Single-cell RNA Sequencing Datasets Research Articles

Transcriptome sequencing reveals inflammation and macrophage heterogeneity in subacromial bursa from degenerative shoulder disorders

ABSTRACT Purpose We aimed to investigate the transcriptomic alterations that occur in the subacromial bursa (SAB) following degenerative or traumatic shoulder diseases. Materials and Methods RNA sequencing was employed to evaluate the transcriptomic alterations of the SAB in individuals afflicted with degenerative rotator cuff tear (RCT), traumatic RCT and proximal humerus fracture (PHF). To gain insights into the biological significance of differentially expressed genes (DEGs), we conducted an enrichment analysis utilizing Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We further utilized single-cell RNA sequencing datasets of SAB from a recently published study to explore the associated cellular dynamics and alterations. Results We detected 1,790 up-regulated and 1,964 down-regulated DEGs between degenerative RCT and PHF, 2,085 up-regulated and 1,919 down-regulated DEGs between degenerative RCT and traumatic RCT, and 20 up-regulated and 12 down-regulated DEGs between traumatic RCT and PHF. Given the similar expression pattern between traumatic RCT and PHF, they were integrated as the traumatic group. In comparison with the traumatic group, 1,983 up-regulated and 2,205 down-regulated DEGs were detected in degenerative SAB. Enrichment analysis of up-regulated DEGs uncovered an elevated inflammatory and immunologic responses in degenerative SAB. Single-cell transcriptomic analysis revealed macrophage represented the immune cell with the most DEGs between the degenerative and traumatic RCT. Conclusion Our results revealed that the SAB in degenerative RCT exhibited a different transcriptional signature compared to that in traumatic RCT, and enrichment analysis showed immunologic and inflammatory activations. Macrophages may play a fundamental role in this process.

Integrative transcriptome analysis reveals the molecular events underlying impaired T-cell responses in EGFR-mutant lung cancer

EGFR mutations are critical oncogenic drivers in lung adenocarcinoma (LUAD). However, the mechanisms by which they impact the tumor microenvironment (TME) and tumor immunity are unclear. Furthermore, the reasons underlying the poor response of EGFR-mutant (EGFR-MU) LUADs to immunotherapy with PD-1/PD-L1 inhibitors are unknown. Utilizing single-cell RNA (sc-RNA) and bulk RNA sequencing datasets, we conducted high-dimensional weighted gene coexpression network analysis to identify key genes and immune-related pathways contributing to the immunosuppressive TME. EGFR-MU cancer cells downregulated MHC class I genes to evade CD8+ cytotoxic T cells, expressed substantial levels of MHC class II molecules, and engaged with CD4+ regulatory T cells (Tregs). EGFR-MU tumors may recruit Tregs primarily through the CCL17/CCL22/CCR4 axis, leading to a Treg-enriched TME. High levels of MHC class II-positive cancer-associated fibroblasts and tumor endothelial cells were found within EGFR-MU tumors. Owing to the absence of costimulatory factors, they may inhibit rather than activate the tumor antigen-specific CD4+ T-cell response, contributing further to immune suppression. Multiplex immunohistochemistry analyses in a LUAD cohort confirmed increased expression of MHC class II molecules in cancer cells and fibroblasts in EGFR-MU tumors. Our research elucidates the highly immunosuppressive TME in EGFR-MU LUAD and suggests potential targets for effective immunotherapy.

Identification and Validation of Prognostic Model for Tumor Microenvironment-Associated Genes in Bladder Cancer Based on Single-Cell RNA Sequencing Data Sets.

The purpose of this study was to elucidate the relationship between the tumor microenvironment (TME) and cellular diversity in bladder cancer (BLCA) progression, leveraging single-cell RNA sequencing (scRNA-seq) data to identify potential prognostic biomarkers and construct a prognostic model for BLCA. We analyzed scRNA-seq data of normal and tumor bladder cells from the Gene Expression Omnibus (GEO) database to uncover crucial markers within the bladder TME. The study compared gene expression in normal versus tumor bladder cells, identifying differentially expressed genes. These genes were subsequently assessed for their prognostic significance using patient follow-up data from The Cancer Genome Atlas. Prognostic models were constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analyses, focusing on eight genes of interest. The predictive performance of the model was also tested against additional GEO data sets (GSE31684, GSE13507, and GSE32894). The prognostic model demonstrated reliable prediction of patient outcomes. Validation through gene set enrichment analysis and immune cell infiltration assessment supported the model's efficacy. The results from both the univariate and multivariate analyses suggest that the risk score is an independent prognostic factor with a hazard ratio of 2.97 (95% CI, 2.28 to 3.9, P < .001). In the validation cohort, the AUC at 1, 2, and 3 years is 0.74, 0.74, and 0.72, respectively. Our findings proposed biomarkers with prognostic potential, laying the groundwork for future in vitro validation and therapeutic exploration. This contributes to a deeper understanding of the genes associated with bladder TME and may improve prognostic precision in BLCA management.

ST6GALNAC1-mediated sialylation in uterine endometrial epithelium facilitates the epithelium-embryo attachment

IntroductionEmbryo implantation requires synergistic interaction between the embryo and the receptive endometrium. Glycoproteins and glycan-binding proteins are involved in endometrium-embryo attachment. Sialyl Tn (sTn), a truncated O-glycan, is catalyzed by ST6 N-Acetylgalactosaminide Alpha-2,6-Sialyltransferase 1 (ST6GALNAC1) and can be detected by specific Sialic-acid-binding immunoglobulin-like lectins (Siglecs). Whether the sTn-Siglecs axis supports embryo implantation remains unknown. ObjectivesThis paper aims to study the role of ST6GALNAC1/sTn-Siglecs axis in embryo implantation. MethodsST6GALNAC1 and sTn in human endometrium were analyzed by immunohistochemistry. An in vitro implantation model was conducted to evaluate the effects of ST6GALNAC1/sTn on the receptivity of human endometrial AN3CA cells to JAR spheroids. Immunoprecipitation combined with mass spectrometry analysis was carried out to identify the key proteins modified by sTn in endometrial cells. Siglec-6 in human embryos was analyzed by published single-cell RNA sequencing (scRNA-seq) datasets. Protein interaction assay was applied to verify the bond between the Siglec-6 with sTn-modified CD44. St6galnac1 siRNAs and anti-sTn antibodies were injected into the uterine horn of the mouse at the pre-implantation stage to evaluate the role of endometrial St6galnac1/sTn in embryo implantation. Siglec-G in murine embryos was analyzed by immunofluorescence staining. The function of Siglec-G is evidenced by uterine horn injection and protein interaction assay. ResultsBoth human and murine endometrium at the receptive stage exhibit higher ST6GALNAC1 and sTn levels compared to the non-receptive stage. Overexpression of ST6GALNAC1 significantly enhanced the receptivity of AN3CA cells to JAR spheroids. Inhibition of endometrial ST6GALNAC1/sTn substantially impaired embryo implantation in vivo. CD44 was identified as a carrier for sTn in the endometrial cells of both species. Siglec-6 and Siglec-G, expressed in the embryonic trophectoderm, were found to promote embryo attachment, which may be achieved through binding with sTn-modified CD44. ConclusionST6GALNAC1-regulated sTn in the endometrium aids in embryo attachment through interaction with trophoblastic Siglecs.

Regulatory B Cells Expressing Granzyme B from Tolerant Renal Transplant Patients: Highly Differentiated B Cells with a Unique Pathway with a Specific Regulatory Profile and Strong Interactions with Immune System Cells.

The aim of our study was to determine whether granzyme B-expressing regulatory B cells (GZMB+ B cells) are enriched in the blood of transplant patients with renal graft tolerance. To achieve this goal, we analysed two single-cell RNA sequencing (scRNAseq) datasets: (1) peripheral blood mononuclear cells (PBMCs), including GZMB+ B cells from renal transplant patients, i.e., patients with stable graft function on conventional immunosuppressive treatment (STA, n = 3), drug-free tolerant patients (TOL, n = 3), and patients with antibody-mediated rejection (ABMR, n = 3), and (2) ex-vivo-induced GZMB+ B cells from these groups. In the patient PBMCs, we first showed that natural GZMB+ B cells were enriched in genes specific to Natural Killer (NK) cells (such as NKG7 and KLRD1) and regulatory B cells (such as GZMB, IL10, and CCL4). We performed a pseudotemporal trajectory analysis of natural GZMB+ B cells and showed that they were highly differentiated B cells with a trajectory that is very different from that of conventional memory B cells and linked to the transcription factor KLF13. By specifically analysing GZMB+ natural B cells in TOLs, we found that these cells had a very specific transcriptomic profile associated with a reduction in the expression of HLA molecules, apoptosis, and the inflammatory response (in general) in the blood and that this signature was conserved after ex vivo induction, with the induction of genes associated with migration processes, such as CCR7, CCL3, or CCL4. An analysis of receptor/ligand interactions between these GZMB+/- natural B cells and all of the immune cells present in PBMCs also demonstrated that GZMB+ B cells were the B cells that carried the most ligands and had the most interactions with other immune cells, particularly in tolerant patients. Finally, we showed that these GZMB+ B cells were able to infiltrate the graft under inflammatory conditions, thus suggesting that they can act in locations where immune events occur.

Analysis of single-cell transcriptome data from a mouse model implicates protein synthesis dysfunction in schizophrenia.

Schizophrenia is a mental disorder that causes considerable morbidity, whose risk largely results from genetic factors. Setd1a is a gene implicated in schizophrenia. To study the gene expression changes found in heterozygous Setd1a± knockout mice in order to gain useful insight into schizophrenia pathogenesis. We mined a single-cell RNA sequencing (scRNAseq) dataset from the prefrontal cortex (PFC) and striatum of Setd1a± mice and identified cell type-specific differentially expressed genes (DEGs) and differential transcript usage (DTU). DEGs and genes containing DTU found in each cell type were used to identify affected biological pathways using Ingenuity Pathway Analysis (IPA). We identified 273 unique DEGs across all cell types in PFC and 675 unique gene peaks containing DTU. In striatum, we identified 327 unique DEGs across all cell types and 8 unique gene peaks containing DTU. Key IPA findings from the analysis of DEGs found in PFC and striatum implicate processes involved in protein synthesis, mitochondrial function, cell metabolism, and inflammation. IPA analysis of genes containing DTU in PFC points to protein synthesis, as well as cellular activities involving intracellular signaling and neurotransmission. One canonical pathway, 'EIF2 Signaling', which is involved in the regulation of protein synthesis, was detected in PFC DEGs, striatum DEGs, and PFC genes containing DTU, drawing attention to its importance in schizophrenia pathophysiology. Processes involving protein synthesis in general and the 'EIF2 Signaling' pathway in particular could be targets for the development of new research strategies and biomarkers in schizophrenia.

A pan-cancer cuproptosis signature predicting immunotherapy response and prognosis

BackgroundCuproptosis may represent a potential biomarker for predicting prognosis and immunotherapy response, but the available evidence is insufficient. MethodsThe multiple single-cell RNA sequencing (scRNA-seq) datasets were analyzed to investigate the specific occurrence of cuproptosis in distinct cell populations. Utilizing 28 scRNA-seq datasets, TCGA pan-cancer cohort, and 10 immunotherapy cohorts, we developed a cuproptosis signature (Cup.Sig). This signature was used to construct prediction models for immunotherapy response and identify potential prognostic biomarkers for pan-cancer using 11 different machine learning algorithms. ResultsMalignant cells demonstrate the higher cuproptosis scores in comparison to other cell types across diverse cancer types. The Cup.Sig exhibits significant associations with cancer hallmarks and immune cell response in multiple cancer types. Leveraging the Cup.Sig, the robust pan-cancer immunotherapy prediction model and prognostic biomarker have been established and validated using diverse datasets from various platforms. ConclusionsWe developed a pan-cancer cuproptosis signature for predicting survival and immunotherapy response.

Metabolic reprogramming and heterogeneity during the decidualization process of endometrial stromal cells

The human endometrial decidualization is a transformative event in the pregnant uterus that involves the differentiation of stromal cells into decidual cells. While crucial to the establishment of a successful pregnancy, the metabolic characteristics of decidual cells in vivo remain largely unexplored. Here, we integrated the single-cell RNA sequencing (scRNA-seq) datasets on the endometrium of the menstrual cycle and the maternal-fetal interface in the first trimester to comprehensively decrypt the metabolic characteristics of stromal fibroblast cells. Our results revealed that the differentiation of stromal cells into decidual cells is accompanied by increased amino acid and sphingolipid metabolism. Furthermore, metabolic heterogeneity exists in decidual cells with differentiation maturity disparities. Decidual cells with high metabolism exhibit higher cellular activity and show a strong propensity for signaling. In addition, significant metabolic reprogramming in amino acids and lipids also occurs during the transition from non-pregnancy to pregnancy in the uteri of pigs, cattle, and mice. Our analysis provides comprehensive insights into the dynamic landscape of stromal fibroblast cell metabolism, contributing to our understanding of the metabolism at the molecular dynamics underlying the decidualization process in the human endometrium.

POSTN+ cancer-associated fibroblasts determine the efficacy of immunotherapy in hepatocellular carcinoma

ObjectiveHepatocellular carcinoma (HCC) poses a significant clinical challenge because the long-term benefits of immune checkpoint blockade therapy are limited. A comprehensive understanding of the mechanisms underlying immunotherapy resistance in HCC...

Tumor necrosis factor receptor 2 promotes endothelial cell-mediated suppression of CD8+ T cells through tuning glycolysis in chemoresistance of breast cancer

BackgroundT cells play a pivotal role in chemotherapy-triggered anti-tumor effects. Emerging evidence underscores the link between impaired anti-tumor immune responses and resistance to paclitaxel therapy in triple-negative breast cancer (TNBC). Tumor-related endothelial cells (ECs) have potential immunoregulatory activity. However, how ECs regulate T cell activity during TNBC chemotherapy remains poorly understood.MethodsSingle-cell analysis of ECs in patients with TNBC receiving paclitaxel therapy was performed using an accessible single-cell RNA sequencing (scRNA-seq) dataset to identify key EC subtypes and their immune characteristics. An integrated analysis of a tumor-bearing mouse model, immunofluorescence, and a spatial transcriptome dataset revealed the spatial relationship between ECs, especially Tumor necrosis factor receptor (TNFR) 2+ ECs, and CD8+ T cells. RNA sequencing, CD8+ T cell proliferation assays, flow cytometry, and bioinformatic analyses were performed to explore the immunosuppressive function of TNFR2 in ECs. The downstream metabolic mechanism of TNFR2 was further investigated using RNA sequencing, cellular glycolysis assays, and western blotting.ResultsIn this study, we identified an immunoregulatory EC subtype, characterized by enhanced TNFR2 expression in non-responders. By a mouse model of TNBC, we revealed a dynamic reduction in the proportion of the CD8+ T cell-contacting tumor vessels that could co-localize spatially with CD8+ T cells during chemotherapy and an increased expression of TNFR2 by ECs. TNFR2 suppresses glycolytic activity in ECs by activating NF-κB signaling in vitro. Tuning endothelial glycolysis enhances programmed death-ligand (PD-L) 1-dependent inhibitory capacity, thereby inducing CD8+ T cell suppression. In addition, TNFR2+ ECs showed a greater spatial affinity for exhausted CD8+ T cells than for non-exhausted CD8+ T cells. TNFR2 blockade restores impaired anti-tumor immunity in vivo, leading to the loss of PD-L1 expression by ECs and enhancement of CD8+ T cell infiltration into the tumors.ConclusionsThese findings reveal the suppression of CD8+ T cells by ECs in chemoresistance and indicate the critical role of TNFR2 in driving the immunosuppressive capacity of ECs via tuning glycolysis. Targeting endothelial TNFR2 may serve as a potent strategy for treating TNBC with paclitaxel.

Systematic Analysis of Human Colorectal Cancer scRNA-seq Revealed Limited Pro-tumoral IL-17 Production Potential in Gamma Delta T Cells.

Gamma delta (γδ) T cells play a crucial role in anti-tumor immunity due to their cytotoxic properties. However, the role and extent of γδ T cells in production of pro-tumorigenic interleukin- 17 (IL-17) within the tumor microenvironment (TME) of colorectal cancer (CRC) remains controversial. In this study, we re-analyzed nine published human CRC whole-tissue single-cell RNA sequencing (scRNA-seq) datasets, identifying 18,483 γδ T cells out of 951,785 total cells, in the neoplastic or adjacent normal tissue of 165 human CRC patients. Our results confirm that tumor-infiltrating γδ T cells exhibit high cytotoxicity-related transcription in both tumor and adjacent normal tissues, but critically, none of the γδ T cell clusters showed IL-17 production potential. We also identified various γδ T cell subsets, including Teff, TRM, Tpex, and Tex, and noted an increased expression of cytotoxic molecules in tumor-infiltrating γδ T cells compared to their normal area counterparts. Our work demonstrates that γδ T cells in CRC primarily function as cytotoxic effector cells rather than IL-17 producers, mitigating the concerns about their potential pro-tumorigenic roles in CRC, highlighting the importance of accurately characterizing these cells for cancer immunotherapy research and the unneglectable cross-species discrepancy between the mouse and human immune system in the study of cancer immunology.

A spatiotemporal molecular atlas of mouse spinal cord injury identifies a distinct astrocyte subpopulation and therapeutic potential of IGFBP2

Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2-expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI invivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential.

Evolutionary origin of the chordate nervous system revealed by amphioxus developmental trajectories.

The common ancestor of all vertebrates had a highly sophisticated nervous system, but questions remain about the evolution of vertebrate neural cell types. The amphioxus, a chordate that diverged before the origin of vertebrates, can inform vertebrate evolution. Here we develop and analyse a single-cell RNA-sequencing dataset from seven amphioxus embryo stages to understand chordate cell type evolution and to study vertebrate neural cell type origins. We identified many new amphioxus cell types, including homologues to the vertebrate hypothalamus and neurohypophysis, rooting the evolutionary origin of these structures. On the basis of ancestor-descendant reconstruction of cell trajectories of the amphioxus and other species, we inferred expression dynamics of transcription factor genes throughout embryogenesis and identified three ancient developmental routes forming chordate neurons. We characterized cell specification at the mechanistic level and generated mutant lines to examine the function of five key transcription factors involved in neural specification. Our results show three developmental origins for the vertebrate nervous system: an anterior FoxQ2-dependent mechanism that is deeply conserved in invertebrates, a less-conserved route leading to more posterior neurons in the vertebrate spinal cord and a mechanism for specifying neuromesoderm progenitors that is restricted to chordates. The evolution of neuromesoderm progenitors may have led to a dramatic shift in posterior neural and mesodermal cell fate decisions and the body elongation process in a stem chordate.

OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing

Single-cell sequencing is frequently affected by “omission” due to limitations in sequencing throughput, yet bulk RNA-seq may contain these ostensibly “omitted” cells. Here, we introduce the single cell trajectory blending from Bulk RNA-seq (BulkTrajBlend) algorithm, a component of the OmicVerse suite that leverages a Beta-Variational AutoEncoder for data deconvolution and graph neural networks for the discovery of overlapping communities. This approach effectively interpolates and restores the continuity of “omitted” cells within single-cell RNA sequencing datasets. Furthermore, OmicVerse provides an extensive toolkit for both bulk and single cell RNA-seq analysis, offering seamless access to diverse methodologies, streamlining computational processes, fostering exquisite data visualization, and facilitating the extraction of significant biological insights to advance scientific research.

Cathepsin D is essential for the degradomic shift of macrophages required to resolve liver fibrosis

Background and objectivesFibrosis contributes to 45% of deaths in industrialized nations and is characterized by an abnormal accumulation of extracellular matrix (ECM). There are no specific anti-fibrotic treatments for liver fibrosis, and previous unsuccessful attempts at drug development have focused on preventing ECM deposition. Because liver fibrosis is largely acknowledged to be reversible, regulating fibrosis resolution could offer novel therapeutical options. However, little is known about the mechanisms controlling ECM remodeling during resolution. Changes in proteolytic activity are essential for ECM homeostasis and macrophages are an important source of proteases. Herein, in this study we evaluate the role of macrophage-derived cathepsin D (CtsD) during liver fibrosis. MethodsCtsD expression and associated pathways were characterized in single-cell RNA sequencing and transcriptomic datasets in human cirrhosis. Liver fibrosis progression, reversion and functional characterization were assessed in novel myeloid-CtsD and hepatocyte-CtsD knock-out mice. ResultsAnalysis of single-cell RNA sequencing datasets demonstrated CtsD was expressed in macrophages and hepatocytes in human cirrhosis. Liver fibrosis progression, reversion and functional characterization were assessed in novel myeloid-CtsD (CtsDΔMyel) and hepatocyte-CtsD knock-out mice. CtsD deletion in macrophages, but not in hepatocytes, resulted in enhanced liver fibrosis. Both inflammatory and matrisome proteomic signatures were enriched in fibrotic CtsDΔMyel livers. Besides, CtsDΔMyel liver macrophages displayed functional, phenotypical and secretomic changes, which resulted in a degradomic phenotypical shift, responsible for the defective proteolytic processing of collagen I in vitro and impaired collagen remodeling during fibrosis resolution in vivo. Finally, CtsD-expressing mononuclear phagocytes of cirrhotic human livers were enriched in lysosomal and ECM degradative signaling pathways. ConclusionsOur work describes for the first-time CtsD-driven lysosomal activity as a central hub for restorative macrophage function during fibrosis resolution and opens new avenues to explore their degradome landscape to inform drug development.

T-distributed Stochastic Neighbor Network for unsupervised representation learning

Unsupervised representation learning (URL) is still lack of a reasonable operator (e.g. convolution kernel) for exploring meaningful structural information from generic data including vector, image and tabular data. In this paper, we propose a simple end-to-end T-distributed Stochastic Neighbor Network (TsNet) for URL with clustering downstream task. Concretely, our TsNet model has three major components: (1) an adaptive connectivity distribution learning module is presented to construct a pairwise graph for preserving the local structure of generic data; (2) a T-distributed stochastic neighbor embedding based loss function is designed to learn a transformation between embeddings and original data, which improves the discrimination of representations; (3) a nonlinear parametric mapping is learned via our TsNet on an unsupervised generalized manner, which can address the “out-of-sample” issue. By combining these components, our method is able to considerably outperform previous related unsupervised learning approaches on visualization and clustering of generic data. A simple deep neural network equipped on our model respectively achieves 74.90%, 76.56% ACC and NMI, which is 8% relative improvement over previous state-of-the-art on real single-cell RNA-sequencing (scRNA-seq) datasets clustering.

Single-Cell Analysis Identifies Distinct Populations of Cytotoxic CD4+ T Cells Linked to the Therapeutic Efficacy of Immune Checkpoint Inhibitors in Metastatic Renal Cell Carcinoma.

The involvement of cytotoxic CD4+ T cells (CD4+ CTLs) and their potential role in dictating the response to immune checkpoint inhibitors (ICIs) in patients with metastatic renal cell carcinoma (mRCC) remains an unexplored area of research. Utilizing single-cell RNA sequencing, we analyzed the immunophenotype and expression patterns of CD4+ T lymphocyte subtypes in mRCC patients, followed by preliminary validation via multi-immunofluorescent staining. In addition, we obtained a comprehensive immunotherapy dataset encompassing single-cell RNA sequencing datasets and bulk RNA-seq cohorts from the European Genome-Phenome Archive and ArrayExpress database. Utilizing the CIBERSORTx deconvolution algorithms, we derived a signature score for CD4+ CTLs from the bulk-RNA-seq datasets of the CheckMate 009/025 clinical trials. Single-cell analysis of CD4+ T lymphocytes in mRCC reveals several cancer-specific states, including diverse phenotypes of regulatory T cells. Remarkably, we observe that CD4+ CTLs cells constitute a substantial proportion of all CD4+ T lymphocyte sub-clusters in mRCC patients, highlighting their potential significance in the disease. Furthermore, within mRCC patients, we identify two distinct cytotoxic states of CD4+ T cells: CD4+GZMK+ T cells, which exhibit a weaker cytotoxic potential, and CD4+GZMB+ T cells, which demonstrate robust cytotoxic activity. Both regulatory T cells and CD4+ CTLs originate from proliferating CD4+ T cells within mRCC tissues. Intriguingly, our trajectory analysis indicates that the weakly cytotoxic CD4+GZMK+ T cells differentiate from their more cytotoxic CD4+GZMB+ counterparts. In comparing patients with lower CD4+ CTLs levels to those with higher CD4+ CTLs abundance in the CheckMate 009 and 25 immunotherapy cohorts, the latter group exhibited significantly improved OS and PFS probability. Our study underscores the pivotal role that intratumoral CD4+ CTLs may play in bolstering anti-tumor immunity, suggesting their potential as a promising biomarker for predicting response to ICIs in patients with mRCC.

Disease-specific transcriptional programs govern airway goblet cell metaplasia

Hypersecretion of airway mucus caused by goblet cell metaplasia is a characteristic of chronic pulmonary inflammatory diseases including asthma, cystic fibrosis (CF), and chronic obstructive pulmonary disease (COPD). Goblet cells originate from airway progenitor club cells. However, the molecular mechanisms and features of goblet cell metaplasia in lung disease are poorly understood. Herein, public single-cell RNA sequencing datasets of human lungs were reanalyzed to explore the transitional phase as club cells differentiate into goblet cells in asthma, CF, and COPD. We found that changes in club and goblet cells during pathogenesis and cellular transition were associated with signalling pathways related to immune response, oxidative stress, and apoptosis. Moreover, other key drivers of goblet cell specification appeared to be pathologically specific, with interleukin (IL)-13 and hypoxia inducible factor 1 (HIF-1)-induced genetic changes in asthma, cystic fibrosis transmembrane conductance regulator (CFTR) mutation being present in CF, and interactions with CD8+ T cells, mitophagy, and mitochondria-induced apoptosis in COPD. In conclusion, this study revealed the similarities and differences in goblet cell metaplasia in asthma, CF, and COPD at the transcriptome level, thereby providing insights into possible novel therapeutic approaches for these diseases.

Integrated Single-Cell Analysis Reveals Spatially and Temporally Dynamic Heterogeneity in Fibroblast States during Wound Healing

Wound healing is a dynamic process over temporal and spatial scales. Key to repair outcomes are fibroblasts, yet how they modulate healing across time and in different wound regions remains incompletely understood. By integrating single-cell RNA-sequencing datasets of mouse skin and wounds, we infer that fibroblasts are the most transcriptionally dynamic skin-resident cells, evolving during postnatal skin maturation, and rapidly after injury towards distinct late scar states. We show that transcriptional dynamics in fibroblasts are largely driven by genes encoding extracellular matrix and signaling factors. Lineage trajectory inference and spatial gene mapping reveal that Prg4-expressing fibroblasts transiently emerge along early wound edges. Within days, they become replaced by long-lasting and likely non-interconverting fibroblast populations, including Col25a1-expressing and Pamr1-expressing fibroblasts that occupy subepidermal and deep scar regions, respectively, where they engage in reciprocal signaling with immune cells. Signaling inference shows that fibroblast-immune crosstalk repeatedly uses some signaling pathways across wound healing time, while use of other signaling pathways is time- and space-limited. Collectively, we uncovered high transcriptional plasticity by wound fibroblasts, with early states transiently forming distinct micro-niches along wound edges and in the fascia, followed by stable states, that stratify scar tissue into molecularly dissimilar upper and lower layers.

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma.

Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response. RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types. Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8. TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.