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DDR1 as a key prognostic biomarker in non-small cell lung cancer: identification, validation, and potential therapeutic implications.
BACKGROUND: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related death, with a limited response to immune checkpoint inhibitors (ICIs). Discoidin domain receptor 1 (DDR1) is a collagen-binding kinase that is implicated in tumor progression and immune escape, but its role in NSCLC is unclear. This study aimed to clarify the clinical significance and therapeutic potential of DDR1 via bioinformatics, machine learning, in vitro experiments, and clinical sample analysis. MATERIALS AND METHODS: NSCLC patients were stratified by DDR1 expression based on retrospective RNA-seq data from The Cancer Genome Atlas (TCGA); after quality control, 495 lung adenocarcinoma (LUAD) and 481 lung squamous cell carcinoma (LUSC) tumor samples, together with 57 LUAD and 48 LUSC normal samples, were retained for further analysis. The analyses included survival, mutation, immune landscape, drug sensitivity, single-cell heterogeneity, and functional Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, accounting for the heterogeneity among NSCLC subtypes. A machine learning-based 4-gene prognostic model was constructed and externally validated using two independent datasets: GSE30219 (GPL570 platform, 278 NSCLC samples) and GSE41271 (GPL6884 platform, 274 NSCLC samples). The biological functions of DDR1 were further evaluated via in vitro assays and immunohistochemistry (IHC) of clinical samples. RESULTS: High DDR1 expression was correlated with advanced T stage (P<0.05), poor progression-free survival (PFS) (HR = 1.62, P<0.001), and an immunosuppressive microenvironment. Drug sensitivity analysis revealed that high DDR1 expression was associated with reduced sensitivity to methotrexate but increased sensitivity to vinblastine, doxorubicin, cisplatin, and docetaxel, with no significant difference observed for gefitinib. Single-cell heterogeneity analysis revealed that DDR1 was enriched in tumor-associated macrophages and neutrophils. A LASSO and random survival forest (RSF) machine learning algorithm revealed a 4-gene signature (PKP2, DKK1, TEF, and GJB5) with strong prognostic value (C-index=0.728). DDR1 knockdown suppressed cell proliferation, migration, and invasion and induced apoptosis in NSCLC cell lines. IHC of clinical samples confirmed DDR1 overexpression in 55.88% of NSCLC patients. CONCLUSION: Our study demonstrated that DDR1 promotes tumor progression and immune evasion and is frequently overexpressed in NSCLC patients, suggesting that DDR1 is a potential prognostic biomarker and therapeutic target.
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An Optimized Tissue Dissociation Protocol for Single-Cell RNA Sequencing Analysis of Fresh and Cultured Human Skin Biopsies.
We present an optimized dissociation protocol for preparing high-quality skin cell suspensions for in-depth single-cell RNA-sequencing (scRNA-seq) analysis of fresh and cultured human skin. Our protocol enabled the isolation of a consistently high number of highly viable skin cells from small freshly dissociated punch skin biopsies, which we use for scRNA-seq studies. We recapitulated not only the main cell populations of existing single-cell skin atlases, but also identified rare cell populations, such as mast cells. Furthermore, we effectively isolated highly viable single cells from ex vivo cultured skin biopsy fragments and generated a global single-cell map of the explanted human skin. The quality metrics of the generated scRNA-seq datasets were comparable between freshly dissociated and cultured skin. Overall, by enabling efficient cell isolation and comprehensive cell mapping, our skin dissociation-scRNA-seq workflow can greatly facilitate scRNA-seq discoveries across diverse human skin pathologies and ex vivo skin explant experimentations.
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Protocol for reconstructing 2D and 3D peptide atlases of the Ciona cerebral ganglion at single-cell resolution.
The distribution of biomolecules is essential information for understanding biological systems. Here, we present a protocol for 2D and 3D reconstruction of tissue images at the single-cell level by integrating microscopy and mass spectrometry imaging (MSI) data through linear interpolation. We describe steps for sample preparation, MSI, and construction of 2D and 3D single-cell peptide atlases of the cerebral ganglion of Ciona robusta. This approach is also applicable to other animals in which target cells are labeled with endogenous fluorescent proteins. For complete details on the use and execution of this protocol, please refer to Osugi et al.1.
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3DCellAtlas Meristem: a tool for the global cellular annotation of shoot apical meristems.
Modern imaging approaches enable the acquisition of 3D and 4D datasets capturing plant organ development at cellular resolution. Computational analyses of these data enable the digitization and analysis of individual cells. In order to fully harness the information encoded within these datasets, annotation of the cell types within organs may be performed. This enables data points to be placed within the context of their position and identity, and for equivalent cell types to be compared between samples. The shoot apical meristem (SAM) in plants is the apical stem cell niche from which all above ground organs are derived. We developed 3DCellAtlas Meristem which enables the complete cellular annotation of all cells within the SAM with up to 96% accuracy across all cell types in Arabidopsis and 99% accuracy in tomato SAMs. Successive layers of cells are identified along with the central stem cells, boundary regions, and layers within developing primordia. Geometric analyses provide insight into the morphogenetic process that occurs during these developmental processes. Coupling these digital analyses with reporter expression will enable multidimensional analyses to be performed at single cell resolution. This provides a rapid and robust means to perform comprehensive cellular annotation of plant SAMs and digital single cell analyses, including cell geometry and gene expression. This fills a key gap in our ability to analyse and understand complex multicellular biology in the apical plant stem cell niche and paves the way for digital cellular atlases and analyses.
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Focus on mapping the cells of the body.
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PD-L1 Activity Is Associated with Partial EMT and Metabolic Reprogramming in Carcinomas.
Immune evasion and metabolic reprogramming are hallmarks of cancer progression often associated with a poor prognosis and frequently present significant challenges for cancer therapies. Recent studies have highlighted the dynamic interaction between immunosuppression and the dysregulation of energy metabolism in modulating the tumor microenvironment to promote cancer aggressiveness. However, a pan-cancer association among these two hallmarks, and a potent common driver for them-epithelial-mesenchymal transition (EMT)-remains to be done. This meta-analysis across 184 publicly available transcriptomic datasets as well as The Cancer Genome Atlas (TCGA) data reveals that an enhanced PD-L1 activity signature along with other immune checkpoint markers correlate positively with a partial EMT and an elevated glycolysis signature but a reduced OXPHOS signature in many carcinomas. These trends were also recapitulated in single-cell, RNA-seq, time-course EMT induction data across cell lines. Furthermore, across multiple cancer types, concurrent enrichment of glycolysis and PD-L1 results in worse outcomes in terms of overall survival as compared to enrichment for only PD-L1 activity or expression. These results highlight potential functional synergy among these interconnected axes of cellular plasticity in enabling metastasis and multi-drug resistance in cancer.
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An atlas of cortical arealization identifies dynamic molecular signatures.
The human brain is subdivided into distinct anatomical structures, including the neocortex, which in turn encompasses dozens of distinct specialized cortical areas. Early morphogenetic gradients are known to establish early brain regions and cortical areas, but how early patterns result in finer and more discrete spatial differences remains poorly understood1. Here we use single-cell RNA sequencing to profile ten major brain structures and six neocortical areas during peak neurogenesis and early gliogenesis. Within the neocortex, we find that early in the second trimester, a large number of genes are differentially expressed across distinct cortical areas in all cell types, including radial glia, the neural progenitors of the cortex. However, the abundance of areal transcriptomic signatures increases as radial glia differentiate into intermediate progenitor cells and ultimately give rise to excitatory neurons. Using an automated, multiplexed single-molecule fluorescent in situ hybridization approach, we find that laminar gene-expression patterns are highly dynamic across cortical regions. Together, our data suggest that early cortical areal patterning is defined by strong, mutually exclusive frontal and occipital gene-expression signatures, with resulting gradients giving rise to the specification of areas between these two poles throughout successive developmental timepoints.
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Age-determined expression of priming protease TMPRSS2 and localization of SARS-CoV-2 in lung epithelium.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) novel coronavirus 2019 (COVID-19) global pandemic has led to millions of cases and hundreds of thousands of deaths. While older adults appear at high risk for severe disease, hospitalizations and deaths due to SARS-CoV-2 among children have been relatively rare. Integrating single-cell RNA sequencing (scRNA-seq) of developing mouse lung with temporally resolved immunofluorescence in mouse and human lung tissue, we found that expression of SARS-CoV-2 Spike protein primer TMPRSS2 was highest in ciliated cells and type I alveolar epithelial cells (AT1), and TMPRSS2 expression increased with aging in mice and humans. Analysis of autopsy tissue from fatal COVID-19 cases detected SARS-CoV-2 RNA most frequently in ciliated and secretory cells in airway epithelium and AT1 cells in peripheral lung. SARS-CoV-2 RNA was highly colocalized in cells expressing TMPRSS2. Together, these data demonstrate the cellular spectrum infected by SARS-CoV-2 in lung epithelium and suggest that developmental regulation of TMPRSS2 may underlie the relative protection of infants and children from severe respiratory illness.
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Fibroblast Heterogeneity Links Inflammatory Microenvironments to Tissue Remodeling in Chronic Rhinosinusitis.
INTRODUCTION: Chronic rhinosinusitis (CRS) is a heterogeneous inflammatory disorder with distinct endotypes and tissue remodeling. Fibroblasts contribute to extracellular matrix remodeling and immune regulation, but their heterogeneity in CRS remains unclear. METHODS: Public single-cell transcriptomic data from 21 CRS and healthy control samples were integrated with bulk RNA-sequencing data from primary fibroblasts derived from nasal polyps stimulated with phosphate-buffered saline, interferon (IFN)-γ, interleukin (IL)-4, or IL-17A. Fibroblast subsets, pseudotime trajectories, and inferred communication between fibroblasts and immune cells were analyzed. Cytokine-induced signatures were projected onto the fibroblast atlas. A subset of longitudinal RNA-seq data from the COMPASS cohort (NCT05598424) was used to validate predefined candidate marker genes, including IL-4-associated markers of the C8 subset and IL-17A-associated markers of the C5/C10 subsets, during glucocorticoid treatment across V1 (baseline), V2 (after 4 weeks of intranasal corticosteroid treatment), and V3 (after subsequent systemic glucocorticoid therapy). Temporal expression changes were assessed using linear mixed-effects models with V1-V2 and V2-V3 comparisons. RESULTS: Twelve transcriptionally distinct fibroblast subsets (C0-C11) were identified across CRS subtypes. C8 fibroblasts were enriched in eosinophilic CRSwNP and associated with type 2 inflammation-related genes, including CCL26 and POSTN, whereas C5 and C10 were associated with non-eosinophilic CRSwNP- and IL-17A-related inflammatory features. Pseudotime analysis suggested two trajectories from C4 toward C8 and C10, respectively. CellChat revealed bidirectional communication between fibroblasts and immune cell subsets. Cytokine stimulation induced distinct transcriptional responses: IFN-γ mainly induced antigen presentation and interferon response; IL-4 induced contraction- and cytoskeleton-related features; and IL-17A activated IL-17, nuclear factor κB, and tumor necrosis factor signaling pathways. Signature projection linked IL-4-related features mainly to C8 fibroblasts and IL-17A-related features mainly to C5 and C10 fibroblasts. Longitudinal analysis of glucocorticoid-treated patients identified a stable C8-associated transcriptional signature characterized by sustained downregulation of CCL26, POSTN, CISH, and CCL13 across V1-V3 time points. CONCLUSIONS: Fibroblasts in CRS exhibit marked heterogeneity and may contribute to tissue remodeling and immune regulation in response to distinct inflammatory stimuli. The IL-4-associated C8 state and IL-17A-associated C5/C10 states may represent distinct fibroblast states associated with different CRS inflammatory microenvironments. The C8-associated transcriptional module shows stable and sustained suppression under glucocorticoid treatment.
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Multiple pathways of CD34+ cell differentiation during embryogenesis.
CD34 has long been defined as a canonical marker for endothelial progenitors as well as hematopoietic stem cells, implicating its role in vascular development and hematopoiesis. However, the precise developmental hierarchy and lineage potential of CD34+ cells remain controversial. In this study, we integrated inducible genetic lineage tracing techniques, proteomics and single-cell RNA-seq (scRNA-seq) analyses to elucidate the dynamic developmental trajectory of CD34+ cells during various embryonic periods in both humans and mice. Remarkably, our analyses indicated that the progeny of CD34+ cells marked distinct, spatiotemporally restricted progenitor waves with divergent fates, at which point cells adopted endothelial, hematopoietic and fibroblastic fates, respectively. During gastrulation (E6.5-E8.5), an initial wave of CD34+ progenitors predominantly orchestrates vasculogenesis via a Kdr-dependent mechanism. Subsequently, from E9.5 to E14.5, cell cycle activation serves as a molecular switch, facilitating the endothelial-to-hematopoietic transition (EHT) of CD34+ progenitors. Unexpectedly, we identify a wave of CD34+ progenitors in late embryogenesis that gives rise to fibroblasts, distinct from earlier endothelial or hematopoietic lineages. Furthermore, because umbilical cord blood is a valuable source of different circulating stem/progenitor cells, we distinguish circulating endothelial progenitors from fibroblast progenitors in human cord blood by unique molecular signatures, with GFPT2 specifically marking the fibroblast progenitors. Collectively, our study provides a high-resolution spatiotemporal atlas of CD34+ cells during embryogenesis, redefining the temporal shifts of CD34+ cells in cell states and offering a precise framework for manipulating CD34+ cells in regenerative medicine.