Insights into the polymorphism in HLA-DRA and its evolutionary relationship with HLA haplotypes

A genome-wide cross-trait analysis identifying shared genetic basis and causal relationships between Hunner-type interstitial cystitis and autoimmune diseases in East Asian populations

PURPOSE

Epidemiological studies have demonstrated the clinical link between Hunner interstitial cystitis (HIC) and autoimmune diseases (ADs), suggesting potential shared genetic bases for their comorbidity. We aimed to investigate the shared genetic architecture and causal relationships between HIC and ADs.

METHODS

We conducted a genome-wide cross-trait study with ~170000 individuals of East Asian ancestry to investigate the shared architecture between HIC and ADs. Bidirectional Mendelian randomization (MR) was used to assess potential causal relationships and a multi-trait analysis of GWAS (MTAG) was conducted to identify their associated pleiotropic loci. Fine-mapping analysis narrowed candidate gene susceptibility loci and colocalization analysis was performed to identify shared variants at specific locus. Lastly, transcriptome-wide association (TWAS) and functional analysis were utilized to explore potential shared gene-tissue associations.

RESULTS

Through bidirectional MR analysis, we observed a positive causal effect of AIH(ORIVW=1.09, PIVW=1.00×10-3) and RA (ORIVW=1.47, PIVW<1.00×10-4) on HIC and a negative causal effect of UC on HIC (ORIVW=0.89, PIVW< 1.00×10-4). Furthermore, we unveiled a robust positive causal effect of HIC on T1D(ORConMix=1.05, PConMix=1.77×10-3). Cross-trait meta-analysis identified a total of 64 independent SNPs associated with HIC and ADs. Functional analysis revealed that the identified variants regulated gene expression in major tissues belonging to the autoimmune system.

CONCLUSIONS

Our findings might offer insights into the shared underlying etiology of HIC and ADs.

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

Introduction

Modern histocompatibility algorithms depend on the comparison and analysis of high-resolution HLA protein sequences and structures, especially when considering epitope-based algorithms, which aim to model the interactions involved in antibody or T cell binding. HLA genotype imputation can be performed in the cases where only low/intermediate-resolution HLA genotype is available or if specific loci are missing, and by providing an individuals' race/ethnicity/ancestry information, imputation results can be more accurate. This study assesses the effect of imputing high-resolution genotypes on molecular mismatch scores under a variety of ancestry assumptions.

Methods

We compared molecular matching scores from "ground-truth" high-resolution genotypes against scores from genotypes which are imputed from low-resolution genotypes. Analysis was focused on a simulated patient-donor dataset and confirmed using two real-world datasets, and deviations were aggregated based on various ancestry assumptions.

Results

We observed that using multiple imputation generally results in lower error in molecular matching scores compared to single imputation, and that using the correct ancestry assumptions can reduce error introduced during imputation.

Discussion

We conclude that for epitope analysis, imputation is a valuable and low-risk strategy, as long as care is taken regarding epitope analysis context, ancestry assumptions, and (multiple) imputation strategy.

Establishment and validation of a novel disulfidptosis-related immune checkpoint gene signature in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal tumors and is associated with a unfavorable prognosis. Disulfidptosis is a recently identified form of cell death mediated by disulfide bonds. Numerous studies have highlighted the significance of immune checkpoint genes (ICGs) in ccRCC. Nevertheless, the involvement of disulfidptosis-related immune checkpoint genes (DRICGs) in ccRCC remains poorly understood.

METHODS

The mRNA expression profiles and clinicopathological data of ccRCC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases. The associations between disulfidptosis-related genes (DRGs) and immune checkpoint genes (ICGs) were assessed to identify DRICGs. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were conducted to construct a risk signature.

RESULTS

A total of 39 differentially expressed immune-related candidate genes were identified. A prognostic signature was constructed utilizing nine DRICGs (CD276, CD80, CD86, HLA-E, LAG3, PDCD1LG2, PVR, TIGIT, and TNFRSF4) and validated using GEO data. The risk model functioned as an independent prognostic indicator for ccRCC, while the associated nomogram provided a reliable scoring system for ccRCC. Gene set enrichment analysis indicated enrichment of phospholipase D, antigen processing and presentation, and ascorbate and aldarate metabolism-related signaling pathways in the high-risk group. Furthermore, the DRICGs exhibited correlations with the infiltration of various immune cells. It is noteworthy that patients with ccRCC categorized into distinct risk groups based on this model displayed varying sensitivities to potential therapeutic agents.

CONCLUSIONS

The novel DRICG-based risk signature is a reliable indicator for the prognosis of ccRCC patients. Moreover, it also aids in drug selection and correlates with the tumour immune microenvironment in ccRCC.

HLA Haplotypes and Relapse After Hematopoietic Cell Transplantation

PURPOSE

Recurrence of blood malignancy is the major cause of hematopoietic cell transplant failure. HLA class II molecules play a fundamental role in antitumor responses but the role of class II haplotypes is not known.

METHODS

HLA-DR, -DQ, -DM, and -DO allele variation was determined in 1,629 related haploidentical transplants to study the clinical significance of individual molecules and haplotypes.

RESULTS

Outcome correlated with patient and donor variation for HLA-DRβ residue 86 (Gly/Val), HLA-DQ (G1/G2) heterodimers, and donor HLA-DM (DM11,11/nonDM11,11) molecules, and depended on patient-donor mismatching. Risks of relapse were lower for DRβ-86 GlyGly patients when the donor was GlyVal (hazard ratio [HR], 0.46 [95% CI, 0.30 to 0.68]; P < .001); GlyVal patients benefited from HLA-DRB1-matched donors, whereas no donor was superior to another for ValVal patients. G1G2 patients with G1G2-mismatched donors had lower relapse. Transplantation from donors with DMα residue 184 ArgHis was associated with higher risk of relapse (HR, 1.60 [95% CI, 1.09 to 2.36]; P = .02) relative to ArgArg. Relapse and mortality risks differed across HLA-DR-DQ-DM haplotypes.

CONCLUSION

HLA class II haplotypes may be functional constituents of the transplantation barrier, and their consideration in patients and donors may improve the success of transplantation.

In Silico Tools for Predicting Novel Epitopes

Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.

HLA diversity in ethnic populations can affect detection of donor-specific antibodies by single antigen beads

Introduction

In solid-organ transplantation, human leukocyte antigen (HLA) donor-specific antibodies (DSA) are strongly associated with graft rejection, graft loss, and patient death. The predominant tests used for detecting HLA DSA before and after solid-organ transplantation are HLA single antigen bead (SAB) assays. However, SAB assays may not detect antibodies directed against HLA epitopes that are not represented in the SAB. The prevalence and potential impact of unrepresented HLA epitopes are expected to vary by ethnicity, but have not been thoroughly investigated. To address this knowledge gap, HLA allele frequencies from seven ethnic populations were compared with HLA proteins present in SAB products from two manufacturers to determine unrepresented HLA proteins.

Materials

Allele frequencies were obtained from the Common, Intermediate, and Well Documented HLA catalog v3.0, and frequencies of unrepresented HLA types were calculated. Next-generation sequencing was used to determine HLA types of 60 deceased solid-organ donors, and results were used to determine if their HLA-A, -B, -C, and -DRB1 proteins were not present in SAB reagents from two vendors. Unrepresented HLA proteins were compared with the most similar protein in SAB assays from either vendor and then visualized using modeling software to assess potential HLA epitopes.

Results

For the seven ethnic populations, 0.5% to 11.8% of each population had HLA proteins not included in SAB assays from one vendor. Non-European populations had greater numbers of unrepresented alleles. Among the deceased donors, 26.7% (16/60) had at least one unrepresented HLA-A, -B, -C, or -DRB1 protein. Structural modeling demonstrated that a subset of these had potential HLA epitopes that are solvent accessible amino acid mismatches and are likely to be accessible to B cell receptors.

Discussion

In conclusion, SAB assays cannot completely rule out the presence of HLA DSA. HLA epitopes not represented in those assays vary by ethnicity and should not be overlooked, especially in non-European populations. Allele-level HLA typing can help determine the potential for HLA antibodies that could evade detection.

Integrative Mendelian randomization reveals the soluble receptor for advanced glycation end products as protective in relation to rheumatoid arthritis

Rheumatoid arthritis (RA) is a risk factor for atherosclerotic cardiovascular diseases (CVD). Given the critical roles of the immune system and inflammatory signals in the pathogenesis of CVD, we hypothesized that interrogation of CVD-related proteins using integrative genomics might provide new insights into the pathophysiology of RA. We utilized two-sample Mendelian randomization (MR) for causal inference between circulating protein levels and RA by incorporating genetic variants, followed by colocalization to characterize the causal associations. Genetic variants from three sources were obtained: those associated with 71 CVD-related proteins measured in nearly 7000 Framingham Heart Study participants, a published genome-wide association study (GWAS) of RA (19 234 cases, 61 565 controls), and GWAS of rheumatoid factor (RF) levels from the UK Biobank (n = 30 565). We identified the soluble receptor for advanced glycation end products (sRAGE), a critical inflammatory pathway protein, as putatively causal and protective for both RA (odds ratio per 1-standard deviation increment in inverse-rank normalized sRAGE level = 0.364; 95% confidence interval 0.342-0.385; P = 6.40 × 10-241) and RF levels (β [change in RF level per sRAGE increment] = - 1.318; SE = 0.434; P = 0.002). Using an integrative genomic approach, we highlight the AGER/RAGE axis as a putatively causal and promising therapeutic target for RA.

A combination of HLA-DP α and β chain polymorphisms paired with a SNP in the DPB1 3' UTR region, denoting expression levels, are associated with atopic dermatitis

Introduction: Components of the immune response have previously been associated with the pathophysiology of atopic dermatitis (AD), specifically the Human Leukocyte Antigen (HLA) Class II region via genome-wide association studies, however the exact elements have not been identified. Methods: This study examines the genetic variation of HLA Class II genes using next generation sequencing (NGS) and evaluates the resultant amino acids, with particular attention on binding site residues, for associations with AD. The Genetics of AD cohort was used to evaluate HLA Class II allelic variation on 464 subjects with AD and 384 controls. Results: Statistically significant associations with HLA-DP α and β alleles and specific amino acids were found, some conferring susceptibility to AD and others with a protective effect. Evaluation of polymorphic residues in DP binding pockets revealed the critical role of P1 and P6 (P1: α31M + (β84G or β84V) [protection]; α31Q + β84D [susceptibility] and P6: α11A + β11G [protection]) and were replicated with a national cohort of children consisting of 424 AD subjects. Independently, AD susceptibility-associated residues were associated with the G polymorphism of SNP rs9277534 in the 3' UTR of the HLA-DPB1 gene, denoting higher expression of these HLA-DP alleles, while protection-associated residues were associated with the A polymorphism, denoting lower expression. Discussion: These findings lay the foundation for evaluating non-self-antigens suspected to be associated with AD as they potentially interact with particular HLA Class II subcomponents, forming a complex involved in the pathophysiology of AD. It is possible that a combination of structural HLA-DP components and levels of expression of these components contribute to AD pathophysiology.

Correspondence analysis for dimension reduction, batch integration, and visualization of single-cell RNA-seq data

Effective dimension reduction is essential for single cell RNA-seq (scRNAseq) analysis. Principal component analysis (PCA) is widely used, but requires continuous, normally-distributed data; therefore, it is often coupled with log-transformation in scRNAseq applications, which can distort the data and obscure meaningful variation. We describe correspondence analysis (CA), a count-based alternative to PCA. CA is based on decomposition of a chi-squared residual matrix, avoiding distortive log-transformation. To address overdispersion and high sparsity in scRNAseq data, we propose five adaptations of CA, which are fast, scalable, and outperform standard CA and glmPCA, to compute cell embeddings with more performant or comparable clustering accuracy in 8 out of 9 datasets. In particular, we find that CA with Freeman-Tukey residuals performs especially well across diverse datasets. Other advantages of the CA framework include visualization of associations between genes and cell populations in a "CA biplot," and extension to multi-table analysis; we introduce corralm for integrative multi-table dimension reduction of scRNAseq data. We implement CA for scRNAseq data in corral, an R/Bioconductor package which interfaces directly with single cell classes in Bioconductor. Switching from PCA to CA is achieved through a simple pipeline substitution and improves dimension reduction of scRNAseq datasets.

A systemic review of T-cell epitopes defined from the proteome of SARS-CoV-2

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains in a global pandemic, and no eradicative therapy is currently available. Host T cells have been shown to play a crucial role in the antiviral immune protection and pathology in Coronavirus disease 2019 (COVID-19) patients; thus, identifying sufficient T-cell epitopes from the SARS-CoV-2 proteome can contribute greatly to the development of T-cell epitope vaccines and the precise evaluation of host SARS-CoV-2-specific cellular immunity. This review presents a comprehensive map of T-cell epitopes functionally validated from SARS-CoV-2 antigens, the human leukocyte antigen (HLA) supertypes to present these epitopes, and the strategies to screen and identify T-cell epitopes. To the best of our knowledge, a total of 1349 CD8+ T-cell epitopes and 790 CD4+ T-cell epitopes have been defined by functional experiments thus far, but most are presented by approximately twenty common HLA supertypes, such as HLA-A0201, A2402, B0702, DR15, DR7 and DR11 molecules, and 74-80% of the T-cell epitopes are derived from S protein and nonstructural protein. These data provide useful insight into the development of vaccines and specific T-cell detection systems. However, the currently defined T-cell epitope repertoire cannot cover the HLA polymorphism of major populations in an indicated geographic region. More research is needed to depict an overall landscape of T-cell epitopes, which covers the overall SARS-CoV-2 proteome and global patients.

Large-Scale Complete Sequencing and Haplotyping of 1-10 kb DNA Molecules Using Short Massively Parallel Reads

In this chapter, we describe a simple, low-cost method for making many copies of a single DNA molecule (1-10 kb in length) as a concatemer on a long DNA strand. This can enable applications requiring high-quality contiguous sequence and haplotype data from long single DNA molecules at large scale.

An Approach to Identify HLA Class II Immunogenic Epitopes in the Greek Population through Machine Learning Algorithms

Current pre-transplantation routine matching involves serum anti-HLA antibodies quantification but cannot always preclude unfavorable graft outcomes. Epitope-based matching is proposed as a more precise approach, but to date no epitope-matching algorithm provides a satisfactory predictive tool for transplantation outcomes. In this study, anti-HLA-II loci responses from 1748 patients were analyzed with unsupervised machine learning algorithms, namely principal component analysis (PCA) and antigenic distances, projected as dendrograms. PCA for anti-HLA-DR anti-bodies revealed three main clusters of responses: anti-HLA-DR51 combined with anti-HLA-DRB1*01, anti-HLA-DR52 combined with anti-HLA-DRB1*08 and anti-HLA-DR53 combined with anti-HLA-DRB1*10. The dendrogram for anti-HLA-DR confirmed the pattern and showed further bisection of each cluster. Common epitopes present exclusively in all HLA molecules of each cluster were determined following the HLA epitope registry. Thus, we propose that 19 out of 123 HLA-DR epitopes are those that mainly lead anti-HLA-DR responses in the studied population. Likewise, we identified 22 out of 83 epitopes responsible for anti-HLA-DQ and 13 out of 62 responsible for anti-HLA-DP responses. Interpretation of these results may elucidate mechanisms of interlocus cross-reactivity, providing an alternative way of estimating the significance of each epitope in a population and thus suggesting a novel strategy towards optimal donor selection.

Pathway Analysis of Genome Wide Association Studies (GWAS) Data Associated with Male Infertility

Background: Infertility is a common condition affecting approximately 10–20% of the reproductive age population. Idiopathic infertility cases are thought to have a genetic basis, but the underlying causes are largely unknown. However, the genetic basis underlying male infertility in humans is only partially understood. The Purpose of the study is to understand the current state of research on the genetics of male infertility and its association with significant biological mechanisms. Results: We performed an Identify Candidate Causal SNPs and Pathway (ICSN Pathway) analysis using a genome-wide association study (GWAS) dataset, and NCBI-PubMed search which included 632 SNPs in GWAS and 451 SNPs from the PubMed server, respectively. The ICSN Pathway analysis produced three hypothetical biological mechanisms associated with male infertility: (1) rs8084 and rs7192→HLA-DRA→inflammatory pathways and cell adhesion; rs7550231 and rs2234167→TNFRSF14→TNF Receptor Superfamily Member 14→T lymphocyte proliferation and activation; rs1105879 and rs2070959→UGT1A6→UDP glucuronosyltransferase family 1 member A6→Metabolism of Xenobiotics, androgen, estrogen, retinol, and carbohydrates. Conclusions: We believe that our results may be helpful to study the genetic mechanisms of male infertility. Pathway-based methods have been applied to male infertility GWAS datasets to investigate the biological mechanisms and reported some novel male infertility risk pathways. This pathway analysis using GWAS dataset suggests that the biological process related to inflammation and metabolism might contribute to male infertility susceptibility. Our analysis suggests that genetic contribution to male infertility operates through multiple genes affecting common inflammatory diseases interacting in functional pathways.

Comparative Genomics of the Major Histocompatibility Complex (MHC) of Felids

This review summarizes the current knowledge on the major histocompatibility complex (MHC) of the family Felidae. This family comprises an important domestic species, the cat, as well as a variety of free-living felids, including several endangered species. As such, the Felidae have the potential to be an informative model for studying different aspects of the biological functions of MHC genes, such as their role in disease mechanisms and adaptation to different environments, as well as the importance of genetic diversity for conservation issues in free-ranging or captive populations. Despite this potential, the current knowledge on the MHC in the family as a whole is fragmentary and based mostly on studies of the domestic cat and selected species of big cats. The overall structure of the domestic cat MHC is similar to other mammalian MHCs following the general scheme "centromere-MHC class I-MHC class III-MHC class II" with some differences in the gene contents. An unambiguously defined orthologue of the non-classical class I HLA-E gene has not been identified so far and the class II DQ and DP genes are missing or pseudogenized, respectively. A comparison with available genomes of other felids showed a generally high level of structural and sequence conservation of the MHC region. Very little and fragmentary information on in vitro and/or in vivo biological functions of felid MHC genes is available. So far, no association studies have indicated effects of MHC genetic diversity on a particular disease. No information is available on the role of MHC class I molecules in interactions with Natural Killer (NK) cell receptors or on the putative evolutionary interactions (co-evolution) of the underlying genes. A comparison of complex genomic regions encoding NK cell receptors (the Leukocyte Receptor Complex, LRC and the Natural Killer Cell Complex, NKC) in the available felid genomes showed a higher variability in the NKC compared to the LRC and the MHC regions. Studies of the genetic diversity of domestic cat populations and/or specific breeds have focused mainly on DRB genes. Not surprisingly, higher levels of MHC diversity were observed in stray cats compared to pure breeds, as evaluated by DRB sequencing as well as by MHC-linked microsatellite typing. Immunogenetic analysis in wild felids has only been performed on MHC class I and II loci in tigers, Namibian leopards and cheetahs. This information is important as part of current conservation tasks to assess the adaptive potential of endangered wild species at the human-wildlife interface, which will be essential for preserving biodiversity in a functional ecosystem.

Epstein-Barr Virus and Neurological Diseases

Epstein-Barr virus (EBV), also known as human herpesvirus 4, is a double-stranded DNA virus that is ubiquitous in 90–95% of the population as a gamma herpesvirus. It exists in two main states, latent infection and lytic replication, each encoding viral proteins with different functions. Human B-lymphocytes and epithelial cells are EBV-susceptible host cells. EBV latently infects B cells and nasopharyngeal epithelial cells throughout life in most immunologically active individuals. EBV-infected cells, free viruses, their gene products, and abnormally elevated EBV titers are observed in the cerebrospinal fluid. Studies have shown that EBV can infect neurons directly or indirectly via infected B-lymphocytes, induce neuroinflammation and demyelination, promote the proliferation, degeneration, and necrosis of glial cells, promote proliferative disorders of B- and T-lymphocytes, and contribute to the occurrence and development of nervous system diseases, such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, acute cerebellar ataxia, meningitis, acute disseminated encephalomyelitis, and brain tumors. However, the specific underlying molecular mechanisms are unclear. In this paper, we review the mechanisms underlying the role of EBV in the development of central nervous system diseases, which could bebeneficial in providing new research ideas and potential clinical therapeutic targets for neurological diseases.

T-Cell Epitopes Shared Between Immunizing HLA and Donor HLA Associate With Graft Failure After Kidney Transplantation

CD4⁺ T-helper cells play an important role in alloimmune reactions following transplantation by stimulating humoral as well as cellular responses, which might lead to failure of the allograft. CD4⁺ memory T-helper cells from a previous immunizing event can potentially be reactivated by exposure to HLA mismatches that share T-cell epitopes with the initial immunizing HLA. Consequently, reactivity of CD4⁺ memory T-helper cells toward T-cell epitopes that are shared between immunizing HLA and donor HLA could increase the risk of alloimmunity following transplantation, thus affecting transplant outcome. In this study, the amount of T-cell epitopes shared between immunizing and donor HLA was used as a surrogate marker to evaluate the effect of donor-reactive CD4⁺ memory T-helper cells on the 10-year risk of death-censored kidney graft failure in 190 donor/recipient combinations using the PIRCHE-II algorithm. The T-cell epitopes of the initial theoretical immunizing HLA and the donor HLA were estimated and the number of shared PIRCHE-II epitopes was calculated. We show that the natural logarithm-transformed PIRCHE-II overlap score, or Shared T-cell EPitopes (STEP) score, significantly associates with the 10-year risk of death-censored kidney graft failure, suggesting that the presence of pre-transplant donor-reactive CD4⁺ memory T-helper cells might be a strong indicator for the risk of graft failure following kidney transplantation.

Identification of three novel HLA-DRA alleles by next-generation sequencing

Three novel HLA-DRA alleles, DRA*01:03, DRA*01:04, and DRA*01:05 alleles with unique amino acid sequences.

MLLT6 maintains PD-L1 expression and mediates tumor immune resistance

Tumor cells subvert immune surveillance by harnessing signals from immune checkpoints to acquire immune resistance. The protein PD‐L1 is an important component in this process, and inhibition of PD‐L1 elicits durable anti‐tumor responses in a broad spectrum of cancers. However, immune checkpoint inhibition that target known pathways is not universally effective. A better understanding of the genetic repertoire underlying these processes is necessary to expand our knowledge in tumor immunity and to facilitate identification of alternative targets. Here, we present a CRISPR/Cas9 screen in human cancer cells to identify genes that confer tumors with the ability to evade the cytotoxic effects of the immune system. We show that the transcriptional regulator MLLT6 (AF17) is required for efficient PD‐L1 protein expression and cell surface presentation in cancer cells. MLLT6 depletion alleviates suppression of CD8⁺ cytotoxic T cell‐mediated cytolysis. Furthermore, cancer cells lacking MLLT6 exhibit impaired STAT1 signaling and are insensitive to interferon‐γ‐induced stimulation of IDO1, GBP5, CD74, and MHC class II genes. Collectively, our findings establish MLLT6 as a regulator of oncogenic and interferon‐γ‐associated immune resistance.

C3, C3AR1, HLA-DRA, and HLA-E as potential prognostic biomarkers for renal clear cell carcinoma

Background

Prognostic biomarkers play a vital role in the early detection of the cancer and assessment of prognosis. With advances in technology, a large number of biomarkers of kidney renal clear cell carcinoma (KIRC) have been discovered, but their prognostic value has not been fully investigated, and thus have not been widely used in clinical practice. We aimed to identify the reliable markers associated with the prognosis of KIRC patients.

Methods

We obtained 72 normal samples and 539 tumor samples from The Cancer Genome Atlas (TCGA), and 23 normal samples and 32 tumor samples from the Gene Expression Omnibus (GEO). Overlapping differentially expressed genes (ODEGs) were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, followed by construction of a protein-protein interaction (PPI) network to screen hub genes. Kaplan-Meier analysis, univariate Cox analysis, multivariate Cox analysis, Wilcoxon signed-rank test, Kruskal-Wallis test, and gene set enrichment analysis (GSEA) were performed to verify the prognostic value and function of the markers we selected. The relationships among gene expression level, tumor immune cell infiltration, and immune-checkpoints were also analyzed.

Results

A total of 910 genes were screened out, and C3, C3AR1, HLA-DRA, and HLA-E were identified as potential tumor markers. The expression of each gene was closely associated with tumor immune cell infiltration, survival rate, and the patients’ clinical characteristics (P<0.05). C3AR1, HLA-DRA, and HLA-E were also verified as independent prognostic factors of KIRC (P<0.05), and all these potential biomarkers had a close correlation with immune checkpoints.

Conclusions

C3, C3AR1, HLA-DRA, and HLA-E could be reliable biomarkers of KIRC and may have a significant contribution to make in immunotherapy, thus playing an important role in the improvement of prognosis.

A long road/read to rapid high-resolution HLA typing: The nanopore perspective

Next-generation sequencing (NGS) has been widely adopted for clinical HLA typing and advanced immunogenetics researches. Current methodologies still face challenges in resolving cis-trans ambiguity involving distant variant positions, and the turnaround time is affected by testing volume and batching. Nanopore sequencing may become a promising addition to the existing options for HLA typing. The technology delivered by the MinION sequencer of Oxford Nanopore Technologies (ONT) can record the ionic current changes during the translocation of DNA/RNA strands through transmembrane pores and translate the signals to sequence reads. It features simple and flexible library preparations, long sequencing reads, portable and affordable sequencing devices, and rapid, real-time sequencing. However, the error rate of the sequencing reads is high and remains a hurdle for its broad application. This review article will provide a brief overview of this technology and then focus on the opportunities and challenges of using nanopore sequencing for high-resolution HLA typing and immunogenetics research.

Long-Read Nanopore Sequencing Validated for Human Leukocyte Antigen Class I Typing in Routine Diagnostics

Matching of human leukocyte antigen (HLA) gene polymorphisms by high-resolution DNA sequence analysis is the gold standard for determining compatibility between patient and donor for hematopoietic stem cell transplantation. Single-molecule sequencing (PacBio or MinION) is a newest (third) generation sequencing approach. MinION is a nanopore sequencing platform, which provides long targeted DNA sequences. The long reads provide unambiguous phasing, but the initial high error profile prevented its use in high-impact applications, such as HLA typing for HLA matching of donor and recipient in the transplantation setting. Ongoing developments on instrumentation and basecalling software have improved the per-base accuracy of 1D² nanopore reads tremendously. In the current study, two validation panels of samples covering 70 of the 71 known HLA class I allele groups were used to compare third field sequences obtained by MinION, with Sanger sequence-based typing showing a 100% concordance between both data sets. In addition, the first validation panel was used to set the acceptance criteria for the use of MinION in a routine setting. The acceptance criteria were subsequently confirmed with the second validation panel. In summary, the present study describes validation and implementation of nanopore sequencing HLA class I typing method and illustrates that nanopore sequencing technology has advanced to a point where it can be used in routine diagnostics with high accuracy.

Plasmodium falciparum pre-erythrocytic stage vaccine development

Worldwide strategies between 2010 and 2017 aimed at controlling malarial parasites (mainly Plasmodium falciparum) led to a reduction of just 18% regarding disease incidence rates. Many biologically-derived anti-malarial vaccine candidates have been developed to date; this has involved using many experimental animals, an immense amount of work and the investment of millions of dollars. This review provides an overview of the current state and the main results of clinical trials for sporozoite-targeting vaccines (i.e. the parasite stage infecting the liver) carried out by research groups in areas having variable malaria transmission rates. However, none has led to promising results regarding the effective control of the disease, thereby making it necessary to complement such efforts at finding/introducing new vaccine candidates by adopting a multi-epitope, multi-stage approach, based on minimal subunits of the main sporozoite proteins involved in the invasion of the liver.