SOAPTyping: an open-source and cross-platform tool for sequence-based typing for HLA class I and II alleles

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field.

HLA Gene Polymorphisms in Romanian Patients with Chronic Lymphocytic Leukemia

Materials and Methods

This study included 66 patients with CLL, diagnosed between 2020 and 2022, and 100 healthy controls. HLA class I and class II genes (HLA-A/B/C, HLA-DQA1/DQB1/DPA1/DPB1, and HLA-DRB1/3/4/5) were investigated using next-generation sequencing technology.

Results

Several HLA alleles were strongly associated with CLL. The most important finding was that HLA-DRB1∗04:02:01 (p=0.001, OR = 1.05) and HLA-DRB3∗02:01:01 (p=0.009, OR = 1.03) have a predisposing role in CLL development. Moreover, we identified that HLA-A∗24:02:01 0.01 (p=0.01, OR = 0.38), HLA-DQA1∗05:05:01 (p=0.01, OR = 0.56), HLA-DQB1∗03:02:01 (p=0.03, OR = 0.40), and HLA-DRB4∗01:03:01 (p=0.03, OR = 0.54 alleles have protective roles. Correlations between HLA expression and gender showed that women had a higher expression of protective HLA alleles when compared to men.

Conclusions

Our data are the first to indicate that in Romanian patients with CLL, the HLA-A∗24:02:01 and HLA-DQA1∗05:05:01 alleles have a protective role against CLL development, whereas HLA-DRB1∗04:02:01 and HLA-DRB3∗02:01:01alleles are positively associated with CLL.

Increased Frequency of the HLA-DRB1*04:04-DQA1*03-DQB1*03:02 Haplotype Among HLA-DQB1*06:02-Positive Children With Type 1 Diabetes

HLA-DR/DQ haplotypes largely define genetic susceptibility to type 1 diabetes (T1D). The DQB1*06:02-positive haplotype (DR15-DQ602) common in individuals of European ancestry is very rare among children with T1D. Among 4,490 children with T1D in the Finnish Pediatric Diabetes Register, 57 (1.3%) case patients with DQB1*06:02 were identified, in comparison with 26.1% of affected family-based association control participants. There were no differences between DQB1*06:02-positive and -negative children with T1D regarding sex, age, islet autoantibody distribution, or autoantibody levels, but significant differences were seen in the frequency of second class II HLA haplotypes. The most prevalent haplotype present with DQB1*06:02 was DRB1*04:04-DQA1*03-DQB1*03:02, which was found in 27 (47.4%) of 57 children, compared with only 797 (18.0%) of 4,433 among DQB1*06:02-negative case patients (P < 0.001 by χ2 test). The other common risk-associated haplotypes, DRB1*04:01-DQA1*03-DQB1*03:02 and (DR3)-DQA1*05-DQB1*02, were less prevalent in DQB1*06:02-positive versus DQB1*06:02-negative children (P < 0.001). HLA-B allele frequencies did not differ by DQB1*06:02 haplotype between children with T1D and control participants or by DRB1*04:04-DQA1*03-DQB1*03:02 haplotype between DQB1*06:02-positive and -negative children with T1D. The increased frequency of the DRB1*04:04 allele among DQB1*06:02-positive case patients may indicate a preferential ability of the DR404 molecule to present islet antigen epitopes despite competition by DQ602.

ARTICLE HIGHLIGHTS

Design and generation of mRNAs encoding conserved regions of SARS-CoV-2 ORF1ab for T cell-mediated immune activation

Aim

To generate mRNAs encoding conserved regions within SARS-CoV-2 ORF1ab which can induce strong T-cell responses to overcome the immune invasion of newly emergent variants.

Methods

We selected two conserved regions with a high density of T-cell epitopes using immunoinformatics for mRNA synthesis. The ability of testing mRNAs to activate T cells for IFN-γ production was examined by an ELISpot assay and flow cytometry.

Results

Two synthesized mRNAs were successfully translated in MDA-MB-231 cells and had comparable potency to the spike mRNA to induce CD4+ and CD8+ T-cell responses in peripheral blood mononuclear cells in 29 out of 34 participants.

Conclusion

This study provides a proof-of-concept for the use of SARS-CoV-2 conserved regions to develop booster vaccines capable of eliciting T-cell-mediated immunity.

The novel HLA-C*03 allele, HLA-C*03:597, identified in a Chinese patient

HLA-C*03:597 differs from HLA-C*03:03:01:01 by a single non-synonymous nucleotide substitution in exon 5 (922 A>G).

Development of a high-resolution typing method for SLA-3, swine MHC class I antigen 3

We developed a high-resolution and comprehensive typing method for swine leukocyte antigen 3 (SLA-3), an MHC class I gene, employing locus-specific genomic PCR followed by subsequent direct sequencing. A total of 292 individuals from nine pure, one cross-breed and six cell lines were successfully typed. A total of 21 SLA-3 alleles were identified, of which four were found to be novel alleles. However, the allelic diversity of SLA-3 was lower than that of previously reported class I genes, SLA-1 and -2. More SLA-3 alleles were observed in the Landrace and Yorkshire breeds than the other breeds. SLA-3*04:01 was identified in seven out of nine breeds and was the most widely distributed allele across all breeds. Therefore, the typing method reported in this study completes our efforts to develop high-resolution typing methods for major SLA molecules, facilitating the combined analysis of major SLA genes from field samples, which is important to understand the relationship between the adaptive immune responses against pathogens and the immunogenetic makeup of an individual.