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Single cell atlas of Xenoturbella bocki highlights limited cell-type complexity.
Phylogenetic analyses over the last two decades have united a few small, and previously orphan clades, the nematodermatids, acoels and xenoturbelids, into the phylum Xenacoelomorpha. Some phylogenetic analyses support a sister relationship between Xenacoelomorpha and Ambulacraria (Xenambulacraria), while others suggest that Xenacoelomorpha may be sister to the rest of the Bilateria (Nephrozoa). An understanding of the cell type complements of Xenacoelomorphs is essential to assessing these alternatives as well as to our broader understanding of bilaterian cell type evolution. Employing whole organism single-cell RNA-seq in the marine xenacoelomorph worm Xenoturbella bocki, we show that Xenambulacrarian nerve nets share regulatory features and a peptidergic identity with those found in cnidarians and protostomes and more broadly share muscle and gland cell similarities with other metazoans. Taken together, these data are consistent with broad homologies of animal gland, muscle, and neurons as well as more specific affinities between Xenoturbella and acoel gut and epidermal tissues, consistent with the monophyly of Xenacoelomorpha.
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Integrative bioinformatics and immunohistochemical analysis unravel the prognostic significance and immunological implication of LIMCH1 in breast cancer: a retrospective study.
The current mortality rates for breast cancer underscore the need for better prognostic tools; moreover, LIM and calponin homology domain 1 (LIMCH1), which is a protein with dual roles in cancer, is a promising candidate for investigation. This study employed an integrative approach combining bioinformatics analysis of The Cancer Genome Atlas (TCGA) cohort and clinical immunohistochemistry (IHC) cohort data. We analysed LIMCH1 expression patterns, its associations with clinicopathological features and prognosis, and its impact on the tumour immune microenvironment (TIME). Functional annotations and single-cell RNA sequencing (scRNA-seq) data were used to explore the underlying molecular mechanisms. Our analysis revealed that high LIMCH1 expression in breast cancer patients was significantly associated with unfavourable clinical outcomes and served as an independent prognostic indicator. The functional annotations revealed pathways related to carcinogenesis and metabolic reconfiguration, thus suggesting the role of LIMCH1 in tumour progression. Additionally, LIMCH1 expression was correlated with an immunosuppressive TIME characterized by increased numbers of M2 macrophages and reduced numbers of CD8 + T cells and NK cells. Finally, we developed a nomogram incorporating LIMCH1 expression for predicting overall survival rates, thus providing a clinically applicable tool. Our research elucidates the diverse functions of LIMCH1 in the pathogenesis of breast cancer, thus highlighting its potential utility as both a prognostic indicator and a therapeutic intervention.
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Cross-scale modeling reveals a TFRC-driven immunosuppressive macrophage niche in cervical cancer.
BACKGROUND: The functional plasticity of tumor-associated macrophages (TAMs) is a critical determinant of the immunosuppressive microenvironment in cervical cancer, yet its integration into actionable prognostic frameworks remains limited. This study aimed to establish a TAM polarization-centered model and elucidate the mechanisms of underlying tumor-immune crosstalk. METHODS: Bulk transcriptomics from The Cancer Genome Atlas (TCGA) were integrated with single-cell RNA sequencing (scRNA-seq) data (GSE208653). By combining weighted gene co-expression network analysis (WGCNA) with a multi-algorithm machine learning framework, a prognostic signature was constructed and independently validated in the Gene Expression Omnibus (GEO) GSE52903 cohort. Single-cell analysis resolved the cellular origins of signature genes, prioritizing tumor-enriched genes for validation. Protein-level expression was verified via immunohistochemistry (IHC) in a paired clinical cohort (n=39). Functional validation of the core gene was performed in vitro using cervical cancer cell lines co-cultured with THP-1-derived macrophages. Polarization was assessed via reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blot (WB), enzyme-linked immunosorbent assay (ELISA), flow cytometry, and multiplex immunofluorescence (mIF). RESULTS: A robust five-gene prognostic signature (TP73, TFRC, SHC1, SCD, and PFKFB3) was developed, effectively stratifying patient survival. High risk scores correlated with a suppressed antitumor immune landscape and diminished predicted chemosensitivity to agents such as cisplatin. Single-cell analysis and IHC confirmed transferrin receptor (TFRC) as a tumor-intrinsic factor that is progressively upregulated during cervical carcinogenesis and enhances pro-M2 signaling. In vitro co-culture assays demonstrated that tumor-derived TFRC actively orchestrates an immunosuppressive M2-like macrophage niche, driving phenotypic shifts and pro-tumorigenic cytokine secretion, characterized by elevated interleukin-10 (IL-10) and reduced TNF-α. RT-qPCR analysis of 40 clinical specimens further confirmed a significant positive correlation between TFRC and the M2 marker Arg-1 at the mRNA level (r = 0.4961, P = 0.0011). CONCLUSIONS: This study establishes a cross-scale, biologically interpretable prognostic model linking macrophage plasticity to clinical outcomes. We identify TFRC as a pivotal metabolic-immune node through which tumor-intrinsic iron metabolism orchestrates an immunosuppressive niche, providing a foundation for novel therapeutic strategies in cervical cancer.
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A comparative brain atlas in the Mexican cavefish identifies widespread changes in cellular composition and gene expression.
Understanding how naturally occurring genetic variation shapes human health and disease is critical for improving diagnosis and treatment strategies. The Mexican cavefish, Astyanax mexicanus, represents a powerful system for evolutionary medicine, enabling investigation of naturally evolved mechanisms of resilience to disease-related traits including diabetes, obesity, insomnia, and eye loss. Larval A. mexicanus, like zebrafish, are transparent, allowing whole-brain imaging, circuit mapping, and the generation of computationally derived atlases that precisely quantify neuroanatomical differences between surface and cave populations. Developing a molecular map of brain cell types provides a foundation for identifying evolved differences in neural circuits and physiology. Here, we present a single-cell atlas of the larval cavefish brain that reveals widespread divergence in the abundance and molecular signatures of neurons and glia. Our cell type map validates known neuroanatomical differences, including a reduction of the optic tectum and expansion of the pineal gland in cavefish. We uncover substantial changes in multiple glial cell classes that are linked to neural regulation of behavior, including microglia. Analysis of differential gene expression between surface and cavefish microglia revealed enhanced genes associated with synaptic pruning and clearance of neural debris, suggesting cavefish increased microglia activity to shape brain development. We also analyzed cell types that did not classify as canonical neurons or glia and identified notable divergence in transcriptomes and cell composition, including reduced meningeal fibroblasts in cavefish and substantial transcriptional changes related to phototransduction in non-visual photoreceptors within the pineal gland. Together, these findings provide a comprehensive atlas of cell type-specific gene expression differences between A. mexicanus surface and cavefish, establishing a platform for dissecting the molecular and cellular basis of evolved disease resilience in cavefish.
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APOA2 mediates immune therapy tolerance in hepatocellular carcinoma by inhibiting the antigen-presenting function of dendritic cells through the PPAR signaling pathway.
BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, characterized by high heterogeneity and poor prognosis. Despite advances in systemic therapies, including immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), treatment efficacy remains limited. This study investigated the mechanisms underlying resistance to combined targeted therapy and immunotherapy in HCC. METHODS: We integrated spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) data from cabozantinib-nivolumab-treated patients, using the RCTD algorithm for cell-type deconvolution. High-dimensional weighted gene co-expression network analysis (hdWGCNA) identified resistance-associated modules, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and correlation analyses to characterize APOA2/SPINK1 roles in the tumor microenvironment (TME). Spatial niches were defined via the Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA) algorithm based on cell-type co-occurrence patterns, and multiscale co-localization was analyzed using the Multiview Intercellular SpaTial modeling framework (Misty). Ligand-receptor interactions were validated by CellChat, with results confirmed using The Cancer Genome Atlas (TCGA) bulk RNA-sequencing data. RESULTS: Thirty-nine resistance-associated genes were identified, with APOA2 and SPINK1 emerging as pivotal hub genes. APOA2 mediated immune resistance by impairing dendritic cell (DC) antigen presentation through the PPAR signaling pathway, contributing to a suppressive TME. SPINK1 was associated with tumor aggressiveness, enhancing invasion, metastasis, and therapy tolerance. Lipid metabolism pathways were enriched in the non-responder (NR) group, underscoring the role of metabolic reprogramming in immune evasion and treatment resistance. Correlation analyses revealed that APOA2 expression was negatively associated with major histocompatibility complex (MHC) molecule expression. CONCLUSIONS: This study highlights the critical roles of APOA2, SPINK1, and lipid metabolism in shaping an immunosuppressive TME and driving treatment resistance in HCC. These findings provide novel insights into the mechanisms of resistance and offer a foundation for developing therapeutic strategies for better clinical outcomes.
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Single-cell transcriptomic analyses of tumor microenvironment and molecular reprograming landscape of metastatic laryngeal squamous cell carcinoma.
Laryngeal squamous cell carcinoma (LSCC) is a malignant tumor with a high probability of metastasis. The tumor microenvironment (TME) plays a critical role in cancer metastasis. To gain insights into the TME of LSCC, we conducted single-cell RNA-seq (scRNA-seq) on samples collected from LSCC patients with or without lymphatic metastasis. The stem and immune cell signatures in LSCC suggest their roles in tumor invasion and metastasis. Infiltration of a large number of regulatory T cells, dysplastic plasma cells, and macrophages that are at the early development stage in the cancerous tissue indicates an immunosuppressive state. Abundant neutrophils detected at the cancer margins reflect the inflammatory microenvironment. In addition to dynamic ligand-receptor interactions between the stromal and myeloid cells, the enhanced autophagy in endothelial cells and fibroblasts implies a role in nutrient supply. Taken together, the comprehensive atlas of LSCC obtained allowed us to identify a complex yet unique TME of LSCC, which may help identify potential diagnostic biomarkers and therapeutic targets for LSCC.
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Integrative single cell transcriptomic analysis reveals 3p deletion associated tumor microenvironment and chemoresistance in head and neck squamous cell carcinoma.
Head and neck squamous cell carcinoma (HNSCC) remains a prevalent and lethal malignancy, with a five-year survival rate of just 50% for cases of locally advanced disease. Chromosomal aberrations, particularly the deletion of the short arm of chromosome 3 (3p), have been strongly associated with poor prognosis and more aggressive tumor phenotypes. The tumor microenvironment (TME) plays a pivotal role in tumor progression and resistance to therapy. This study aims to elucidate the impact of 3p deletion on the TME, immune cell infiltration, and treatment response in HNSCC, to identify novel therapeutic targets to improve patient outcomes. We analyzed single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and bulk transcriptome data from The Cancer Genome Atlas (TCGA). Pseudo-time trajectory and cell-cell communication analyses were performed with the Monocle and CellChat packages. The Wilcoxon test was used to evaluate the differential gene expression between wild-type (wt) and mutant (mut) groups. Prognostic models were developed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Cox regression analyses to find the genes related to survival, with survival analysis conducted via Kaplan-Meier curves. Gene set enrichment analysis (GSEA) was employed to investigate pathway dysregulation, and immune cell infiltration was assessed using various immune scoring methodologies to explore the differences immune environment. The Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to predict the potential efficacy of immune checkpoint inhibitors. mRNA and protein expression levels of SPP1 were examined by RT-qPCR and Western blotting, while cell proliferation was assessed using the CCK8 assay. The mut group demonstrated significant alterations in cellular composition, characterized by increased endothelial cells and macrophages and decreased fibroblasts and CD8 + T cells, indicative of an immunosuppressive TME. Differential expression analysis revealed downregulation of immune pathways, including antigen processing and presentation, T cell receptor signaling, and B cell receptor signaling pathways in the mut group, along with enhanced metabolic activity in glycolysis and lipid metabolism. The prognostic model identified nine key genes associated with poor survival in HNSCC. The mut group exhibited poorer overall survival and a more immunosuppressive microenvironment compared to the wt group, which correlated with the outcomes observed in high-risk versus low-risk groups. High-risk patients also showed a diminished response to immunotherapy compared to low-risk patients. Additionally, SPP1 emerged as a critical gene associated with chemotherapy resistance and macrophage M2 polarization. This study demonstrates that 3p deletion significantly reshapes the TME, contributing to poor prognosis in HNSCC by fostering an immunosuppressive environment and enhancing chemoresistance. These findings highlight the potential for developing targeted therapies that address the genetic and immunological landscape of HNSCC.
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Single-Cell Atlases as Meta-Analytic Compasses for Developmental Biology: A Case Study Using the Arabidopsis Root.
Plant development arises from the coordinated execution of gene regulatory programs across diverse cell types. While classical genetic and genomic approaches have revealed many of the genes required for plant growth and patterning, these methods often average signals across heterogeneous tissues, thereby obscuring how regulatory programs operate within individual cells. Resolving gene expression at cellular resolution is therefore essential for understanding how developmental decisions are made, integrated, and propagated during organ growth. The Arabidopsis root, with its simple anatomy and invariant cell lineages, provides an ideal system for addressing these questions. Recent advances in single-cell and single-nucleus transcriptomics have enabled the construction of comprehensive cellular atlases that capture gene expression dynamics across cell identities and developmental trajectories. In this Expert Views article, we highlight recent conceptual and technical developments that illustrate how single-cell atlases have transformed studies of root development. We emphasize how these atlases both serve as community resources to inform the interpretation of new datasets, including those generated from mutants and in response to perturbation, as well as provide a platform for meta-analysis to initiate new studies. Using auxin signaling as a meta-analysis case study, we demonstrate how legacy transcriptomic data can be reinterpreted within a cell lineage-resolved framework. Finally, we highlight how spatial transcriptomics and rigorous data-sharing practices will extend cellular atlases across tissues and species, thereby enabling increasingly precise strategies for understanding and engineering plant growth and resilience.
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CART-GPT: A T Cell-Informed AI Linguistic Framework for Interpreting Neurotoxicity and Therapeutic Outcomes in CAR-T Therapy.
Chimeric antigen receptor (CAR) T cell therapy holds transformative potential for hematologic malignancies, yet predicting patient-specific treatment efficacy and neurotoxicity remains a major clinical challenge due to the complex and heterogeneous nature of the infused CAR-T cell populations. Here, we introduce CART-GPT, a transformer-based model fine-tuned on a curated atlas of 1.12 million CAR-T single-cell RNA-seq profiles annotated with clinical outcomes. CART-GPT is the first AI model developed for CAR-T therapy that predicts both treatment response and the risk of immune effector cell-associated neurotoxicity syndrome (ICANS), achieving state-of-the-art performance (AUC ~0.8) and marking a significant advance in the field. The model provides interpretable insights, revealing that neither therapeutic efficacy nor neurotoxicity is driven by individual cell types alone, but by the combined influence of discrete, distinct subsets across diverse T cell states and transcriptional programs. A novel cell aggregation strategy links single-cell predictions to patient-level metrics, enhancing both accuracy and biological relevance. As a contribution to this ever-evolving field, we also release a comprehensive, annotated single-cell CAR-T atlas as a community resource to facilitate future research in immunotherapy. These advances demonstrate the potential of foundation models in single-cell biology to inform precision CAR-T treatment planning and facilitate the rational design of next-generation cell therapies.
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Single-cell-resolution transcriptome map revealed novel genes involved in testicular germ cell progression and somatic cells specification in Chinese tongue sole with sex reversal.
Female-to-male sex reversals (pseudomales) are common in lower vertebrates and have been found in natural populations, which is a concern under rapid changes in environmental conditions. Pseudomales can exhibit altered spermatogenesis. However, the regulatory mechanisms underlying pseudomale spermatogenesis remain unclear. Here, we characterized spermatogenesis in Chinese tongue sole (Cynoglossus semilaevis), a species with genetic and environmental sex determination, based on a high-resolution single-cell RNA-seq atlas of cells derived from the testes of genotypic males and pseudomales. We identified five germ cell types and six somatic cell types and obtained a single-cell atlas of dynamic changes in gene expression during spermatogenesis in Chinese tongue sole, including alterations in pseudomales. We detected decreased levels of Ca2+ signaling pathway-related genes in spermatogonia, insufficient meiotic initiation in spermatocytes, and a malfunction of somatic niche cells in pseudomales. However, a cluster of CaSR genes and MAPK signaling factors were upregulated in undifferentiated spermatogonia of pseudomales. Additionally, we revealed that Z chromosome-specific genes, such as piwil2, dhx37, and ehmt1, were important for spermatogenesis. These results improve our understanding of reproduction after female-to-male sex-reversal and provide new insights into the adaptability of reproductive strategies in lower vertebrates.