Cell Subtypes Research Articles

Screening of potential regulatory genes in carotid atherosclerosis vascular immune microenvironment.

Immune microenvironment is one of the essential characteristics of carotid atherosclerosis (CAS), which cannot be reversed by drug therapy alone. Thus, there is a pressing need to develop novel immunoregulatory strategies to delay this pathological process that drives cardiovascular-related diseases. This study aimed to detect changes in the immune microenvironment of vascular tissues at various stages of carotid atherosclerosis, as well as cluster and stratify vascular tissue samples based on the infiltration levels of immune cell subtypes to distinguish immune phenotypes and identify potential hub genes regulating the immune microenvironment of carotid atherosclerosis. RNA sequencing datasets for CAS vascular tissue and healthy vascular tissue (GSE43292 and GSE28829) were downloaded from the Gene Expression Omnibus (GEO) database. To begin, the immune cell subtype infiltration level of all samples in both GSE43292 and GSE28829 cohorts was assessed using the ssGSEA algorithm. Following this, consensus clustering was performed to stratify CAS samples into different clusters. Finally, hub genes were identified using the maximum neighborhood component algorithm based on the construction of interaction networks, and their diagnostic efficiency was evaluated. Compared to the controls, a higher number of immune cell subtypes were enriched in CAS samples with higher immune scores in the GSE43292 cohort. Advanced CAS was characterized by high immune cell infiltration, whereas early CAS was characterized by low immune cell infiltration in the GSE28829 cohort. Moreover, CAS progression may be related to the immune response pathway. Biological processes associated with muscle cell development may impede the progression of CAS. Finally, the hub genes PTPRC, ACTN2, ACTC1, LDB3, MYOZ2, and TPM2 had satisfactory efficacy in the diagnosis and prediction of high and low immune cell infiltration in CAS and distinguishing between early and advanced CAS samples. The enrichment of immune cells in vascular tissues is a primary factor driving pathological changes in CAS. Additionally, CAS progression may be related to the immune response pathway. Biological processes linked to muscle cell development may delay the progression of CAS. PTPRC, ACTN2, ACTC1, LDB3, MYOZ2, and TPM2 may regulate the immune microenvironment of CAS and participate in the occurrence and progression of the disease.

Innovative strategies to optimise colorectal cancer immunotherapy through molecular mechanism insights

BackgroundColorectal cancer (CRC) is a leading cause of cancer-related deaths globally. The heterogeneity of the tumor microenvironment significantly influences patient prognosis, while the diversity of tumor cells shapes its unique characteristics. A comprehensive analysis of the molecular profile of tumor cells is crucial for identifying novel molecular targets for drug sensitivity analysis and for uncovering the pathophysiological mechanisms underlying CRC.MethodsWe utilized single-cell RNA sequencing technology to analyze 13 tissue samples from 4 CRC patients, identifying key cell types within the tumor microenvironment. Intercellular communication was assessed using CellChat, and a risk score model was developed based on eight prognostic genes to enhance patient stratification for immunotherapeutic approaches. Additionally, in vitro experiments were performed on DLX2, a gene strongly associated with poor prognosis, to validate its potential role as a therapeutic target in CRC progression.ResultsEight major cell types were identified across the tissue samples. Within the tumor cell population, seven distinct subtypes were recognized, with the C0 FXYD5+ tumor cells subtype being significantly linked to cancer progression and poor prognosis. CellChat analysis indicated extensive communication among tumor cells, fibroblasts, and immune cells, underscoring the complexity of the tumor microenvironment. The risk score model demonstrated high accuracy in predicting 1-, 3-, and 5-year survival rates in CRC patients. Enrichment analysis revealed that the C0 FXYD5+ tumor cell subtype exhibited increased energy metabolism, protein synthesis, and oxidative phosphorylation, contributing to its aggressive behavior. In vitro experiments confirmed DLX2 as a critical gene associated with poor prognosis, suggesting its viability as a target for improving drug sensitivity.ConclusionIn summary, this study advances our understanding of CRC progression by identifying critical tumor subtypes, molecular pathways, and prognostic markers that can inform innovative strategies for predicting and enhancing drug sensitivity. These findings hold promise for optimizing immunotherapeutic approaches and developing new targeted therapies, ultimately aiming to improve patient outcomes in CRC.

The immune mechanism of the mTOR/ACC1/CPT1A fatty acid oxidation signaling pathway in Hashimoto's thyroiditis.

Hashimoto's thyroiditis (HT) is the most common autoimmune thyroid disease (AITD), which is distinguished by high thyroid peroxidase antibody (TPOAb) or thyroglobulin antibody (TgAb). The differentiation of CD4+T cell subsets in patients with HT is imbalanced, with Treg cells decreased and Th17 cells abnormally activated. Fatty acid oxidation supports the differentiation of Th17 cells and induces inflammation, but the specific mechanism is still unknown. This study aimed to explore the role of fatty acid oxidation and its pathway in the pathogenesis of autoimmune thyroiditis and the immune mechanism. In in vitro experiments, a total of 60 HT patients and 20 healthy controls were selected and their CD4+T cells were sorted by magnetic beads. All 80 samples were divided into 4 groups on average: HC group (Healthy control group), HT group (Hashimoto thyroiditis CD4+T cell inactive group), TCC group(Hashimoto thyroiditis CD4+T cell activation), TCC + ETO group(Hashimoto thyroiditis CD4+T cell activation + Etomoxir group). In in vivo experiments, the mice were randomly divided into 3 groups: Con group(Control group), mTg group (CBA/J mice were injected with mTg for modeling, that is EAT mice group), and mTg + ETO group (Etomoxir intervention in EAT mice group). Fatty acid oxidation substrates of CD4+T cells in human peripheral blood were detected by targeted metabolomics. The expressions of key fatty acid oxidation proteins mTOR, ACC1 and CPT1A were detected by Western blotting. The proportion of CD4+T cell subtype differentiation in human and mouse models was detected by flow cytometry. The severity of EAT was detected by HE staining. Compared with healthy controls, the level of CPT1A in CD4+T cells of HT patients was increased, and the intracellular fatty acid content was significantly decreased, indicating that the level of fatty acid oxidation was enhanced in HT patients. After adding Etomoxir, the level of fatty acid oxidation was significantly inhibited, and the imbalance of CD4+T cell subpopulation differentiation in HT patients was reversed. In EAT mice, the mTOR/ACC1/CPT1A pathway was significantly activated, and its expression level was decreased after adding Etomoxir. At the same time, Etomoxir could reverse the reprogramming of abnormal metabolism in EAT mice cells, reduce the spleen index, and improve lymphocyte infiltration in the thyroid. The mTOR/ACC1/CPT1A fatty acid oxidation pathway of CD4+T cells in Hashimoto's thyroiditis was increased, and treatment with Etomoxir could inhibit the activation of this pathway, and reverse the reprogramming of abnormal metabolism in CD4+T cells, thereby reducing Hashimoto's thyroiditis.

Clinical Characteristics, Management and Outcomes of Colitis-associated Colorectal Cancer and the Comparison to Sporadic Colorectal Cancer in Taiwan.

We explored the clinical characteristics, treatment, and outcomes of colitis-associated colorectal cancer and compared with sporadic colorectal cancer in Taiwan. In this retrospective study spanning 1987-2022, colitis-associated colorectal cancers diagnosed according to endoscopic and pathological reports from 14 tertiary centers were reported to our cohort. Clinical demographics, endoscopic findings, histological results, treatment modalities, and outcomes were analyzed. Sporadic colorectal cancer data were retrieved from the Cancer Registry Annual Report, Ministry of Health and Welfare, Taiwan. We enrolled 65 colitis-associated colorectal cancer patients (median age: 56 years; male: 66.2%). Distal colon was the most common tumor location (41.5%). Of ulcerative colitis patients, 77.2% had extensive colitis and 76.5% had Mayo endoscopic subscores of ≥2. Moreover, 50% of lesions were nonpolypoid with indistinct borders in 66.7%. Signet-ring cell subtype consisted 12.3%. Surveillance colonoscopy adherence was 78.4%, yet 51.3% interval cancers occurred. Disease stage 0-4 distribution was 15%, 20%, 13.3%, 20%, and 31.7%, respectively. Endoscopic resection was feasible for 14%, while 67.7% required surgery. During follow-up (median: 21.5 months), we recorded 23.2% recurrence and 34.5% mortality. Lesions with indistinct borders were associated with adverse outcomes (adjusted odds ratio = 11.5 [1.35-98.16]). Colitis-associated rectal cancers, diagnosed later (p < 0.001), had worse outcomes than sporadic rectal cancers. This is the largest Asian colitis-associated colorectal cancer cohort study, emphasizing the need for stringent disease control, improving detection and reducing interval cancers. Signet-ring cell subtype was prevalent. Rectal colitis-associated cancers were diagnosed later with poorer outcomes then sporadic rectal cancers.

Spatial Transcriptome and Single Nucleus Transcriptome Sequencing Reveals Tetrahydroxy Stilbene Glucoside Promotes Ovarian Organoids Development Through the Vegfa-Ephb2 Pair.

Ovarian dysfunction is a major factor leading to female infertility. Understanding how to improve or reshape ovarian function has become an important entry point for preventing and treating female infertility caused by ovarian dysfunction. Here, plant-derived compounds are screened for in vitro activity upon ovarian organoids derived from feeder-free female germline stem cells. Tetrahydroxy stilbene glucoside (TSG) is found to promote the development of ovarian organoids. Single nucleus transcriptome sequencing and spatial transcriptome sequencing are used to establish a comprehensive spatiotemporal map to elucidate the role of TSG in ovarian organoid development, encompassing cell types and subtypes, transcription factors, pseudo-time sequence, and cell communication dynamics. This analysis indicates that TSG promotes ovarian organoid development through the vascular endothelial growth factor A-Eph receptor B2 ligand-receptor pair between granulosa cells and oocytes. This study has enhanced the understanding of the mechanisms of ovarian organoid development, establishes a technical platform for screening compounds for treating infertility and related diseases, and lays a foundation for clinically applying plant-derived compounds.

The impact of gut microbiota in full-term pregnant women on immune regulation during pregnancy: A prospective, exploratory study.

This study aims to investigate the correlation between gut microbiota and both placental local immune function and the maternal systemic immune system in pregnant women. Twenty-six pregnant women were included in this study, utilizing high-throughput sequencing for gut microbiota analysis. Immune cells and cytokine levels were measured in placental tissue and peripheral venous blood. Integration of gut microbiota data with immune parameters was performed using R, and network correlation analysis was conducted with Cytoscape software. In placental tissues, gut microbiota predominantly influences B lymphocytes (CD3-CD19+/CD3-), indicating a potential bidirectional regulatory role. The impact on CD56+CD16+/CD56+CD16- and CD4+/CD8+ ratios appear minor. Notably, a significant positive correlation was observed between gut microbiota and the placental cytokine interleukin (IL)-5. In peripheral blood, gut microbiota was primarily associated with negative regulation of peripheral B lymphocytes and positive regulation of peripheral Treg cells. Minimal effects are observed on peripheral macrophages and NK cell subtypes. The most substantial impact on peripheral immune balance was reflected in the CD4+/CD8+ ratio, showing a predominant negative correlation, while the influence on the CD56+CD16+/CD56+CD16- ratio is minimal. A significant negative correlation was found between gut microbiota and peripheral cytokines IL-1 and IL-18, while the interaction with the peripheral interferon-γ/IL-4 ratio appears relatively less pronounced. The close correlation between gut microbiota and placental local immune function, as well as maternal systemic immune responses, is evident. This study contributes to a preliminary understanding of the immunomodulatory relationship of gut microbiota during pregnancy.

Diverse RNA methylation patterns in neutrophils: key drivers in hepatocellular carcinoma.

Neutrophils, crucial in the immune system, have recently been implicated in promoting malignancy. RNA methylation, an essential epigenetic feature, plays a key role in tumor microenvironment (TME) reprogramming. However, the relationship between neutrophils and RNA methylation in hepatocellular carcinoma (HCC) remains unclear. We analyzed single-cell sequencing data from HCC, focusing on cell subtype and TME construction. RNA methylation "writers" were selected, and their expression in neutrophils was evaluated. Two neutrophil subtypes (high/low RNA methylation) were identified. Differentially expressed genes (DEGs) between these subtypes were confirmed, leading to the identification of 6 molecular subtypes via consensus clustering. A prognostic scoring system was developed using LASSO Cox regression, resulting in a novel neutrophil RNA methylation (NRM) scoring system to assess TME heterogeneity and clinical features. TRPM3, specifically expressed in HCC-infiltrating neutrophils, may regulate RNA modification in tumor pathogenesis. HCC patients were stratified into low/high-NRM score groups, further refined into an advanced NRM (a-NRM) score by incorporating lncRNA data. High a-NRM scores correlated with advanced TNM stage, higher pathological grade, and increased suppressive immune cells. A nomogram incorporating the a-NRM score demonstrated a concordance index indicative of good predictive performance. The a-NRM score is a reliable predictor of prognosis and could guide treatment selection in HCC patients, enhancing clinical response to immunotherapy. TRPM3 also presents as a potential therapeutic target in HCC.

Deciphering the Underlying Mechanisms of Sanleng-Ezhu for the Treatment of Idiopathic Pulmonary Fibrosis Based on Network Pharmacology and Single-cell RNA Sequencing Data.

To decipher the underlying mechanisms of Sanleng-Ezhu for the treatment of idiopathic pulmonary fibrosis based on network pharmacology and single-cell RNA sequencing data. Idiopathic Pulmonary Fibrosis (IPF) is the most common type of interstitial lung disease. Although the combination of herbs Sanleng (SL) and Ezhu (EZ) has shown reliable efficacy in the management of IPF, its underlying mechanisms remain unknown. Based on LC-MS/MS analysis and the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, we identified the bioactive components of SL-EZ. After obtaining the IPF-related dataset GSE53845 from the Gene Expression Omnibus (GEO) database, we performed the differential expression analysis and the weighted gene co-expression network analysis (WGCNA), respectively. We obtained lowly and highly expressed IPF subtype gene sets by comparing Differentially Expressed Genes (DEGs) with the most significantly negatively and positively related IPF modules in WGCNA. Subsequently, we performed Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on IPF subtype gene sets. The low- and highexpression MCODE subgroup feature genes were identified by the MCODE plug-in and were adopted for Disease Ontology (DO), GO, and KEGG enrichment analyses. Next, we performed the immune cell infiltration analysis of the MCODE subgroup feature genes. Single-cell RNA sequencing analysis demonstrated the cell types which expressed different MCODE subgroup feature genes. Molecular docking and animal experiments validated the effectiveness of SL-EZ in delaying the progression of pulmonary fibrosis. We obtained 5 bioactive components of SL-EZ as well as their corresponding 66 candidate targets. After normalizing the samples of the GSE53845 dataset from the GEO database source, we obtained 1907 DEGs of IPF. Next, we performed a WGCNA analysis on the dataset and got 11 modules. Notably, we obtained 2 IPF subgroups by contrasting the most significantly up- and down-regulated modular genes in IPF with DEGs, respectively. The different IPF subgroups were compared with drugcandidate targets to obtain direct targets of action. After constructing the protein interaction networks between IPF subgroup genes and drug candidate targets, we applied the MCODE plug-in to filter the highest-scoring MCODE components. DO, GO, and KEGG enrichment analyses were applied to drug targets, IPF subgroup genes, and MCODE component signature genes. In addition, we downloaded the single-cell dataset GSE157376 from the GEO database. By performing quality control and dimensionality reduction, we clustered the scattered primary sample cells into 11 clusters and annotated them into 2 cell subtypes. Drug sensitivity analysis suggested that SL-EZ acts on different cell subtypes in IPF subgroups. Molecular docking revealed the mode of interaction between targets and their corresponding components. Animal experiments confirmed the efficacy of SL-EZ. We found SL-EZ acted on epithelial cells mainly through the calcium signaling pathway in the lowly-expressed IPF subtype, while in the highly-expressed IPF subtype, SL-EZ acted on smooth muscle cells mainly through the viral infection, apoptosis, and p53 signaling pathway.

Integrating multi-omics data reveals neuroblastoma subtypes in the tumor microenvironment

Neuroblastoma (NB) is a severe pediatric tumor originating from the developing sympathetic nervous system, characterized by diverse clinical outcomes, including spontaneous regression and aggressive metastasis. This variability suggests the existence of different NB subtypes, necessitating accurate classification for effective targeted treatment. In this study, we employed the similarity network fusion (SNF) algorithm and identified three NB subtypes, including mesenchymal-like (MES), MYCN-like (MYCN), and neurogenic-like (Neurogenic). The MES subtype exhibited the highest activation of immune-related pathways. The MYCN subtype demonstrated the worst prognosis, with enrichment in cell growth and proliferation pathways. Conversely, the Neurogenic subtype showed the best prognosis, with enrichment in sympathetic nervous system development processes. Through single-cell RNA sequencing (scRNA-seq) analysis, we examined the tumor microenvironments of these distinct NB subtypes, revealing divergent differentiation trajectories for adrenergic cells within the MYCN and Neurogenic subtypes. We also identified a significant presence of naïve T cells in the MES subtype, as well as mesenchymal cell subtypes associated with the unique plasticity observed in both the MES and MYCN subtypes. Drug sensitivity prediction analysis suggested that the MES subtype may respond favorably to MEK inhibitors, while the MYCN subtype may be susceptible to Bcl-2 inhibitors. Our integrative multi-omics approach enabled precise stratification of NB into biologically distinct subtypes, potentially facilitating the development of subtype-specific therapeutic strategies for improved patient management and survival outcomes.

Integrated Single-Cell and Spatial Transcriptome Reveal Metabolic Gene SLC16A3 as a Key Regulator of Immune Suppression in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most lethal cancers, usually diagnosed at an advanced stage. Metabolic reprogramming plays a significant role in HCC progression, probably related to immune evasion, yet the key gene is unclear. In this study, six metabolism-related genes with prognostic implications were screened. Correlation analysis between the key genes and immune cell subtypes was conducted, and a prominent gene strongly associated with immunosuppression, SLC16A3, was identified. Overexpression of SLC16A3 is associated with the loss of T-cell function and might lead to the upregulation of several immunosuppressive proteins. Gene function enrichment analysis showed genes correlated with SLC16A3 primarily involved in cell adhesion. Single-cell analysis showed that the SLC16A3 gene was mainly expressed in macrophages, especially some tumour-promoting macrophages. Further analysis of spatial transcriptome data indicated that SLC16A3 was enriched at the tumour invasion front. The mIHC revealed that patients with high SLC16A3 expression exhibited significantly reduced infiltration of GZMB+ cells. And SLC16A3 inhibitors significantly suppressed the proliferation of HCC, while simultaneously enhancing T-cell cytotoxicity and reducing exhaustion. These results reveal the phenomenon of immune escape mediated by metabolic reprogramming and suggest that SLC16A3 may serve as a novel target for intervention.

Integrative mapping of human CD8+ T cells in inflammation and cancer.

CD8+ T cells exhibit remarkable phenotypic diversity in inflammation and cancer. However, a comprehensive understanding of their clonal landscape and dynamics remains elusive. Here we introduce scAtlasVAE, a deep-learning-based model for the integration of large-scale single-cell RNA sequencing data and cross-atlas comparisons. scAtlasVAE has enabled us to construct an extensive human CD8+ T cell atlas, comprising 1,151,678 cells from 961 samples across 68 studies and 42 disease conditions, with paired T cell receptor information. Through incorporating information in T cell receptor clonal expansion and sharing, we have successfully established connections between distinct cell subtypes and shed light on their phenotypic and functional transitions. Notably, our approach characterizes three distinct exhausted T cell subtypes and reveals diverse transcriptome and clonal sharing patterns in autoimmune and immune-related adverse event inflammation. Furthermore, scAtlasVAE facilitates the automatic annotation of CD8+ T cell subtypes in query single-cell RNA sequencing datasets, enabling unbiased and scalable analyses. In conclusion, our work presents a comprehensive single-cell reference and computational framework for CD8+ T cell research.

Single-cell transcriptome analysis reveals CD34 as a marker of human sinoatrial node pacemaker cardiomyocytes

The sinoatrial node regulates the heart rate throughout life. Failure of this primary pacemaker results in life-threatening, slow heart rhythm. Despite its critical function, the cellular and molecular composition of the human sinoatrial node is not resolved. Particularly, no cell surface marker to identify and isolate sinoatrial node pacemaker cells has been reported. Here we use single-nuclei/cell RNA sequencing of fetal and human pluripotent stem cell-derived sinoatrial node cells to reveal that they consist of three subtypes of pacemaker cells: Core Pacemaker, Sinus Venosus, and Transitional Cells. Our study identifies a host of sinoatrial node pacemaker markers including MYH11, BMP4, and the cell surface antigen CD34. We demonstrate that sorting for CD34+ cells from stem cell differentiation cultures enriches for sinoatrial node cells exhibiting a functional pacemaker phenotype. This sinoatrial node pacemaker cell surface marker is highly valuable for stem cell-based disease modeling, drug discovery, cell replacement therapies, and the targeted delivery of therapeutics to sinoatrial node cells in vivo using antibody-drug conjugates.

In Silico Integrative scRNA Analysis of Human Colonic Epithelium Indicates Four Tuft Cell Subtypes.

This study integrated and analyzed human single-cell RNA sequencing data from four publicly available datasets to enhance cellular resolution, unveiling a complex landscape of tuft cell heterogeneity within the human colon. Four tuft subtypes (TC1-TC4) emerged as defined by unique gene expression profiles, indicating potentially novel biological function. Tuft cell 1 (TC1) was characterized by an antimicrobial peptide signature; TC2 had an increased transcription machinery gene expression profile consistent with a progenitor-like cell; TC3 expressed genes related to ganglion (neuronal) development; and TC4 expressed genes related to tight junctions. Our analysis of subtype-specific gene expression and pathway enrichment showed variances in tuft cell subtypes between healthy individuals and those with inflammatory bowel disease (IBD). The frequency of TC1 and TC2 differed between healthy controls and IBD. Relative to healthy controls, TC1 and TC2 in IBD-tissue showed an upregulation of gene expression, favouring increased metabolism and immune function. These findings provide foundational knowledge about the complexity of the human colon tuft cell population and hint at their potential contributions to gut health. They provide a basis for future studies to explore the specific roles these cells may play in gut function during homeostasis and disease. We demonstrate the value of in silico approaches for hypothesis generation in relation to the putative functions of low-frequency gut cells for subsequent physiological analyses.

Single-cell transcriptome analysis identifies subclusters and signature with N-glycosylation in endometrial cancer.

Endometrial cancer (EC) is a prevalent gynecologic cancer, with worldwide increasing incidence and disease-associated mortality. N-glycosylation, a critical post-translational modification, has been implicated in cancer progression and immune response modulation. We aimed to elucidate the role of N-glycosylation-related genes on EC cell heterogeneity, prognosis, and immunotherapy response. Data from single-cell RNA sequencing (scRNA) of five patients with EC were acquired from the Gene Expression Omnibus (GEO) database. Nonnegative matrix factorization (NMF) was used to identify cell subtypes related to N-glycosylation from a scRNA matrix. Subsequently, a consensus prognostic signature by integrating 101 combinations of 10 machine learning algorithms. The response to immunotherapy in EC was further examined by multiple algorithms. Our findings identified 11,020 differentially expressed genes (DEGs), of which 34 N-glycosylation-related DEGs were remarkably associated with overall survival (OS) in EC. Single-cell RNA sequencing analysis revealed 30,233 cells divided into eight clusters, with T cells and epithelial cells showing distinct functional characteristics. NMF clustering further classified malignant cells into four subtypes: N-glycosylation-C0, Glycosphingolipid-C1, O-GalNAc-C2, and Elongation-C3. The O-GalNAc-C2 subtype exhibited the highest metabolic pathway activity and activation of transcription factors SOX4, JUND, and FOS. Additionally, cell-cell interaction networks highlighted the MK signaling pathway as a critical mediator of intercellular communication. An integrated machine learning framework generated a prognostic model comprising eight DEGs (LAMC2, KRT7, IL32, KRT18, SERPINA1, PGR, AKAP12, EDN2), achieving an average C-index of 0.712 in training and validation cohorts. A low-risk score implies more significant immune cell infiltration and better response to immunotherapy. Our study underscores the role of N-glycosylation-related genes in EC prognosis and immunotherapy response prediction, and may provide a basis for the development of targeted therapies and personalized treatment strategies.

A comprehensive analysis of gene expression and the immune landscape in gastric cancer through single-cell and multi-omics approaches

Gastric cancer (GC) is a common malignant tumor worldwide, characterized by complex biological processes. The distribution of various cell types and gene expression profiles in the GC microenvironment remains unclear. This study uses single-cell RNA sequencing to explore gene expression patterns and identify differentially expressed genes in GC samples, offering new insights into cellular diversity and potential molecular mechanisms. We conducted temporal and clustering analyses with single-cell sequencing, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to clarify their functions. Using machine learning, we identified relevant genes to create highly accurate prediction models. Additionally, ssGSEA analysis provided detailed insights into the immunosuppressive tumor microenvironment, revealing complex gene expression interactions and diverse immune infiltrates in cancer. Correlation analysis highlighted TIMP1 as having significant prognostic value across different immune cell subtypes. Single-cell RNA sequencing revealed the cellular landscape and gene expression profiles of the GC microenvironment, offering crucial data on how cell heterogeneity is regulated in relation to the tumor microenvironment. Moreover, new insights into the expression levels of AGT, INHBA, and TIMP1 showed distinct sex-biased gene functions within the tumor microenvironment. These findings enhance our understanding of the molecular mechanisms associated with gastric cancer development and may lay the groundwork for identifying novel therapeutic targets and diagnostic strategies.

Immune cells and the trajectories of depression, anxiety, and cognitive function among people with amyotrophic lateral sclerosis

BackgroundAmyotrophic lateral sclerosis (ALS) represents a complex syndrome characterized by motor, psychiatric, and cognitive symptoms, where associations between cellular immune features and non-motor manifestations remain unknown. MethodsIn this cohort study, we enrolled 250 incident people with ALS (pwALS) assessed with the Hospital Anxiety and Depression Scale, and 226 pwALS with the Montreal Cognitive Assessment, including 218 overlapping pwALS. All individuals were diagnosed between January 2015 and January 2023 in Stockholm, Sweden. We applied joint latent class models to delineate distinct trajectories of anxiety, depression, and cognition, incorporating survival outcomes. A majority of the pwALS had data on leukocyte counts and flow cytometric analyses using a comprehensive T cell panel. We then used immune cell subtypes measured at diagnosis to predict trajectories of these outcomes following ALS diagnosis. ResultsWe identified two distinct trajectories for anxiety, depression, and cognitive function following ALS diagnosis. PwALS with longer survival displayed more stable trajectories, while those with shorter survival showed decreasing anxiety symptom, increasing depressive symptom, and declining cognitive function. Higher count of leukocytes at the time of ALS diagnosis tended to associate with anxiety and depression trajectories related to shorter survival. Among T cell subpopulations, several CD8+ T cell subsets were associated with a stable trajectory of depressive symptom, and, in turn, better survival. ConclusionALS-associated psychiatric and cognitive trajectories vary significantly between pwALS with different prognosis. Certain T cell subsets measured at diagnosis might be indicative of depression trajectories post-diagnosis.

Molecular basis for chemokine recognition and activation of XCR1

The X-C motif chemokine receptor XCR1, which selectively binds to the chemokine XCL1, is highly expressed in conventional dendritic cells subtype 1 (cDC1s) and crucial for their activation. Modulating XCR1 signaling in cDC1s could offer novel opportunities in cancer immunotherapy and vaccine development by enhancing the antigen presentation function of cDC1s. To investigate the molecular mechanism of XCL-induced XCR1 signaling, we determined a high-resolution structure of the human XCR1 and Gi complex with an engineered form of XCL1, XCL1 CC3, by cryoelectron microscopy. Through mutagenesis and structural analysis, we elucidated the molecular details for the binding of the N-terminal segment of XCL1 CC3, which is vital for activating XCR1. The unique arrangement within the XCL1 CC3 binding site confers specificity for XCL1 in XCR1. We propose an activation mechanism for XCR1 involving structural alterations of key residues at the bottom of the XCL1 binding pocket. These detailed insights into XCL1 CC3-XCR1 interaction and XCR1 activation pave the way for developing novel XCR1-targeted therapeutics.

Uncovering the dual roles of peripheral immune cells and their connections to brain cells in stroke and post-stroke stages through single-cell sequencing.

Ischemic stroke is a cerebrovascular disease that affects the blood vessels and the blood supply to the brain, making it the second leading cause of death worldwide. Studies suggest that immune cells play a dual role during the inflammatory and recovery phases of stroke. However, in-depth investigations of specific cell subtypes and their differentiation trajectories remain to be elucidated. In this review, we highlight the application of single-cell RNA sequencing (scRNA-seq) for the unbiased identification of cell heterogeneity in brain and peripheral blood mononuclear cells (PBMCs) during and after a stroke. Our goal is to explore the phenotypic landscape of cells with different roles in this context. Specifically, we provide an overview of the roles, cell surface markers, immune cell-released cytokines, and intercellular interactions identified in major immune cells during and after stroke, as identified by different technologies. Additionally, we summarize the connection between immune cells in peripheral blood and the brain via their differentiation trajectories. By synthesizing the application of scRNA-seq in the combined analysis of PBMCs and brain tissue at higher sampling frequencies, we aim to unveil the dual role of peripheral immune cells, which could facilitate the development of new treatment strategies for ischemic stroke.

All the single cells: Single-cell transcriptomics/epigenomics experimental design and analysis considerations for glial biologists.

Single-cell transcriptomics, epigenomics, and other 'omics applied at single-cell resolution can significantly advance hypotheses and understanding of glial biology. Omics technologies are revealing a large and growing number of new glial cell subtypes, defined by their gene expression profile. These subtypes have significant implications for understanding glial cell function, cell-cell communications, and glia-specific changes between homeostasis and conditions such as neurological disease. For many, the training in how to analyze, interpret, and understand these large datasets has been through reading and understanding literature from other fields like biostatistics. Here, we provide a primer for glial biologists on experimental design and analysis of single-cell RNA-seq datasets. Our goal is to further the understanding of why decisions are made about datasets and to enhance biologists' ability to interpret and critique their work and the work of others. We review the steps involved in single-cell analysis with a focus on decision points and particular notes for glia. The goal of this primer is to ensure that single-cell 'omics experiments continue to advance glial biology in a rigorous and replicable way.

CALML6 as a potential diagnostic marker for thyroid cancer promotes thyroid cancer cell proliferation via modulating the immune microenvironment

PurposeCALML6 is an inflammation-related gene, and its expression may be associated with cancer. Here we evaluated the role of CALML6 expression in papillary thyroid carcinoma (PTC). MethodsWe utilized databases such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx) and UALCAN to evaluate the relationship between CALML6 expression and clinicopathological features in thyroid cancer. Immunohistochemical assays were used to observe CALML6 expression in thyroid cancer tissues. The role of CALML6 in PTC cells was investigated using RNA interference. ResultsWe found CALML6 expression was lower than normal and associated with extrathyroidal extension, lymph node metastasis, pathological T stage, tall cell PTC and the expressions of immune checkpoint genes CD274 and PDCD1LG2 in THCA. Additionally, Immunohistochemical staining showed that CALML6 expression was significantly upregulated in thyroid cancer tissues. RNAi analysis showed that CALML6 knockdown significantly reduced cell growth and blocked the cell cycle of PTC cells. Conclusions: Our results suggest that CALML6 may be a novel diagnostic marker for PTC that is closely associated with the invasive and tall cell subtypes, and it may be a potential target for immunotherapy.