of the worldwide variability of cattle BoLA-DRB3 genes, an important locus for immune response and protection against pathogens.