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PRDM1 Drives a TIM3+ Macrophage Immunosuppressive Niche via LGALS9 Signaling in Prostate Cancer Progression.
Background: Prostate cancer (PCa) responds poorly to immunotherapy. We investigated the myeloid checkpoint TIM3 (HAVCR2) to define its lineage localization and regulatory logic in the PCa microenvironment. Methods: We integrated stage-resolved public single-cell RNA-seq datasets spanning primary PCa, metastatic hormone-sensitive PCa, and castration-resistant PCa. Myeloid compartments were analyzed via differential expression, regulon inference, and ligand-receptor modeling. Clinical relevance was evaluated in the Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) cohort and independent cohorts using a myeloid TIM3 signature. Mechanistic validation was achieved through PR domain zinc finger protein 1 (PRDM1) chromatin immunoprecipitation followed by Chromatin Immunoprecipitation (ChIP)-qPCR (ChIP-qPCR), TIM3-promoter luciferase assays, and functional perturbation of the galectin 9 (LGALS9)-TIM3 signaling pathway in macrophages differentiated. Results: TIM3 expression was predominantly confined to monocytes/macrophages, indicating TIM3 as a microenvironmental checkpoint in PCa. TIM3_high macrophages formed a Secreted Phosphoprotein 1 (SPP1)-enriched tumor-associated macrophage (TAM) state coupled to chemokine programs and extracellular matrix remodeling. Regulon profiling nominated PR domain zinc finger protein 1 (PRDM1) as an upstream driver; PRDM1 correlated with TIM3. Communication inference further highlighted an LGALS9-TIM3 axis and a C-X-C motif chemokine receptor 4/integrin subunit beta 1 (CXCR4/ITGB1)-associated permissive niche. Recombinant LGALS9 induced TIM3-linked M2-like macrophages polarization and increased CXCR4/ITGB1, which was attenuated by TIM3 blockade. Conclusions: Our results delineate a PRDM1-licensed TIM3_high macrophage program sustained by an LGALS9-TIM3 reinforcement loop and coupled to immunosuppressive and remodeling-associated phenotypes. Targeting TIM3 in the myeloid compartment, alone or in rational combinations, may represent a feasible strategy to reprogram tumor-associated macrophage states in PCa.
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In silico analysis of inner ear development using public whole embryonic body single-cell RNA-sequencing data.
The inner ear comprises four epithelial domains: the cochlea, vestibule, semicircular canals, and endolymphatic duct/sac. These structures are segregated at embryonic day 13.5 (E13.5). However, these four anatomical structures remain undefined at E10.5. Here, we aimed to identify lineage-specific genes in the early developing inner ear using published data obtained from single-cell RNA-sequencing (scRNA-seq) of embryonic mice. We downloaded 5000 single-cell transcriptome data, named 'auditory epithelial trajectory', from the Mouse Organogenesis Cell Atlas. The dataset was supposed to include otic epithelial cells at E9.5-13.5. We projected the 5000 cells onto a two-dimensional space encoding the transcriptional state and visualised the pattern of otic epithelial cell differentiation. We identified 15 clusters, which were annotated as one of the four components of the inner ear epithelium using known genes that characterise the four different tissues. Additionally, we classified 15 clusters into sub-regions of the four inner ear components. By comparing transcriptomes between these 15 clusters, we identified several candidates of lineage-specific genes. Characterising these new candidate genes will help future studies about inner ear development.
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Integrated Single-Nucleus Multi-Omics Atlases Reveal Lineage Plasticity and Regulatory Networks of Luminal Epithelial Cells During Mammary Gland Lactation and Involution.
Dynamic changes in mammary cells are essential for sustaining lactation and maintaining epithelial homeostasis. However, the phenotypic transition process of mammary cells during lactation remains unclear. Here, single-nucleus RNA sequencing (snRNA-seq) of 64 199 cells and single-nucleus chromatin accessibility sequencing (snATAC-seq) of 78 984 cells were generated from the goat mammary gland of dry and lactation stages. A total of 18 cell types were annotated, and spatial transcriptomic analysis confirmed the localization of lactation-related cell types within the mammary tissue. Enrichment analysis of SNP within cell type-specific chromatin accessibility regions revealed strong associations between mammary epithelial cells (MECs) with milk production traits. To further explore the MECs functional diversification during lactation and their differences from the dry stage, four differentiation trajectories from luminal progenitor to luminal mature cells were reconstructed. Lineage-specific gene regulatory networks (GRNs) were constructed by integrating snRNA-seq and snATAC-seq data, and stage-specific signals were identified through cell-cell communications. Finally, to explore the evolutionary conservation and divergence of MECs, cross-species comparative analyses were conducted and revealed MEC differential evolutionary rates, conserved milk-producing subtypes, and lineage-specific populations driving species-specific differences in milk composition. Overall, these findings uncover the coordinated transcriptional and chromatin dynamics that drive mammary epithelial differentiation and functional maintenance during lactation.
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Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Based on EcoTyper Machine Learning Framework Identifies Cell-State-Specific M2 Macrophage Markers Associated with Gastric Cancer Prognosis.
BACKGROUND: Tumor is a complex and dynamic ecosystem formed by the interaction of numerous diverse cells types and the microenvironments they inhabit. Determining how cellular states change and develop distinct cellular communities in response to the tumor microenvironment is critical to understanding cancer progression. Tumour-associated macrophages (TAMs) are an important component of the tumour microenvironment and play a crucial role in cancer progression. This study was designed to identify cell-state-specific M2 macrophage markers associated with gastric cancer (GC) prognosis through integrative analysis of single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data using a machine learning framework named EcoTyper. RESULTS: The results showed that TAMs were classified into M1 macrophages, M2 macrophages, monocytes, undefined macrophages and dendritic cells, with M2 macrophages predominating. EcoTyper assigned macrophages to different cell states and ecotypes. A total of 168 cell-state-specific M2 macrophage markers were obtained by integrative analysis of scRNA-seq and bulk RNA-seq data. These markers could categorize GC patients into two clusters (clusters A and B) with different survival and M2 macrophages infiltration abundance. Cell adhesion molecules, cytokine-cytokine receptor interaction, JAK/STAT pathway, MAPK pathway were significantly enriched in cluster A, which had worse survival and higher M2 macrophages infiltration. CONCLUSION: In conclusion, this study profiles a single-cell atlas of intratumor heterogeneity and defines the cell states and ecotypes of TAMs in GC. Furthermore, we have identified prognostically relevant cell-state-specific M2 macrophage markers. These findings provide novel insights into the tumor ecosystem and cancer progression.
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Automatic quality control of single-cell and single-nucleus RNA-seq using valiDrops.
Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) measures gene expression in individual cells or nuclei enabling comprehensive characterization of cell types and states. However, isolation of cells or nuclei for sxRNA-seq releases contaminating RNA, which can distort biological signals, through, for example, cell damage and transcript leakage. Thus, identifying barcodes containing high-quality cells or nuclei is a critical analytical step in the processing of sxRNA-seq data. Here, we present valiDrops, an automated method to identify high-quality barcodes and flag dead cells. In valiDrops, barcodes are initially filtered using data-adaptive thresholding on community-standard quality metrics, and subsequently, valiDrops uses a novel clustering-based approach to identify barcodes with distinct biological signals. We benchmark valiDrops and show that biological signals from cell types and states are more distinct, easier to separate and more consistent after filtering by valiDrops compared to existing tools. Finally, we show that valiDrops can predict and flag dead cells with high accuracy. This novel classifier can further improve data quality or be used to identify dead cells to interrogate the biology of cell death. Thus, valiDrops is an effective and easy-to-use method to improve data quality and biological interpretation. Our method is openly available as an R package at www.github.com/madsen-lab/valiDrops.
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Single-nucleus RNA-Seq reveals apical-basal polarity as a somatic embryogenesis checkpoint in Picea abies.
Somatic embryogenesis is pivotal for conifer propagation, yet its molecular basis remains poorly understood in gymnosperms. Single-nucleus RNA-seq offers unprecedented resolution for deciphering cell-type-specific transcriptional dynamics during gymnosperm embryogenesis. Here, we constructed a high-resolution transcriptomic atlas of Norway spruce (Picea abies) using high-efficiency and non/low-efficiency proembryogenic masses (HEMs and LEMs) collected before and after somatic embryo induction. Analysis of 55,635 nuclei identified 11 clusters, including somatic embryogenic cells (SCs) responsible for somatic embryo formation. Developmental trajectory analysis revealed a polarity-associated state S6 enriched in SCs, which was abundant in HEMs but nearly absent in LEMs. Key polarity genes, such as ROP-Guanine Exchange Factors, a homolog of PIN-FORMED 1, and PaWOX2, were enriched in the S6 state. Strikingly, overexpression of P. abies AGAMOUS-like 104 (PaAGL104), an S6-enriched transcription factor, induced excessive suspensor growth and apical-basal defects in both HEMs and LEMs embryos. TUNEL assays showed impaired suspensor elimination via suppressed programmed cell death in PaAGL104 overexpressors. Spatial expression analysis using a PaAGL104pro::NLS-mCherry reporter line revealed dynamic expression from ubiquitous to basal-enriched in the embryo proper. This region potentially contains the htube cell", a gymnosperm-specific stem cell crucial for suspensor formation and embryonic polarization. Our study identifies embryonic polarization as a key developmental checkpoint in conifer somatic embryogenesis and provides a high-resolution transcriptomic atlas of gymnosperm callus. These findings advance our understanding of totipotency in spruce and offer practical insights for improving clonal propagation in forestry.
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Single-cell transcriptomic atlas reveals the underlying mechanism of indole-3-acetic acid in protecting against acute cholestatic liver injury.
Cholestasis resulting from disorders of bile secretion and excretion is a serious manifestation of hepatopathy. Indole-3-acetic acid (3-IAA), a biologically active indole derivative from the tryptophan metabolic pathway, has recently attracted considerable attention. However, the therapeutic potential of 3-IAA in acute cholestatic liver injury (ACLI) remains unclear. By integrating transcriptomics and metabolomics, our study revealed that endogenous 3-IAA was downregulated in bile duct ligation induced ACLI rats. Further in vivo animal experiments demonstrated that exogenous 3-IAA administration effectively attenuated the progression of ACLI. Through single-cell RNA sequencing, our study comprehensively mapped the single-cell atlas relating to 3-IAA alleviating ACLI. Mechanistically, 3-IAA may inhibit hepatocyte inflammatory response and promote hepatocyte regeneration by regulating GZMA+GZMK+ effector NK cell and expanding hepatic anti-inflammatory CD59+ macrophages. Taken together, our study revealed the liver protective effect and potential immune mechanism of 3-IAA in ACLI, positioning it as a promising therapeutic candidate for cholestatic liver injury.
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Identification of renal cyst cells of type I Nephronophthisis by single-nucleus RNA sequencing.
Background: Nephronophthisis (NPH) is the most common genetic cause of end-stage renal disease (ESRD) in childhood, and NPHP1 is the major pathogenic gene. Cyst formation at the corticomedullary junction is a pathological feature of NPH, but the mechanism underlying cystogenesis is not well understood. The isolation and identification of cystic cell subpopulation could help to identify their origins and provide vital clues to the mechanisms underlying cystogenesis in NPH. Methods: Single-nucleus RNA sequencing (snRNA-seq) was performed to produce an atlas of NPHP1 renal cells. Kidney samples were collected from WT (Nphp1 +/+) mice and NPHP1 (Nphp1 del2-20/del2-20) model mice. Results: A comprehensive atlas of the renal cellular landscape in NPHP1 was generated, consisting of 14 basic renal cell types as well as a subpopulation of DCT cells that was overrepresented in NPHP1 kidneys compared to WT kidneys. GO analysis revealed significant downregulation of genes associated with tubular development and kidney morphogenesis in this subpopulation. Furthermore, the reconstruction of differentiation trajectories of individual cells within this subpopulation confirmed that a specific group of cells in NPHP1 mice become arrested at an early stage of differentiation and proliferate to form cysts. We demonstrate that Niban1 is a specific molecular marker of cystic cells in both mice and human NPHP1. Conclusion: In summary, we report a novel subpopulation of DCT cells, marked by Niban1, that are classified as cystic cells in the NPHP1 mice kidney. These results offer fresh insights into the cellular and molecular basis of cystogenesis in NPH.
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Identification of a differentiation-related prognostic nomogram based on single-cell RNA sequencing in clear cell renal cell carcinoma.
Renal cell carcinoma (RCC) is a kidney cancer that is originated from the lined proximal convoluted tubule, and its major histological subtype is clear cell RCC (ccRCC). This study aimed to retrospectively analyze single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, to explore the correlation among the evolution of tumor microenvironment (TME), clinical outcomes, and potential immunotherapeutic responses in combination with bulk RNA-seq data from The Cancer Genome Atlas (TCGA) database, and to construct a differentiation-related genes (DRG)-based prognostic risk signature (PRS) and a nomogram to predict the prognosis of ccRCC patients. First, scRNA-seq data of ccRCC samples were systematically analyzed, and three subsets with distinct differentiation trajectories were identified. Then, ccRCC samples from TCGA database were divided into four DRG-based molecular subtypes, and it was revealed that the molecular subtypes were significantly correlated with prognosis, clinicopathological features, TME, and the expression levels of immune checkpoint genes (ICGs). A DRG-based PRS was constructed, and it was an independent prognostic factor, which could well predict the prognosis of ccRCC patients. Finally, we constructed a prognostic nomogram based on the PRS and clinicopathological characteristics, which exhibited a high accuracy and a robust predictive performance. This study highlighted the significance of trajectory differentiation of ccRCC cells and TME evolution in predicting clinical outcomes and potential immunotherapeutic responses of ccRCC patients, and the nomogram provided an intuitive and accurate method for predicting the prognosis of such patients.
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A single-cell gene expression atlas of human follicular aspirates: Identification of leukocyte subpopulations and their paracrine factors.
Leukocytes are in situ regulators critical for ovarian function. However, little is known about leukocyte subpopulations and their interaction with follicular cells in ovulatory follicles, especially in humans. Single-cell RNA sequencing (scRNA-seq) was performed using follicular aspirates obtained from four IVF patients and identified 13 cell groups: one granulosa cell group, one thecal cell group, 10 subsets of leukocytes, and one group of RBC/platelet. RNA velocity analyses on five granulosa cell populations predicted developmental dynamics denoting two projections of differentiation states. The cell type-specific transcriptomic profiling analyses revealed the presence of a diverse array of leukocyte-derived factors that can directly impact granulosa cell function by activating their receptors (e.g., cytokines and secretory ligands) and are involved in tissue remodeling (e.g., MMPs, ADAMs, ADAMTSs, and TIMPs) and angiogenesis (e.g., VEGFs, PGF, FGF, IGF, and THBS1) in ovulatory follicles. Consistent with the findings from the scRNA-seq data, the leukocyte-specific expression of CD68, IL1B, and MMP9 was verified in follicle tissues collected before and at defined hours after hCG administration from regularly cycling women. Collectively, this study demonstrates that this data can be used as an invaluable resource for identifying important leukocyte-derived factors that promote follicular cell function, thereby facilitating ovulation and luteinization in women.