BACKGROUND: Gastrointestinal malignancies encompass a diverse group of cancers that pose significant challenges to global health. The major histocompatibility complex (MHC) plays a pivotal role in immune surveillance, orchestrating the recognition and elimination of tumor cells by the immune system. However, the intricate regulation of MHC gene expression is susceptible to dynamic epigenetic modification, which can influence functionality and pathological outcomes.
METHODS: By understanding the epigenetic alterations that drive MHC downregulation, insights are gained into the molecular mechanisms underlying immune escape, tumor progression, and immunotherapy resistance. This systematic review examines the current literature on epigenetic mechanisms that contribute to MHC deregulation in esophageal, gastric, pancreatic, hepatic and colorectal malignancies. Potential clinical implications are discussed of targeting aberrant epigenetic modifications to restore MHC expression and 0 the effectiveness of immunotherapeutic interventions.
CONCLUSIONS: The integration of epigenetic-targeted therapies with immunotherapies holds great potential for improving clinical outcomes in patients with gastrointestinal malignancies and represents a compelling avenue for future research and therapeutic development.

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, yet persistent challenges such as low response rate and significant heterogeneity necessitate attention. The pivotal role of the major histocompatibility complex (MHC) in ICI efficacy, its intricate impacts and potentials as a prognostic marker, warrants comprehensive exploration. This study integrates single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and spatial transcriptomic analyses to unveil pan-cancer immune characteristics governed by the MHC transcriptional feature (MHC.sig). Developed through scRNA-seq analysis of 663,760 cells across diverse cohorts and validated in 30 solid cancer types, the MHC.sig demonstrates a robust correlation between immune-related genes and infiltrating immune cells, highlighting its potential as a universal pan-cancer marker for anti-tumor immunity. Screening the MHC.sig for therapeutic targets using CRISPR data identifies potential genes for immune therapy synergy and validates its predictive efficacy for ICIs responsiveness across diverse datasets and cancer types. Finally, analysis of cellular communication patterns reveals interactions between C1QC+macrophages and malignant cells, providing insights into potential therapeutic agents and their sensitivity characteristics. This comprehensive analysis positions the MHC.sig as a promising marker for predicting immune therapy outcomes and guiding combinatorial therapeutic strategies.

Recent advances in cancer immunotherapy have highlighted the potential of neoantigen-based vaccines. However, the design of such vaccines is hindered by the possibility of weak binding affinity between the peptides and the patient\'s specific human leukocyte antigen (HLA) alleles, which may not elicit a robust adaptive immune response. Triggering cross-immunity by utilizing peptide mutations that have enhanced binding affinity to target HLA molecules, while preserving their homology with the original one, can be a promising avenue for neoantigen vaccine design. In this study, we introduced UltraMutate, a novel algorithm that combines Reinforcement Learning and Monte Carlo Tree Search, which identifies peptide mutations that not only exhibit enhanced binding affinities to target HLA molecules but also retains a high degree of homology with the original neoantigen. UltraMutate outperformed existing state-of-the-art methods in identifying affinity-enhancing mutations in an independent test set consisting of 3660 peptide-HLA pairs. UltraMutate further showed its applicability in the design of peptide vaccines for Human Papillomavirus and Human Cytomegalovirus, demonstrating its potential as a promising tool in the advancement of personalized immunotherapy.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

BACKGROUND: Atherosclerosis is a chronic cardiovascular disease of great concern. However, it is difficult to establish a direct connection between conventional small animal models and clinical practice. The pig\'s genome, physiology, and anatomy reflect human biology better than other laboratory animals, which is crucial for studying the pathogenesis of atherosclerosis.
METHODS: We used whole-genome sequencing data from nine Bama minipigs to perform a genome-wide linkage analysis, and further used bioinformatic tools to filter and identify underlying candidate genes. Candidate gene function prediction was performed using the online prediction tool STRING 12.0. Immunohistochemistry and immunofluorescence were used to detect the expression of proteins encoded by candidate genes.
RESULTS: We mapped differential single nucleotide polymorphisms (SNPs) to genes and obtained a total of 102 differential genes, then we used GO and KEGG pathway enrichment analysis to identify four candidate genes, including SLA-1, SLA-2, SLA-3, and TAP2. nsSNPs cause changes in the primary and tertiary structures of SLA-I and TAP2 proteins, the primary structures of these two proteins have undergone amino acid changes, and the tertiary structures also show slight changes. In addition, immunohistochemistry and immunofluorescence results showed that the expression changes of TAP2 protein in coronary arteries showed a trend of increasing from the middle layer to the inner layer.
CONCLUSIONS: We have identified SLA-I and TAP2 as potential susceptibility genes of atherosclerosis, highlighting the importance of antigen processing and immune response in atherogenesis.

Major histocompatibility complex (MHC) could serve as a potential biomarker for tumor immunotherapy, however, it is not yet known whether MHC could distinguish potential beneficiaries. Single-cell RNA sequencing datasets derived from patients with immunotherapy were collected to elucidate the association between MHC and immunotherapy response. A novel MHCsig was developed and validated using large-scale pan-cancer data, including The Cancer Genome Atlas and immunotherapy cohorts. The therapeutic value of MHCsig was further explored using 17 CRISPR/Cas9 datasets. MHC-related genes were associated with drug resistance and MHCsig was significantly and positively associated with immunotherapy response and total mutational burden. Remarkably, MHCsig significantly enriched 6% top-ranked genes, which were potential therapeutic targets. Moreover, we generated Hub-MHCsig, which was associated with survival and disease-special survival of pan-cancer, especially low-grade glioma. This result was also confirmed in cell lines and in our own clinical cohort. Later low-grade glioma-related Hub-MHCsig was established and the regulatory network was constructed. We provided conclusive clinical evidence regarding the association between MHCsig and immunotherapy response. We developed MHCsig, which could effectively predict the benefits of immunotherapy for multiple tumors. Further exploration of MHCsig revealed some potential therapeutic targets and regulatory networks.

Precision medicine\'s emphasis on individual genetic variants highlights the importance of haplotype-resolved assembly, a computational challenge in bioinformatics given its combinatorial nature. While classical algorithms have made strides in addressing this issue, the potential of quantum computing remains largely untapped. Here, we present the vehicle routing problem (VRP) assembler: an approach that transforms this task into a vehicle routing problem, an optimization formulation solvable on a quantum computer. We demonstrate its potential and feasibility through a proof of concept on short synthetic diploid and triploid genomes using a D-Wave quantum annealer. To tackle larger-scale assembly problems, we integrate the VRP assembler with Google\'s OR-Tools, achieving a haplotype-resolved local assembly across the human major histocompatibility complex (MHC) region. Our results show encouraging performance compared to Hifiasm with phasing accuracy approaching the theoretical limit, underscoring the promising future of quantum computing in bioinformatics.

Lactic acid bacteria (LAB) possess the ability to argument T cell activity through functional modification of antigen presenting cells (APCs), such as dendritic cells (DCs) and macrophages. Nevertheless, the precise mechanism underlying LAB-induced enhancement of antigen presentation in APCs remains incompletely understood. To address this question, we investigated the detailed mechanism underlying the enhancement of major histocompatibility complex (MHC) class I-restricted antigen presentation in DCs using a probiotic strain known as Lactococcus lactis subsp. Cremoris C60. We found that Heat-killed-C60 (HK-C60) facilitated the processing and presentation of ovalbumin (OVA) peptide antigen OVA257-264 (SIINFEKL) via H-2Kb in bone marrow-derived dendritic cells (BMDCs), leading to increased generation of effector CD8+ T cells both in vitro and in vivo. We also revealed that HK-C60 stimulation augmented the activity of 20S immunoproteasome (20SI) in BMDCs, thereby enhancing the MHC class I-restricted antigen presentation machinery. Furthermore, we assessed the impact of HK-C60 on CD8+ T cell activation in an OVA-expressing B16-F10 murine melanoma model. Oral administration of HK-C60 significantly attenuated tumor growth compared to control treatment. Enhanced Ag processing and presentation machineries in DCs from both Peyer\'s Patches (PPs) and lymph nodes (LNs) resulted in an increased tumor antigen specific CD8+ T cells. These findings shed new light on the role of LAB in MHC class-I restricted antigen presentation and activation of CD8+ T cells through functional modification of DCs.

Parkinson\'s disease (PD) is a common neurodegenerative disease characterized by progressive loss of dopaminergic neurons in the substantia nigra and the aggregation of alpha-synuclein (α-syn). The central nervous system (CNS) has previously been considered as an immune-privileged area. However, studies have shown that the immune responses are involved in PD. The major histocompatibility complex (MHC) presents antigens from antigen-presenting cells (APCs) to T lymphocytes, immune responses will be induced. MHCs are expressed in microglia, astrocytes, and dopaminergic neurons. Single nucleotide polymorphisms in MHC are related to the risk of PD. The aggregated α-syn triggers the expression of MHCs by activating glia cells. CD4+ and CD8+ T lymphocytes responses and microglia activation are detected in brains of PD patients. In addiction immune responses further increase blood-brain barrier (BBB) permeability and T cell infiltration in PD. Thus, MHCs are involved in PD through participating in immune and inflammatory responses.

BACKGROUND: The genetic improvement in growth and food habit domestication of largemouth bass (Micropterus salmoides) have made breakthroughs in past decades, while the relevant work on disease resistance were rarely carried out. Major histocompatibility complex (MHC) genes, which are well known as their numbers and high polymorphisms, have been used as candidate genes to mine disease-resistant-related molecular markers in many species.
RESULTS: In present study, we developed and characterized 40 polymorphic and biallelic InDel markers from the major histocompatibility complex genes of largemouth bass. The minor allele frequency, observed heterozygosity, expected heterozygosity and polymorphic information content of these markers ranged from 0.0556 to 0.5000, 0.1111 to 0.6389, 0.1064 to 0.5070, and 0.0994 to 0.3750, respectively. Three loci deviated significantly from Hardy-Weinberg equilibrium, while linkage disequilibrium existed at none of these loci.
CONCLUSIONS: These InDel markers might provide references for the further correlation analysis and molecular assisted selection of disease resistance in largemouth bass.