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Human Cell Aging Transcriptome Atlas (HCATA): a single-cell atlas of age-associated transcriptomic alterations across human tissues.
Biological aging is associated with progressively more severe genetic and epigenetic alterations. While these changes are expected to affect the transcriptional profile of cells, the magnitude of that effect is unknown as the aging transcriptome is still poorly understood. Understanding the aging transcriptional landscape will give us greater insight into how cells are affected by and/or respond to the aging process. To facilitate the large-scale exploration of the aging transcriptome, we report the development of the Human Cell Aging Transcriptome Atlas (HCATA). HCATA, contains single-cell RNA-sequencing datasets from 76 publications totaling 92 million cells and 3,475 tissue-level samples across more than 50 tissue types with ages ranging from 0 to 103 years. HCATA includes a genome browser that allows users to interactively explore age-related differential expression, as well as functions to explore related pathways at the tissue and cell-type level. HCATA is publicly accessible at http://hcata-xiaodonglab.org:3304 .
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An integrated single-cell lung cancer atlas reveals distinct fibroblast phenotypes between adenocarcinoma and squamous cell carcinomas.
The tumor microenvironment (TME) not only influences cancer progression but also has been shown to have a significant effect on the prognosis. One of the major TME components is cancer-associated fibroblasts (CAFs), of which several subtypes have been identified in tumor tissues. Although single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for investigating the proportions and composition of cells in tissues, large-scale datasets are needed to analyze small cell populations. Here, we constructed an integrated scRNA-seq dataset for non-small cell lung cancer (NSCLC) by compiling publicly available data and observed differences in TME heterogeneity and cellular composition between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In particular, we identified significant differences in CAF subtypes between LUAD and LUSC. Inflammatory CAFs (iCAFs) were predominantly found in LUAD, whereas myofibroblastic CAFs (mCAFs) were more common in LUSC. A coculture analysis of lung fibroblasts confirmed that LUAD cells induced the iCAF phenotype and, in contrast, that LUSC cells promoted myofibroblastic differentiation. A correlation analysis with the prognosis identified mCAFs as poor prognostic factors in both LUAD and LUSC, but iCAFs were found to be a poor prognostic factor only in LUSC, with the opposite pattern observed in LUAD. This work highlights important considerations regarding the CAF subtype dominance in LUAD and LUSC, which may be related to the prognosis.
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A high-resolution atlas of the brain predicts lineage and birth order underlying neuronal identity.
Gene expression shapes the nervous system at every biological level, from molecular and cellular processes defining neuronal identity and function to systems-level wiring and circuit dynamics underlying behavior. Here, we generate the first high-resolution, single-cell transcriptomic atlas of the adult Drosophila melanogaster central brain by integrating multiple datasets, achieving an unprecedented 10-fold coverage of every neuron in this complex tissue. We show that a neuron's genetic identity overwhelmingly reflects its developmental origin, preserving a genetic address based on both lineage and birth order. We reveal foundational rules linking neurogenesis to transcriptional identity and provide a framework for systematically defining neuronal types. This atlas provides a powerful resource for mapping the cellular substrates of behavior by integrating annotations of hemilineage, cell types/subtypes, and molecular signatures of underlying physiological properties. It lays the groundwork for a long-sought bridge between developmental processes and the functional circuits that give rise to behavior.
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Integrated single-cell and bulk RNA sequencing analysis reveals ACACA as a potential prognostic and immunotherapeutic biomarker across cancers.
BACKGROUND: Acetyl-CoA carboxylase alpha (ACACA), a crucial rate-limiting enzyme governing de novo biosynthesis of fatty acids, drives oncogenic metabolic reprogramming in diverse malignancies. However, the multiomics investigation and immunological implications of ACACA across cancers remain unclear. METHODS: We performed a comprehensive pan-cancer analysis of ACACA via transcriptomic, proteomic, and clinical data from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA) databases. Then, single-cell RNA sequencing acquired from the Gene Expression Omnibus (GEO) database was employed to map the expression pattern of ACACA in the tumor microenvironment (TME). Subsequently, functional validation experiments were conducted in lung cancer and sarcoma cells. RESULTS: High ACACA expression was associated with poor survival in various cancers, particularly those exhibiting dysregulated lipid metabolism. Immune profiling revealed that elevated ACACA expression was associated with low infiltration of CD8+ T cells and activated natural killer (NK) cells. Single-cell analysis of lung adenocarcinoma revealed that ACACA was expressed predominantly within malignant cells and contributed to an immunosuppressive microenvironment through migration inhibitory factor (MIF) signaling and the extracellular matrix (ECM) remodeling pathway. Furthermore, in vitro studies demonstrated that ACACA inhibition suppresses fatty acid synthesis and tumor growth in lung cancer and sarcoma cells. CONCLUSIONS: Our study establishes ACACA as a key metabolic regulator that links lipid metabolism to immune evasion and drug resistance, highlighting its potential as a promising therapeutic target across cancers.
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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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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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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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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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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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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.