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Construction of a novel choline metabolism-related signature to predict prognosis, immune landscape, and chemotherapy response in colon adenocarcinoma.
BACKGROUND: Colon adenocarcinoma (COAD) is a common digestive system malignancy with high mortality and poor prognosis. Accumulating evidence indicates that choline metabolism is closely related to tumorigenesis and development. However, the efficacy of choline metabolism-related signature in predicting patient prognosis, immune microenvironment and chemotherapy response has not been fully clarified. METHODS: Choline metabolism-related differentially expressed genes (DEGs) between normal and COAD tissues were screened using datasets from The Cancer Genome Atlas (TCGA), Kyoto Encyclopedia of Genes and Genomes (KEGG), AmiGO2 and Reactome Pathway databases. Two choline metabolism-related genes (CHKB and PEMT) were identified by univariate and multivariate Cox regression analyses. TCGA-COAD was the training cohort, and GSE17536 was the validation cohort. Patients in the high- and low-risk groups were distinguished according to the optimal cutoff value of the risk score. A nomogram was used to assess the prognostic accuracy of the choline metabolism-related signature. Calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC) were used to improve the clinical applicability of the prognostic signature. Gene Ontology (GO) and KEGG pathway enrichment analyses of DEGs in the high- and low-risk groups were performed. KEGG cluster analysis was conducted by the KOBAS-i database. The distribution and expression of CHKB and PEMT in various types of immune cells were analyzed based on single-cell RNA sequencing (scRNA-seq). The CIBERSORT and ESTIMATE algorithms evaluated tumor immune cell infiltration in the high- and low-risk groups. Evaluation of the half maximal inhibitory concentration (IC50) of common chemotherapeutic drugs based on the choline metabolism-related signature was performed. Small molecule compounds were predicted using the Connectivity Map (CMap) database. Molecular docking is used to simulate the binding conformation of small molecule compounds and key targets. By immunohistochemistry (IHC), Western blot, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) experiments, the expression levels of CHKB and PEMT in human, mouse, and cell lines were detected. RESULTS: We constructed and validated a choline metabolism-related signature containing two genes (CHKB and PEMT). The overall survival (OS) of patients in the high-risk group was significantly worse than that of patients in the low-risk group. The nomogram could effectively and accurately predict the OS of COAD patients at 1, 3, and 5 years. The DCA curve and CIC demonstrate the clinical utility of the nomogram. scRNA-seq showed that CHKB was mainly distributed in endothelial cells, while PEMT was mainly distributed in CD4+ T cells and CD8+ T cells. In addition, multiple types of immune cells expressing CHKB and PEMT differed significantly. There were significant differences in the immune microenvironment, immune checkpoint expression and chemotherapy response between the two risk groups. In addition, we screened five potential small molecule drugs that targeted treatment for COAD. Finally, the results of IHC, Western blot, and qRT-PCR consistently showed that the expression of CHKB in human, mouse, and cell lines was elevated in normal samples, while PMET showed the opposite trend. CONCLUSION: In conclusion, we constructed a choline metabolism-related signature in COAD and revealed its potential application value in predicting the prognosis, immune microenvironment, and chemotherapy response of patients, which may lay an important theoretical basis for future personalized precision therapy.
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Cancer cell-specific PD-L1 expression is a predictor of poor outcome in patients with locally advanced oral cavity squamous cell carcinoma.
BACKGROUND: Locally advanced oral cavity squamous cell carcinoma (OCSCC) presents a significant clinical challenge despite being partially responsive to standard treatment modalities. This study investigates the prognostic implications of programmed death-ligand 1 (PD-L1) expression in these tumors, focusing on its association with treatment outcomes and the immune microenvironment. METHODS: We assessed tumor-infiltrating lymphocytes (TILs) in 132 patients with OCSCC to evaluate their impact on survival. Multiplex immunohistochemistry staining for CD3, CD68, CD11c, PD-L1, and P40 was used to explore correlations with clinical outcomes in patients with early-stage (n=22) and locally advanced (n=36) OCSCC. These initial findings were validated through differential gene expression analysis, gene set enrichment, and immune cell deconvolution in a The Cancer Genome Atlas cohort of 163 locally advanced OCSCC tumors. Additionally, single-cell RNA sequencing (scRNA-seq) on a smaller cohort (n=10) further characterized the PD-L1hi or PD-L1lo cancer cells in these tumors. RESULTS: Elevated PD-L1 expression was associated with poor outcomes in patients with locally advanced OCSCC undergoing standard adjuvant therapy, irrespective of "hot" or "cold" classification based on TILs assessment. PD-L1hi tumors exhibited an active immune response phenotype, enriched with M1 macrophages, CD8+ T cells and T regulatory cells in the tumor microenvironment. Notably, the negative impact of PD-L1 expression on outcomes was primarily attributed to its expression by cancer cells, rather than immune cells. Furthermore, scRNA-seq revealed that immune interactions were not essential for PD-L1 upregulation in cancer cells, instead, complex regulatory networks were involved. Additionally, PD-L1lo locally advanced tumors exhibited more complex pathway enrichment and diverse T-cell populations compared with those in the early-stage. CONCLUSION: Our findings underscore the prognostic significance of PD-L1 expression in locally advanced OCSCC, and unveil the complex interplay between PD-L1 expression, immune responses, and molecular pathways in the tumor microenvironment. This study provides insights that may inform future therapeutic strategies, including the possibility of tailored immunotherapeutic approaches for patients with PD-L1hi locally advanced OCSCC.
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Mapping epidermal and dermal cellular senescence in human skin aging.
Single-cell RNA sequencing and spatial transcriptomics enable unprecedented insight into cellular and molecular pathways implicated in human skin aging and regeneration. Senescent cells are individual cells that are irreversibly cell cycle arrested and can accumulate across the human lifespan due to cell-intrinsic and -extrinsic stressors. With an atlas of single-cell RNA-sequencing and spatial transcriptomics, epidermal and dermal senescence and its effects were investigated, with a focus on melanocytes and fibroblasts. Photoaging due to ultraviolet light exposure was associated with higher burdens of senescent cells, a sign of biological aging, compared to chronological aging. A skin-specific cellular senescence gene set, termed SenSkin™, was curated and confirmed to be elevated in the context of photoaging, chronological aging, and non-replicating CDKN1A+ (p21) cells. In the epidermis, senescent melanocytes were associated with elevated melanin synthesis, suggesting haphazard pigmentation, while in the dermis, senescent reticular dermal fibroblasts were associated with decreased collagen and elastic fiber synthesis. Spatial analysis revealed the tendency for senescent cells to cluster, particularly in photoaged skin. This work proposes a strategy for characterizing age-related skin dysfunction through the lens of cellular senescence and suggests a role for senescent epidermal cells (i.e., melanocytes) and senescent dermal cells (i.e., reticular dermal fibroblasts) in age-related skin sequelae.
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HOSCA: Human Ocular Single-Cell Atlas for Decoding Ocular Biology and Disease Complexity.
The human eye is a highly specialized organ composed of different tissue types, each with a unique cellular microenvironment critical to visual function. Recent advances in single-cell RNA sequencing (scRNA-seq) have provided unprecedented opportunities to explore the cellular heterogeneity of ocular tissues and diseases. However, the rapid accumulation of scRNA-seq data in ophthalmology poses challenges in integrating, aligning, and effectively reusing different datasets. Here, we present the Human Ocular Single-Cell Atlas (HOSCA), an atlas-scale curated database and analysis platform that integrates and harmonizes more than 3.88 million single-cell transcriptomic profiles from 704 human samples and 60 high-quality scRNA-seq datasets, covering 16 anatomical regions of the eye and 15 associated diseases. HOSCA provides user-friendly, interactive tools for conducting cross-tissue, cross-disease, and demographic comparative analyses using a unified bioinformatics pipeline for data standardization, cross-platform batch correction, and accurate cell type annotation. As the largest ocular single-cell resource to date, HOSCA bridges the gap between atlas-scale data and precision ophthalmology, providing a powerful platform for advancing our understanding of ocular biology and disease. HOSCA is publicly available at http://www.bio-data.cn/HOSCA/.
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Population-level single-cell genomics reveals conserved gene programs in systemic juvenile idiopathic arthritis.
Systemic autoimmune and autoinflammatory diseases are characterized by genetic and cellular heterogeneity. While current single-cell genomics methods provide insights into known disease subtypes, these analysis methods do not readily reveal novel cell-type perturbation programs shared among distinct patient subsets. Here, we performed single-cell RNA-Seq of PBMCs of patients with systemic juvenile idiopathic arthritis (SJIA) with diverse clinical manifestations, including macrophage activation syndrome (MAS) and lung disease (LD). We introduced two new computational frameworks called UDON and SATAY-UDON, which define patient subtypes based on their underlying disrupted cellular programs as well as associated biomarkers or clinical features. Among twelve independently identified subtypes, this analysis uncovered what we believe to be a novel complement and interferon activation program identified in SJIA-LD monocytes. Extending these analyses to adult and pediatric lupus patients found new but also shared disease programs with SJIA, including interferon and complement activation. Finally, supervised comparison of these programs in a compiled single-cell pan-immune atlas of over 1,000 healthy donors found a handful of normal healthy donors with evidence of early inflammatory activation in subsets of monocytes and platelets, nominating possible biomarkers for early disease detection. Thus, integrative pan-immune single-cell analysis resolved what we believe to be new conserved gene programs underlying inflammatory disease pathogenesis and associated complications.
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Graph-based contrastive learning enables unified integration and niche transfer across single-cell and spatial multi-omics.
The rapid growth of single-cell and spatial omics has outpaced computational methods capable of unifying these data into a cohesive framework for tissue atlas construction and cross-sample analysis. A critical bottleneck lies in the inability of existing tools to co-embed cells from diverse technologies-spanning transcriptomics, epigenomics, and proteomics-into a shared reference space while preserving spatial architecture and molecular specificity. Here, we present Garfield (Graph-based Contrastive Learning Enables Fast Single-Cell Embedding), a geometric deep-learning framework that addresses these challenges through spatially or molecularly aware cell embedding. Leveraging a graph contrastive learning framework, Garfield learns a shared embedding space for data generated by diverse technologies, enabling seamless construction and querying of spatial reference atlases. Our results show that Garfield consistently outperforms state-of-the-art benchmark models in identifying spatial niches across multiple datasets. We further demonstrate Garfield's versatility by applying it to multimodal spatial data, including gene expression and chromatin accessibility, where it successfully identifies distinct niches in the mouse brain. Notably, Garfield reveals tumor microenvironment heterogeneity in non-small cell lung cancer and breast cancer, uncovered conserved, barrier-like immune niches at tumor margins orchestrating CD80-mediated T cell-B cell-dendritic cell interactions and IFN-$\gamma$/B cell activation pathways, forming spatially coordinated immune surveillance hubs. These findings underscore Garfield's potential to advance spatial omics research by offering a robust, scalable solution for integrating and interpreting complex spatial data across diverse tissue types and modalities.
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Opportunities and challenges in the application of single-cell transcriptomics in plant tissue research.
Single-cell transcriptomics overcomes the limitations of conventional transcriptome methods by isolating and sequencing RNA from individual cells, thus capturing unique expression values for each cell. This technology allows unprecedented precision in observing the stochasticity and heterogeneity of gene expression within cells. However, single-cell RNA sequencing (scRNA-seq) experiments often fail to capture all cells and genes comprehensively, and single-modality data is insufficient to explain cell states and systemic changes. To address this, the integration of multi-source scRNA-seq and single-cell multi-modality data has emerged, enabling the construction of comprehensive cell atlases. These integration methods also facilitate the exploration of causal relationships and gene regulatory mechanisms across different modalities. This review summarizes the fundamental principles, applications, and value of these integration methods in revealing biological changes, and analyzes the advantages, disadvantages, and future directions of current approaches.
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Single-cell atlas of the liver myeloid compartment before and after cure of chronic viral hepatitis.
BACKGROUND & AIMS: Chronic viral infections present serious public health challenges; however, direct-acting antivirals (DAAs) are now able to cure nearly all patients infected with hepatitis C virus (HCV), representing the only cure of a human chronic viral infection to date. DAAs provide a valuable opportunity to study immune pathways in the reversal of chronic immune failures in an in vivo human system. METHODS: To leverage this opportunity, we used plate-based single-cell RNA-seq to deeply profile myeloid cells from liver fine needle aspirates in patients with HCV before and after DAA treatment. We comprehensively characterised liver neutrophils, eosinophils, mast cells, conventional dendritic cells, plasmacytoid dendritic cells, classical monocytes, non-classical monocytes, and macrophages, and defined fine-grained subpopulations of several cell types. RESULTS: We discovered cell type-specific changes post-cure, including an increase in MCM7+STMN1+ proliferating CD1C+ conventional dendritic cells, which may support restoration from chronic exhaustion. We observed an expected downregulation of interferon-stimulated genes (ISGs) post-cure as well as an unexpected inverse relationship between pre-treatment viral load and post-cure ISG expression in each cell type, revealing a link between viral loads and sustained modifications of the host's immune system. We found an upregulation of PD-L1/L2 gene expression in ISG-high neutrophils and IDO1 expression in eosinophils, pinpointing cell subpopulations crucial for immune regulation. We identified three recurring gene programmes shared by multiple cell types, distilling core functions of the myeloid compartment. CONCLUSIONS: This comprehensive single-cell RNA-seq atlas of human liver myeloid cells in response to cure of chronic viral infections reveals principles of liver immunity and provides immunotherapeutic insights. CLINICAL TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov (NCT02476617). IMPACT AND IMPLICATIONS: Chronic viral liver infections continue to be a major public health problem. Single-cell characterisation of liver immune cells during hepatitis C and post-cure provides unique insights into the architecture of liver immunity contributing to the resolution of the first curable chronic viral infection of humans. Multiple layers of innate immune regulation during chronic infections and persistent immune modifications after cure are revealed. Researchers and clinicians may leverage these findings to develop methods to optimise the post-cure environment for HCV and develop novel therapeutic approaches for other chronic viral infections.
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Hemoglobin-based oxygen carriers promote the expression of antiviral defense genes in bone marrow leukocytes.
Hemoglobin-based oxygen carriers (HBOCs) are blood substitutes utilized for oxygen delivery, but their systemic effects on immune homeostasis remain insufficiently characterized. In this study, healthy C57BL/6J mice were intravenously administered with either HBOC (RedpCarrier, 600 mg/kg/day) or vehicle for three consecutive days. Using single-cell RNA sequencing (scRNA-seq), we generated a comprehensive transcriptomic atlas of bone marrow (BM) leukocytes. Unbiased clustering revealed that HBOC exposure significantly remodeled the BM landscape, characterized by a proportional decrease in neutrophils and monocytes alongside an expansion of B cells, T cells, and dendritic cells. Quantitative analysis identified 124 significantly upregulated genes across immune compartments, which were overwhelmingly enriched in Type-I interferon signaling and defense responses to viruses. The interferon-stimulated gene Isg15 was identified as a core upregulated marker across multiple lineages. To evaluate functional outcomes, we employed lethal SARS-CoV-2 and HSV-1 infection models, where HBOC-pretreated mice exhibited significantly higher 14-day survival rates compared to controls. In summary, our findings demonstrate that HBOC administration induces a distinctive antiviral-like transcriptional priming state within the bone marrow microenvironment. Crucially, in vitro functional assays and protein-level validations confirm that high-dose HBOC treatment drives intracellular ROS accumulation and subsequently activates Stat1 expression and phosphorylation in macrophages. Together, these transcriptomic and experimental insights establish a solid mechanistic link between HBOC-induced redox modulation and innate immune activation, providing a foundational framework for exploring HBOCs as potential adjunctive immunomodulators for enhanced viral defense.
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A human cell atlas of fetal chromatin accessibility.
The chromatin landscape underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of chromatin accessibility and gene expression in fetal tissues. For chromatin accessibility, we devised a three-level combinatorial indexing assay and applied it to 53 samples representing 15 organs, profiling ~800,000 single cells. We leveraged cell types defined by gene expression to annotate these data and cataloged hundreds of thousands of candidate regulatory elements that exhibit cell type-specific chromatin accessibility. We investigated the properties of lineage-specific transcription factors (such as POU2F1 in neurons), organ-specific specializations of broadly distributed cell types (such as blood and endothelial), and cell type-specific enrichments of complex trait heritability. These data represent a rich resource for the exploration of in vivo human gene regulation in diverse tissues and cell types.