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Machine Learning Identifies Key Gene Markers Related to Fetal Retina Development at Single-Cell Transcription Level.
PURPOSE: The retina is part of the central nervous system, and its function is vision. During the embryonic development of the fetus, it diversifies the seven major types of cells from a retinal progenitor cell. The purpose of this study is to investigate essential features that are necessary for the development of the fetal retina. METHODS: We generated a comprehensive single-cell transcriptional atlas of the human retina by leveraging datasets from the Chan Zuckerberg Initiative Single-Cell Biology collection of human fetal retinas. The eight critical types of retinal cells were investigated, including amacrine, bipolar, cone, horizontal, Müller glia, retinal ganglion, rod, and retinal progenitor cells. We evaluated a total of 36,503 gene features across three developmental stages (early, middle, and late) for each cell type. Using seven feature ranking algorithms and incremental feature selection method, we identified key gene features, constructed efficient classifiers and classification rules. RESULTS: For amacrine cells, RELN and DAB1 are critical; for bipolar cells, ANK3 and RIMS2; for cone cells, PDE6H and FRMPD2; for horizontal cells, NFIA; for Müller glial cells, WIF1 and TF; for retinal ganglion cells, IL1RAPL2 and PCP4; for rod cells, RIMS2 and NRG1; and for retinal progenitor cells, BTG1. These gene features bring into focus the pattern of gene regulation and developmental pathways of the retinal cells for deeper insights into retinal development. CONCLUSIONS: This study explored molecular features related to the development of the fetal retina and their potential roles in certain pathways, which may provide novel insights into retinal development and contribute to a better understanding of other retinal diseases.
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Decoding transcriptional identity in developing human sensory neurons and organoid modeling.
Dorsal root ganglia (DRGs) play a crucial role in processing sensory information, making it essential to understand their development. Here, we construct a single-cell spatiotemporal transcriptomic atlas of human embryonic DRG. This atlas reveals the diversity of cell types and highlights the extrinsic signaling cascades and intrinsic regulatory hierarchies that guide cell fate decisions, including neuronal/glial lineage restriction, sensory neuron differentiation and specification, and the formation of neuron-satellite glial cell (SGC) units. Additionally, we identify a human-enriched NTRK3+/DCC+ nociceptor subtype, which is involved in multimodal nociceptive processing. Mimicking the programmed activation of signaling pathways in vivo, we successfully establish functional human DRG organoids and underscore the critical roles of transcriptional regulators in the fate commitment of unspecialized sensory neurons (uSNs). Overall, our research elucidates the multilevel signaling pathways and transcription factor (TF) regulatory hierarchies that underpin the diversity of somatosensory neurons, emphasizing the phenotypic distinctions in human nociceptor subtypes.
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Novel PAP-targeted CAR-T therapy enhances antitumor efficacy through CoupledCAR approach.
BACKGROUND: The challenges that remain in the treatment of solid tumors with chimeric antigen receptor (CAR)-T cells include limited solid tumor-specific targets and poor CAR-T cell expansion and function due to limited availability of solid tumor antigens outside the tumor microenvironment. Prostate cancer is the second most common cancer among men worldwide. Current CAR-T therapies for prostate cancer lack specific targets, posing safety risks. To overcome these problems, we identified prostatic acid phosphatase (PAP, also known as ACPP or ACP3) as a feasible CAR-T target for prostate cancer and developed CoupledCAR, a novel approach for expanding tumor-targeting CAR-T cells without tumor antigens. METHODS: We analyzed the expression of PAP from The Cancer Genome Atlas database and validated its expression in normal and cancer tissues through immunohistochemistry staining. To generate anti-PAP specific antibodies, we screened the human single-chain antibody library using transmembrane PAP-His antigen and selected antibodies based on their binding ability and specificity. We constructed PAP-targeted CAR and evaluated their antitumor efficacy both in vitro and in vivo. We validated the function of PAP CoupledCAR in both in vitro and in vivo experiments, and further analyzed its mechanism using single-cell RNA sequencing (scRNA-Seq). RESULTS: PAP was specifically expressed in prostate epithelial and prostate cancer cells, with no expression in other tissues. Seven single-chain variable fragments were screened from the human single-chain antibody library, with S5D1 showing the highest binding ability for the PAP. PAP CAR-T cells demonstrated strong antitumor efficacy both in vitro and in vivo. Furthermore, the CoupledCAR system significantly expanded PAP CAR-T cells, promoting memory-like status, reducing exhaustion, and enhancing their antitumor efficacy. The scRNA-Seq demonstrated that the expansion of PAP CAR-T cells in the CoupledCAR system is mediated by costimulatory signals and cytokine signals, rather than T-cell receptor signals. CONCLUSIONS: Our study is the first to demonstrate that PAP is a specific target for CAR-T therapy in prostate cancer, both in vitro and in vivo. We developed the CoupledCAR platform technology for solid tumor CAR-T cell therapy, enabling the expansion of tumor-targeting CAR-T cells without requiring tumor antigens and thereby enhancing their functionality against solid tumors.
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Changes in Nucleus Pulposus Cell Atlas and the Role of SPP1 During Intervertebral Disc Degeneration: Single-Cell Sequencing Analysis.
BACKGROUND: The nucleus pulposus (NP) plays a central role in the pathogenesis of intervertebral disc degeneration (IVDD); however, its internal cellular heterogeneity and molecular mechanisms have not yet been elucidated. METHODS: ScRNA-seq was used to evaluate the structure of the NP at different degenerative stages in the same individual with IVDD. Unsupervised clustering of cells based on gene expression profiles was performed using the Seurat package and passed to uniform manifold approximation and projection (UMAP) for cluster visualization. A rat disc degeneration model and an in vitro human NP cell degeneration model were established to validate the scRNA-seq identification results. RESULTS: Six NP subclusters and immune cells were identified and their distribution and functional differences between healthy and degenerative states were investigated. Immune cells were present only in degenerated NPs and may trigger NP degeneration. Cellular communication within the NP was altered by the intervention of immune cells. Secreted phosphorylated protein 1 (SPP1), secreted by immune cells, plays a major role and is a key molecule in NP degeneration. The results of in vivo animal experiments and in vitro cellular experiments showed that the expression of SPP1 was increased in degenerating NPs. High expression of SPP1 promoted NP degeneration, whereas inhibition of its expression attenuated degeneration. CONCLUSIONS: Cytoarchitectural changes in NP were revealed by scRNA-seq. SPP1 is involved in the pathogenesis of disc degeneration and may be a new target for intervention in IVDD.
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Single-cell genomics reveals transcriptional heterogeneity and cellular crosstalk in salivary gland fibrosis.
BACKGROUND/PURPOSE: Salivary gland fibrosis (SGF) is a prevalent condition associated with various pathological states. However, a detailed understanding of the single-cell transcriptional profiles and cell-cell communication networks in this context remains elusive. Therefore, we aimed to unveil the gene expression profiles and intercellular communication patterns in SGF. MATERIALS AND METHODS: We established fibrosis models of the submandibular gland (SMG) and generated a detailed single-cell transcriptomic atlas to investigate cellular heterogeneity and communication patterns. Utilizing CellChat, we dissected the intercellular dialogues within these fibrotic environments. RESULTS: The analysis distinguished fifteen distinct cellular clusters, highlighting significant heterogeneity among fibroblasts in fibrotic SMGs compared to their healthy counterparts. This heterogeneity was linked to TGF-β signaling, collagen fibril assembly, and extracellular matrix organization. CellChat analyses uncovered enhanced cell-cell interactions, notably between fibroblasts and endothelial cells (ECs) via the Gas6-Axl signaling axis. Additionally, our data indicated the activation of cell adhesion molecules and Rap1 pathways in ECs within the fibrotic SMG microenvironment. CONCLUSION: This study offers an in-depth single-cell resolution perspective on the cellular and molecular changes in SMG fibrosis, identifying new potential therapeutic targets for this condition.
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Liver in infections: a single-cell and spatial transcriptomics perspective.
The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.
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Single-cell RNA landscape of cell heterogeneity and immune microenvironment in ligation-induced vascular remodeling in rat.
BACKGROUND AND AIMS: Vascular remodeling is a common pathological basis for cardiovascular diseases. Although both immune and non-immune cells have been suggested to contribute to this process, the complex cellular heterogeneity and intercellular interactions remain largely uncharacterized. METHODS AND RESULTS: In this study, we simulated early and late vascular remodeling by ligating the rat carotid artery for 1 week and 4 weeks, respectively. Using single-cell RNA-sequencing, we characterized gene expression signatures and driver signals of major cell types involved in vascular remodeling. Focused analysis revealed a novel sub-population of Selenbp1hi smooth muscle cells (SMCs) associated with vascular remodeling. Results of intercellular communication analyses predicted several ligand-receptor pairs between immune cells with SMCs and endothelial cells (ECs), implicating SMCs apoptosis and repair, ECs aging and inflammatory responses. CONCLUSIONS: We present a comprehensive single-cell atlas of vascular cells in early and late stages of ligated rat carotid artery, providing valuable insights into the understanding of the initiation and progression of vascular remodeling.
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Machine learning-based integration of CD8 T cell-related gene signatures for comprehensive prognostic assessment in lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) stands as the most prevalent histological subtype of lung cancer, exhibiting heterogeneity in outcomes and diverse responses to therapy. CD8 T cells are consistently present throughout all stages of tumor development and play a pivotal role within the tumor microenvironment (TME). Our objective was to investigate the expression profiles of CD8 T cell marker genes, establish a prognostic risk model based on these genes in LUAD, and explore its relationship with immunotherapy response. METHODS: By leveraging the expression data and clinical records from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, we identified 23 consensus prognostic genes. Employing ten machine-learning algorithms, we generated 101 combinations, ultimately selecting the optimal algorithm to construct an artificial intelligence-derived prognostic signature named riskScore. This selection was based on the average concordance index (C-index) across three testing cohorts. RESULTS: RiskScore emerged as an independent risk factor for overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS) in LUAD. Notably, riskScore exhibited notably superior predictive accuracy compared to traditional clinical variables. Furthermore, we observed a positive correlation between the high-risk riskScore group and tumor-promoting biological functions, lower tumor mutational burden (TMB), lower neoantigen (NEO) load, and lower microsatellite instability (MSI) scores, as well as reduced immune cell infiltration and an increased probability of immune evasion within the TME. Of significance, the immunophenoscore (IPS) score displayed significant differences among risk subgroups, and riskScore effectively stratified patients in the IMvigor210 and GSE135222 immunotherapy cohort based on their survival outcomes. Additionally, we identified potential drugs that could target specific risk subgroups. CONCLUSIONS: In summary, riskScore demonstrates its potential as a robust and promising tool for guiding clinical management and tailoring individualized treatments for LUAD patients.
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FOXP2+ Chief Cells and CXCL14+ Fibroblasts Drive Fibrotic Remodeling in Carotid Body Tumors.
Carotid body tumors (CBTs) exhibit pronounced clinical heterogeneity, particularly in fibrotic progression, yet the underlying cellular mechanisms remain poorly defined. Here, we performed single-cell RNA sequencing on 64,944 cells from three fibrotic CBT (FCBT) and three non-fibrotic CBT (nFCBT) specimens to construct a high-resolution cellular atlas of CBT fibrosis. Integrated analyses revealed that FCBTs are distinguished by a FOXP2+ chief cell subpopulation exhibiting a metabolic shift toward mitochondrial respiration and enhanced MIF signaling, which may facilitate macrophage recruitment. Endothelial cells expanded in FCBTs and acquired pro-angiogenic signatures driven by macrophage-derived CXCL signaling. Notably, CXCL14+ fibroblasts emerged as the principal effectors of extracellular matrix deposition, with lineage inference suggesting their origin from smooth muscle cells. Immune cells, including T/NK and mast cells, further modulated the fibrotic niche through cytokine interactions. This study provides the first comprehensive single-cell dissection of CBT fibrosis, identifies FOXP2+ chief cells as initiators of stromal remodeling, and highlights CXCL14+ fibroblasts as key matrix-producing effectors. These findings nominate FOXP2 and CXCL14 as potential therapeutic targets for mitigating fibrosis in CBT patients.
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Dysregulation of neuroprotective astrocytes, a spectrum of microglial activation states, and altered hippocampal neurogenesis are revealed by single-cell RNA sequencing in prion disease.
Prion diseases are neurodegenerative disorders with long asymptomatic incubation periods, followed by a rapid progression of cognitive and functional decline culminating in death. The complexity of intercellular interactions in the brain is challenging to unravel and the basis of disease pathobiology remains poorly understood. In this study, we employed single cell RNA sequencing (scRNAseq) to produce an atlas of 147,536 single cell transcriptomes from cortex and hippocampus of mice infected with prions and showing clinical signs. We identified transcriptionally distinct populations and sub-populations of all the major brain cell-types. Disease-related transcription was highly specific to not only overarching cell-types, but also to sub-populations of glia and neurons. Most striking was an apparent decrease in relative frequency of astrocytes expressing genes that are required for brain homeostasis such as lipid synthesis, glutamate clearance, synaptic modulation and regulation of blood flow. Additionally, we described a spectrum of microglial activation states that suggest delineation of phagocytic and neuroinflammatory functions in different cell subsets. Differential responses of immature and mature neuron populations were also observed, alongside abnormal hippocampal neurogenesis. Our scRNAseq library provides a new layer of knowledge on single cell gene expression in prion disease, and is a basis for a more detailed understanding of cellular interplay that leads to neurodegeneration.