Binding Of Antigenic Peptides Research Articles

IFI30 as a key regulator of PDL1 immunotherapy prognosis in breast cancer

BackgroundIFI30 is a lysosomal thiol reductase involved in antigen presentation and immune regulation in various cancers, including breast cancer. Despite its known involvement, the precise mechanism, function, and relationship with the PD-L1 axis and immune response remain unclear. MethodsWe conducted an extensive investigation into IFI30 mRNA expression in breast cancer utilizing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Furthermore, we characterized IFI30 mRNA expression across various cell types using publicly available single-cell RNA sequencing datasets, and assessed protein expression through immunohistochemistry using an in-house breast cancer tissue microarray. Functional experiments were performed to elucidate the effects of IFI30 overexpression on PD-L1 expression and inhibitory efficacy in both macrophages and breast tumor cells. ResultsOur study unveiled a marked upregulation of IFI30 expression in breast cancer tissues compared to their normal counterparts, with notable associations identified with tumor stage and prognosis. Additionally, IFI30 expression demonstrated significant correlations with various immune-related signaling pathways, encompassing peptide antigen binding, cytokine binding, and MHC class II presentation. Notably, breast cancer samples exhibiting high IFI30 expression in tumor cells displayed high PD-L1 expression on corresponding cells, alongside a diminished ratio of CD8 + T cell infiltration within the tumor microenvironment. Furthermore, ectopic knockdown of IFI30 in both tumor cells and macrophages resulted in a reduction of PD-L1 expression, while conversely, overexpression of IFI30 led to an increase in PD-L1 expression. ConclusionsThis study offers new insights into the involvement of IFI30 in breast cancer, elucidating its interplay with the PD-L1 axis and immune response dynamics. Our findings suggest that modulation of the IFI30-PD-L1 axis could serve as a promising strategy for regulating T cells infiltration in breast cancer thus treating breast cancer.

Transcriptome analysis reveals modulation of differentially expressed genes in LPS-treated mouse macrophages (RAW264.7cells) by grouper (Epinephelus coioides) Epinecidin-1.

The marine antimicrobial peptide Epinecidin (Epi)-1 has been shown to exert direct antimicrobial and immunomodulatory actions in teleost, mammalian and avian organisms. For instance, Epi-1 can suppress bacterial endotoxin lipolysachcharide (LPS)-induced proinflammatory cytokines in RAW264.7 murine macrophages. However, it remains unknown how Epi-1 might broadly affect non-activated and LPS-activated macrophages. To address this question, we performed a comparative transcriptomic analysis of non-treated and LPS-treated RAW264.7cells in the presence and absence of Epi-1. Gene enrichment analysis was conducted on filtered reads, followed by GO and KEGG analyses. The results showed that Epi-1 treatment modulated pathways and genes associated with nucleoside binding, intramolecular oxidoreductase activity, GTPase activity, peptide antigen binding, GTP binding, ribonucleoside/nucleotide binding, phosphatidylinositol binding and phosphatidylinositol-4-phosphate binding. Based on the GO analysis results, we performed real-time PCR at different treatment times to compare expression levels of selected proinflammatory cytokines, anti-inflammatory cytokines, MHC, proliferation and differentiation genes. Epi-1 decreased expression of the proinflammatory cytokines, TNF-α, IL-6 and IL-1β, and it increased the anti-inflammatory cytokine TGFβ and Sytx1. MHC-associated genes, GM7030, Arfip1, Gpb11 and Gem, were induced by Epi-1, which is expected to enhance the immune response against LPS. Immunoglobulin-associated Nuggc was also upregulated by Epi-1. Finally, we found that Epi-1 downregulated the expression of host defense peptides CRAMP, Leap2 and BD3. Taken together, these findings suggest that Epi-1 treatment induces orchestrated changes in the transcriptome of LPS-stimulated RAW264.7cells.

MRNA Expression Profiles and Molecular Biomarkers Involved in Inflammatory Response for Essential Hypertension in Kazakh Population From Xinjiang

Abstract Background To identify hypertensive inflammation-related mRNA in peripheral blood mononuclear cells (PBMCs) from patients with essential hypertension (EH) of Kazakh Chinese population in Xinjiang, and offer theoretical foundation for further understanding the immune mechanisms that contribute to EH in Kazakh and provide specific molecular biomarkers for clinical diagnosis and targeted-specific treatments of this disorder. Methods Thirty Kazakh patients with EH and 30 age-matched healthy Kazakh people were divided into EH group and control group. After performing blood pressure measurement and determination of serum lipids and blood glucose, total RNA was isolated from PBMCs of hypertensive Kazakh patients and healthy Kazakh subjects, and differentially expressed mRNA in 6 randomly selected samples from each group were identified with human lncRNA/mRNA V4.0 microarray. Gene set enrichment analysis (GSEA), disease process, the Gene Ontology (GO), and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of differentially expressed mRNA were carried out using R language and ClusterProfiler software package. Reverse transcription quantitative real-time PCR (qRT-PCR) was used to validate the differential expression pattern of inflammation-related genes in the mRNA microarray data and results of bioinformatics analysis. Results The average blood pressure was significantly higher in the EH group than those in the control group (P < 0.01), while there was no statistical significance for the levels of serum lipids and blood glucose between the 2 groups. Compared with healthy Kazakh controls, a total of 522 mRNA were significantly differentially expressed from PBMCs of hypertensive Kazakh patients with fold change of ≥1.5 and P value <5% in expression. Among them, 411 were upregulated and 111 were downregulated. GO enrichment analysis of upregulated mRNA identified numerous inflammation-related biological processes and molecular functions. Many of these processes and molecular function were mainly involved in immune response-regulating signaling pathway, immune response-activating signal transduction, antigen binding, immunoglobulin receptor binding and peptide antigen binding, etc. GSEA and KEGG pathway analysis for the upregulated mRNA indicated several positively enriched gene sets and pathways related to inflammatory response, such as focal adhesion, cell adhesion molecules, chemokine signaling pathway, leukocyte transendothelial migration, cytokine–cytokine receptor interaction, and B-cell receptor signaling pathway. qRT-PCR validation results of 14 mRNA related to inflammatory response were consistent with the microarray data. Conclusions This is the first study to identify gene expression profile involved in hypertensive inflammation in Kazakh Chinese population in Xinjiang with EH, and not only provides specific molecular biomarkers for predicting and diagnosing progression of EH, but also will provide targeted-specific treatments of this disorder in Kazakh Chinese population in Xinjiang.

Chimeric Peptides from Californiconus californicus and Heterodontus francisci with Antigen-Binding Capacity: A Conotoxin Scaffold to Create Non-Natural Antibodies (NoNaBodies).

Research into various proteins capable of blocking metabolic pathways has improved the detection and treatment of multiple pathologies associated with the malfunction and overexpression of different metabolites. However, antigen-binding proteins have limitations. To overcome the disadvantages of the available antigen-binding proteins, the present investigation aims to provide chimeric antigen-binding peptides by binding a complementarity-determining region 3 (CDR3) of variable domains of new antigen receptors (VNARs) with a conotoxin. Six non-natural antibodies (NoNaBodies) were obtained from the complexes of conotoxin cal14.1a with six CDR3s from the VNARs of Heterodontus francisci and two NoNaBodies from the VNARs of other shark species. The peptides cal_P98Y vs. vascular endothelial growth factor 165 (VEGF165), cal_T10 vs. transforming growth factor beta (TGF-β), and cal_CV043 vs. carcinoembryonic antigen (CEA) showed in-silico and in vitro recognition capacity. Likewise, cal_P98Y and cal_CV043 demonstrated the capacity to neutralize the antigens for which they were designed.

Exploring Prognostic Biomarkers of Acute Myeloid Leukemia to Determine Its Most Effective Drugs from the FDA-Approved List through Molecular Docking and Dynamic Simulation.

Acute myeloid leukemia (AML) is a blood cancer caused by the abnormal proliferation and differentiation of hematopoietic stem cells in the bone marrow. The actual genetic markers and molecular mechanisms of AML prognosis are unclear till today. This study used bioinformatics approaches for identifying hub genes and pathways associated with AML development to uncover potential molecular mechanisms. The expression profiles of RNA-Seq datasets, GSE68925 and GSE183817, were retrieved from the Gene Expression Omnibus (GEO) database. These two datasets were analyzed by GREIN to obtain differentially expressed genes (DEGs), which were used for performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and survival analysis. The molecular docking and dynamic simulation were performed to identify the most effective drug/s for AML from the drug list approved by the Food and Drug Administration (FDA). By integrating the two datasets, 238 DEGs were identified as likely to be affected by AML progression. GO enrichment analyses exhibited that the upregulated genes were mainly associated with inflammatory response (BP) and extracellular region (CC). The downregulated DEGs were involved in the T-cell receptor signalling pathway (BP), an integral component of the lumenal side of the endoplasmic reticulum membrane (CC) and peptide antigen binding (MF). The pathway enrichment analysis showed that the upregulated DEGs were mainly associated with the T-cell receptor signalling pathway. Among the top 15 hub genes, the expression levels of ALDH1A1 and CFD were associated with the prognosis of AML. Four FDA-approved drugs were selected, and a top-ranked drug was identified for each biomarker through molecular docking studies. The top-ranked drugs were further confirmed by molecular dynamic simulation that revealed their binding stability and confirmed their stable performance. Therefore, the drug compounds, enasidenib and gilteritinib, can be recommended as the most effective drugs against the ALDH1A1 and CFD proteins, respectively.

Enzymatic processing and MHC loading in cancer immunotherapyAdvanced immunopeptidomics based discovery engine for the development of personalized cancer immunotherapy

The remarkable clinical efficacy of the immune checkpoint blockade therapies has motivated researchers to discover immunogenic epitopes and exploit them for personalized vaccines. Mutated human leukocyte antigen binding peptides (HLAp) are currently the leading targets. Most studies attempt to identify neoantigens based on predicted affinity to HLA molecules. We have shown that the direct identification of tissue-derived neoantigens by mass spectrometry is becoming feasible and we have recently designed a novel high-throughput, reproducible and sensitive method for sequential immuno-affinity purification of HLA-I and -II peptides that is suitable for both cell lines and tissues. The massive amount of HLAp data we acquire while hunting down the neo-antigens is highly valuable. We have compiled a large immunopeptidomics database across dozens of cell types and HLA allotypes. First, we have shown that by taking advantage of co-occurring HLA-I alleles across dozens of immunopeptidomics datasets we can rapidly and accurately identify HLA-I binding motifs. Consequently, training HLA-I ligand predictors on refined motifs significantly improves the identification of neoantigens. Recently, we have acquired the largest reported high-quality HLA-II peptidomics dataset. We introduced completely novel algorithmic tools to analyze such data and developed for the first time HLA-II epitope prediction tool trained on peptidomics data that results in major improvements in prediction accuracy. Second, our database captures the global nature of the in vivo peptidome averaged over many HLA alleles, and therefore, reflects the propensity of peptides to be presented on HLA complexes, which is complementary to the existing neoantigen prediction features. We have shown as a proof of concept that our immunopeptidomics MS-based features improved neoantigen prioritization by up to 50%. Overall, immunopeptidomics facilitates direct identification of neoantigens and it can also improve the prediction of clinically relevant neoantigens, and we develop a novel clinical pipeline for target selection for personalized anti-cancer vaccines.

How many post-translationally proteasomal spliced HLA-I peptides can be confidently identified in large scale MS/MS data?

Mass spectrometry-based immunopeptidomics is the method of choice for characterizing human leukocyte antigen binding peptides (HLAp) which play a key role in adaptive immunity. Recently two studies [1,2] reported that a large portion (20-40%) of HLAp’s originate from proteasomal splicing events. Both studies used large-scale mass spectrometry measurements of HLAp’s and bioinformatics analysis: the first study created a large sequence database containing all cis-spliced peptides to search the HLAp MS/MS spectra and the second study was based on de novo sequencing and subsequent filtration of cis-and trans-spliced peptides. We performed a reanalysis of the data of 1 and could not confirm most of the identifications reported in these studies 3,4 . Our results indicate that the proportion of HLAp that could be explained by proteasomal splicing was maximally a few percent. More recently, we reanalyzed part of the data from 2 . Comparison of predicted and observed hydrophobicity for the reported spliced and nonspliced peptides, and reanalysis of the data using state of the art MS/MS search engines indicate that the fraction of spliced peptides reported was vastly overestimated. Here we discuss the issues that arise when searching spliced peptides in large scale MS/MS data. We propose practical MS/MS search strategies and methods to properly control the error rate. We would like to emphasize that spliced peptides identifications from large-scale immunopeptidomics measurements should be carefully validated and confirmed with further biological experiments.

Charge-based interactions through peptide position 4 drive diversity of antigen presentation by human leukocyte antigen class I molecules.

Human leukocyte antigen class I (HLA-I) molecules bind and present peptides at the cell surface to facilitate the induction of appropriate CD8+ T cell-mediated immune responses to pathogen- and self-derived proteins. The HLA-I peptide-binding cleft contains dominant anchor sites in the B and F pockets that interact primarily with amino acids at peptide position 2 and the C-terminus, respectively. Nonpocket peptide–HLA interactions also contribute to peptide binding and stability, but these secondary interactions are thought to be unique to individual HLA allotypes or to specific peptide antigens. Here, we show that two positively charged residues located near the top of peptide-binding cleft facilitate interactions with negatively charged residues at position 4 of presented peptides, which occur at elevated frequencies across most HLA-I allotypes. Loss of these interactions was shown to impair HLA-I/peptide binding and complex stability, as demonstrated by both in vitro and in silico experiments. Furthermore, mutation of these Arginine-65 (R65) and/or Lysine-66 (K66) residues in HLA-A*02:01 and A*24:02 significantly reduced HLA-I cell surface expression while also reducing the diversity of the presented peptide repertoire by up to 5-fold. The impact of the R65 mutation demonstrates that nonpocket HLA-I/peptide interactions can constitute anchor motifs that exert an unexpectedly broad influence on HLA-I-mediated antigen presentation. These findings provide fundamental insights into peptide antigen binding that could broadly inform epitope discovery in the context of viral vaccine development and cancer immunotherapy.

Opening opportunities for Kd determination and screening of MHC peptide complexes

An essential element of adaptive immunity is selective binding of peptide antigens by major histocompatibility complex (MHC) class I proteins and their presentation to cytotoxic T lymphocytes. Using native mass spectrometry, we analyze the binding of peptides to an empty disulfide-stabilized HLA-A*02:01 molecule and, due to its unique stability, we determine binding affinities of complexes loaded with truncated or charge-reduced peptides. We find that the two anchor positions can be stabilized independently, and we further analyze the contribution of additional amino acid positions to the binding strength. As a complement to computational prediction tools, our method estimates binding strength of even low-affinity peptides to MHC class I complexes quickly and efficiently. It has huge potential to eliminate binding affinity biases and thus accelerate drug discovery in infectious diseases, autoimmunity, vaccine design, and cancer immunotherapy.

Genome-wide pharmacogenetics of anti-drug antibody response to bococizumab highlights key residues in HLA DRB1 and DQB1

In this largest to-date genetic analysis of anti-drug antibody (ADA) response to a therapeutic monoclonal antibody (MAb), genome-wide association was performed for five measures of ADA status among 8844 individuals randomized to bococizumab, which targets PCSK9 for LDL-C lowering and cardiovascular protection. Index associations prioritized specific amino acid substitutions at the DRB1 and DQB1 MHC class II genes rather than canonical haplotypes. Two clusters of missense variants at DRB1 were associated with general ADA measures (residues 9, 11, 13; and 96, 112, 120, 180) and a third cluster of missense variants in DQB1 was associated with ADA measures including neutralizing antibody (NAb) titers (residues 66, 67, 71, 74, 75). The structural disposition of the missense substitutions implicates peptide antigen binding and CD4 effector function, mechanisms that are potentially generalizable to other therapeutic mAbs.Clinicaltrials.gov: NCT01968954, NCT01968967, NCT01968980, NCT01975376, NCT01975389, NCT02100514.

Single HLA Class I Mismatches with High Peptide Divergence in the Graft-Versus-Host Direction Are Associated with Inferior Survival after 9/10 HLA-Matched UD-HCT: A Retrospective Study from the CIBMTR

IntroductionUnrelated donor (UD)-recipient disparity for human leukocyte antigen (HLA) class I adversely affects outcome of hematopoietic cell transplantation (UD-HCT). HLA polymorphisms in the peptide antigen binding groove can affect the repertoire of presented peptides. We have recently shown that the degree of peptide divergence between mismatched HLA-DP allotypes is related to T-cell alloreactivity and clinical permissiveness after UD-HCT (Meurer et al Blood 2021). Here, we hypothesized that the clinical tolerability also of HLA class I mismatches in UD-HCT might depend on the divergence of their respective peptide repertoires.MethodsWe studied 2,562 patients after 9/10 HLA-A, -B, -C, -DRB1, -DQB1-matched UD-HCT for acute myeloid or lymphocytic leukemia, or myelodysplastic syndrome, between 2008 and 2018, and 14,426 10/10 HLA-matched UD-HCT with similar characteristics. Peptide divergence of the mismatched HLA allotypes was predicted based on hierarchical clustering of experimentally determined peptide binding motifs (PBM) (Bassani-Sternberg et al Front Immunol 2018), with 21 different PBM groups identified in 122 HLA class I allotypes (44, 63 and 18 for HLA-A, -B and -C, respectively). The mismatched cohort was stratified into PBM-matches or PBM-mismatches, and within the latter into host-versus-graft (HvG), graft-versus-host (GvH) or bidirectional PBM-mismatches (Figure 1A). The primary study endpoint was overall survival (OS); secondary endpoints included treatment-related mortality (TRM), GVHD and relapse. P-value<0.01 was considered statistically significant.ResultsThe available PBM data allowed us to classify 1,629/2,562 (63.6%) of our pairs. Of these, 386 (23.7%) were PBM-matched and 1,243 (76.3%) were PBM-mismatched, and in the latter, 254 (20.5%), 238 (19.1%) and 751 (60.4%) had HvG, GvH or bidirectional PBM-mismatches, respectively. Transplants were performed mainly with peripheral blood stem cells (78%), myeloablative conditioning (65%) and tacrolimus-based graft-versus-host disease (GvHD) prophylaxis (74%). About half of the 9/10 HLA-matched HCT were performed using in vivo T-cell depletion by anti-thymocyte globulin or Campath, and none used post-transplant cyclophosphamide. Multivariable analyses showed that 10/10 HLA-matched transplants had significantly higher OS, lower TRM and aGvHD 3-4 compared to 9/10 HLA-matched transplants but relapse was similar (Figure 1B,C). There were no significant differences between the PBM-matched and aggregate PBM-mismatched group (Figure 1B). In further analysis, pairs with a bidirectional or only GvH PBM-mismatch had significantly worse OS, compared to pairs in the PBM-matched group or with only a unidirectional HvG (hazards ratio [HR] 0.76, 95% confidence interval [CI] 0.63-0.92, P = 0.0036; Figure 1C). The hazards of TRM and aGvHD 3-4 were lower for the HvG or PBM-matched group compared to the reference (HR 0.78, 95% CI 0.65-0.95, P = 0.0135 and HR 0.79, 95% CI 0.65-0.95, P = 0.0126, respectively), although these were not statistically significant (Figure 1C).ConclusionWe show that single HLA class I PBM-mismatches with high peptide divergence in the unidirectional or bidirectional GvH directions are significantly associated with worse survival after 9/10 HLA-matched UD-HCT compared to PBM-matched or unidirectional mismatching in the HvG direction. These data suggest that the mechanistic role of peptide-diversity for T-cell alloreactivity we previously observed for HLA-DPB1 disparity (Meurer et al., Blood 2021), is also a relevant to class I mismatches, providing a new rationale for selecting permissive donors in the setting of 9/10 HLA-matched UD-HCT. Avoiding class I PBM mismatches in the GvH direction is associated with better survival. [Display omitted] DisclosuresPaczesny: Medical University of South Carolina: Patents & Royalties: inventor on the ST2 bispecific antibody patent application. Lee: Amgen: Research Funding; AstraZeneca: Research Funding; Incyte: Research Funding; Janssen: Other; Kadmon: Research Funding; National Marrow Donor Program: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Syndax: Research Funding; Takeda: Research Funding.

The KAG motif of HLA-DRB1 (β71, β74, β86) predicts seroconversion and development of type 1 diabetes.

BackgroundHLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated.MethodsWe used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions.FindingsThree amino acid residues of HLA-DRB1 (β71, β74, β86) were found to be predictive of T1D risk in the population-based study. The “KAG” motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10−64). Three less frequent motifs (“EAV”, OR = 2.55, p = 0.025; “RAG”, OR = 1.93, p = 0.043; and “RAV”, OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs (“REG” and “REV”) were equally protective (OR = 0.11, p = 4.23 × 10−4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the “KAG” motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10−14) after adjusting potential confounders.InterpretationsDNA sequence variation in HLA-DRB1 at positions β71, β74, and β86 are non-conservative (β74 A→E, β71 E vs K vs R and β86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65.FundingNational Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

Gene signatures with predictive and prognostic survival values in human osteosarcoma

Osteosarcoma is a common malignancy seen mainly in children and adolescents. The disease is characterized by poor overall prognosis and lower survival due to a lack of predictive markers. Many gene signatures with diagnostic, prognostic, and predictive values were evaluated to achieve better clinical outcomes. Two public data series, GSE21257 and UCSC Xena, were used to identify the minimum number of robust genes needed for a predictive signature to guide prognosis of patients with osteosarcoma. The lasso regression algorithm was used to analyze sequencing data from TCGA-TARGET, and methods such as Cox regression analysis, risk factor scoring, receiving operating curve, KMplot prognosis analysis, and nomogram were used to characterize the prognostic predictive power of the identified genes. Their utility was assessed using the GEO osteosarcoma dataset. Finally, the functional enrichment analysis of the identified genes was performed. A total of twenty-gene signatures were found to have a good prognostic value for predicting patient survival. Gene ontology analysis showed that the key genes related to osteosarcoma were categorized as peptide–antigen binding, clathrin-coated endocytic vesicle membrane, peptide binding, and MHC class II protein complex. The osteosarcoma related genes in these modules were significantly enriched in the processes of antigen processing and presentation, phagocytosis, cell adhesion molecules, Staphylococcus aureus infection. Twenty gene signatures were identified related to osteosarcoma, which would be helpful for predicting prognosis of patients with OS. Further, these signatures can be used to determine the subtypes of osteosarcoma.

Identification of biomarkers associated with cervical lymph node metastasis in papillary thyroid carcinoma: Evidence from an integrated bioinformatic analysis.

Integrated analysis of accumulated data is an effective way to obtain reliable potential diagnostic molecular of cervical lymph node metastases (LNM) in papillary thyroid carcinoma (PTC). The benefits of prophylactic lymph node dissection (PLND) for these clinically node-negative (cN0) patients remained considerable controversies. Hence, elucidation of the mechanisms of LNM and exploration of potential biomarkers and prognostic indicators are essential for accurate diagnosis of LNM in PTC patients. Up to date, advanced microarray and bioinformatics analysis have advanced an understanding of the molecular mechanisms of disease occurrence and development, which are necessary to explore genetic changes and identify potential diagnostic biomarkers. In present study, we performed a comprehensive analysis of the differential expression, biological functions, and interactions of LNM-related genes. Two publicly available microarray datasets GSE60542 and GSE129562 were available from Gene Expression Omnibus (GEO) database. Differentially expressed genes between clinically node-positive (cN1) and cN0 PTC samples were screened by an integrated analysis of multiple gene expression profile after gene reannotation and batch normalization. Our results identified 48 differentially expressed genes (DEGs) genetically associated with LNM in PTC patients. Gene ontology (GO) analyses revealed the changes in the modules were mostly enriched in the regulation of MHC class II receptor activity, the immune receptor activity, and the peptide antigen binding. Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of DEGs displayed the intestinal immune network for IgA production, staphylococcus aureus infection, and cell adhesion molecules (CAMs). To screen core genes related to LNM of PTC from the protein-protein interaction network, top 10 hub genes were identified with highest scores. Our results help us understand the exact mechanisms underlying the metastasis of cervical LNM in PTC tissues and pave an avenue for the progress of precise medicine for individual patients.

Identification of a hippocampal lncRNA-regulating network in cognitive dysfunction caused by chronic cerebral hypoperfusion.

Cognitive dysfunction caused by chronic cerebral hypoperfusion is a common underlying cause of many cognition-related neurodegenerative diseases. The mechanisms of cognitive dysfunction caused by CCH are not clear. Long non-coding RNA is involved in synaptic plasticity and cognitive function, but whether lncRNA is involved in cognitive dysfunction caused by CCH has not yet been reported. In the present study, we identified the altered lncRNAs and mRNAs by deep RNA sequencing. A total of 128 mRNAs and 91 lncRNAs were up-regulated, and 108 mRNAs and 98 lncRNAs were down-regulated. Real-time reverse transcription-polymerase chain reaction verified the reliability of the lncRNA and mRNA sequencing. Gene Ontology and KEGG pathway analyses showed that differentially-expressed mRNAs were related to peptide antigen binding, the extracellular space, the monocarboxylic acid transport, and tryptophan metabolism. The co-expression analysis showed that 161 differentially expressed lncRNAs were correlated with DE mRNAs. By predicting the miRNA in which both DE lncRNAs and DE mRNAs bind together, we constructed a competitive endogenous RNA network. In this lncRNAs-miRNAs-mRNAs network, 559 lncRNA-miRNA-mRNA targeted pairs were identified, including 83 lncRNAs, 67 miRNAs, and 108 mRNAs. Through GO and KEGG pathway analysis, we further analyzed and predicted the regulatory function and potential mechanism of ceRNA network regulation. Our results are helpful for understanding the pathogenesis of cognitive dysfunction caused by CCH and provide direction for further research.

Next-Generation HLA Sequence Analysis Uncovers Seven HLA-DQ Amino Acid Residues and Six Motifs Resistant to Childhood Type 1 Diabetes.

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, β9, β30, β57, and β70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7-resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations (P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs "DAAFYDG," "DAAYHDG," and "DAAYYDR" have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10-24, 3.54 × 10-15, and 1.03 × 10-21, respectively). Remarkably, a change of a single residue from the motif "DAAYHDG" to "DAAYHSG" (D to S at β57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10-15) to a neutral motif (P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide-MHC class II complex stability, β167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-β heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

Insights from an in vitro derived T cell receptor

Abstract Heterodimeric alpha-beta T cell receptors (TCRs) play a key role in cell-mediated immune responses of adaptive immunity. T cells continuously probe peptides presented by major histocompatibility complex (MHC) found on the cell surface. T cell activation initiates through the binding of antigenic peptides on MHCs. Yeast display technology has proven an effective way to gain insight into the underpinnings of peptide-MHC specificity enabling the switching of TCR affinity and specificity to unrelated antigens through directed evolution. Interestingly, in vitro directed evolution also generates mutants that lose peptide specificity. Here, we provide further detail of one of these cross-reactive TCRs, S3–4, which binds tightly but with a highly unusual geometry. Despite binding with an affinity that is characteristic of a strong agonist, S3–4’s odd binding geometry does not support T cell signaling. Further investigation with functional experiments and 2D kinetics shows that lack of signaling by S3–4 is ultimately attributable to the TCR’s inability to reach ligand. Although S3–4 is an example from a constrained system generated outside the bounds of usual immune function, our results show how unusual binding can influence T cell function and further demonstrate how divergences between 3D and 2D binding parameters can emerge.

Activation of Dendritic Cells Alters the Mechanism of MHC Class II Antigen Presentation to CD4 T Cells

Abstract Both immature and mature DCs can process and present foreign antigens to CD4 T cells, however the mechanism by which MHC-II in mature DCs acquires antigenic peptides remains unknown. To address this we have studied antigen processing and presentation of two distinct CD4 T cells epitopes of the influenza virus haemagglutinin coat protein by both immature and mature DCs. We find that immature DCs almost exclusively use newly-synthesized MHC-II targeted to DM+ late endosomes for presentation to influenza virus-specific CD4 T cells. By contrast, mature DCs exclusively use recycling MHC-II that traffics to both early and late endosomes for antigenic peptide binding. Knock-down of the small GTPase Rab11a partially inhibits recycling of MHC-II in mature DCs and inhibits presentation of an influenza virus hemagglutinin CD4 T cell epitope generated in early endosomes. By contrast, knock-down of Rab11a does not affect presentation of an influenza virus hemagglutinin CD4 T cell epitope that is DM-dependent and is generated in late endosomes in both immature and mature DCs. These studies highlight a “division of labor” in MHC-II peptide binding in which immature DCs preferentially present antigens acquired in Rab11a− DM+ late endosomes whereas mature DCs use recycling MHC-II to present antigenic peptides acquired in both Rab11a+ early endosomes and Rab11a− endosomes for CD4 T cell activation.

Activation of Dendritic Cells Alters the Mechanism of MHC Class II Antigen Presentation to CD4 T Cells.

Both immature and mature dendritic cells (DCs) can process and present foreign Ags to CD4 T cells; however, the mechanism by which MHC class II (MHC-II) in mature DCs acquires antigenic peptides remains unknown. To address this, we have studied Ag processing and presentation of two distinct CD4 T cell epitopes of the influenza virus hemagglutinin coat protein by both immature and mature mouse DCs. We find that immature DCs almost exclusively use newly synthesized MHC-II targeted to DM+ late endosomes for presentation to influenza virus-specific CD4 T cells. By contrast, mature DCs exclusively use recycling MHC-II that traffics to both early and late endosomes for antigenic peptide binding. Rab11a knockdown partially inhibits recycling of MHC-II in mature DCs and selectively inhibits presentation of an influenza virus hemagglutinin CD4 T cell epitope generated in early endosomes. These studies highlight a "division of labor" in MHC-II peptide binding, in which immature DCs preferentially present Ags acquired in Rab11a- DM+ late endosomes, whereas mature DCs use recycling MHC-II to present antigenic peptides acquired in both Rab11a+ early endosomes and Rab11a- endosomes for CD4 T cell activation.

An engineered vaccine encompassing an MHC class I antigen presenting molecule induces self-reacting CTL in a setting of profound tolerance

Abstract Engineered antigen presenting molecules can promote allorecognition and activate CTL capable of recognizing weak or self-antigens in the context of self-MHC. Traditionally, allogeneic antigen presenting molecules differ from self MHC molecules in their interactions with the bound peptides and with TCR expressed in the immune repertoire to promote peptide dependent alloimmunity. Alloreactive T cells target their inducing alloantigens, as well as third-party alloantigens, but as a result of tolerance, generally not self-antigen presenting molecules. Certain residues located on the alpha-1/2 domains of class I antigen presenting molecules interface with TCR CDR loops and do not influence the nature or orientation of bound peptides. These residues are more conserved within and across species than are residues that determine peptide antigen binding properties. Class I variants designed with amino acid substitutions at key positions within the conserved helical structures at this MHC:TCR interface are found to provide strong activating signals to alloreactive CD8 T cells in the self tolerant immune repertoire. We demonstrate that CTL activated in this manner can break self-tolerance by reacting to self-peptides presented by native MHC. The ability to activate self-tolerant T cells capable of cross-reacting on self-peptide-MHC in vivo represents a novel approach for inducing autoimmunity, with possible application the development of cancer vaccines.