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Single-Cell atlas of aqueous humor outflow in glaucomatous Non-Human Primates identified MGP as a regulator of ECM remodeling.
PURPOSE: This study investigated the heterogeneity and molecular alterations of trabecular meshwork (TM) in glaucomatous non-human primates, aiming to identify potential pathogenic genes and signaling pathways involved in glaucoma. METHODS: TM tissues were analyzed using 10x Genomics single-cell RNA sequencing on the Illumina platform. After quality control, dimensionality reduction and clustering were performed. Differentially expressed genes (DEGs) were identified using Seurat and DESeq2. Functional enrichment analyses were conducted via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Protein expression was assessed by Western blotting, mRNA levels by RT-PCR, protein localization and fluorescence intensity by immunofluorescence, and mitochondrial morphology by transmission electron microscopy. RESULTS: We classified the outflow tissue into 10 cell subtypes, and TM cells were further classified into three subtypes: Beam A, Beam B, and JCT. Beam A cells exhibited the most significant proportional changes, and GO analysis indicated their strong association with extracellular matrix regulation. MGP emerged as the most significantly upregulated gene in both the overall TM population and the Beam A subcluster. Dexamethasone (DEX) treatment induced MGP expression in human primary TM cells, while MGP knockdown partially restored Wnt/β-catenin signaling, decreased Wnt5a levels, and reduced ECM deposition. CONCLUSION: This study generated a transcriptional atlas of TM in glaucoma. MGP may contribute to TM dysfunction via the Wnt/β-catenin-Wnt5a-ECM signaling pathway, offering novel insights into potential therapeutic targets for glaucoma intervention.
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A single-nucleus atlas of ligular region uncovers brassinosteroid-driven cell fate transitions controlling leaf angle in maize.
The ligular region is a critical determinant of leaf angle (LA) and plant architecture in maize, yet its developmental mechanisms remain largely unknown. In this study, we generate a comprehensive single-nucleus RNA-seq atlas of the maize ligular region, spanning from leaf primordium through the preligule band (PLB) to the mature stage. By integrating cellular and transcriptomic analyses, we reveal that brassinosteroid (BR) inhibits cell division in the adaxial division zone while promoting elongation in adaxial hypodermal cells. Consequently, BR treatment leads to ectopic emergence of the auricle and ligule. At early stages, GDSL esterases/lipase genes (GELP2/3/6) act as key regulators of emergence, as their disruption causes both ectopic initiation and impaired outgrowth of the ligule and auricle. At later stages, adaxial hypodermal cells serve as pivotal sites for BR-mediated cell elongation and LA expansion, where the transcription factors LIGULELESS1 (LG1) and BRASSINAZOLE-RESISTANT1 (BZR1) cooperatively drive cell elongation to increase LA. Strikingly, comparative snRNA-seq analyses reveal that variation in adaxial cell elongation and subsequent hypodermal lignification explains LA diversity across inbred lines. Together, our findings elucidate the molecular mechanism of BR-driven cell fate transitions in the ligular region and offer potential targets for breeding high-yield maize varieties with ideal plant architecture.
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Single-cell atlas of developing murine adrenal gland reveals relation of Schwann cell precursor signature to neuroblastoma phenotype.
Neuroblastoma is the most common extracranial solid tumor and accounts for ∼10% of pediatric cancer-related deaths. The exact cell of origin has yet to be elucidated, but it is generally accepted that neuroblastoma derives from the neural crest and should thus be considered an embryonal malignancy. About 50% of primary neuroblastoma tumors arise in the adrenal gland. Here, we present an atlas of the developing mouse adrenal gland at a single-cell level. Five main cell cluster groups (medulla, cortex, endothelial, stroma, and immune) make up the mouse adrenal gland during fetal development. The medulla group, which is of neural crest origin, is further divided into seven clusters. Of interest is the Schwann cell precursor ("SCP") and the "neuroblast" cluster, a highly cycling cluster that shares markers with sympathoblasts. The signature of the medullary SCP cluster differentiates neuroblastoma patients based on disease phenotype: The SCP signature score anticorrelates with ALK and MYCN expression, two indicators of poor prognosis. Furthermore, a high SCP signature score is associated with better overall survival rates. This study provides an insight into the developing adrenal gland and introduces the SCP gene signature as being of interest for further research in understanding neuroblastoma phenotype.
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Cross-species consensus atlas of the primate basal ganglia.
The basal ganglia (BG) are conserved brain regions essential for motor control, learning, emotion, and cognition, and are implicated in neurological and psychiatric disease. Yet a unified cross-species taxonomy of BG cell types is lacking, limiting translation of BG circuit mechanisms, interpretation of human genetic risk, and development of cell type-targeted tools. We present a multiomic consensus atlas of 1.8 million nuclei from human, macaque, and marmoset spanning eight BG structures. Integrating cross-species gene expression, open chromatin, and spatial profiling enables definition of conserved and divergent cell types. Alignment to existing mouse and human atlases identifies 61 homologous cell types conserved over 80 million years. We identify a STRd D2 StrioMat Hybrid medium spiny neuron (MSN) type with molecular, electrophysiological, and morphological features that clarify hybrid MSN identities. Comparative cis-regulatory analysis reveals conserved sequence grammars that encode cell identity and inform viral targeting strategies, providing a foundational resource for BG evolution, function, and disease.
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Development and validation of a gene-based classification model for pN2 lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) with pathological ipsilateral mediastinal lymph node (LN) involvement (pN2) exhibits strong biological and clinical heterogeneity. Thus, it is necessary to classify the biomolecular characteristics that lead to the prognostic heterogeneity of pN2-LUAD. METHODS: The clinical characteristics and bulk RNA sequencing (RNA-seq) data of 75 patients with pN2-LUAD obtained from The Cancer Genome Atlas (TCGA) database were collected as the training set. The disease-free survival (DFS) and overall survival (OS) of patients with different molecular classifications were evaluated. Next, differentially expressed genes (DEGs), biology, and immune cell infiltration in the microenvironment were analysed. Finally, DEGs in the pN2-A and pN2-B groups were included using a least absolute shrinkage and selection operator (LASSO) model, and gene signatures were selected for pN2-A/B type classification. The RNA-seq and single-nucleus RNA sequencing (snRNA-seq) data from our center (n=58) and the GSE68465 dataset (n=53) were used as the validation data sets. RESULTS: Patients with pN2 LUAD were classified into two distinct molecular categories (pN2-A and pN2-B) based on transcriptome information, pN2-A and pN2-B represent low-risk and high-risk patients, respectively. The survival analysis showed that pN2-A patients had significantly better DFS (P=0.0162) and OS (P=0.0105) compared to pN2-B patients. Multivariate analysis confirmed that molecular classification was an independent factor affecting the prognosis of pN2 LUAD (P=0.0038, and P=0.0024). Next, we found that compared with pN2-A stage patients, pN2-B stage patients had a higher frequency of canonical oncogenic pathway mutations and enrichments. At the single-cell level, we also found that the increase of endothelial cells and the decrease of cytotoxic T/natural killer (NK) cells led to a worse prognosis for pN2-B patients compared to pN2-A patients. Moreover, we established a reasonable gene prediction model of 18 differentially expressed genes (DEGs) to classify the pN2-A and pN2-B patients. Finally, the key above-mentioned results were confirmed using our data and the GES68645 dataset. CONCLUSIONS: The molecular classification of pN2 LUAD is expected to be a powerful supplement to pN2 substaging. Driver gene status and the immune microenvironment mediate different molecular types of LUAD and provide evidence for individualized treatment strategies.
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Serum levels of iCAF-derived osteoglycin predict favorable outcome in pancreatic cancer.
Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma, the main cellular constituents of which are cancer-associated fibroblasts (CAFs). Stroma-targeting agents have been proposed to improve the poor outcome of current treatments. However, clinical trials using these agents showed disappointing results. Heterogeneity in the PDAC CAF population was recently delineated demonstrating that both tumor-promoting and tumor-suppressive activities co-exist in the stroma. Here, we aimed to identify biomarkers for the CAF population that contribute to a favorable outcome. RNA-sequencing reads from patient-derived xenografts (PDXs) were mapped to the human and mouse genome to allocate the expression of genes to the tumor or stroma. Survival meta-analysis for stromal genes was performed and applied to human protein atlas data to identify circulating biomarkers. The candidate protein was perturbed in co-cultures and assessed in existing and novel single-cell gene expression analysis from control, pancreatitis, pancreatitis-recovered and PDAC mouse models. Serum levels of the candidate biomarker were measured in two independent cohorts totaling 148 PDAC patients and related them to overall survival. Osteoglycin (OGN) was identified as a candidate serum prognostic marker. Single-cell analysis indicated that Ogn is derived from a subgroup of inflammatory CAFs. Ogn-expressing fibroblasts are distinct from resident healthy pancreatic stellate cells and arise during pancreatitis. Serum OGN levels were prognostic for favorable overall survival in two independent PDAC cohorts (HR = 0.47, P = .042 and HR = 0.53, P = .006). Altogether, we conclude that high circulating OGN levels inform on a previously unrecognized subgroup of CAFs and predict favorable outcomes in resectable PDAC.
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Atlas of breast cancer infiltrated B-lymphocytes revealed by paired single-cell RNA-sequencing and antigen receptor profiling.
To gain mechanistic insights into the functions and developmental dynamics of tumor-infiltrated immune cells, especially B-lymphocytes, here we combine single-cell RNA-sequencing and antigen receptor lineage analysis to characterize a large number of triple-negative breast cancer infiltrated immune cells and report a comprehensive atlas of tumor-infiltrated B-lymphocytes. The single-cell transcriptional profiles reveal significant heterogeneity in tumor-infiltrated B-cell subgroups. The single-cell antigen receptor analyses demonstrate that compared with those in peripheral blood, tumor-infiltrated B-cells have more mature and memory B-cell characteristics, higher clonality, more class switching recombination and somatic hypermutations. Combined analyses suggest local differentiation of infiltrated memory B-cells within breast tumors. The B-cell signatures based on the single-cell RNA-sequencing results are significantly associated with improved survival in breast tumor patients. Functional analyses of tumor-infiltrated B-cell populations suggest that mechanistically, B-cell subgroups may contribute to immunosurveillance through various pathways. Further dissection of tumor-infiltrated B-cell populations will provide valuable clues for tumor immunotherapy.
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Single-Cell and Spatial Analysis of Emergent Organoid Platforms.
Organoids have emerged as a promising advancement of the two-dimensional (2D) culture systems to improve studies in organogenesis, drug discovery, precision medicine, and regenerative medicine applications. Organoids can self-organize as three-dimensional (3D) tissues derived from stem cells and patient tissues to resemble organs. This chapter presents growth strategies, molecular screening methods, and emerging issues of the organoid platforms. Single-cell and spatial analysis resolve organoid heterogeneity to obtain information about the structural and molecular cellular states. Culture media diversity and varying lab-to-lab practices have resulted in organoid-to-organoid variability in morphology and cell compositions. An essential resource is an organoid atlas that can catalog protocols and standardize data analysis for different organoid types. Molecular profiling of individual cells in organoids and data organization of the organoid landscape will impact biomedical applications from basic science to translational use.
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Cellular and Transcriptional Landscape of Human Hypoplastic Left Heart Syndrome.
Hypoplastic left heart syndrome (HLHS) is a congenital heart defect characterized by impaired development of the left ventricle, often managed through surgical palliation creating a single ventricle (SV). Failure of the anatomical right ventricle (RV) represents a common complication with high mortality. We used single-nucleus RNA sequencing to generate a map of the pediatric non-failing (NF) and failing (SysHF) SV. Fibroblasts and endocardial cells displayed the greatest transcriptional shifts between NF and SysHF. Notably, activated fibroblasts expanded in SysHF, and endocardial cells in NF demonstrated adaptive transcriptomic shifts absent from controls or SysHF samples. Ligand-target analysis predicted disease-state specific signaling from endocardial cells to fibroblasts: NRG3 signaling in NF and CCN2 signaling in SysHF. In silico perturbation predicted FOS, JUN, and STAT3 as regulators of fibroblast activation and endocardial adaptation. Finally, HLHS data was compared to adult human and murine RV failure to gain insight into shared pathological processes and the suitability of current animal models. These findings provide a comprehensive SV atlas and implicate cell non-autonomous signaling between endocardial cells and fibroblasts as drivers of SV systolic heart failure.
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Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium.
Understanding the normal state of human tissue transcriptome profiles is essential for recognizing tissue disease states and identifying disease markers. Recently, the Human Protein Atlas and the FANTOM5 consortium have each published extensive transcriptome data for human samples using Illumina-sequenced RNA-Seq and Heliscope-sequenced CAGE. Here, we report on the first large-scale complex tissue transcriptome comparison between full-length versus 5'-capped mRNA sequencing data. Overall gene expression correlation was high between the 22 corresponding tissues analyzed (R > 0.8). For genes ubiquitously expressed across all tissues, the two data sets showed high genome-wide correlation (91% agreement), with differences observed for a small number of individual genes indicating the need to update their gene models. Among the identified single-tissue enriched genes, up to 75% showed consensus of 7-fold enrichment in the same tissue in both methods, while another 17% exhibited multiple tissue enrichment and/or high expression variety in the other data set, likely dependent on the cell type proportions included in each tissue sample. Our results show that RNA-Seq and CAGE tissue transcriptome data sets are highly complementary for improving gene model annotations and highlight biological complexities within tissue transcriptomes. Furthermore, integration with image-based protein expression data is highly advantageous for understanding expression specificities for many genes.