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Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma.
INTRODUCTION: The development of high-throughput sequencing technologies and targeted therapeutic strategies has significantly improved the prognosis of lung adenocarcinoma (LUAD) patients with sensitive gene mutations. However, patients harboring rare or no actionable mutations were rarely benefit from these targeted therapies. This study aimed to identify novel molecular subtypes and construct a prognostic signature to enhance the stratification of LUAD prognosis. MATERIALS AND METHODS: Novel molecular subtypes of LUAD patients were identified by applying 10 distinct clustering algorithms on multi-omics data. Single-cell RNA-sequencing (scRNA-seq) data were integrated to characterize subtype-specific immune microenvironments. A multi-omics and machine learning-driven prognostic signature (MO-MLPS) was constructed in The Cancer Genome Atlas (TCGA) LUAD dataset using ten machine learning algorithms and subsequently validated across six independent datasets from the Gene Expression Omnibus (GEO) database. The robustness of the model was assessed using the concordance index (C-index), Kaplan-Meier survival analyses, receiver operating characteristic (ROC) curves, and both univariate and multivariate Cox regression analyses. We further confirmed the effects of ANLN knockdown and the expression of a domain-negative anillin protein (dnANLN) via western blotting, cell proliferation assays, flow cytometry, and transwell migration assays in vitro. RESULTS: Our analysis revealed that the novel molecular subtypes exhibited differences in prognoses, biological functions, and immune infiltration profiles in LUAD. The MO-MLPS was successfully established and validated across TCGA-LUAD cohorts, six independent GEO datasets, and their composite meta-cohort. Higher risk scores from the MO-MLPS correlated with poorer prognosis in LUAD, with AUC values exceeding 0.5 at 1, 3, and 5 years across various cohorts. The signature outperformed 49 previously published prognostic signatures. Furthermore, patients classified as high risk exhibited significantly worse overall and progression-free survival than those classified as low risk. Notably, ANLN knockdown and dnANLN expression significantly inhibited cell proliferation and migration in vitro and enhanced the efficacy of docetaxel. CONCLUSION: A comprehensive analysis of multi-omics data redefines the molecular subtype of LUAD patients. The MO-MLPS derived from subtype characteristics has the potential to serve as a clinically valuable prognostic tool. Furthermore, ANLN emerges as a promising novel therapeutic target in the treatment of LUAD.
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A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution.
Caenorhabditis elegans is an animal with few cells but a wide diversity of cell types. In this study, we characterize the molecular basis for their specification by profiling the transcriptomes of 86,024 single embryonic cells. We identify 502 terminal and preterminal cell types, mapping most single-cell transcriptomes to their exact position in C. elegans' invariant lineage. Using these annotations, we find that (i) the correlation between a cell's lineage and its transcriptome increases from middle to late gastrulation, then falls substantially as cells in the nervous system and pharynx adopt their terminal fates; (ii) multilineage priming contributes to the differentiation of sister cells at dozens of lineage branches; and (iii) most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state.
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Single-cell transcriptomics reveals systemic immune dysregulation in non-segmental vitiligo.
BACKGROUND: Non-segmental vitiligo (NSV) is an autoimmune disorder characterized by irregular depigmented skin patches due to melanocyte loss, which causes considerable psychosocial burden. Although localized mechanisms underlying vitiligo pathogenesis have been studied extensively, investigations into peripheral blood mononuclear cells (PBMCs), key mediators of autoimmune diseases, remain limited. METHODS: To address this gap, we performed single-cell RNA sequencing (scRNA-seq) on peripheral blood samples from 3 untreated patients with generalized, progressive non-segmental vitiligo (GP-NSV) and 3 healthy controls. Findings were validated using flow cytometry in an additional cohort of 7 GP-NSV patients and 30 controls. Computational analyses, including pseudotime trajectory reconstruction and pathway enrichment, were employed to characterize immune cell subsets and their functional states. RESULTS: Vitiligo patients exhibited striking heterogeneity in PBMC subsets. KLRC2+ NK cells were markedly reduced and enriched in tumor necrosis factor (TNF) and apoptotic signaling pathways, a finding further confirmed by flow cytometry. Pseudotime analysis indicated that NK cells underwent negative regulation of DNA metabolic processes alongside activation of granzyme-mediated programmed cell death. In addition, the frequency of FCGR3A+ Cytotoxic CD8+T cell was reduced, with enrichment in T cell activation and differentiation signatures. STAM+ regulatory T cells (Tregs) were increased, whereas EGR1+ B cells were decreased, both subsets showing enrichment in pathways linked to osteoclast differentiation and calcium ion metabolism, suggesting a potential role of calcium homeostasis dysregulation in disease pathogenesis. CONCLUSIONS: This study provides the single-cell atlas of PBMCs in GP-NSV, uncovering profound transcriptional and compositional alterations across multiple immune cell subsets in active vitiligo. These findings offer novel insights into systemic immune dysregulation in GP-NSV and pave the way for novel targeted therapeutic strategies.
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LINC01871 is exclusively expressed in T and NK cells and is highly induced upon CD4+ T cell activation.
Long intergenic noncoding RNAs (lincRNAs) regulate biological processes in health and disease. Recent findings highlight the importance of lincRNAs in regulating T cell development and function. Here, we identified a lincRNA, LINC01871, which is highly induced upon CD4+ T cell activation and is predominantly located in the cytoplasm. The anti-inflammatory cytokine TGF-β was found to suppress its expression. Silencing LINC01871 led to a modest decrease in IL-2 secretion. Notably, LINC01871 expression was highly specific to NK cells and T cells in several cross-tissue single cell RNA-seq atlases. These data suggest that LINC01871 is specifically expressed in T and NK cells and may contribute to T cell-mediated immunity in humans.
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HypoMap-a unified single-cell gene expression atlas of the murine hypothalamus.
The hypothalamus plays a key role in coordinating fundamental body functions. Despite recent progress in single-cell technologies, a unified catalog and molecular characterization of the heterogeneous cell types and, specifically, neuronal subtypes in this brain region are still lacking. Here, we present an integrated reference atlas, 'HypoMap,' of the murine hypothalamus, consisting of 384,925 cells, with the ability to incorporate new additional experiments. We validate HypoMap by comparing data collected from Smart-Seq+Fluidigm C1 and bulk RNA sequencing of selected neuronal cell types with different degrees of cellular heterogeneity. Finally, via HypoMap, we identify classes of neurons expressing glucagon-like peptide-1 receptor (Glp1r) and prepronociceptin (Pnoc), and validate them using single-molecule in situ hybridization. Collectively, HypoMap provides a unified framework for the systematic functional annotation of murine hypothalamic cell types, and it can serve as an important platform to unravel the functional organization of hypothalamic neurocircuits and to identify druggable targets for treating metabolic disorders.
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Benchmarking single-cell RNA-sequencing protocols for cell atlas projects.
Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas.
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Deciphering decidual deficiencies in recurrent spontaneous abortion and the therapeutic potential of mesenchymal stem cells at single-cell resolution.
BACKGROUND: Recurrent spontaneous abortion (RSA) is a challenging condition that affects the health of women both physically and mentally, but its pathogenesis and treatment have yet to be studied in detail. In recent years, Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) have been shown to be effective in treating various diseases. Current understanding of RSA treatment using WJ-MSCs is limited, and the exact mechanisms of WJ-MSCs action in RSA remains largely unclear. In this study, we explored the decidual deficiencies in RSA and the therapeutic potential of WJ-MSCs at single-cell resolution. METHODS: Three mouse models were established: a normal pregnancy group, an RSA group, and a WJ-MSC treatment group. Decidual tissue samples were collected for single-cell RNA sequencing (scRNA-seq) and functional verification, including single-cell resolution in situ hybridization on tissues (SCRINSHOT) and immunofluorescence. RESULTS: We generated a single-cell atlas of decidual tissues from normal pregnant, RSA, and WJ-MSC-treated mice and identified 14 cell clusters in the decidua on day 14. Among these cell populations, stromal cells were the most abundant cell clusters in the decidua, and we further identified three novel subclusters (Str_0, Str_1, and Str_2). We also demonstrated that the IL17 and TNF signaling pathways were enriched for upregulated DEGs of stromal cells in RSA mice. Intriguingly, cell-cell communication analysis revealed that Str_1 cell-related gene expression was greatly reduced in the RSA group and rescued in the WJ-MSC treatment group. Notably, the interaction between NK cells and other cells in the RSA group was attenuated, and the expression of Spp1 (identified as an endometrial toleration-related marker) was significantly reduced in the NK cells of the RSA group but could be restored by WJ-MSC treatment. CONCLUSION: Herein, we implemented scRNA-seq to systematically evaluate the cellular heterogeneity and transcriptional regulatory networks associated with RSA and its treatment with WJ-MSCs. These data revealed potential therapeutic targets of WJ-MSCs to remodel the decidual subpopulations in RSA and provided new insights into decidua-derived developmental defects at the maternal-foetal interface.
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Multimodal Human Scalp Atlas Defines Cell Landscape and Lineage Architecture In Situ.
Human scalp hair has an extraordinary ability to grow continuously for years while maintaining structural and functional integrity. However, the cell states and lineage organization that enable this capacity and how they are disrupted in inflammatory hair loss disorders remain poorly defined in humans. Here we establish a high-resolution, multimodal atlas of human scalp by integrating deep-coverage spatial transcriptomics with single-cell RNA-seq and multiomics data. This reference resolves spatially organized epithelial and mesenchymal states and links in situ transcriptional programs to chromatin accessibility dynamics and lineage trajectories at single-cell resolution, revealing human-specific principles of tissue organization and previously unrecognized features of hair follicle architecture and lineage progression. We validate key aspects of matrix cell organization and cell activities using live imaging, connecting molecularly defined cell states to dynamic cell behaviors and lineage progression in the matrix. Leveraging the atlas as a spatial reference, we project patient scRNA-seq profiles from alopecia areata and lichen planopilaris onto defined cell compartments, resolving disease-specific perturbations in fibroblasts, epithelial and immune populations. This comparison delineates distinct cellular programs associated with non-scarring versus scarring hair loss and highlights compartment- and state-specific pathways with diagnostic and therapeutic potential. Together, this work provides a foundational resource for human hair biology and establishes a generalizable framework for spatially resolved, multimodal interrogation of tissue organization and disease in complex human tissues.
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies.
BACKGROUND: Lung adenocarcinoma (LUAD) presents a considerable danger to human health and has evolved into a major public health concern. Ribosome biogenesis (RiboSis) is a critical process for synthesizing ribosomes, closely associated with cancer initiation, progression, and treatment resistance, potentially serving as a target for future cancer therapies. METHODS: Utilizing single-cell RNA sequencing (scRNA-seq) technology, a single-cell atlas of LUAD was delineated, focusing on the analysis of T cell subpopulations. Cells were scored based on the expression patterns of 331 genes associated with RiboSis across different cell types, and monocle2 was employed to analyze the developmental trajectory of CD4+ T cells. Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. The relationship between RBS risk scores and various factors in LUAD patients, including prognosis, the tumor immune microenvironment (TIME), responsiveness to immunotherapy, and sensitivity to pharmacological treatments was specifically analyzed. Immunohistochemistry was utilized to validate the expression levels of immune markers in the high- and low- RBS groups, and in vitro experiments were performed to validate the functional role of the pivotal gene KIF23 in the progression of LUAD. RESULTS: Using single-cell analysis, two distinct T cell subtypes were identified: CD8+ interferon (IFN) response T cells and CD4+ stress response T cells. It was observed that CD4+ naive-like T cells exhibit high expression of RiboSis-related genes, with a gradual decrease in RiboSis activity as CD4+ T cells develop. Compared to other prognostic models, RBS demonstrated superior performance in prognosis prediction. The low-RBS group exhibited a tumor microenvironment (TME) more favorable for efficient immune monitoring and reaction, higher responsiveness to immunotherapy, and a better prognosis. Immunohistochemistry confirmed higher expression levels of immune markers in the low-RBS group, while in vitro experiments validated the promoting role of KIF23 in LUAD cell proliferation, migration and invasion. CONCLUSION: This study delves into the relationship between RiboSis and LUAD cell subpopulations, identifying a potent prognostic biomarker for LUAD. This biomarker aids in assessing immunotherapy efficacy in LUAD patients, ultimately enhancing their prognosis and guiding clinical decision-making.
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MUC1-C integrates activation of the IFN-γ pathway with suppression of the tumor immune microenvironment in triple-negative breast cancer.
BACKGROUND: Immune checkpoint inhibitors (ICIs) have had a profound impact on the treatment of many tumors; however, their effectiveness against triple-negative breast cancers (TNBCs) has been limited. One factor limiting responsiveness of TNBCs to ICIs is a lack of functional tumor-infiltrating lymphocytes (TILs) in 'non-inflamed' or 'cold' tumor immune microenvironments (TIMEs), although by unknown mechanisms. Targeting MUC1-C in a mouse transgenic TNBC tumor model increases cytotoxic tumor-infiltrating CD8+ T cells (CTLs), supporting a role for MUC1-C in immune evasion. The basis for these findings and whether they extend to human TNBCs are not known. METHODS: Human TNBC cells silenced for MUC1-C using short hairpin RNAs (shRNAs) were analyzed for the effects of MUC1-C on global transcriptional profiles. Differential expression and rank order analysis was used for gene set enrichment analysis (GSEA). Gene expression was confirmed by quantitative reverse-transcription PCR and immunoblotting. The The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets were analyzed for effects of MUC1 on GSEA, cell-type enrichment, and tumor immune dysfunction and exclusion. Single-cell scRNA-seq datasets of TNBC samples were analyzed for normalized expression associations between MUC1 and selected genes within tumor cells. RESULTS: Our results demonstrate that MUC1-C is a master regulator of the TNBC transcriptome and that MUC1-C-induced gene expression is driven by STAT1 and IRF1. We found that MUC1-C activates the inflammatory interferon (IFN)-γ-driven JAK1→STAT1→IRF1 pathway and induces the IDO1 and COX2/PTGS2 effectors, which play key roles in immunosuppression. Involvement of MUC1-C in activating the immunosuppressive IFN-γ pathway was extended by analysis of human bulk and scRNA-seq datasets. We further demonstrate that MUC1 associates with the depletion and dysfunction of CD8+ T cells in the TNBC TIME. CONCLUSIONS: These findings demonstrate that MUC1-C integrates activation of the immunosuppressive IFN-γ pathway with depletion of TILs in the TNBC TIME and provide support for MUC1-C as a potential target for improving TNBC treatment alone and in combination with ICIs. Of translational significance, MUC1-C is a druggable target with chimeric antigen receptor (CAR) T cells, antibody-drug conjugates (ADCs) and a functional inhibitor that are under clinical development.