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Dynamic tumor microenvironment remodeling from laryngeal leukoplakia to carcinoma revealed by single-cell transcriptomics.
Laryngeal leukoplakia represents the most frequent precancerous lesion in laryngeal carcinogenesis, yet its transformation mechanisms remain elusive. By performing scRNA-seq on ten clinical specimens (five leukoplakia lesions across pathological stages, four early carcinomas, and one control), we established the first single-cell atlas of this malignant progression. Computational analysis revealed dynamic microenvironmental shifts dominated by epithelial cells, fibroblasts, and mononuclear phagocytes. We identified two critical epithelial subpopulations: Epi_4 (tumor-like cells), a high-grade dysplasia-specific subpopulation with high malignant potential, and Epi_5 (tumor cells) in carcinoma, which carries a favorable prognostic gene signature (Module 3). Furthermore, Epi_4 showed preferential communication with cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs) via the JAG1-NOTCH4 and CXCL5-CXCR1 axes, suggesting actionable therapeutic targets. We also observed the progressive activation of genes involved in redox processes (NQO1, GSTM3, UCHL1, NTRK2) via the KEAP1-NRF2 pathway. This work systematically characterizes the cellular and molecular landscape during laryngeal leukoplakia malignant transformation, providing a framework for future mechanistic studies and early detection strategies.
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Deciphering Tumour Microenvironment of Liver Cancer through Deconvolution of Bulk RNA-Seq Data with Single-Cell Atlas.
Liver cancers give rise to a heavy burden on healthcare worldwide. Understanding the tumour microenvironment (TME) underpins the development of precision therapy. Single-cell RNA sequencing (scRNA-seq) technology has generated high-quality cell atlases of the TME, but its wider application faces enormous costs for various clinical circumstances. Fortunately, a variety of deconvolution algorithms can instead repurpose bulk RNA-seq data, alleviating the need for generating scRNA-seq datasets. In this study, we reviewed major public omics databases for relevance in this study and utilised eight RNA-seqs and one microarray dataset from clinical studies. To decipher the TME of liver cancer, we estimated the fractions of liver cell components by deconvoluting the samples with Cibersortx using three reference scRNA-seq atlases. We also confirmed that Cibersortx can accurately deconvolute cell types/subtypes of interest. Compared with non-tumorous liver, liver cancers showed multiple decreased cell types forming normal liver microarchitecture, as well as elevated cell types involved in fibrogenesis, abnormal angiogenesis, and disturbed immune responses. Survival analysis shows that the fractions of five cell types/subtypes significantly correlated with patient outcomes, indicating potential therapeutic targets. Therefore, deconvolution of bulk RNA-seq data with scRNA-seq atlas references can be a useful tool to help understand the TME.
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Deciphering the gonadal cell atlas of Monopterus albus and cell fate during sex reversal based on single-cell RNA sequencing.
BACKGROUND: The Monopterus albus serves as a unique model for studying sex reversal, transitioning naturally from female to male. However, the origins of male germline stem cells (GSCs) and the roles of somatic cells during sex reversal remain poorly understood. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on ovarian, ovotestis, and testicular tissues to construct a gonadal cell atlas. RNA fluorescence in situ hybridization (RNA-FISH) validated cell subpopulations. RESULTS: Cell types of germ cells and somatic cells in gonads were identified, and their differentiation trajectories during sex reversal were depicted. Our results show that GSCswdr17+tep1- in the ovaries possess bipotential differentiation capacity and can transform into GSCswdr17+ tep1+ with the capability to differentiating into sperm during sex reversal. Two theca cell subpopulations cooperate to synthesize steroid precursors in ovaries, with Leydig cells in testes likely originating from theca cell transitions. Proliferative gdf9+ follicle cells promoted folliculogenesis and persisted in male gonads with reduced hsd17b1 expression. Stromal heterogen-eity analysis revealed bmp4+ mesenchymal stem cells (MSCsbmp4+) as potential precursors for Sertoli cells in testes. CONCLUSIONS: This study provides a comprehensive cellular roadmap of gonadal cell dynamics during sex reversal in Monopterus albus. Our findings unveil the molecular mechanisms underlying germline and somatic cell fate determination, offering novel insights into vertebrate sex reversal and potential therapeutic strategies for disorders of sex development (DSD).
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Discovery of GJC1 as a prognostic biomarker in glioma cells: insights into its cell-cycle relationship and differential expression in non-neuronal cells.
BACKGROUND: Gliomas, originating from the most common non-neuronal cells in the brain (glial cells), are the most common brain tumors and are associated with high mortality and poor prognosis. Glioma cells exhibit a tendency to disrupt normal cell-cycle regulation, leading to abnormal proliferation and malignant growth. This study investigated the predictive potential of GJC1 in gliomas and explored its relationship with the cell cycle. METHODS: Retrospective analysis of RNA-seq and single-cell sequencing data was conducted using the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. The differential expression of GJC1 in gliomas with various pathological features and in different non-neuronal cell groups was analyzed. Functional data were examined using gene set variation analysis (GSVA). Furthermore, CellMiner was used to evaluate the relationship between GJC1 expression and predicted treatment response across these databases. RESULTS: GJC1 expression was enriched in high-grade gliomas and 1p/19q non-codeletion gliomas. GJC1 enrichment was observed in classical and mesenchymal subtypes within the TCGA glioma subtype group. In single-cell subgroup analysis, GJC1 expression was higher in glioma tissues compared to other non-neuronal cells. Additionally, the TCGA classical subtype of glioma cells exhibited more GJC1 expression than the other subgroups. GJC1 emerged as an independent prognostic factor for overall survival in glioma. GSVA unveiled potential mechanisms by which GJC1 may impact cell-cycle regulation in glioma. Finally, a significant correlation was observed between GJC1 expression and the sensitivity of multiple anti-cancer drugs. CONCLUSION: These findings confirmed GJC1 as a novel biomarker and provided insights into the differential gene expression in non-neuronal cells and the impact of the cell cycle on gliomas. Consequently, GJC1 may be used to predict glioma prognosis and has potential therapeutic value.
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Single-cell RNA sequencing defines developmental progression and reproductive transitions of Pneumocystis carinii.
UNLABELLED: Pneumocystis species are host-obligate fungal pathogens that cause severe pneumonia in immunocompromised individuals. Despite their clinical importance, their life cycle remains poorly understood, in part because Pneumocystis depends on the host environment for most nutrients and requires sexual reproduction for survival, which occurs exclusively in vivo. This study presents the first single-cell RNA sequencing (scRNA-seq) atlas of Pneumocystis carinii, generated from isolated organisms recovered from the bronchoalveolar lavage fluid of infected rats to map the life cycle of P. carinii. Transcriptomes from 87,716 cells were analyzed using the 10× Genomics platform, revealing 13 transcriptionally distinct clusters representing key developmental stages, including biosynthetically active trophic forms, mating-competent intermediates, and asci undergoing sporulation. These states were characterized by expression of MAPK signaling components, β-glucan-modifying enzymes, and spore-associated genes, respectively. The scRNA-seq data support previous evidence that these host-obligate fungi undergo sexual reproduction and provide new insights into the gene expression patterns associated with different life cycle phases. Biomarkers associated with ascus formation identified by scRNA-seq were validated by RT-qPCR, showing decreased expression levels in ascus-depleted populations treated with anidulafungin, a drug that halts ascus formation. More broadly, this approach provides a strategy for studying the full life cycles of fungal pathogens that cannot be continuously cultured. IMPORTANCE: Pneumocystis species (spp.) are clinically significant fungal pathogens that cannot be sustainably cultured in vitro due to their host-obligate nature. This longstanding limitation has impeded progress in understanding their life cycle and identifying therapeutic vulnerabilities. Here, we apply scRNA-seq to P. carinii isolated directly from infected rat lungs, generating the first transcriptional map of its developmental progression. Our results define discrete gene expression states associated with trophic growth, mating activation, and ascus formation and provide transcriptional evidence for a structured life cycle, clarifying key developmental transitions and identifying potential regulatory targets for therapeutic intervention. Importantly, this study demonstrates that scRNA-seq can resolve the developmental biology of host-restricted fungal pathogens that cannot be cultured in vitro. This approach offers a generalizable framework for investigating other unculturable or obligate microbial pathogens directly within their native host environments, where traditional experimental tools are limited.
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Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps.
Colorectal cancers (CRCs) arise from precursor polyps whose cellular origins, molecular heterogeneity, and immunogenic potential may reveal diagnostic and therapeutic insights when analyzed at high resolution. We present a single-cell transcriptomic and imaging atlas of the two most common human colorectal polyps, conventional adenomas and serrated polyps, and their resulting CRC counterparts. Integrative analysis of 128 datasets from 62 participants reveals adenomas arise from WNT-driven expansion of stem cells, while serrated polyps derive from differentiated cells through gastric metaplasia. Metaplasia-associated damage is coupled to a cytotoxic immune microenvironment preceding hypermutation, driven partly by antigen-presentation differences associated with tumor cell-differentiation status. Microsatellite unstable CRCs contain distinct non-metaplastic regions where tumor cells acquire stem cell properties and cytotoxic immune cells are depleted. Our multi-omic atlas provides insights into malignant progression of colorectal polyps and their microenvironment, serving as a framework for precision surveillance and prevention of CRC.
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R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue.
Breast cancer is a common and highly heterogeneous disease. Understanding cellular diversity in the mammary gland and its surrounding micro-environment across different states can provide insight into cancer development in the human breast. Recently, we published a large-scale single-cell RNA expression atlas of the human breast spanning normal, preneoplastic and tumorigenic states. Single-cell expression profiles of nearly 430,000 cells were obtained from 69 distinct surgical tissue specimens from 55 patients. This article extends the study by providing quality filtering thresholds, downstream processed R data objects, complete cell annotation and R code to reproduce all the analyses. Data quality assessment measures are presented and details are provided for all the bioinformatic analyses that produced results described in the study.
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HemaScope: A Tool for Analyzing Single-cell and Spatial Transcriptomics Data of Hematopoietic Cells.
Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues. These two techniques are highly complementary, with scRNA-seq offering single-cell resolution and ST retaining spatial information. However, there is an urgent demand for well-organized and user-friendly toolkits capable of handling single-cell and spatial information. Here, we present HemaScope, a specialized bioinformatics toolkit featuring modular designs to analyze scRNA-seq and ST data generated from hematopoietic cells. It enables users to perform quality control, basic analysis, cell atlas construction, cellular heterogeneity exploration, and dynamical examination on scRNA-seq data. Also, it can perform spatial analysis and microenvironment analysis on ST data. Meanwhile, HemaScope takes into consideration hematopoietic cell-specific features, including lineage affiliation evaluation, cell cycle prediction, and marker gene collection. To enhance the user experience, we have deployed the toolkit in user-friendly forms: HemaScopeR (an R package), HemaScopeCloud (a web server), HemaScopeDocker (a Docker image), and HemaScopeShiny (a graphical interface). In case studies, we employed it to construct a cell atlas of human bone marrow, analyze age-related changes, and identify acute myeloid leukemia cells in mice. Moreover, we characterized the microenvironments in angioimmunoblastic T cell lymphoma and primary central nervous system lymphoma, elucidating tumor boundaries. HemaScope is freely available at https://zhenyiwangthu.github.io/HemaScope_Tutorial/.
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Ploidy inference from single-cell data: application to human and mouse cell atlases.
Ploidy is relevant to numerous biological phenomena, including development, metabolism, and tissue regeneration. Single-cell RNA-seq and other omics studies are revolutionizing our understanding of biology, yet they have largely overlooked ploidy. This is likely due to the additional assay step required for ploidy measurement. Here, we developed a statistical method to infer ploidy from single-cell ATAC-seq data, addressing this gap. When applied to data from human and mouse cell atlases, our method enabled systematic detection of polyploidy across diverse cell types. This method allows for the integration of ploidy analysis into single-cell studies. Additionally, this method can be adapted to detect the proliferating stage in the cell cycle and copy number variations in cancer cells. The software is implemented as the scPloidy package of the R software and is freely available from CRAN.
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Single-Cell RNA Sequencing of Rabbit Sclera at Different Developmental Stages: Unveiling Scleral Cells Atlas and the Heterogeneity of Fibroblasts.
PURPOSE: This study aims to construct a single-cell transcriptomic atlas of the developing rabbit sclera to elucidate fibroblast heterogeneity, differentiation trajectories, matrisome expression patterns, and intercellular communication, while revealing conserved molecular features of scleral cells through cross-species analysis. METHODS: Single-cell RNA sequencing (scRNA-seq) was performed on scleral tissues from New Zealand rabbits at embryonic day 25 (E25) and postnatal days 7 (P7), 21 (P21), and 180 (P180). Libraries were prepared using the DNBelab C Series Kit and sequenced on the BGISEQ-2000 platform. Sequencing reads were aligned to the OryCun2.0 genome using STAR, and unique molecular identifier (UMI) count matrices were generated with PISA. Data preprocessing was conducted using Seurat. Fibroblast lineage differentiation was analyzed via VIA, intercellular communication via CellChat, matrisome expression patterns via AUCell, and cross-species analyses via CACIMAR and hdWGCNA. RESULTS: We identified 7 major cell types and 15 subpopulations, with fibroblasts dominating the cellular landscape. Distinct fibroblast subtypes exhibited varied expression profiles and functions: KERAlow SPARCL1⁺ fibroblasts showed stem/progenitor-like features, while KERAhigh myocilin (MYOC)⁺ fibroblasts displayed senescence-associated phenotypes. Matrisome analysis revealed dynamic alterations in collagen and extracellular matrix (ECM)-related genes, and intercellular communication analysis highlighted complex signaling networks, particularly the MDK/PTN pathway. Cross-species comparisons demonstrated high conservation of fibroblasts between rabbit and human sclera, identifying four conserved co-expression modules. CONCLUSIONS: This study presents the first single-cell atlas of rabbit scleral development, unveiling fibroblast heterogeneity, ECM remodeling mechanisms, and cross-species conserved features. These findings enhance our understanding of scleral biology and provide valuable insights for future research on ocular development and associated diseases, including myopia.