Immune Cell Profiles Research Articles

Identification of TRAPPC4 as a Key Autoantigen in Immune-Related Pancytopenia: Epitope Characterization and Immune Activation Mechanisms.

Immune-related pancytopenia (IRP) is characterized by autoantibody-mediated destruction or suppression of bone marrow cells, leading to pancytopenia. This study aimed to explore the role of TRAPPC4 (trafficking protein particle complex subunit 4) as a key autoantigen in IRP, including epitope identification and immune activation mechanisms. A total of 90 participants were included in the study, divided into four groups: 30 newly diagnosed IRP patients, 25 IRP remission patients, 20 patients with control hematologic conditions (severe aplastic anemia [SAA] and myelodysplastic syndrome [MDS]), and 15 healthy controls. TRAPPC4 was identified using affinity screening with a phage random peptide library and confirmed with ELISPOT and epitope prediction software. TRAPPC4 expression in bone marrow cells and serum antibody titers was assessed via flow cytometry, ELISA, and real-time PCR. Immune cell profiling of peripheral blood mononuclear cells (PBMNCs) was conducted using flow cytometry. TRAPPC4 was overexpressed on CD34+ bone marrow hematopoietic progenitor cells in newly diagnosed IRP patients compared to remission patients, disease controls (SAA and MDS), and healthy controls, with no significant differences observed in CD15+ granulocytes or CD235a+ nucleated red blood cells. The epitope peptide YTADGKEVLEYLG activated Th2 cells, as confirmed by ELISPOT. Newly diagnosed IRP patients exhibited elevated TRAPPC4 mRNA and protein levels in bone marrow mononuclear cells and higher serum antibody titers compared with controls. Immune profiling revealed increased CD19+ and CD5+CD19+ B lymphocytes in IRP patients. TRAPPC4 was found as a key autoantigen in IRP, along with CD34+ cells as primary targets of autoantibody attacks. The identification of TRAPPC4 and its epitope provided insights into IRP pathogenesis and suggested potential diagnostic and therapeutic strategies.

Identification and validation of mitochondria-related LncRNA signatures as a novel prognostic model for glioma.

A predictive model for long-term survival is needed, and mitochondrial dysfunction is a key feature of cancer metabolism, though its link to glioma is not well understood. The aim of this study was to identify the molecular characteristics associated with glioma prognosis and explore its potential function. We analyzed RNA-seq data from The Cancer Genome Atlas and identified differentially expressed mitochondrial long noncoding RNAs (lncRNAs) using R's 'limma' package. A prognostic model was developed using 10 selected lncRNAs and validated with Cox regression and least absolute shrinkage and selection operator algorithm. The model's efficacy was assessed using Kaplan-Meier and receiver operating characteristic curve analyses, and its correlation with immune cell profiles and drug sensitivity was explored. A 10-mitochondria-related LncRNA signature was generated. The median risk score values are used to classify glioma samples into low-risk and high-risk groups. In breast patients, the signature-based risk score demonstrated a more potent ability to predict survival than conventional clinicopathological features. Furthermore, we noted a substantial disparity in the number of immune cells, including B cells, CD8+T cells, and macrophages, between the two groups. In addition, the high-risk group exhibited lower half-maximal inhibitory concentration values for specific chemotherapy medications, including bortezomib, luminespib, rapamycin, and 5-fluorouracil. Our study elucidates the diagnostic and prognostic value of mitochondria-related-lncRNAs in the promotion, suppression, and treatment of glioma.

Differences in immune cells and gene expression in human milk by parity on integrated scRNA sequencing.

Human breast milk (HBM) is an important source of tolerogenic immune mediators that influence the infant immune system. HBM-derived immune components are affected by various factors; however, few studies have examined the relationship between parity and immune cell profiles of HBM. This study aimed to clarify the effects of parity on HBM immune cell heterogeneity and gene expression by integrating and analyzing publicly available single-cell RNA sequencing datasets. The proportion of innate immune cells was significantly higher in the primiparous versus multiparous group, whereas the proportion of adaptive immune cells was significantly higher in the multiparous group (p = 0.021). The two immune clusters were re-annotated and classified into monocyte, T/B cell, and CD45 groups. The proportions of monocytes and T/B cells were higher in the primiparous and multiparous groups, respectively. In a gene set enrichment analysis of monocytes, genes with a direct role in the infant immune system and immune response-related genes were more highly expressed in the primiparous group. Our results support the parity-dependent differences in gene expression between innate and adaptive immune cells.

Uncovering NK cell sabotage in gut diseases via single cell transcriptomics

The identification of immune environments and cellular interactions in the colon microenvironment is essential for understanding the mechanisms of chronic inflammatory disease. Despite occurring in the same organ, there is a significant gap in understanding the pathophysiology of ulcerative colitis (UC) and colorectal cancer (CRC). Our study aims to address the distinct immunopathological response of UC and CRC. Using single-cell RNA sequencing datasets, we analyzed the profiles of immune cells in colorectal tissues obtained from healthy donors, UC patients, and CRC patients. The colon tissues from patients and healthy participants were visualized by immunostaining followed by laser confocal microscopy for select targets. Natural killer (NK) cells from UC patients on medication showed reduced cytotoxicity compared to those from healthy individuals. Nonetheless, a UC-specific pathway called the BAG6-NCR3 axis led to higher levels of inflammatory cytokines and increased the cytotoxicity of NCR3+ NK cells, thereby contributing to the persistence of colitis. In the context of colorectal cancer (CRC), both NK cells and CD8+ T cells exhibited significant changes in cytotoxicity and exhaustion. The GALECTIN-9 (LGALS9)-HAVCR2 axis was identified as one of the CRC-specific pathways. Within this pathway, NK cells solely communicated with myeloid cells under CRC conditions. HAVCR2+ NK cells from CRC patients suppressed NK cell-mediated cytotoxicity, indicating a reduction in immune surveillance. Overall, we elucidated the comprehensive UC and CRC immune microenvironments and NK cell-mediated immune responses. Our findings can aid in selecting therapeutic targets that increase the efficacy of immunotherapy.

Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning

Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. This study leverages single-cell sequencing and machine learning to unravel the complex cellular and molecular mechanisms underlying pulmonary fibrosis, aiming to improve diagnostic accuracy and uncover potential therapeutic targets. By analyzing lung tissue samples from pulmonary fibrosis patients, we identified distinct cellular phenotypes and gene expression patterns that contribute to the fibrotic process. Notably, our findings revealed a significant enrichment of activated B cells, CD4 T cells, macrophages, and specific fibroblast subpopulations in fibrotic versus normal lung tissue. Machine learning analysis further refined these observations, resulting in the development of a diagnostic model with enhanced precision, based on key gene signatures including TMEM52B, PHACTR1, and BLVRB. Comparative analysis with existing diagnostic models demonstrates the superior accuracy and specificity of our approach. Through In vitro experiments involving the knockdown of PHACTR1, TMEM52B, and BLVRB genes demonstrated that these genes play crucial roles in inhibiting the expression of α-SMA and collagen in lung fibroblasts induced by TGF-β. Additionally, knockout of the PHACTR1 gene reduced inflammation and collagen deposition in a bleomycin-induced mouse model of pulmonary fibrosis in vivo. Additionally, our study highlights novel gene signatures and immune cell profiles associated with pulmonary fibrosis, offering insights into potential therapeutic targets. This research underscores the importance of integrating advanced technologies like single-cell sequencing and machine learning to deepen our understanding of pulmonary fibrosis and pave the way for personalized therapeutic strategies.

Exploring perinatal mesenchymal stromal cells as a potential therapeutic strategy for rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease characterized by inflammation in the synovial tissue, driven by aberrant activation of both the innate and adaptive immune systems, which can lead to irreversible disability. Despite the increasing therapeutic approaches for RA, only a low percentage of patients achieve sustained disease remission, and the persistence of immune dysregulation is likely responsible for disease recurrence once remission is attained. Cell therapy is an attractive, wide-spectrum strategy to modulate inflammation, and mesenchymal stromal cells (MSC) derived from perinatal tissues provide valuable tools for their use in regenerative medicine, mainly due to their immunomodulatory properties. Several in vitro studies have shown that perinatal MSC modulate the proliferation, maturation, and cytokine secretion profile of both innate and adaptive immune cells. Moreover, different beneficial effects have also been described when perinatal MSC were used to treat animal models of diseases associated with inflammatory conditions and degenerative processes. Specifically, in experimental models of RA, treatment with perinatal MSC resulted in a strong reduction of articular damage, which was associated with the modulation of both inflammation and activation of stromal resident cells in the synovial tissue. Here, we present in vitro and in vivo evidence supporting the use of perinatal MSC in RA. We also highlight the promising results from the few published clinical trials, which demonstrate the safety of perinatal MSC.

Integrative Transcriptomic Analysis of Peripheral Blood Monocytes in Systemic Sclerosis and Shared Pathogenic Pathways in Autoimmune Diseases

Systemic sclerosis (SSc) is an autoimmune disease (AD), that receives less attention compared to rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and primary Sjögren's syndrome (pSS). This study aims to analyze transcriptional profiles and immune cell composition in peripheral blood mononuclear cells (PBMC) from SSc patients compared to other ADs. RNA-seq data from 119 untreated patients (eight with SSc, 42 with RA, 41 with pSS, 28 with SLE) and 20 healthy controls were analyzed. Bioinformatics tools were employed to identify differentially expressed genes (DEGs), biological functions and immune cell profiles unique to SSc and shared with other ADs. 1,148 DEGs were found in SSc, with upregulated genes associated with megakaryocyte processes and downregulated genes associated with neutrophil function and immune response. DEGs, including ALDH1A1 and MEGF9, were associated with neutropenia. Upregulated transcription factors (TFs) were linked to embryonic hematopoiesis and downregulated TFs were involved in leukocyte differentiation and immune regulation. Comparative analysis with other ADs revealed common pathogenic pathways, emphasizing megakaryocyte proliferation. Neutrophils count was significantly decreased in ADs (p < 0.001) compared to healthy controls. Comparative analysis highlighted common pathways, particularly in megakaryocyte proliferation, and unique genes (MEGF9, MMP8, and KRT family members) in SSc, suggesting roles in neutrophil function, skin integrity, and fibrosis. This study identifies dysregulated gene expression (KRT and MMP8) associated with neutrophil function and increased megakaryocytes in SSc, highlighting common patterns across autoimmune diseases. These findings offer new insights into the potential pathogenesis of SSc, and help to explore new targets for the treatment.

THE INTERPLAY AMONG IMMUNITY, INFLAMMATION, AND FRIED FRAILTY ON ALZHEIMER’S DISEASE

Abstract Unraveling shared mechanisms for both frailty and Alzheimer’s Disease (AD) including immunity and inflammation is crucial for understanding the link between these two complex multifactorial conditions. This study aimed to characterize the interplay among circulating immune cells, inflammatory biomarkers, and frailty phenotypes on AD onset in the Framingham Heart Study Offspring cohort. A sample of 519 participants (52% female, mean age 66 years), had extensive profiling of immune cells from peripheral blood mononuclear cells and inflammatory protein biomarkers (OLINK Proteomics) at Exam 7 and were dementia-free at the time of Fried frailty measurement (Exam 8). Data from 146 immune cells, 68 proteins, and 5 frailty phenotype components were integrated using sparse multiple Canonical Correlation Analysis (SmCCA) adjusted for relevant covariates. SmCCA seeks linear combinations of variables maximizing inter-correlated canonical scores for all three datasets, yielding signatures of immunity, inflammation, and frailty for each participant that screened variables contributing to the establishment of signatures and inter-datasets pathways. Full follow-up for up to 13.8 years (median 12.1 years) identified 24 incident AD cases. Cox proportional hazard models, accounting for covariates including age, sex, education, and APOE genotype, were employed to assess signatures as risk factors for AD incidence. The inflammation and immunity signatures were correlated (r2=0.32, p-value&amp;lt; 0.001). Both immunity and frailty signatures were significantly associated with AD incidence (immunity: HR=1.1, p-value=0.03; frailty: HR=3.14, p-value=0.02). This study disentangles potential pathways among immune cells and inflammatory biomarkers that contributed to associations with frailty and AD. We will extend to larger studies for replication.

Immune Cell Profiling Reveals a Common Pattern in Premetastatic Niche Formation Across Various Cancer Types

ABSTRACTBackgroundMetastasis is the major cause of cancer‐related mortality. The premetastatic niche is a promising target for its prevention. However, the generality and cellular dynamics in premetastatic niche formation have remained unclear.AimsThis study aimed to elucidate the generality and cellular dynamics in premetastatic niche formation.Materials and MethodsWe performed comprehensive flow cytometric analysis of lung and peripheral immune cells at three time points (early premetastatic, late premetastatic, and micrometastatic phases) for mice with subcutaneous implants of three types of cancer cells (breast cancer, lung cancer, or melanoma cells). The immuno‐cell profiles were then used to predict the metastatic phase by machine learning.ResultsWe found a common pattern of changes in both lung and peripheral immune cell profiles across the three cancer types, including a decrease in the proportion of eosinophils in the early premetastatic phase, an increase in that of regulatory T cells in the late premetastatic phase, and an increase in that of polymorphonuclear myeloid‐derived suppressor cells and a decrease in that of B cells in the micrometastatic phase. Machine learning using immune cell profiles could predict the metastatic phase with approximately 75% accuracy.DiscussionValidation of our findings in humans will require data on the presence or absence of micrometastases in patients and the accumulation of comprehensive and temporal information on immune cells. In addition, blood proteins, extracellular vesicles, DNA, RNA, or metabolites may be useful for more accurate prediction.ConclusionThe discovery of generalities in premetastatic niche formation allow prediction of metastatic phase and provide a basis for the development of methods for early detection and prevention of cancer metastasis in a cancer type‐independent manner.

HFD aggravated the arthritis and atherosclerosis by altering the intestinal status and gut microbiota

AbstractRheumatoid arthritis (RA) and cardiovascular disease (CVD) are both the chronic inflammatory disease. To investigate the influence of secondary atherosclerosis on arthritis mice, we treated the ApoE−/− mice with K/BxN serum and high fat diet (HFD), and subsequently assessed the phenotypes as well as immune profiles of K/BxN serum and HFD induced ApoE−/− mice. We found that HFD treatment aggravated the hyperlipidemia, atherosclerotic lesions, ankle swelling and arthropathy of mice. We further demonstrated that HFD altered the gut microbiota and metabolism, intestinal homeostasis and Th17/Treg cell balance in lamina propria lymphocytes. Moreover, HFD decreased the number of Peyer’ s patches and altered the expression profiling of gut immune cells. In addition, HFD increased the number of aortic leukocytes and macrophages, then aggravated the atherosclerosis in aorta, which led to greater inflammation in mice aorta and aortic root. Collectively, our study indicated that HFD aggravated the arthritis and atherosclerosis, which may be contributed by microbiota dysbiosis, the intestinal permeability and disrupted immunological homeostasis.

Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning

BackgroundSepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their simultaneous occurrence are unclear.MethodsWe acquired sepsis and ARDS datasets from GEO and Arrayexpress databases and screened hub genes by WGCNA and machine learning algorithm. For diagnosis and prognosis, ROC curve and survival analysis were used. We performed GO, KEGG, GSEA, immune cell infiltration, drug prediction, molecular docking, transcription factor prediction, and constructed PPI and ceRNA networks to explore these genes and the common mechanisms of sepsis and ARDS. Single-cell data analysis compared immune cell profiles and hub gene localization. Finally, RT-qPCR and H&amp;amp;E staining confirmed the reliability of hub genes using PBMCs samples and mouse models.ResultsWe identified 242 common differentially expressed genes in sepsis and ARDS. WGCNA analysis showed that the turquoise module in GSE95233 is strongly linked to sepsis occurrence and poor prognosis, while the black module in GSE10474 is associated with ARDS. Using WGCNA and three machine learning methods (LASSO, random forest and Boruta), we identified three key genes CX3CR1, PID1 and PTGDS. Models built with them showed high AUC values in ROC curve evaluations and were validated by external datasets, accurately predicting the occurrence and mortality. We further explored the immunological landscape of these genes using immune infiltration and single-cell analysis. Then, the ceRNA, predicted drugs and molecular docking were analyzed. Ultimately, we demonstrated that these genes are expressed differently in human and mouse samples with sepsis and ARDS.ConclusionThis study identified three molecular signatures (CX3CR1, PID1 and PTGDS) linked to the diagnosis and poor prognosis of sepsis and ARDS, validated by RT-qPCR and H&amp;amp;E staining in both patient and mouse samples. This research may be valuable for identifying shared biological mechanisms and potential treatment targets for both diseases.

Oat Beta-Glucans Modulate the Gut Microbiome, Barrier Function, and Immune Responses in an In Vivo Model of Early-Stage Colorectal Cancer

Oat beta-glucans (OBGs) are known for their beneficial effects on gut health, including anti-inflammatory and prebiotic effects. The aim of this study was to evaluate the impact of two doses (1% or 3% w/w) of dietary low-molar-mass OBG supplementation on colorectal cancer (CRC) development, immune cell profiles, intestinal barrier protein expression, and microbiota composition in a rat model of CRC induced by azoxymethane (AOM). Microbiome analysis revealed significant differences between the control and CRC groups. OBG supplementation influenced microbial diversity and abundance, particularly increasing the population of beneficial bacteria, such as Lachnospiraceae and Ruminococcaceae, associated with butyrate production. However, higher doses of OBG (3%) led to a decrease in butyrate-producing bacteria and a shift toward higher levels of Akkermansia muciniphila and Enterococcus faecalis. Immune cell profiling showed a higher percentage of T lymphocytes (CD3+) in rats fed a diet supplemented with 3% OBG, both in the intraepithelial (IEL) and lamina propria lymphocytes (LPLs). Immunohistochemical analysis of the large intestine revealed a significantly elevated expression of intestinal barrier proteins, i.e., claudin 3 and 4 in rats receiving 1% OBG, while claudin 7 expression was reduced in early-stage CRC. Gene expression analysis also revealed a significant downregulation of Cldn1 in CRC rats. These findings suggest that dietary OBG supplementation modulates the gut microbiota, immune response, and intestinal barrier integrity, with potential implications for nutritional CRC development prevention and treatment strategies.

Interferon-stimulated gene subtypes as key indicators of immune landscape and survival outcomes in ovarian cancer

PurposeOvarian cancer (OV) remains the most lethal gynecological malignancy, underscoring the critical need for robust prognostic biomarkers to enhance patient outcomes. In this study, we classified OV patients by their interferon-stimulated gene (ISG) expression profiles and investigated the associations between these subtypes, the immune microenvironment, and survival outcomes.MethodsWe employed consensus clustering in the TCGA-OV cohort (n = 376) to classify patients into ISG-related subgroups. Survival analysis, differential gene expression (DESeq), KEGG and GSEA pathway enrichment analyses, genomic variation assessments, immune cell profiling using the CIBERSORT algorithm, and TIDE analysis were conducted in the TCGA-OV cohort. In addition, immune checkpoint marker expressions were assessed using data from the TCGA-OV cohort and multiplex immunofluorescence (mIF) staining on an independent cohort (n = 80).ResultsTwo distinct ISG subtypes were identified: ISG Cluster A and ISG Cluster B. Patients in ISG Cluster B exhibited significantly improved overall survival (OS) (p = 0.0442). A total of 328 dysregulated genes were identified, with Cluster B showing overexpression of immune-related genes and enhanced involvement in immune signaling pathways. ISG Cluster B also presented higher tumor mutation burden (TMB) and an enriched immune profile, including M1 macrophages and CD8 + T cells. TIDE analysis indicated a more favorable response to immune checkpoint inhibitors in this cluster, corroborated by high expressions of PD-L1 and ISG15, which were associated with prolonged OS.ConclusionsOur findings demonstrate that ISG-related subtypes are significantly associated with the immune microenvironment and survival outcomes in OV. The biomarkers identified in this study have the potential to inform precision therapy development, thereby enhancing treatment efficacy and personalized care for OV patients.

Innate Immune Cell Profiling in Peripheral Blood Mononuclear Cells of Patientswith Moyamoya Disease.

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by stenosis or occlusion of the internal carotid artery, thus leading to ischaemic and haemorrhagic strokes. Although genetic studies have identified ring finger protein 213 (RNF213) as a susceptibility gene, the low disease penetrance suggests that a secondary trigger, such as infection, may initiate disease onset. This study aimed to characterize the innate immune cell profile of peripheral blood mononuclear cells (PBMCs) of MMD patients via mass cytometry (CyTOF). Blood samples from 10 MMD patients and 10 healthy controls were analysed, with a focus on natural killer (NK) cells, monocytes, and dendritic cells (DCs). The results revealed significant changes in the NK and monocyte subpopulations in MMD patients; specifically, there was a decrease in the CD56dimCD16- NK03 subset and an increase in CD163high classical monocytes, thus indicating compromised microbial defences and heightened inflammation. Additionally, significant changes were observed in DC subpopulations, including an increase in CCR7+ mature DCs and a decrease in CD141+ and CD1c+ DCs. Overactivation of the TLR/MyD88/NF-κB pathway was observed in most innate immune cells, thus indicating its potential role in disease progression. These findings provide novel insights into immune dysfunction in MMD and highlight potential therapeutic targets.

TLS and immune cell profiling: immunomodulatory effects of immunochemotherapy on tumor microenvironment in resectable stage III NSCLC.

The use of programmed death-1 (PD-1) inhibitors in the neoadjuvant setting for patients with resectable stage III NSCLC has revolutionized this field in recent years. However, there is still 40%-60% of patients do not benefit from this approach. The complex interactions between immune cell subtypes and tertiary lymphoid structures (TLSs) within the tumor microenvironment (TME) may influence prognosis and the response to immunochemotherapy. This study aims to assess the relationship between immune cells subtypes and TLSs to better understand their impact on immunotherapy response. This study initially compared the tertiary lymphoid structures (TLSs) density among patients who underwent immunochemotherapy, chemotherapy and upfront surgery using 123 tumor samples from stage-matched patients. Multiplex immunohistochemistry (mIHC) was employed to analyze the spatial distribution of PD-L1+CD11c+ cells and PD1+CD8+ T cells within TLSs. Cytometry by time-of-flight (CyTOF) was used to assess immune cell dynamics in paired biopsy and resection specimens from six patients who underwent immunochemotherapy. Key immune cells were validated in newly collected samples using flow cytometry, mIHC, and in vitro CAR-T cells model. Patients who underwent neoadjuvant chemotherapy or immunochemotherapy exhibited increased TLSs compared to those who opted for upfront surgery. The TLS area-to-tumor area ratio distinguished pCR+MPR and NR patients in the immunochemotherapy group. Spatial analysis revealed variations in the distance between PD-L1+CD11c+ cells and PD1+CD8+ T cells within TLSs in the immunochemotherapy group. CyTOF analysis revealed an increase in the frequency of key immune cells (CCR7+CD127+CD69+CD4+ and CD38+CD8+ cells) following combined therapy. Treatment responders exhibited an increase in CCR7+CD4+ Tcells,whereas CD38+CD8+ T cells were associated with compromised treatment effectiveness. Immunochemotherapy and chemotherapy increase TLSs and granzyme B+ CD8+ T cells in tumors. The TLS area-to-tumor ratio distinguishes responders from non-responders, with PD-L1+ dendritic cells near CD8+PD-1+ T cells linked to efficacy, suggesting that PD-1 inhibitors disrupt harmful interactions. Post-immunochemotherapy, CD8+ T cells increase, but CD38+CD8+ T cells show reduced functionality. These findings highlight the complex immune dynamics and their implications for NSCLC treatment.

Comprehensive analysis of IRF8-related genes and immune characteristics in lupus nephritis

BackgroundThere are currently no reliable diagnostic biomarkers or treatments for lupus nephritis (LN), a complication of systemic lupus erythematosus. Objective: We aimed to explore gene networks and potential biomarkers for LN by analyzing the GSE32591 and GSE113342 datasets from the Gene Expression Omnibus database, focusing on IRF8 and IRF8-related genes.MethodsWe used differential expression analysis, functional enrichment, protein-protein interaction (PPI) network construction, and the CIBERSORT algorithm for immune infiltration assessment. To validate the expression levels of the IRF8 gene in the kidneys of lupus mice models, we used quantitative real-time PCR (qRT-PCR) and Western blotting (WB). A diagnostic classifier was built using the RandomForest method to evaluate the diagnostic potential of selected key genes. To bridge our findings with potential therapeutic implications, we used the drug-gene interaction database to predict drugs targeting the identified genes.ResultsTwenty co-differentially expressed genes (DEGs) were identified, with IRF8 exhibiting significant expression differences and potential as a biomarker. Functional enrichment analysis revealed pathways associated with immune response. Validation through qRT-PCR and WB confirmed that the IRF8 gene and its protein exhibited elevated expression levels in the kidneys of lupus mice compared to control groups. The diagnostic classifier revealed impressive accuracy in differentiating LN from control samples, achieving a notable area under the curve values across various datasets. Additionally, immune infiltration analysis indicated significant differences in the immune cell profiles between the LN and control groups.ConclusionIRF8 and its related genes show promise as biomarkers and therapeutic targets for LN. These findings contribute to a deeper understanding of the molecular mechanisms involved in LN and may support the development of precision medicine strategies for improved patient outcomes.

Diverse immune cell profiles in ASFV-associated lymphopenia

Pathogenic African swine fever virus (ASFV) remains a lethal causative agent in the domestic pig industry, which poses a burden on the swine market and causes substantial socioeconomic losses worldwide. Currently, there are no commercially efficacious vaccines or specific treatments available for ASF prevention and control. Unfortunately, little is known about the swine immune response upon ASFV infection. Here, we investigated the host immune response discrepancy induced by the field moderately virulent strain ASFV HB-2208 among healthy, diseased and asymptomatic pigs. In the peripheral blood of diseased swine, lymphopenia is caused by the massive loss of bystander lymphocytes, such as γδ T cells, B cells and CD4+ T cells. Conversely, ASFV has a strong tropism for the mononuclear phagocyte system (MPS) and partial dendritic cells (DCs), whose antigen-presenting ability is impeded by the downregulation of CD80 and MHC I. However, no significant difference in the number of CD8αhigh T cells was detected, whereas the frequencies of NK cells, NKT cells, and regulatory T cells (Tregs) were significantly increased. Additionally, an in vitro model was established with a coculture of primary pulmonary alveolar macrophages (PAMs) and peripheral blood mononuclear cells (PBMCs), which significantly reduced γδ T cells, B cells and CD4+ T cells and increased Tregs. The differentiated immune response might aid in enhancing the understanding of ASFV pathogenesis in suids and provide insights into the mechanism of ASFV-induced lymphopenia for further studies.

Single-cell immune profiling and validation of PBMCs in the onset of and recovery from herpes zoster

To gain deeper insights into pathogenesis of herpes zoster, the peripheral blood mononuclear cells (PBMCs) from male patients mostly were subjected to single-cell RNA-seq (scRNA-seq) and ATAC-seq analysis. Here we show a detailed immune cell profile in the onset of and recovery from herpes zoster, revealing proportion alterations of the subpopulations, which were validated by flow cytometric analysis and comparison of blood routine data. The integrative analysis of the transcriptomes and epigenomes provided a comprehensive description and validation of the key changes in peripheral blood. This study may provide deep insight into the immune profile during herpes zoster progression and holds potential clinical significance.

The amino acid metabolism pathway of peripheral T lymphocytes and ketamine-induced schizophrenia-like phenotype.

The intricate interplay between peripheral adaptive immune cells and the central nervous system (CNS) has garnered increasing recognition. Given that alterations in cell quantities often translate into modifications in metabolite profiles and that these metabolic changes can potentially traverse the bloodstream and enter the CNS, thereby modulating the progression of mental illnesses, we sought to explore the metabolic profiles of peripheral immune cells in a ketamine-treated mouse model of schizophrenia. We used flow cytometry to scrutinize the alterations in peripheral adaptive immune cells in a ketamine-induced schizophrenia mouse model. Subsequently, we implemented an untargeted metabolomic approach with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to detect the metabolite profiles of peripheral abnormal lymphocytes and identify differential metabolites present in plasma. We then employed targeted metabolomics using UPLC-MS/MS to quantify the common differential metabolites detected in mouse plasma. Flow cytometry analysis detected a notable increase in the count of peripheral CD3+ T cells in a ketamine-induced schizophrenia mouse model. Subsequent untargeted metabolomics analysis revealed that the amino acid metabolism pathway underwent substantial alterations. A detailed quantification of 22 amino acid profiles in the peripheral plasma indicated significant elevation in the levels of glycine, alanine, asparagine, and aspartic acid. Our ongoing research has yet to conclusively identify the precise amino acid metabolism pathway that serves as the pivotal factor in the manifestation of the schizophrenia-like phenotype induced by ketamine. The peripheral amino acid metabolism pathway is involved in the ketamine-induced schizophrenia-like phenotype. The metabolic profile of peripheral immune cells could provide accurate biomarkers for the diagnosis and treatment of psychiatric diseases.

Subtype-specific analysis of gene co-expression networks and immune cell profiling reveals high grade serous ovarian cancer subtype linkage to variable immune microenvironment

High-grade serous ovarian cancer (HGSOC) is marked by significant molecular diversity, presenting a major clinical challenge due to its aggressive nature and poor prognosis. This study aims to deepen the understanding of HGSOC by characterizing mRNA subtypes and examining their immune microenvironment (TIME) and its role in disease progression. Using transcriptomic data and an advanced computational pipeline, we investigated four mRNA subtypes: immunoreactive, differentiated, proliferative, and mesenchymal, each associated with distinct gene expression profiles and clinical behaviors. We performed differential expression analysis among mRNA subtypes using DESeq2 and conducted Weighted Gene Co-Expression Network Analysis (WGCNA) to identify co-expressed gene modules related to clinical traits, e.g., age, survival, and subtype classification. Gene Ontology (GO) analysis highlighted key pathways involved in tumor progression and immune evasion. Additionally, we utilized TIMER 2.0 to assess immune cell infiltration across different HGSOC subtypes, providing insights into the interplay between tumor immune microenvironment (TIME). Our findings show that the immunoreactive subtype, particularly the M3 module-associated network, was marked by high immune cell infiltration, including M1 (p < 0.0001) and M2 macrophages (p < 0.01), and Th1 cells (p < 0.01) along with LAIR-1 expression (p = 1.63e-101). The M18 module exhibited strong B cell signatures (p = 6.24e-28), along with significant FCRL5 (adj. p = 3.09e-30) and IRF4 (adj. p = 3.09e-30) coexpression. In contrast, the M5 module was significantly associated with the mesenchymal subtype, along with fibroblasts (p < 0.0001). The proliferative subtype was characterized by M15 module-driven cellular growth and proliferation gene expression signatures, along with significant ovarian stromal cell involvement (p < 0.0001). Our study reveals the complex interplay between mRNA subtypes and suggests genes contributing to molecular subtypes, underscoring the important clinical implications of mRNA subtyping in HGSOC.