Identification Of CD4 Research Articles

Comprehensive scRNA-seq Analysis and Identification of CD8_+T Cell Related Gene Markers for Predicting Prognosis and Drug Resistance of Hepatocellular Carcinoma.

Tumor heterogeneity of immune infiltration of cells plays a decisive role in hepatocellular carcinoma (HCC) therapy response and prognosis. This study investigated the effect of different subtypes of CD8+T cells on the HCC tumor microenvironment about its prognosis. Single-cell RNA sequencing, transcriptome, and single-nucleotide variant data from LUAD patients were obtained based on the GEO, TCGA, and HCCD18 databases. CD8+ T cells-associated subtypes were identified by consensus clustering analysis, and genes with the highest correlation with prognostic CD8+ T cell subtypes were identified using WGCNA. The ssGSEA and ESTIMATE algorithms were used to calculate pathway enrichment scores and immune cell infiltration levels between different subtypes. Finally, the TIDE algorithm, CYT score, and tumor responsiveness score were utilized to predict patient response to immunotherapy. We defined 3 CD8+T cell clusters (CD8_0, CD8_1, CD8_2) based on the scRNA- seq dataset (GSE149614). Among, CD8_2 was prognosis-related risk factor with HCC. We screened 30 prognosis genes from CD8_2, and identified 3 molecular subtypes (clust1, clust2, clust3). Clust1 had better survival outcomes, higher gene mutation, and enhanced immune infiltration. Furthermore, we identified a 12 genes signature (including CYP7A1, SPP1, MSC, CXCL8, CXCL1, GCNT3, TMEM45A, SPP2, ME1, TSPAN13, S100A9, and NQO1) with excellent prediction performance for HCC prognosis. In addition, High-score patients with higher immune infiltration benefited less from immunotherapy. The sensitivity of low-score patients to multiple drugs including Parthenolide and Shikonin was significantly higher than that of high-score patients. Moreover, high-score patients had increased oxidative stress pathways scores, and the RiskScore was closely associated with oxidative stress pathways scores. And the nomogram had good clinical utility. To predict the survival outcome and immunotherapy response for HCC, we developed a 12-gene signature based on the heterogeneity of the CD8+ T cells.

Identification of CD8+ T cell-related biomarkers and immune infiltration characteristic of rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune rheumatic disease, which do not respond well to current treatment partially. Therefore, further in-depth elucidation of the molecular mechanism and pathogenesis of RA is urgently needed for the diagnosis, personalized therapy and drug development. Herein, we collected 111 RA samples from Gene Expression Omnibus (GEO) database, and conducted differentially expressed genes and GESA analysis. Abnormal activation and imbalance of immune cells in RA were observed. WGCNA was utilized to explore the gene modules and CD8+ T cell-related genes (CRGs) were chosen for KEGG and GO analysis. Besides, to explore biomarkers of RA in depth, machine learning algorithms and bioinformatics analysis were used, and we identified GDF15, IGLC1, and IGHM as diagnostic markers of RA, which was confirmed by clinical samples. Next, ssGSEA algorithms were adopted to investigate the differences in immune infiltration of 23 immune cell subsets between RA and healthy control group. Finally, optimal classification analysis based on consensus clustering combined with ssGSEA algorithms were conducted. GDF15 was revealed that to be positively correlated with mast cells and type 2 T helper cells, but negatively correlated with most other immune cells. On the other hand, IGHM and IGLC1 were negatively correlated with CD56dim natural killer cells, while positively associated with other immune cells. Finally, RA samples in subtype A exhibited a higher immune infiltration status. This study could provide guidance for individualized treatment of RA patients and provide new targets for drug design.

Identification of CD8+ T-cell exhaustion signatures for prognosis in HBV-related hepatocellular carcinoma patients by integrated analysis of single-cell and bulk RNA-sequencing

BackgroundHBV infection is the leading risk factor for HCC. HBV infection has been confirmed to be associated with the exhaustion status of CD8+ T cells and immunotherapeutic efficacy in HCC. In this study, we aimed to investigate the prognostic value of the CD8+ T-cell exhaustion signature and immunotherapy response in patients with HBV-related HCC.MethodsWe identified different clusters of HBV-related HCC cells by single-cell RNA sequencing (scRNA-seq) and identified CD8+ T-cell exhaustion-related genes (TERGs) by pseudotime analysis. We conducted differential expression analysis and LASSO Cox regression to detect genes and construct a CD8+ T-cell exhaustion index (TEI). We next combined the TEI with other clinicopathological factors to design a prognostic nomogram for HCC patients. We also analysed the difference in the TEI between the non-responder and responder groups during anti-PD-L1 therapy. In addition, we investigated how HBV induces CD8+ T lymphocyte exhaustion through the inhibition of tyrosine metabolism in HCC using gene set enrichment analysis and RT‒qPCR.ResultsA CD8+ T-cell exhaustion index (TEI) was established with 5 TERGs (EEF1E1, GAGE1, CHORDC1, IKBIP and MAGOH). An AFP level > 500 ng, vascular invasion, histologic grade (G3-G4), advanced TNM stage and poor five-year prognosis were related to a higher TEI score, while HBV infection was related to a lower TEI score. Among those receiving anti-PD-L1 therapy, responders had lower TEIs than non-responders did. The TEI also serves as an independent prognostic factor for HCC, and the nomogram incorporating the TEI, TNM stage, and vascular invasion exhibited excellent predictive value for the prognosis in HCC patients. RT‒qPCR revealed that among the tyrosine metabolism-associated genes, TAT (tyrosine aminotransferase) and HGD (homogentisate 1,2 dioxygenase) were expressed at lower levels in HBV-HCC than in non-HBV HCC.ConclusionGenerally, we established a novel TEI model by comprehensively analysing the progression of CD8+ T-cell exhaustion, which shows promise for predicting the clinical prognosis and potential immunotherapeutic efficacy in HBV-related HCC patients.

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes

CD4+ Tcells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4+ Tcell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ Tcell epitopes and enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.

Identification of CD8 + T-Cell-Immune Cell Communications in Ileal Crohn's Disease.

Crohn's disease (CD) is a major subtype of inflammatory bowel disease (IBD), a spectrum of chronic intestinal disorders caused by dysregulated immune responses to gut microbiota. Although transcriptional and functional changes in a number of immune cell types have been implicated in the pathogenesis of IBD, the cellular interactions and signals that drive these changes have been less well-studied. We performed Cellular Indexing of Transcriptomes and Epitopes by sequencing on peripheral blood, colon, and ileal immune cells derived from healthy subjects and patients with CD. We applied a previously published computational approach, NicheNet, to predict immune cell types interacting with CD8 + T-cell subsets, revealing putative ligand-receptor pairs and key transcriptional changes downstream of these cell-cell communications. As a number of recent studies have revealed a potential role for CD8 + T-cell subsets in the pathogenesis of IBD, we focused our analyses on identifying the interactions of CD8 + T-cell subsets with other immune cells in the intestinal tissue microenvironment. We identified ligands and signaling pathways that have implicated in IBD, such as interleukin-1β, supporting the validity of the approach, along with unexpected ligands, such as granzyme B, which may play previously unappreciated roles in IBD. Overall, these findings suggest that future efforts focused on elucidating cell-cell communications among immune and nonimmune cell types may further our understanding of IBD pathogenesis.

High-throughput, targeted MHC class I immunopeptidomics using a functional genetics screening platform.

Identification of CD8+ T cell epitopes is critical for the development of immunotherapeutics. Existing methods for major histocompatibility complex class I (MHC class I) ligand discovery are time intensive, specialized and unable to interrogate specific proteins on a large scale. Here, we present EpiScan, which uses surface MHC class I levels as a readout for whether a genetically encoded peptide is an MHC class I ligand. Predetermined starting pools composed of >100,000 peptides can be designed using oligonucleotide synthesis, permitting large-scale MHC class I screening. We exploit this programmability of EpiScan to uncover an unappreciated role for cysteine that increases the number of predicted ligands by 9-21%, reveal affinity hierarchies by analysis of biased anchor peptide libraries and screen viral proteomes for MHC class I ligands. Using these data, we generate and iteratively refine peptide binding predictions to create EpiScan Predictor. EpiScan Predictor performs comparably to other state-of-the-art MHC class I peptide binding prediction algorithms without suffering from underrepresentation of cysteine-containing peptides. Thus, targeted immunopeptidomics using EpiScan will accelerate CD8+ T cell epitope discovery toward the goal of individual-specific immunotherapeutics.

Identification of CD8+ T cell infiltration-related genes and their prognostic values in cervical cancer

Cervical cancer is a female-specific cancer with relatively high morbidity and mortality. As known to all, immune cell infiltrations in the cancer microenvironment are closely related to the cancer diagnosis and prognosis. Here we revealed that the CD8+ T cell infiltration was significantly upregulated in cervical cancer versus normal cervix uteri samples. Through univariate and multivariate cox analyses, we discovered that the CD8+ T cell infiltration was the only independent beneficial factor for the prognosis of cervical cancer. To explore the genes associated with the CD8+ T cell infiltration in cervical cancer, we performed the WGCNA analysis on the differentially expressed genes (DEGs) of cervical cancer versus normal cervix uteri tissues. As a result, 231 DEGs were found to be associated with CD8+ T cell infiltration in cervical cancer. Subsequently, with the Cytoscape analysis, we identified 105 hub genes out of the 231 DEGs. To further explore the genes that might be responsible for the prognosis of cervical cancer, we performed a univariate cox analysis followed by a LASSO assay on the 105 hub genes and located four genes (IGSF6, TLR10, FCRL3, and IFI30) finally. The four genes could be applied to the prediction of the prognosis of cervical cancer, and relatively higher expression of these four genes predicted a better prognosis. These findings contributed to our understanding of the prognostic values of CD8+ T cell infiltration and its associated genes in cervical cancer and thus might benefit future immune-related therapies.

The CD8+ and CD4+ T Cell Immunogen Atlas of Zika Virus Reveals E, NS1 and NS4 Proteins as the Vaccine Targets.

Zika virus (ZIKV)-specific T cells are activated by different peptides derived from virus structural and nonstructural proteins, and contributed to the viral clearance or protective immunity. Herein, we have depicted the profile of CD8+ and CD4+ T cell immunogenicity of ZIKV proteins in C57BL/6 (H-2b) and BALB/c (H-2d) mice, and found that featured cellular immunity antigens were variant among different murine alleles. In H-2b mice, the proteins E, NS2, NS3 and NS5 are recognized as immunodominant antigens by CD8+ T cells, while NS4 is dominantly recognized by CD4+ T cells. In contrast, in H-2d mice, NS1 and NS4 are the dominant CD8+ T cell antigen and NS4 as the dominant CD4+ T cell antigen, respectively. Among the synthesized 364 overlapping polypeptides spanning the whole proteome of ZIKV, we mapped 91 and 39 polypeptides which can induce ZIKV-specific T cell responses in H-2b and H-2d mice, respectively. Through the identification of CD8+ T cell epitopes, we found that immunodominant regions E294-302 and NS42351-2360 are hotspots epitopes with a distinct immunodominance hierarchy present in H-2b and H-2d mice, respectively. Our data characterized an overall landscape of the immunogenic spectrum of the ZIKV polyprotein, and provide useful insight into the vaccine development.

Identification of CD8+ T cell subsets that normalize in early-treated people living with HIV receiving antiretroviral therapy

BackgroundAlthough combined antiretroviral therapy (cART) has decreased the mortality associated with HIV infection, complete immune reconstitution is not achieved despite viral suppression. Alterations of CD8+ T cells and some of their subpopulations, such as interleukin (IL)-17-producing cells, are evidenced in treated individuals and are associated with systemic inflammation and adverse disease outcomes. We sought to evaluate if different CD8+ T cell subsets are differentially normalized during a clinical follow-up of people living with HIV (PLWH) receiving suppressive cART.MethodsWe explored the changes in the frequencies, activation/exhaustion phenotypes (HLA-DR, CD38, PD-1, and TIM-3), and function (total and HIV-specific cells expressing CD107a, perforin, granzyme B, interferon [IFN]-γ and IL-17) of CD8+ T cells from early-treated PLWH receiving cART in a 1-year follow-up, using a multidimensional flow cytometry approach.ResultsDespite continuous cART-induced viral suppression and recovery of CD4+ T cells, after a 1-year follow-up, the CD8+ T cell counts, CD4:CD8 ratio, PD-1 expression, and IL-17 production by CD8+ T cells exhibited incomplete normalization compared with seronegative controls. However, the proportion of CD8+ T cells with an exhausted phenotype (co-expressing PD-1 andTIM-3), and cells co-expressing cytotoxic molecules (Perforin and Granzyme B), reached normalization.ConclusionsAlthough suppressive cART achieves normalization of CD4+ T cell counts, only particular subsets of CD8+ T cells are more rapidly normalized in PLWH receiving cART, which could be routinely used as biomarkers for therapy efficiency in these patients.

Identification of CD8+ T cell PRDM1 in high-risk human plaques and its regulatory role in murine lesion development

Background and Aims : T cells have a prominent role in the pathogenesis of atherosclerosis, although their function in atherosclerotic plaques is only partly understood. In this study, we utilize the advantages of high-throughput techniques and data analytic strategies to compare the inherent biological changes of T cells during plaque transition from a stable, non-haemorrhaged (low-risk) to a rupture-prone, haemorrhaged (high-risk) phenotype.

Identification of CD8+ T-cell epitope from multiple myeloma-specific antigen AKAP4.

Multiple myeloma (MM) is a malignant plasma cell disorder affecting mainly the elderly population. Revolutionary progress in immunotherapy has been made recently, including monoclonal antibodies and chimeric antigen receptor T cell (CAR-T) therapies; however, the high relapse rate remains problematic. Therefore, combination therapies against different targets would be a reasonable strategy. In this study, we present a new X-chromosome encoded testis-cancer antigen (CTA) AKAP4 as a potential target for MM. AKAP4 is expressed in MM cell lines and MM primary malignant plasma cells. HLA-A*0201-restricted cytotoxic T lymphocytes (CTLs) induced by dendritic cells (DCs) transduced with an adenovirus vector encoding the full-length AKAP4 gene were demonstrated to lyse AKAP4+ myeloma cells. Seven of the 12 candidate epitopes predicated by the BIMAS and SYFPEITH algorithms were able to bind HLA-A*0201 in the T2 binding assay, of which only two peptides were able to induce CTL cytotoxicity in the co-culture of peptide-loaded human mature dendritic cells and the autologous peripheral blood mononuclear cells (PBMCs) from the same HLA-A*0201 donor. The AKAP4 630–638 VLMLIQKLL was identified as the strongest CTL epitope by the human IFN-γ ELISPOT assay. Finally, the VLMLIQKLL-specific CTLs can lyse the HLA-A*0201+AKAP4+ myeloma cell line U266 in vitro, and inhibit tumor growth in the mice bearing U266 tumors in vivo. These results suggest that the VLMLIQKLL epitope could be used to develop cancer vaccine or T-cell receptor transgenic T cells (TCR-T) to kill myeloma cells.

139 Pathogenic CD8+ T cell infiltration and immune synapse formation in alopecia areata hair follicles

Alopecia Areata (AA) involves CD8+ NKG2D+ T cell-mediated hair follicle (HF) damage that causes hair loss. Despite the identification of CD8+ T cells as primary pathogenic cells involved in AA, the molecular mechanisms used by these cells to kill their target cells within HF are not known. CD8+ T cells form immune synapses (IS) to contact, recognize and destroy their target cells, therefore we postulated that CD8+ T cells employ a cytolytic IS for target cell killing in AA. Here, we aimed to directly visualize the interactions of CD8+ T cells with HF target cells in a C3H/HeJ mouse model of AA using high-resolution confocal microscopy.

Targeting TFH cells in human diseases and vaccination: rationale and practice.

The identification of CD4+ T cells localizing to B cell follicles has revolutionized the knowledge of how humoral immunity is generated. Follicular helper T (TFH) cells support germinal center (GC) formation and regulate clonal selection and differentiation of memory and antibody-secreting B cells, thus controlling antibody affinity maturation and memory. TFH cells are essential in sustaining protective antibody responses necessary for pathogen clearance in infection and vaccine-mediated protection. Conversely, aberrant and excessive TFH cell responses mediate and sustain pathogenic antibodies to autoantigens, alloantigens, and allergens, facilitate lymphomagenesis, and even harbor viral reservoirs. TFH cell generation and function are determined by T cell antigen receptor (TCR), costimulation, and cytokine signals, together with specific metabolic and survival mechanisms. Such regulation is crucial to understanding disease pathogenesis and informing the development of emerging therapies for disease or novel approaches to boost vaccine efficacy.

Identification of CD4+ T cells with T follicular helper cell characteristics in the pig

T follicular helper (Tfh) cells provide help to germinal center B cells for affinity maturation, class switch and memory formation. Despite these important functions, this subset has not been studied in detail in pigs due to a lack of species-specific antibodies. We investigated putative Tfh cells from lymphoid tissues and blood of healthy pigs by using cross-reactive antibodies for inducible T-cell costimulator (ICOS) and B-cell lymphoma 6 (Bcl-6). In lymph nodes, we identified a CD4+ T cell population with an ICOS+Bcl-6+CD8α+ phenotype, reminiscent of human and murine germinal center Tfh cells. Within blood-derived CD4+ T cells, sorted ICOShiCD25- and ICOSdimCD25dim cells were able to induce the differentiation of CD21+IgM+ B cells into Ig-secreting plasmablasts. Compared to naïve CD4+ T cells, these two phenotypes were 3- to 7-fold enriched for cells expressing the Tfh-related transcripts CD28, CD40LG, IL6R and MAF, as identified by single-cell RNA sequencing. These results provide a first characterization of Tfh cells in swine and confirm their ability to provide B-cell help.

Identification of CD8+ T Cell Related Biomarkers in Ovarian Cancer.

Background: Immunotherapy is a promising strategy for ovarian cancer (OC), and this study aims to identify biomarkers related to CD8+ T cell infiltration to further discover the potential therapeutic target. Methods: Three datasets with OC transcriptomic data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Two immunotherapy treated cohorts were obtained from the Single Cell Portal and Mariathasan’s study. The infiltration fraction of immune cells was quantified using three different algorithms, Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), and microenvironment cell populations counter (MCPcounter), and single-sample GSEA (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was applied to identify the co-expression modules and related genes. The nonnegative matrix factorization (NMF) method was proposed for sample classification. The mutation analysis was conducted using the “maftools” R package. Key molecular markers with implications for prognosis were screened by univariate COX regression analysis and K-M survival analysis, which were further determined by the receiver operating characteristic (ROC) curve. Results: A total of 313 candidate CD8+ T cell-related genes were identified by taking the intersection from the TCGA-OV and GSE140082 cohorts. The NMF clustering analysis suggested that patients in the TCGA-OV cohort were divided into two clusters and the Cluster 1 group showed a worse prognosis. In contrast, Cluster 2 had higher amounts of immune cell infiltration, elevated ssGSEA scores in immunotherapy, and a higher mutation burden. CSMD3, MACF1, PDE4DIP, and OBSCN were more frequently mutated in Cluster 1, while SYNE2 was more frequently mutated in Cluster 2. CD38 and CXCL13 were identified by univariate COX regression analysis and K-M survival analysis in the TCGA-OV cohort, which were further externally validated in GSE140082 and GSE32062. Of note, patients with lower CXCL13 expression showed a worse prognosis and the CR/PR group had a higher expression of CXCL13 in two immunotherapy treated cohorts. Conclusion: OC patients with different CD8+ T cell infiltration had distinct clinical prognoses. CXCL13 might be a potential therapeutic target for the treatment of OC.

Identification of CD4+ Conventional T Cells-Related lncRNA Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Breast Cancer.

BackgroundBreast cancer (BC) is one of the most common malignancies in women, and long non-coding RNAs (lncRNAs) are key regulators of its development. T cells can recognize and kill cancer cells, and CD4+ T conventional (Tconv) cells are the main orchestrators of cancer immune function. However, research on CD4+ Tconv-related lncRNAs (CD4TLAs) prognostic signature in patients with BC is still lacking.MethodA TCGA database and a GEO database were used to collect the BC patients. Through LASSO Cox regression analysis CD4TLAs-related prognostic models were further constructed, and risk scores (RS) were generated and developed a nomogram based on CD4TLAs. The accuracy of this model was validated in randomized cohorts and different clinical subgroups. Gene set enrichment analysis (GSEA) was used to explore potential signature-based functions. The role of RS has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy.ResultA prognostic model based on 16 CD4TLAs was identified. High-RS was significantly associated with a poorer prognosis. RS was shown to be an independent prognostic indicator in BC patients. The low-RS group had a significant expression of immune infiltrating cells and significantly enriched immune-related functional pathways. In addition, the results of immunotherapy prediction indicated that patients with low-RS were more sensitive to immunotherapy.ConclusionsOur signature has potential predictive value for BC prognosis and immunotherapy response. The findings of this work have greatly increased our understanding of CD4TLA in BC.

Retraction: Identification of CD4+ T-cell-derived CD161+CD39+ and CD39+CD73+ microparticles as new biomarkers for rheumatoid arthritis.

Retraction: Identification of CD4+ T-cell-derived CD161+CD39+ and CD39+CD73+ microparticles as new biomarkers for rheumatoid arthritis.

Neuroblastoma Formation Requires Unconventional CD4 T Cells and Arginase-1-Dependent Myeloid Cells.

Immune cells regulate tumor growth by mirroring their function as tissue repair organizers in normal tissues. To understand the different facets of immune-tumor collaboration through genetics, spatial transcriptomics, and immunologic manipulation with noninvasive, longitudinal imaging, we generated a penetrant double oncogene-driven autochthonous model of neuroblastoma. Spatial transcriptomic analysis showed that CD4+ and myeloid populations colocalized within the tumor parenchyma, while CD8+ T cells and B cells were peripherally dispersed. Depletion of CD4+ T cells or CCR2+ macrophages, but not B cells, CD8+ T cells, or natural killer (NK) cells, prevented tumor formation. Tumor CD4+ T cells displayed unconventional phenotypes and were clonotypically diverse and antigen independent. Within the myeloid fraction, tumor growth required myeloid cells expressing arginase-1. Overall, these results demonstrate how arginine-metabolizing myeloid cells conspire with pathogenic CD4+ T cells to create permissive conditions for tumor formation, suggesting that these protumorigenic pathways could be disabled by targeting myeloid arginine metabolism. SIGNIFICANCE: A new model of human neuroblastoma provides ways to track tumor formation and expansion in living animals, allowing identification of CD4+ T-cell and macrophage functions required for oncogenesis.

Broad and Efficient Activation of Memory CD4+ T Cells by Novel HAdV- and HCMV-Derived Peptide Pools.

Reactivation of Human Cytomegalovirus (HCMV) and Human Adenovirus (HAdV) in immunocompromised patients following stem cell transplantation (SCT) or solid organ transplantation (SOT) is associated with high morbidity and mortality. The adoptive transfer of virus-specific CD8+ and CD4+ T cells has been shown to re-establish the antiviral T-cell response and improve clinical outcome. The viral load in immunocompromised patients can efficiently be reduced solely by the infusion of virus-specific CD4+ T cells. The identification of CD4+ T-cell epitopes has mainly focused on a limited number of viral proteins that were characterized as immunodominant. Here, we used in silico prediction to determine promiscuous CD4+ T-cell epitopes from the entire proteomes of HCMV and HAdV. Immunogenicity testing with enzyme-linked immuno spot (ELISpot) assays and intracellular cytokine staining (ICS) revealed numerous novel CD4+ T-cell epitopes derived from a broad spectrum of viral antigens. We identified 17 novel HCMV-derived and seven novel HAdV-derived CD4+ T-cell epitopes that were recognized by > 50% of the assessed peripheral blood mononuclear cell (PBMC) samples. The newly identified epitopes were pooled with previously published, retested epitopes to stimulate virus-specific memory T cells in PBMCs from numerous randomly selected blood donors. Our peptide pools induced strong IFNγ secretion in 46 out of 48 (HCMV) and 31 out of 31 (HAdV) PBMC cultures. In conclusion, we applied an efficient method to screen large viral proteomes for promiscuous CD4+ T-cell epitopes to improve the detection and isolation of virus-specific T cells in a clinical setting.

Identification of CD8+ T Cell-Related Genes: Correlations with Immune Phenotypes and Outcomes of Liver Cancer.

Purpose Treatment outcomes for advanced liver cancer are poor. Immunotherapy is a treatment strategy that has been widely used to treat other cancers. Studies have shown that CD8+ T lymphocytes are essential factors affecting the efficacy of immunotherapy. We used computational biology methods to determine the coexpressed gene network that promotes CD8+ T lymphocyte infiltration. Method We obtained the liver cancer gene matrix and clinical follow-up information data from TCGA liver hepatocellular carcinoma FPKM. We obtained single nucleotide polymorphism (SNP) data to evaluate the tumor mutation burden. The “estimate” package and the CIBERSORT algorithm were used to evaluate tumor purity and the proportion of CD8+ T lymphocytes in the liver cancer cohort. We used the gene expression matrix of liver cancer and the relative proportion of CD8+ T lymphocytes as input files and performed WGCNA based on this analysis. The weighted coexpression network identified the most CD8+ T lymphocyte-related coexpression modules in liver cancer. Then, we analyzed the biological processes involved in the module. We determined the coexpression module with CD8+ T lymphocyte infiltration in terms of data and function. We then screened the factors in the coexpression module correlated with CD8+ T lymphocyte content greater than 0.4. Finally, the expression levels of these factors were verified at the protein level using immunohistochemistry and single-cell sequencing. Results We determined the CD8+ T lymphocyte proportions that correlated with coexpression networks. Four coexpressed genes (C1QC, CD3D, GZMA, and PSMB9) were identified as CD8+ T cell coexpression genes that promoted infiltration of CD8+ T cells. Because the factors in the coexpression network often participate in similar biological processes, we found that these factors were most related to antigen processing and presentation of peptide antigen through functional enrichment. In the clinical phenotype analysis, we found that 18 factors can be used as independent prognostic protective factors. We found that these factors were significantly negatively correlated with tumor purity and negatively correlated with M2 macrophages in the immunophenotyping analysis. Using immunohistochemistry and single-cell sequencing analysis, we found that CD3D antibody staining was weaker in tumor tissues than normal tissues and was related to CD8+ T cells. Conclusion These coexpressed genes were positively related to the high infiltration proportion of CD8+ T lymphocytes in an antigen presentation process. The biological process might provide new directions for patients who are insensitive to immune therapy.