Immune Cell Clusters Research Articles

Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenvironment and mechanisms remain elusive. Single-cell sequencing allows for the exploration of immune characteristics within tumor at the cellular level. However, current knowledge regarding the roles of different immune cell populations in liver cancer progression is limited. The main objective of this study is to identify molecular markers with NK cell immune characteristics in hepatocellular carcinoma using various machine learning methods based on Single-Cell Sequencing and Bulk RNA Sequencing. We collected samples from eight normal liver tissues and eight HCC tumor tissues and performed single-cell RNA sequencing for immune cell clustering and expression profile analysis. Using various bioinformatic approaches, we investigated the immune phenotype associated with natural killer (NK) cells expressing high CD7 level. In addition, we verified the role of CD7 in the growth of HCC after NK cell and HCC cells cocultured by RT-qPCR, MTS and Flow cytometer experiments. Finally, we constructed a machine learning model to develop a prognostic prediction system for HCC based on NK cell-related genes. Through single-cell typing, we found that the proportions of hepatocytes and NK cells were significantly elevated in the tumor samples. Moreover, we found that the expression of CD7 was high in HCC and correlated with prognosis. More importantly, Overexpression of CD7 in NK cells significantly inhibited the activity of MHCC97 cells and increased the number of apoptosis of HCC cells (p < 0.05). Furthermore, we observed that NK cells with high CD7 expression were associated with an activated immune phenotype. Our study found that CD7 is an important biomarker for assessing immune status and predicting survival of HCC patients; hence, it is a potential target for immune therapy against HCC.

Mouse Corneal Immune Cell Heterogeneity Revealed by Single-Cell RNA Sequencing.

This study aimed to define the heterogeneity, spatial localization, and functional roles of immune cells in the mouse cornea using single-cell RNA sequencing (scRNA-seq) and immunofluorescent staining. Enriched mouse corneal immune cells (C57BL/6 strain, age 16-20 weeks) underwent single-cell RNA sequencing library preparation, sequencing, and analysis with Seurat, Monocle 3, and CellChat packages in R. Pathway analysis used Qiagen Ingenuity Pathway Analysis software. Immunostaining confirmed cell distribution. We identified 14 distinct immune cell clusters (56% myeloid and 44% lymphoid). Myeloid populations included resident macrophages, conventional dendritic cells (cDC2s), Langerhans cells, neutrophils, monocytes, and mast cells. Additionally, lymphocyte subsets (B, CD8, CD4, γδT, natural killer, natural killer T, and group 2 innate lymphoid cells) were found. We also found three new subtypes of resident macrophages in the cornea. Trajectory analysis suggested a differentiation pathway from monocytes to conventional dendritic cells, resident macrophages, and LCs. Intercellular communication network analysis using cord diagram identified amyloid precursor protein, chemokine (C-C motif) ligands (2, 3, 4, 6, 7, 9, and 12), Cxcl2, Mif, Tnf, Tgfb1, Igf1, and Il10 as prominent ligands involved in these interactions. Sexually dimorphic gene expression patterns were observed, with male myeloid cells expressing genes linked to immune regulation (Egr1, Foxp1, Mrc1, and Il1rn) and females showing higher expression of antigen presentation genes (Clic1, Psmb8, and Psmb9). Finally, immunostaining confirmed the spatial distribution of these cell populations within the cornea. This study unveils a diverse immune landscape in the mouse cornea, with evidence for cell differentiation and sex-based differences. Immunostaining validates the spatial distribution of these populations, furthering our knowledge of corneal immune function.

Maturity and density of tertiary lymphoid structures associate with tumor metastasis and chemotherapy response

BackgroundTertiary Lymphoid Structures (TLSs) are abnormal clusters of immune cells that form in tissues not normally associated with the immune system, usually in cases of long-lasting inflammation, like cancer. TLSs have been suggested as a potential prognostic indicator in various cancer types.MethodsWe retrospectively enrolled 223 gastric cancer (GC) patients who had surgical resections in this study. We utilized hematoxylin and eosin (HE) staining to detect the presence, abundance, and maturity of TLSs. In serial sections, we used immunohistochemistry to examine the cellular composition of TLSs.ResultsThe pathological review identified TLSs in 95.1% of the tumors, lymphoid aggregates in 79.8%, primary follicles in 45.7%, and lymphoid aggregates in 95.1% of the cases. Based on Kaplan-Meier curves, the maturation and abundance of TLSs contributed to longer disease-free survival (DFS) and overall survival (OS). In addition, the density of TLSs was strongly associated with the occurrence of tumor metastases and the response to adjuvant chemotherapy.ConclusionsWe validated the prognostic value of TLSs in GC patients in both independent cohorts, and the maturity and density of TLS correlated with tumor metastasis. In addition, TLS may reflect sustained antitumor potency, which has important implications for adjuvant chemotherapy.

Deep learning pipeline for automated cell profiling from cyclic imaging

Cyclic fluorescence microscopy enables multiple targets to be detected simultaneously. This, in turn, has deepened our understanding of tissue composition, cell-to-cell interactions, and cell signaling. Unfortunately, analysis of these datasets can be time-prohibitive due to the sheer volume of data. In this paper, we present CycloNET, a computational pipeline tailored for analyzing raw fluorescent images obtained through cyclic immunofluorescence. The automated pipeline pre-processes raw image files, quickly corrects for translation errors between imaging cycles, and leverages a pre-trained neural network to segment individual cells and generate single-cell molecular profiles. We applied CycloNET to a dataset of 22 human samples from head and neck squamous cell carcinoma patients and trained a neural network to segment immune cells. CycloNET efficiently processed a large-scale dataset (17 fields of view per cycle and 13 staining cycles per specimen) in 10 min, delivering insights at the single-cell resolution and facilitating the identification of rare immune cell clusters. We expect that this rapid pipeline will serve as a powerful tool to understand complex biological systems at the cellular level, with the potential to facilitate breakthroughs in areas such as developmental biology, disease pathology, and personalized medicine.

Detailed cellular and spatial characterization of chronic lung allograft dysfunction using imaging mass cytometry

Long-term survival after lung transplantation remains limited by chronic lung allograft dysfunction (CLAD), with two main phenotypes: bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS). We aimed to assess CLAD lung allografts using imaging mass cytometry (IMC), a high dimensional tissue imaging system allowing a multiparametric in situ exploration at a single cell level. 4 BOS, 4 RAS, and 4 control lung samples were stained with 35 heavy metal-tagged antibodies selected to assess structural and immune proteins of interest. We identified 50 immune and non-immune cell clusters. CLAD lungs had significantly reduced club cells. A Ki67-high basal cell population was mostly present in RAS and in proximity to memory T cells. Memory CD8+ T cells were more frequent in CLAD lungs, regulatory T cells more prominent in RAS. IMC is a powerful technology for detailed cellular analysis within intact organ structures that may shed further light on CLAD mechanisms.

Clinical prognosticators and targets in the immune microenvironment of intrahepatic cholangiocarcinoma

ABSTRACT Background Intrahepatic cholangiocarcinoma (ICC) is a disease with poor prognosis and limited therapeutic options. We investigated the tumor immune microenvironment (TIME) to identify predictors of disease outcome and to explore targets for therapeutic modulation. Methods Liver tissue samples were collected during 2008–2019 from patients (n = 139) diagnosed with ICC who underwent curative intent surgery without neoadjuvant chemotherapy. Samples from the discovery cohort (n = 86) were immunohistochemically analyzed on tissue microarrays (TMAs) for the expression of CD68, CD3, CD4, CD8, Foxp3, PD-L1, STAT1, and p-STAT1 in tumor core and stroma areas. Results were digitally analyzed using QuPath software and correlated with clinicopathological characteristics. For validation of TIME-related biomarkers, we performed multiplex imaging mass cytometry (IMC) in a validation cohort (n = 53). Results CD68+ cells were the predominant immune cell type in the TIME of ICC. CD4+high T cell density correlated with better overall survival (OS). Prediction modeling together with validation cohort confirmed relevance of CD4+ cells, PD-L1 expression by immune cells in the stroma and N-stage on overall disease outcome. In turn, IMC analyses revealed that silent CD3+CD4+ clusters inversely impacted survival. Among annotated immune cell clusters, PD-L1 was most relevantly expressed by CD4+FoxP3+ cells. A subset of tumors with high density of immune cells (“hot” cluster) correlated with PD-L1 expression and could identify a group of candidates for immune checkpoint inhibition (ICI). Ultimately, higher levels of STAT1 expression were associated with higher lymphocyte infiltration and PD-L1 expression. Conclusions These results highlight the importance of CD4+ T cells in immune response against ICC. Secondly, a subset of tumors with “hot” TIME represents potential candidates for ICI, while stimulation of STAT1 pathway could be a potential target to turn “cold” into “hot” TIME in ICC.

Sublingual immune cell clusters and dendritic cell distribution in the oral cavity.

The oral mucosa is the first line of defense against pathogenic bacteria and plays a vital role in maintaining tolerance to food antigens and commensal bacteria. We used CD11c reporter mice to visualize dendritic cells (DCs), a key immune cell population, in the oral cavity. We identified differences in DC density in each oral tissue region. Sublingual immune cell clusters (SLICs) extended from the lamina propria to the epithelium, where DCs and T cells resided in close contact with each other and innate lymphoid cells (ILCs). Targeted in situ photolabeling revealed that the SLICs comprised mostly of CD11c+CD11b+ DCs and were enriched for cDC1s and Langerhans cells. Although the frequency of T cell subsets was similar within and outside the SLICs, tissue resident memory T cells were significantly enriched within the clusters and cluster size increased in response to inflammation. Collectively, we found that SLICs form a unique microenvironment that facilitates T cell-DC interactions in the steady state and during inflammation. Since the oral mucosa is an important target for needle-free vaccination and sublingual immunotherapy to induce tolerogenic responses, the novel insight into the localized immunoregulation provided in this study may accelerate the development of these approaches.

Lifestyle score is associated with cellular immune profiles in healthy Tanzanian adults

Immune system and vaccine responses vary across geographical locations worldwide, not only between high and low-middle income countries (LMICs), but also between rural and urban populations within the same country. Lifestyle factors such as housing conditions, exposure to microorganisms and parasites and diet are associated with rural-and urban-living. However, the relationships between these lifestyle factors and immune profiles have not been mapped in detail. Here, we profiled the immune system of 100 healthy Tanzanians living across four rural/urban areas using mass cytometry. We developed a lifestyle score based on an individual's household assets, housing condition and recent dietary history and studied the association with cellular immune profiles. Seventeen out of 80 immune cell clusters were associated with living location or lifestyle score, with eight identifiable only using lifestyle score. Individuals with low lifestyle score, most of whom live in rural settings, showed higher frequencies of NK cells, plasmablasts, atypical memory B cells, T helper 2 cells, regulatory T cells and activated CD4+ T effector memory cells expressing CD38, HLA-DR and CTLA-4. In contrast, those with high lifestyle score, most of whom live in urban areas, showed a less activated state of the immune system illustrated by higher frequencies of naïve CD8+ T cells. Using an elastic net machine learning model, we identified cellular immune signatures most associated with lifestyle score. Assuming a link between these immune profiles and vaccine responses, these signatures may inform us on the cellular mechanisms underlying poor responses to vaccines, but also reduced autoimmunity and allergies in low- and middle-income countries.

A spatiotemporal comparative analysis on tumor immune microenvironment characteristics between neoadjuvant chemotherapy and preoperative immunotherapy for ESCC

The average five-year survival rate for esophageal cancer, a common malignant tumor of the digestive system, is barely 20%. The majority of esophageal squamous cell carcinoma (ESCC) patients had already progressed to a locally advanced or even advanced stage at initial diagnosis, making routine surgery ineffective. Chemotherapy and immunotherapy are important neoadjuvant treatments for ESCC, however, it remains unknown how treatment will affect the immunological microenvironment, especially at the spatial level. Here, we presented the TME characters of ESCC from the temporal and spatial dimensions using scRNA-seq and ST, investigated the changes of immune cell clusters in the TME under neoadjuvant chemotherapy and preoperative immunotherapy, and explored the potential mechanisms. It was found that compared with chemotherapy, immunotherapy combined with chemotherapy increased the level of T cell proliferation, partially restored the function of exhausted T cells, induced the expansion of specific exhausted CD8 T cells, increased the production of dendritic cells (DCs), and supported the immune hot microenvironment of the tumor. We also found that CD52 and ID3 have potential as biomarkers of ESCC. Particularly, CD52 may be served as a predictor of the efficacy to screen the advantaged population of different regimens. Through multiple pathways, CAF2 and CAF5’s antigen-presenting role affected the other fibroblast clusters, resulting in malignant transformation. We analyzed the immune microenvironment differences between the two regimens to provide a more thorough description of the ESCC microenvironment profile and serve as a foundation for customized neoadjuvant treatment of ESCC.

A novel prognostic model based on telomere-related lncRNAs in gastric cancer.

Telomeres are specialized structures at the ends of chromosomes that are important for their protection. Over time, long non-coding RNAs (lncRNAs) have gradually come into the spotlight as essential biomarkers of proliferation, migration, and invasion of human malignant tumors. Nevertheless, the impact of telomere-related lncRNAs (TRLs) in gastric cancer is currently unknown. In the present study, we screen the TRLs and identify a prognostic TRLs signature in gastric cancer. First, telomere-related genes (TRGs) were retrieved from the website, and RNA sequencing (RNA-seq) data and clinical data of stomach adenocarcinoma (STAD) patients were gathered from The Cancer Genome Atlas (TCGA) database. Gastric cancer patients' lncRNAs and overall survival (OS) were found to be related using univariate Cox regression analysis. Next, least absolute shrinkage and selection operator (LASSO) regression analysis and multifactorial Cox regression analysis were used to further screen telomere-related differentially expressed lncRNAs (TRDELs), and finally six lncRNAs were obtained, including LINC01537, CFAP61-AS1, DIRC1, RABGAP1L-IT1, DBH-AS1, and REPIN1-AS1. According to these six TRDELs, a prognostic model for gastric cancer was constructed. The samples were divided into the training group and the testing group at random, and the reliability of prognostic model was validated in both groups and overall samples. In addition, we performed Kaplan-Meier (K-M) survival curve analysis, independent prognostic analysis, and functional enrichment analysis to validate the predictive value and independence of the model, as well as immune cell correlation analysis, clustering analysis, and principal component analysis (PCA) to further explore the relationship between this model and the tumor cells. Finally, we performed the drug sensitivity analysis to identify a few small molecules that may have a therapeutic effect on gastric cancer. Finally, we constructed a prognostic model for gastric cancer consisting of six TRDELs. According to the K-M curve, the prognosis of the low-risk group was noticeably superior than that of the high-risk group. Multivariate Cox regression analysis suggested that risk score was an independent prognostic element. Receiver operating characteristic (ROC) curves, nomogram, and calibration curve indicated that the prognostic model had good predictive ability. Functional enrichment analysis demonstrated major pathways with high- and low-risk groups. Next, both tumor microenvironment (TME) and immune correlation analysis showed discrepancy in the high- and low-risk groups. Through drug sensitivity analysis, we screened four small molecules that might be beneficial for gastric cancer treatment. A prognostic model consisting of these six TRDELs was capable to predict the prognosis of gastric cancer patients.

Disturbance of Immune Microenvironment in Androgenetic Alopecia through Spatial Transcriptomics.

Androgenetic alopecia (AGA) is characterized by microinflammation and abnormal immune responses, particularly in the upper segment of hair follicles (HFs). However, the precise patterns of immune dysregulation remain unclear, partly due to limitations in current analysis techniques to preserve tissue architecture. The infundibulum, a major part of the upper segment of HFs, is associated with significant clusters of immune cells. In this study, we investigated immune cells around the infundibulum, referred to as peri-infundibular immune infiltration (PII). We employed spatial transcriptome profiling, a high-throughput analysis technology, to investigate the immunological disruptions within the PII region. Our comprehensive analysis included an evaluation of overall immune infiltrates, gene set enrichment analysis (GSEA), cellular deconvolution, differential expression analysis, over-representation analysis, protein-protein interaction (PPI) networks, and upstream regulator analysis to identify cell types and molecular dysregulation in immune cells. Our results demonstrated significant differences in immune signatures between the PII of AGA patients (PII-A) and the PII of control donors (PII-C). Specifically, PII-A exhibited an enrichment of CD4+ helper T cells, distinct immune response patterns, and a bias toward a T helper (Th) 2 response. Immunohistochemistry revealed disruptions in T cell subpopulations, with more CD4+ T cells displaying an elevated Th2 response and a reduced Th1-cytotoxic response compared to PII-C. These findings reveal the unique immune landscapes of PII-A and PII-C, suggesting potential for the development of innovative treatment approaches.

Identification of steroid-induced osteonecrosis of the femoral head biomarkers based on immunization and animal experiments

BackgroundSteroid-induced osteonecrosis of femoral head (SONFH) is a severe health risk, and this study aims to identify immune-related biomarkers and pathways associated with the disease through bioinformatics analysis and animal experiments.MethodUsing SONFH-related datasets obtained from the GEO database, we performed differential expression analysis and weighted gene co-expression network analysis (WGCNA) to extract SONFH-related genes. A protein-protein interaction (PPI) network was then constructed, and core sub-network genes were identified. Immune cell infiltration and clustering analysis of SONFH samples were performed to assess differences in immune cell populations. WGCNA analysis was used to identify module genes associated with immune cells, and hub genes were identified using machine learning. Internal and external validation along with animal experiments were conducted to confirm the differential expression of hub genes and infiltration of immune cells in SONFH.ResultsDifferential expression analysis revealed 502 DEGs. WGCNA analysis identified a blue module closely related to SONFH, containing 1928 module genes. Intersection analysis between DEGs and blue module genes resulted in 453 intersecting genes. The PPI network and MCODE module identified 15 key targets enriched in various signaling pathways. Analysis of immune cell infiltration showed statistically significant differences in CD8 + t cells, monocytes, macrophages M2 and neutrophils between SONFH and control samples. Unsupervised clustering classified SONFH samples into two clusters (C1 and C2), which also exhibited significant differences in immune cell infiltration. The hub genes (ICAM1, NR3C1, and IKBKB) were further identified using WGCNA and machine learning analysis. Based on these hub genes, a clinical prediction model was constructed and validated internally and externally. Animal experiments confirmed the upregulation of hub genes in SONFH, with an associated increase in immune cell infiltration.ConclusionThis study identified ICAM1, NR3C1, and IKBKB as potential immune-related biomarkers involved in immune cell infiltration of CD8 + t cells, monocytes, macrophages M2, neutrophils and other immune cells in the pathogenesis of SONFH. These biomarkers act through modulation of the chemokine signaling pathway, Toll-like receptor signaling pathway, and other pathways. These findings provide valuable insights into the disease mechanism of SONFH and may aid in future drug development efforts.

Tumor-associated characteristics and immune dysregulation in nasopharyngeal carcinoma under the regulation of m7G-related tumor microenvironment cells

BackgroundNasopharyngeal carcinoma (NPC) is a type of malignant tumor with high morbidity. Aberrant levels of N7-methylguanosine (m7G) are closely associated with tumor progression. However, the characteristics of the tumor microenvironment (TME) in NPC associated with m7G modification remain unclear.MethodsA total of 68,795 single cells from single-cell RNA sequencing data derived from 11 NPC tumor samples and 3 nasopharyngeal lymphatic hyperplasia (NLH) samples were clustered using a nonnegative matrix factorization algorithm according to 61 m7G RNA modification regulators.ResultsThe m7G regulators were found differential expression in the TME cells of NPC, and most m7G-related immune cell clusters in NPC tissues had a higher abundance compared to non-NPC tissues. Specifically, m7G scores in the CD4+ and CD8+ T cell clusters were significantly lower in NPC than in NLH. T cell clusters differentially expressed immune co-stimulators and co-inhibitors. Macrophage clusters differentially expressed EIF4A1, and high EIF4A1 expression was associated with poor survival in patients with head and neck squamous carcinoma. EIF4A1 was upregulated in NPC tissues compared to the non-NPC tissues and mainly expressed in CD86+ macrophages. Moreover, B cell clusters exhibited tumor biological characteristics under the regulation of m7G-related genes in NPC. The fibroblast clusters interacted with the above immune cell clusters and enriched tumor biological pathways, such as FGER2 signaling pathway. Importantly, there were correlations and interactions through various ligand-receptor links among epithelial cells and m7G-related TME cell clusters.ConclusionOur study revealed tumor-associated characteristics and immune dysregulation in the NPC microenvironment under the regulation of m7G-related TME cells. These results demonstrated the underlying regulatory roles of m7G in NPC.

DIPG-49. SPATIAL TRANSCRIPTOMIC SEQUENCING OF A DIPG PATIENT TUMOUR RESOURCE

Abstract BACKGROUND Diffuse Intrinsic Pontine Glioma (DIPG), the most common subtype of Diffuse Midline Glioma (DMG), is a brainstem high-grade glioma arising in young children and always proves fatal. Major challenges include the disease’s intratumoural genetic and cellular heterogeneity as well as its diffusely invasive phenotype. Research of the last few years has highlighted that interactions between cancer cells, the nervous system and immune cells crucially contribute to tumour cell invasion and disease malignancy. Hence, a better understanding of cancer-promoting interactions is a key requirement to elucidate novel strategies for the treatment of this devastating disease. METHOD We performed spatial transcriptomic sequencing on 10 sequential tumour-infiltrated DIPG patient brainstem regions, using the 10x Genomics Visium platform. RESULTS Spatially-informed analysis and cell type clustering overall highlighted the molecular intratumoural heterogeneity present in the disease. We assessed cell cluster interactions as well as receptor-ligand (RL) pairing, illustrating communication between neuronal, immune cell and tumour clusters. We further determined respective RL pairs involved in such. To address the question whether invasive edges genetically differ from the tumour core, we evaluated genes that are significantly correlated with distal brainstem regions compared to tumour proximal sites. Results revealed gene signatures that are highly associated with neuronal signalling and communication, validating previous findings emphasising the importance of neuron-to-glioma interactions driving DIPG disease progression. CONCLUSION DIPG is a lethal paediatric brainstem glioma for which more durable therapeutic modalities remain to be found. In-depth analysis of this disease is often hampered due to the lack of patient tissue suitable for laboratory studies. Our patient autopsy specimen, spanning the entire tumour-infiltrated brainstem provided a platform to study this aggressive disease in a spatio-temporal manner. This analysis elucidates how DIPG is driven by the tumour microenvironment, including associated receptor-ligand interactions. This has the potential to ultimately discover new treatment targets.

Single-cell transcriptomics reveal the microenvironment landscape of perfluorooctane sulfonate-induced liver injury in female mice

Epidemic and animal studies have reported that perfluoroalkyl and polyfluoroalkyl substances (PFASs) are strongly associated with liver injury; however, to date, the effects of PFASs on the hepatic microenvironment remain largely unknown. In this study, we established perfluorooctane sulfonic acid (PFOS)–induced liver injury models by providing male and female C57BL/6 mice with water containing PFOS at varying doses for 4 weeks. Hematoxylin and eosin staining revealed that PFOS induced liver injury in both sexes. Elevated levels of serum aminotransferases including those of alanine aminotransferase and aspartate transaminase were detected in the serum of mice treated with PFOS. Female mice exhibited more severe liver injury than male mice. We collected the livers from female mice and performed single-cell RNA sequencing. In total, 36,529 cells were included and grouped into 10 major cell types: B cells, granulocytes, T cells, NK cells, monocytes, dendritic cells, macrophages, endothelial cells, fibroblasts, and hepatocytes. Osteoclast differentiation was upregulated and the T cell receptor signaling pathway was significantly downregulated in PFOS-treated livers. Further analyses revealed that among immune cell clusters in PFOS-treated livers, Tcf7+CD4+T cells were predominantly downregulated, whereas conventional dendritic cells and macrophages were upregulated. Among the fibroblast subpopulations, hepatic stellate cells were significantly enriched in PFOS-treated female mice. CellphoneDB analysis suggested that fibroblasts interact closely with endothelial cells. The major ligand–receptor pairs between fibroblasts and endothelial cells in PFOS-treated livers were Dpp4_Cxcl12, Ackr3_Cxcl12, and Flt1_complex_Vegfa. These genes are associated with directing cell migration and angiogenesis. Our study provides a general framework for understanding the microenvironment in the livers of female mice exposed to PFOS at the single-cell level.

#1449 Maturation of tertiary lymphoid structures in progressive kidney damage due to chronic phosphate load

Abstract Background and Aims We have recently shown that a high phosphate diet (HPD) in mice leads to an increase in FGF23 levels and causes progressive tubular damage and interstitial fibrosis with increased accumulation of macrophages and concomitant perivascular immune cell aggregates in the corticomedullary zone. Such tertiary lymphoid structures (TLS) can develop as a result of chronic inflammation and have already been described in lupus nephritis and IgA nephropathy, among others. In our model, the question arose to what extent damage to the proximal tubule is temporally associated with the development and maturation of TLS and which factors favor TLS development. Method Wild-type mice were fed HPD for 1, 2, 3, 4 and 6 months and the kidneys of each were compared with those of mice on a normal phosphate diet (NPD). To evaluate the effect of high FGF23 ± phosphate, Fgf23 was overexpressed in mice on NPD and HPD using an adeno-associated virus (AAV-Fgf23), and hypophosphatemic Hyp mice were used. Results An increased tubular damage score was seen after only two months of HPD. In parallel, perivascular immune cell clusters developed in the corticomedullary zone and in the renal cortex, which were characterized by aggregates of CD45R+ B cells and CD3+ T cells, as well as LYVE1+ lymphatic vessels after three months of HPD and were accompanied by increased expression of venous markers (Plvap, Aplnr, EphB4) and cell adhesion molecules (Sell, Vcam1, Madcam1). Further analyses showed a time-dependent induction of the immunofibroblast-derived chemokines Cxcl13 and Ccl19, as well as the lymphotoxins Lta and Ltb, which are important for the differentiation of immunofibroblasts into follicular dendritic cells (FDC) and follicular reticular cells (FRC). Already after four months of HPD, proliferating B-cell clusters with FDCs, FRCs located in T-cell clusters, podoplanin+ networks, high endothelial venules, plasma cells and increased IgD synthesis indicated fully mature TLS, while tubular damage and fibrosis continued to increase until six months of HPD. Compared to AAV-Fgf23 mice on NPD, only AAV-Fgf23 animals on HPD developed tubular damage with fibrosis and fully mature TLS. Hypophosphatemic Hyp mice with high FGF23 showed neither signs of tubular damage nor the development of TLS. Conclusion The development of renal TLS due to chronic high phosphate load coincides with the development of tubular damage, with earlier maturation of TLS and progression of tubular damage.

Single cells and TRUST4 reveal immunological features of the HFRS transcriptome.

The etiology of hemorrhagic fever with renal syndrome (HFRS) is significantly impacted by a variety of immune cells. Nevertheless, the existing techniques for sequencing peripheral blood T cell receptor (TCR) or B cell receptor (BCR) libraries in HFRS are constrained by both limitations and high costs. In this investigation, we utilized the computational tool TRUST4 to generate TCR and BCR libraries utilizing comprehensive RNA-seq data from peripheral blood specimens of HFRS patients. This facilitated the examination of clonality and diversity within immune libraries linked to the condition. Despite previous research on immune cell function, the underlying mechanisms remain intricate, and differential gene expression across immune cell types and cell-to-cell interactions within immune cell clusters have not been thoroughly explored. To address this gap, we performed clustering analysis on 11 cell subsets derived from raw single-cell RNA-seq data, elucidating characteristic changes in cell subset proportions under disease conditions. Additionally, we utilized CellChat, a tool for cell-cell communication analysis, to investigate the impact of MIF family, CD70 family, and GALECTIN family cytokines-known to be involved in cell communication-on immune cell subsets. Furthermore, hdWGCNA analysis identified core genes implicated in HFRS pathogenesis within T cells and B cells. Trajectory analysis revealed that most cell subsets were in a developmental stage, with high expression of transcription factors such as NFKB and JUN in Effector CD8+ T cells, as well as in Naive CD4+ T cells and Naive B cells. Our findings provide a comprehensive understanding of the dynamic changes in immune cells during HFRS pathogenesis, identifying specific V genes and J genes in TCR and BCR that contribute to advancing our knowledge of HFRS. These insights offer potential implications for the diagnosis and treatment of this autoimmune disease.

Single-cell transcriptomic analysis of decidual immune cell landscape in the occurrence of adverse pregnancy outcomes induced by Toxoplasma gondii infection

BackgroundToxoplasma gondii is an obligate intracellular parasite that can lead to adverse pregnancy outcomes, particularly in early pregnancy. Previous studies have illustrated the landscape of decidual immune cells. However, the landscape of decidual immune cells in the maternal–fetal microenvironment during T. gondii infection remains unknown.MethodsIn this study, we employed single-cell RNA sequencing to analyze the changes in human decidual immune cells following T. gondii infection. The results of scRNA-seq were further validated with flow cytometry, reverse transcription-polymerase chain reaction, western blot, and immunofluorescence staining.ResultsOur results showed that the proportion of 17 decidual immune cell clusters and the expression levels of 21 genes were changed after T. gondii infection. Differential gene analysis demonstrated that T. gondii infection induced the differential expression of 279, 312, and 380 genes in decidual NK cells (dNK), decidual macrophages (dMφ), and decidual T cells (dT), respectively. Our results revealed for the first time that several previously unknown molecules in decidual immune cells changed following infection. This result revealed that the function of maternal–fetal immune tolerance declined, whereas the killing ability of decidual immune cells enhanced, eventually contributing to the occurrence of adverse pregnancy outcomes.ConclusionsThis study provides valuable resource for uncovering several novel molecules that play an important role in the occurrence of abnormal pregnancy outcomes induced by T. gondii infection.Graphical

Spatial Profiling of Ovarian Carcinoma and Tumor Microenvironment Evolution under Neoadjuvant Chemotherapy.

This study investigates changes in CD8+ cells, CD8+/Foxp3 ratio, HLA I expression, and immune coregulator density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes. Multiplexed immune profiling and cell clustering analysis were performed on paired matched ovarian cancer samples to characterize the immune tumor microenvironment (iTME) at diagnosis and under NACT in patients enrolled in the CHIVA trial (NCT01583322). Several immune cell (IC) subsets and immune coregulators were quantified pre/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA I+-enriched tumors were associated with a better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance, and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into four subsets: high Binf, enriched in B clusters; high Tinf and low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors were segregated into three clusters: high BinfTinf, low Tinf, and desert. The high BinfTinf, more diverse in IC composition encompassing T, B, and NK cells, correlated with improved survival. PDL1 was rarely expressed, whereas TIM3, LAG3, and IDO1 were more prevalent. Several iTMEs exist during tumor evolution, and the NACT impact on iTME is heterogeneous. Clustering analysis of patients unravels several IC subsets within ovarian cancer and can guide future personalized approaches. Targeting different checkpoints such as TIM3, LAG3, and IDO1, more prevalent than PDL1, could more effectively harness antitumor immunity in this anti-PDL1-resistant malignancy.

The causal relationship between thoracic aortic aneurysm and immune cells: a mendelian randomization study

One of the pathogenic causes of thoracic aortic aneurysm (TAA), a dangerous vascular condition that can cause aortic rupture, is autoimmune disorders. Currently, immune cell clustering is becoming more and more refined, and the specific immune cell phenotypes involved are yet unknown. Here, we want to clarify the causal link between TAA risk and 731 immune cell traits. There was a Mendelian randomization analysis (MR). We discovered that the presence of TAA led to an increase in CD45 on CD33− HLA-DR− myeloid cells, an increase in CD45 on natural killer cells, and a decrease in FSC-A on granulocytes after applying FDR correction. Our research also revealed a strong correlation between the incidence of TAA and an increase in immune cells with CD3 on CD39+ CD4+, and CD25 on IgD− CD27− phenotypes. Through genetic techniques, our research has shown the intimate relationship between immune cells and TAA, offering direction for future clinical investigations.