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Integrated single-cell transcriptomics and epigenomics reveals strong germinal center-associated etiology of autoimmune risk loci.
The germinal center (GC) response is critical for both effective adaptive immunity and establishing peripheral tolerance by limiting autoreactive B cells. Dysfunction in these processes can lead to defective immune responses to infection or contribute to autoimmune disease. To understand the gene regulatory principles underlying the GC response, we generated a single-cell transcriptomic and epigenomic atlas of the human tonsil, a widely studied and representative lymphoid tissue. We characterize diverse immune cell subsets and build a trajectory of dynamic gene expression and transcription factor activity during B cell activation, GC formation, and plasma cell differentiation. We subsequently leverage cell type–specific transcriptomic and epigenomic maps to interpret potential regulatory impact of genetic variants implicated in autoimmunity, revealing that many exhibit their greatest regulatory potential in GC-associated cellular populations. These included gene loci linked with known roles in GC biology (IL21, IL21R, IL4R, and BCL6) and transcription factors regulating B cell differentiation (POU2AF1 and HHEX). Together, these analyses provide a powerful new cell type–resolved resource for the interpretation of cellular and genetic causes underpinning autoimmune disease.
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Single-Cell RNA-Seq Reveals Lineage and X Chromosome Dynamics in Human Preimplantation Embryos.
Mouse studies have been instrumental in forming our current understanding of early cell-lineage decisions; however, similar insights into the early human development are severely limited. Here, we present a comprehensive transcriptional map of human embryo development, including the sequenced transcriptomes of 1,529 individual cells from 88 human preimplantation embryos. These data show that cells undergo an intermediate state of co-expression of lineage-specific genes, followed by a concurrent establishment of the trophectoderm, epiblast, and primitive endoderm lineages, which coincide with blastocyst formation. Female cells of all three lineages achieve dosage compensation of X chromosome RNA levels prior to implantation. However, in contrast to the mouse, XIST is transcribed from both alleles throughout the progression of this expression dampening, and X chromosome genes maintain biallelic expression while dosage compensation proceeds. We envision broad utility of this transcriptional atlas in future studies on human development as well as in stem cell research.
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Identification of fatty acids synthesis and metabolism-related gene signature and prediction of prognostic model in hepatocellular carcinoma.
BACKGROUND: Fatty acids synthesis and metabolism (FASM)-driven lipid mobilization is essential for energy production during nutrient shortages. However, the molecular characteristics, physiological function and clinical prognosis value of FASM-associated gene signatures in hepatocellular carcinoma (HCC) remain elusive. METHODS: The Gene Expression Omnibus database (GEO), the Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) database were utilized to acquire transcriptome data and clinical information of HCC patients. The ConsensusClusterPlus was employed for unsupervised clustering. Subsequently, immune cell infiltration, stemness index and therapeutic response among distinct clusters were decoded. The tumor immune dysfunction and exclusion (TIDE) algorithm was utilized to anticipate the response of patients towards immunotherapy, and the genomics of drug sensitivity in cancer (GDSC) tool was employed to predict their response to antineoplastic medications. Least absolute shrinkage and selection operator (LASSO) regression analysis and protein-protein interaction (PPI) network were employed to construct prognostic model and identity hub gene. Single cell RNA sequencing (scRNA-seq) and CellChat were used to analyze cellular interactions. The hub gene of FASM effect on promoting tumor progression was confirmed through a series of functional experiments. RESULTS: Twenty-six FASM-related genes showed differential expression in HCC. Based on these FASM-related differential genes, two molecular subtypes were established, including Cluster1 and Cluster2 subtype. Compared with cluster2, Cluster1 subtype exhibited a worse prognosis, higher risk, higher immunosuppressive cells infiltrations, higher immune escape, higher cancer stemness and enhanced treatment-resistant. PPI network identified Acetyl-CoA carboxylase1 (ACACA) as central gene of FASM and predicted a poor prognosis. A strong interaction between cancer stem cells (CSCs) with high expression of ACACA and macrophages through CD74 molecule (CD74) and integrin subunit beta 1 (ITGB1) signaling was identified. Finally, increased ACACA expression was observed in HCC cells and patients, whereas depleted ACACA inhibited the stemness straits and drug resistance of HCC cells. CONCLUSIONS: This study provides a resource for understanding FASM heterogeneity in HCC. Evaluating the FASM patterns can help predict the prognosis and provide new insights into treatment response in HCC patients.
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A Novel 14-Gene Panel Associated With Efferocytosis for Predicting Pancreatic Cancer Prognosis Through Bulk and Single-Cell Databases.
BACKGROUND: Efferocytosis (ER) plays a crucial role in the programmed clearance of dead cells, a process that is mediated by phagocytic immune cells. However, further exploration is needed to determine the full extent of its impact on the progression of pancreatic ductal adenocarcinoma (PDAC), particularly through interactions among tumor cells, stromal cells, and immune cells within the tumor microenvironment (TME). METHODOLOGY AND RESULTS: In this study, we comprehensively analyzed the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as additional databases from multiple bioinformatics websites, utilizing 167 ER features derived from the integration of single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data. A set of 14 ER-associated prognostic signatures, referred to as the "14-gene panel" genes, was identified based on overall survival (OS)/disease-free survival (DFS) data, Pearson correlation coefficients, and multivariate Cox regression analyses. The model pathways enriched by the four-gene combination represented by "LEAF" and the 14-gene combination represented by the "14-gene panel" presented a high degree of similarity, including among the adhesion, mitotic, G2/M checkpoint, and epithelial‒mesenchymal transition (EMT) signaling pathways. Least absolute shrinkage and selection operator (LASSO) regression was subsequently employed to construct an ER risk scoring system using deep learning, based on the following formula: LGALS3, EMP1, ASPH, and FNDC3B, collectively termed the "LEAF" panel. Additionally, random survival forest (RSF) algorithms facilitated the identification of a key panel of genes, designated "LEAP" genes, including LGALS3, EREG, ASPH, and PLS3; three of which genes (ASPH, LGALS3, and EREG) were identified as key factors influencing the behaviors of PDAC tumors, tumor-associated stroma, and macrophages. Finally, we utilized experimental methods, including Boyden chamber analyses, immunohistochemical staining, and cell cycle analyses, to demonstrate that interference with ASPH suppresses the malignant properties of tumors, including proliferation and migration. Multiplex immunofluorescence staining was employed to identify EREG as highly relevant to the M2 macrophage subpopulation. CONCLUSION: Our findings underscore the importance of considering a novel prognostic signature comprising 14 ER genes in the context of the TME when investigating the biology of PDAC. Future studies may explore how modulating these interactions could lead to novel therapeutic opportunities.
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SEC61G promotes colorectal cancer progression by regulating cytosolic Ca2+ concentration.
BACKGROUND: Intracellular calcium (Ca2+) signaling regulates key cancer processes. Research findings suggest that the SEC61 complex, involved in protein translocation, contributes to calcium leakage from the endoplasmic reticulum. However, the mechanism by which SEC61 Translocon Subunit Gamma (SEC61G), a component of this complex, influences colorectal cancer (CRC) progression remains unclear. METHODS: Bioinformatics analysis was performed using The Cancer Genome Atlas data sets to identify candidate genes on chromosome 7p, examine their association with DNA copy number amplification. In addition, SEC61G expression in CRC cells and tissues was validated using reverse-transcription quantitative polymerase chain reaction and immunohistochemistry. Moreover, in vitro and in vivo experiments were performed to investigate the effects of SEC61G overexpression and knockdown on CRC cell proliferation. Furthermore, publicly available single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (ST-seq) data were used to validate the role of SEC61G in CRC. RESULTS: SEC61G was significantly upregulated in CRC tissues and was correlated with poor prognosis in patients with CRC. SEC61G overexpression enhanced cell proliferation and activated the EGFR pathway, promoting cell cycle progression from the G1 to S phase. In addition, SEC61G overexpression increased cytosolic Ca2+ levels, which activated EGFR signaling via calmodulin. Moreover, analyses of scRNA-seq and ST-seq data confirmed that SEC61G expression was higher in tumor epithelial cells and that it was co-expressed with EGFR pathway-related genes. CONCLUSIONS: SEC61G promotes CRC progression by regulating cytosolic Ca2+ concentration, EGFR activation, and cell cycle progression, highlighting its potential as a prognostic biomarker and therapeutic target in CRC.
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Osteostaticytes: A novel osteoclast subset couples bone resorption and bone formation.
BACKGROUND: Osteomyelitis (OM) is an inflammatory condition of bone characterized by cortical bone devascularization and necrosis. Dysregulation of bone remodelling is triggered by OM. Bone remodelling is precisely coordinated by bone resorption and formation via a reversal phase. However, the cellular and molecular mechanisms underlying bone remodelling failure after osteomyelitis remain elusive. METHODS: To elucidate the cellular and molecular mechanism underlying bone healing after osteomyelitis, we employed single-cell RNA sequencing (scRNA-seq) to depict the atlas of human cortical bone in normal, infected and reconstructed states. Dimensionality reduction by t-stochastic neighbourhood embedding (t-SNE) and graph-based clustering were applied to analyse the detailed clusters of osteoclast lineages. After trajectory analysis of osteoclast lineages over pseudotime, real-time PCR and immunofluorescence (IF) staining were applied to identify marker gene expression of various osteoclast lineages in the osteoclast induction model and human bone sections, respectively. The potential function and communication of osteoclasts were analysed via gene set enrichment analysis (GSEA) and CellChat. The chemotactic ability of mesenchymal stem cells (MSCs) and osteoclast lineage cells in various differentiation states was determined by transwell assays and coculture assays. The effects of various osteoclast lineages on the osteogenic differentiation potential of MSCs were also determined by using this coculture system. A normal mouse tibia fracture model and an osteomyelitis-related tibia fracture model were generated via injection of luciferase-labelled Staphylococcus aureus to verify the relationships between a novel osteoclast lineage and MSCs. Then, the infection was detected by a bioluminescence imaging system. Finally, immunofluorescence staining was used to detect the expression of markers of MSCs and novel osteoclast lineages in different remodelling phases in normal and infected bone remodelling models. RESULTS: In this study, we constructed a cell atlas encompassing normal, infected, and reconstructed cortical bone. Then, we identified a novel subset at the earlier stage of the osteoclast lineage that exhibited increased expression of IDO1, CCL3, and CCL4. These IDO1highCCL3highCCL4high cells, termed osteostaticytes (OSCs), were further regarded as the reservoir of osteoclasts in the reversal phase. Notably, OSCs exhibited the highest chemotactic activity, surpassing other lineage subsets. We also discovered that cells at the earlier stage of the osteoclast lineage play a significant role in recruiting mesenchymal stem cells (MSCs). Finally, the data revealed that OSCs might be positively related to the occurrence of bone MSCs and the contribution of bone remodelling. CONCLUSION: Collectively, our findings revealed a novel stage (OSC) within the osteoclast lineage, potentially representing elusive bone reversal cells due to its increased chemotactic ability towards MSCs and potential contribution to bone remodelling. This study provides valuable insights into the intricate mechanisms of the reversal phase during bone remodelling and unveils potential therapeutic strategies for diseases associated with bone uncoupling. TRANSLATIONAL POTENTIAL OF THIS ARTICLE: This study identified a new subset, referred to as IDO1(plus symbol) CCL3(plus symbol) CCL4(plus symbol) osteostaticytes which displayed the highest chemotactic activity among all osteoclast lineages and may serve as reversal cells in bone remodelling. These findings offer new insights and insights for understanding bone reversal-related diseases and may serve as novel therapeutic targets for conditions such as osteomyelitis and delayed bone healing.
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In vivo human embryonic spinal cord atlas validates stem cell-derived human dorsal interneurons and reveals ASD spinal signatures.
Spinal cord injuries (SCI) result in the loss of motor and sensory function. We are working towards restoring sensation by developing directed differentiation protocols to generate dorsal spinal interneurons (dIs; dI1-dI6) from human embryonic stem cells (hESCs). Here, we present an improved method that produces human dIs via a neuromesodermal progenitor state, the physiological intermediate for spinal cord development. We show that retinoic acid (RA), bone morphogenetic protein 4 (BMP4) and growth differentiation factor (GDF) 11 direct dI identity, while GDF11 and extended time in culture promotes posterior spinal identities. Together, these protocols generate the full complement of dorsal subtypes along the entire anterior-posterior axis of the spinal cord. To benchmark in vitro-derived dIs, we constructed a single-cell RNA-Seq atlas of the human embryonic spinal cord and used it to show that hESC-derived dIs closely match their endogenous counterparts. The atlas also reveals that the dI4/dI5 populations dramatically expand in comparison with the other spinal lineages. Moreover, they have mechanosensory circuit signatures linked to autism spectrum disorder, implicating spinal circuits in autistic phenotypes.
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Single-Cell Atlas Reveals Tumorigenic Profiles and Immune Dynamics of Adrenal Incidentalomas.
Adrenal incidentalomas (AIs) are commonly detected endocrine lesions, identified during imaging for unrelated conditions. These lesions exhibit considerable heterogeneity and diverse clinical outcomes. This study employed single-cell RNA sequencing to investigate tumorigenic characteristics of AIs, including non-functional adrenocortical adenomas, Conn's syndrome, and pheochromocytomas. Through integrating public datasets, 302 696 cells are analyzed. Three adrenocortical cell subtypes exhibit gene expression patterns linked to tumorigenesis. Clusterin emerges as a potential biomarker for adrenocortical adenomas. Adrenocortical tumor cells show dysregulated hormone secretion and transcription factor steroidogenic factor 1 (SF1) is significantly upregulated, distinguishing cortical from medullary tumors. In pheochromocytomas, a MYCN proto-oncogene (MYCN)-positive cluster correlates with poorer survival. Immune microenvironment analysis reveals specific immune subtypes and roles in tumor progression. Specifically, myeloid cells may regulate benign tumors, while lymphoid cells, such as CD8-positive (CD8+) T cells, appear to promote immune activation and infiltration in malignant tumors. Overall, this study enhances the understanding of adrenal adenoma heterogeneity, revealing crucial transcriptional profiles, immune interactions, and clinically relevant candidate biomarkers.
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Single-cell sequencing in diabetic retinopathy: progress and prospects.
Diabetic retinopathy is a major ocular complication of diabetes, characterized by progressive retinal microvascular damage and significant visual impairment in working-age adults. Traditional bulk RNA sequencing offers overall gene expression profiles but does not account for cellular heterogeneity. Single-cell RNA sequencing overcomes this limitation by providing transcriptomic data at the individual cell level and distinguishing novel cell subtypes, developmental trajectories, and intercellular communications. Researchers can use single-cell sequencing to draw retinal cell atlases and identify the transcriptomic features of retinal cells, enhancing our understanding of the pathogenesis and pathological changes in diabetic retinopathy. Additionally, single-cell sequencing is widely employed to analyze retinal organoids and single extracellular vesicles. Single-cell multi-omics sequencing integrates omics information, whereas stereo-sequencing analyzes gene expression and spatiotemporal data simultaneously. This review discusses the protocols of single-cell sequencing for obtaining single cells from retina and accurate sequencing data. It highlights the applications and advancements of single-cell sequencing in the study of normal retinas and the pathological changes associated with diabetic retinopathy. This underscores the potential of these technologies to deepen our understanding of the pathogenesis of diabetic retinopathy that may lead to the introduction of new therapeutic strategies.
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Construction of a ferroptosis-related prognostic signature and identification of SRSF9 as a key biomarker in lung adenocarcinoma.
BACKGROUND: Ferroptosis is a distinct form of regulated cell death characterized by iron-dependent lipid peroxidation, which plays crucial roles in tumor biology and therapeutic response. However, the prognostic significance of ferroptosis-related genes (FRGs) in lung adenocarcinoma (LUAD) remains incompletely understood. This study aimed to construct and validate a ferroptosis-related prognostic model for LUAD by integrating single-cell and bulk transcriptomic data. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE127465 were integrated with bulk transcriptomic data from The Cancer Genome Atlas lung adenocarcinoma cohort (TCGA-LUAD). FRGs were identified through single-cell gene set scoring with the AUCell algorithm and differential expression analysis. A least absolute shrinkage and selection operator (LASSO)-Cox regression model was constructed and externally validated using the GSE72094 and GSE68465 cohorts. Associations between the model, genomic features, and the tumor immune microenvironment were systematically analyzed. The functional role of SRSF9 was verified through in vitro experiments. RESULTS: A total of 93 candidate genes significantly associated with ferroptosis activity were identified, and an 8-gene prognostic signature (PEBP1, TXN, TIMP1, SRSF9, CFL1, OTUB1, FURIN, and PTPN6) was constructed. The signature demonstrated robust prognostic performance across validation cohorts, with time-dependent area under the curve (AUC) values ranging from 0.65 to 0.74. High-risk patients exhibited elevated tumor mutation burden (TMB) and distinct immune infiltration patterns. Consensus clustering analysis classified patients into two ferroptosis-related molecular subtypes with significantly different prognoses. Functional experiments demonstrated that SRSF9 knockdown inhibited LUAD cell proliferation, migration, and invasion. Moreover, SRSF9 knockdown downregulated glutathione peroxidase 4 (GPX4) and SLC7A11, increased lipid peroxidation and malondialdehyde (MDA) levels, and the resulting cell viability loss was rescued by ferrostatin-1, indicating that SRSF9 knockdown induces ferroptosis in LUAD cells. CONCLUSIONS: The ferroptosis-related prognostic signature established in this study may facilitate risk stratification in LUAD patients. SRSF9 may regulate ferroptosis-related pathways through modulation of GPX4 and SLC7A11, and functional experiments further confirmed that SRSF9 knockdown induces ferroptosis in LUAD cells, highlighting SRSF9 as a candidate therapeutic target that warrants further investigation.