Your browser does not allow saving data (e.g. private mode): bookmarks will be lost when the tab closes.
Search PubMed
Keywords, author, journal, years — results from PubMed, abstracts with Russian translation, bookmarks in your browser.
Found: 4 915
Page 137 of 492-
A versatile and efficient method to isolate nuclei from low-input cryopreserved tissues for single-nuclei transcriptomics.
Clinical samples are vital for understanding diseases, but their scarcity requires refined research methods. Emerging single-cell technologies offer detailed views of tissue heterogeneity but need sufficient fully characterized tissues. We developed an optimized single-nuclei RNA sequencing (snRNA-seq) protocol to extract nuclei from just 15 mg of cryopreserved human tissue. Applied to four cancer tissues (brain, bladder, lung, prostate), it profiled 1550-7468 nuclei per tissue, revealing heterogeneity comparable to public single-cell atlases. This method enhances the use and sharing of rare, cryopreserved biospecimens, supporting research where sample quantity is limited and full tissue characterization is needed.
-
Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.
BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.
-
Single-cell RNA sequencing reveals palmitoylation-driven cellular heterogeneity and prognostic biomarkers in lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) is marked by significant variation within tumor cells and continues to be a major global cause of cancer deaths. Palmitoylation is a dynamic lipid-based modification that occurs after protein synthesis and influences the behavior and lifespan of various cancer-related proteins. However, its role in shaping cellular complexity and predicting outcomes in LUAD patients is not yet fully clarified. METHODS: We examined single-cell RNA sequencing datasets from LUAD samples to identify distinct malignant cell groups. Palmitoylation-related gene activity was estimated using GSVA and ssGSEA techniques. To further define cellular characteristics, we applied copy number variation mapping, pseudotime progression modeling, transcription factor regulatory scoring, and cell-cell interaction analyses. A 12-gene risk model was developed using marker genes from the cluster (C1) with the most prominent palmitoylation pattern. This model was trained on The Cancer Genome Atlas (TCGA) dataset and confirmed using separate GEO datasets. To evaluate tumor immune context, we analyzed immune cell presence and tumor mutational burden across different risk levels. Laboratory experiments involving both upregulation and silencing of aspartate beta-hydroxylase (ASPH) in LUAD cell cultures were conducted to validate its biological significance. RESULTS: We identified six tumor cell subsets (C0 to C5), with cluster C1 showing peak palmitoylation levels, distinct genomic alterations, and stronger communication with stromal and immune cells. The 12-gene model effectively categorized LUAD patients into high- and low-risk profiles, showing marked survival differences (p < 0.001) and strong performance in time-dependent ROC analysis. Patients in the high-risk group had increased tumor mutational burden and a more immunosuppressive tumor environment. Laboratory findings revealed that raising ASPH expression promoted cell growth, motility, and epithelial-mesenchymal transition. In contrast, reducing ASPH levels triggered cell death and decreased invasiveness. CONCLUSIONS: Our single-cell analysis focused on palmitoylation reveals new dimensions of tumor diversity in LUAD and establishes a validated 12-gene risk signature. Functional studies highlight ASPH as a promising candidate for therapeutic targeting. These results deepen our understanding of palmitoylation-associated pathways and present a foundation for both outcome prediction and precision-based treatment strategies in LUAD.
-
An organ-wide spatiotemporal transcriptomic and cellular atlas of the regenerating zebrafish heart.
Adult zebrafish robustly regenerate injured hearts through a complex orchestration of molecular and cellular activities. However, this remarkable process, which is largely non-existent in humans, remains incompletely understood. Here, we utilize integrated spatial transcriptomics (Stereo-seq) and single-cell RNA-sequencing (scRNA-seq) to generate a spatially-resolved molecular and cellular atlas of regenerating zebrafish heart across eight stages. We characterize the cascade of cardiomyocyte cell states responsible for producing regenerated myocardium and explore a potential role for tpm4a in cardiomyocyte re-differentiation. Moreover, we uncover the activation of ifrd1 and atp6ap2 genes as a unique feature of regenerative hearts. Lastly, we reconstruct a 4D "virtual regenerating heart" comprising 569,896 cells/spots derived from 36 scRNA-seq libraries and 224 Stereo-seq slices. Our comprehensive atlas serves as a valuable resource to the cardiovascular and regeneration scientific communities and their ongoing efforts to understand the molecular and cellular mechanisms underlying vertebrate heart regeneration.
-
Decoding the annulus fibrosus cell atlas by scRNA-seq to develop an inducible composite hydrogel: A novel strategy for disc reconstruction.
Low back pain is one of the most serious public health problems worldwide and the major clinical manifestation of intervertebral disc degeneration (IVDD). The key pathological change during IVDD is dysfunction of the annulus fibrosus (AF). However, due to the lack of an in-depth understanding of AF biology, the methods to reconstruct the AF are very limited. In this study, the mice AF cell atlas were decoded by single-cell RNA sequencing to provide a guide for AF reconstruction. The results first identify a new population of AF cells, fibrochondrocyte-like AF cells, which synthesize both collagen I and collagen II and are potential functional cells for AF reconstruction. According to the dual features of the AF extracellular matrix, a composite hydrogel based on the acylation of methacrylated silk fibroin with methacrylated hyaluronic acid was produced. To obtain the ability to stimulate differentiation, the composite hydrogels were combined with a fibrochondrocyte-inducing supplement. Finally, reconstruction of the AF defects, by the novel AF stem cell-loaded composite hydrogel, could be observed, its amount of chondroid matrices recovered to 31.7% of AF aera which is significantly higher than that in other control groups. In summary, this study decodes the AF cell atlas, based on which a novel strategy for AF reconstruction is proposed.
-
Single-Cell Sequencing Reveals Thalidomide-Induced Teratogenicity in Zebrafish via Endoplasmic Reticulum Stress and Dysregulated Angiogenic Signaling.
Thalidomide (TD) can lead to zebrafish having various malformations, including pectoral fin bud deformities, ear malformations. It induces the degradation of protein substrates, such as ∆Np63α, TAp63α, and SALL4, thereby exerting teratogenic effects on zebrafish. The degradation of these protein substrates triggers downstream changes, including oxidative stress and anti-angiogenesis. However, the genes involved in oxidative stress and anti-angiogenesis remain unclear. Here, the authors used single-cell RNA sequencing (scRNA-seq) to assess how TD exposure affects the transcriptome diversity of 69,115 cells at 1, 2, and 5 days post-fertilization (dpf). Wide-type group data sets were obtained from the NCBI SRA database (Accession: SRP221273). The authors' analysis identified 43 cell populations, with significant alterations in the gene expression profiles of 16 of these populations. Expression of the heat shock protein family gene hsp was upregulated in several cellular subpopulations (heart, vessel, pectoral fin bud, etc.), and the heat shock protein family genes were associated with stress. A protein-protein interaction (PPI) network was constructed using STRING and Cyto-scape software, and hub genes associated with TD-induced zebrafish teratogenicity were identified through the CytoHubba plugin. These genes play crucial roles in cellular stress responses, particularly the significance of heat shock proteins (HSPs) in regulating cellular stress and protecting cell survival. Functional analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed enrichment in pathways associated with endoplasmic reticulum protein processing and spliceosome. The genes her15.1 , her4.3 , and her4.4 exert an anti-angiogenic effect by modulating the Notch signaling pathway. The results obtained from RT-qPCR agreed with the sequencing data. This study constructed a single-cell transcriptomic atlas of zebrafish embryos under TD exposure through transcriptomic analysis at the single-cell level, supplementing the investigation of oxidative stress and anti-angiogenesis-related genes in TD-induced zebrafish malformations. Our research on TD, which causes cranio-maxillofacial-related malformations like ear and eye defects across multiple species, holds great significance for cranio-maxillofacial surgery.
-
Expression analysis of epithelial membrane protein 1 (EMP1) gene in kidney stone patients.
BACKGROUND: Calcium oxalate (CaOx) nephrolithiasis is a recurrent urological disorder, and Randall's plaque (RP) of the renal papilla is widely accepted as an early site of stone nucleation. Although immune activation, epithelial injury, and extracellular matrix (ECM) remodeling have been reported in RP, the cell-type-specific transcriptional features of Epithelial Membrane Protein 1 (EMP1) in this tissue context remain undefined. METHODS: A secondary, hypothesis-generating analysis of a publicly available single-cell RNA sequencing (scRNA-seq) dataset (NCBI GEO accession GSE176155; BioProject PRJNA735197) comprising renal papillary tissue from patients undergoing percutaneous nephrolithotomy for CaOx nephrolithiasis (RP samples) and matched normal renal papilla samples was performed. Raw FASTQ data were processed through Cell Ranger (v6.0.1) aligned to GRCh38, followed by quality control, normalization, dimensionality reduction (PCA, UMAP), graph-based clustering, and cell-type annotation in Seurat (v4.0.5) using canonical markers cross-checked against the Kidney Cell Atlas. Differential expression at the single-cell level was assessed by the Wilcoxon rank-sum test with Bonferroni correction. Coexpression, functional enrichment (GO, KEGG), and weighted gene coexpression network analysis (WGCNA) were used to characterise EMP1-associated transcriptional modules. Pseudobulk-style ANOVA and linear regression were performed as exploratory sensitivity checks at the sample level. RESULTS: At the single-cell level, EMP1 was significantly downregulated in RP-derived epithelial and stromal clusters compared with normal renal papilla (adjusted p < 0.01, log2FC ≤ -0.30). EMP1 was co-expressed with C3, RNASE1, NRG1, IFI16, S100A10, HSPA6, and FN1, and the EMP1-correlated module identified by WGCNA was negatively correlated with the RP phenotype (r = -0.72, p < 0.001). GO and KEGG enrichment showed associations with cell adhesion, integrin and heparin binding, leukocyte migration, neutrophil extracellular trap formation, and focal adhesion. Sample-level pseudobulk ANOVA and regression analyses did not reach statistical significance for most genes, consistent with the limited number of donors and the loss of cell-type resolution after pseudobulk aggregation; these results are presented as exploratory. CONCLUSIONS: This study reports an associative, hypothesis-generating link between reduced EMP1 expression in renal papillary epithelial and stromal populations and the molecular landscape of Randall's plaque. Independent transcriptomic, spatial, and functional validation will be required before EMP1 can be considered a candidate biomarker or therapeutic target in CaOx nephrolithiasis.
-
A 3D Atlas of Hematopoietic Stem and Progenitor Cell Expansion by Multi-dimensional RNA-Seq Analysis.
In vertebrates, hematopoiesis occurring in different niches is orchestrated by intrinsic and extrinsic regulators. Previous studies have revealed numerous linear and planar regulatory mechanisms. However, a multi-dimensional transcriptomic atlas of any given hematopoietic organ has not yet been established. Here, we use multiple RNA sequencing (RNA-seq) approaches, including cell type-specific, temporal bulk RNA-seq, in vivo GEO-seq, and single-cell RNA-seq (scRNA-seq), to characterize the detailed spatiotemporal transcriptome during hematopoietic stem and progenitor cell (HSPC) expansion in the caudal hematopoietic tissue (CHT) of zebrafish. Combinatorial expression profiling reveals that, in the CHT niche, HSPCs and their neighboring supporting cells are co-regulated by shared signaling pathways and intrinsic factors, such as integrin signaling and Smchd1. Moreover, scRNA-seq analysis unveils the strong association between cell cycle status and HSPC differentiation. Taken together, we report a global transcriptome landscape that provides valuable insights and a rich resource to understand HSPC expansion in an intact vertebrate hematopoietic organ.
-
Metastasis and basement membrane-related signature enhances hepatocellular carcinoma prognosis and diagnosis by integrating single-cell RNA sequencing analysis and immune microenvironment assessment.
BACKGROUND: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and second leading cause of cancer-related deaths worldwide. The heightened mortality associated with HCC is largely attributed to its propensity for metastasis, which cannot be achieved without remodeling or loss of the basement membrane (BM). Despite advancements in targeted therapies and immunotherapies, resistance and limited efficacy in late-stage HCC underscore the urgent need for better therapeutic options and early diagnostic biomarkers. Our study aimed to address these gaps by investigating and evaluating potential biomarkers to improve survival outcomes and treatment efficacy in patients with HCC. METHOD: In this study, we collected the transcriptome sequencing, clinical, and mutation data of 424 patients with HCC from The Cancer Genome Atlas (TCGA) and 240 from the International Cancer Genome Consortium (ICGC) databases. We then constructed and validated a prognostic model based on metastasis and basement membrane-related genes (MBRGs) using univariate and multivariate Cox regression analyses. Five immune-related algorithms (CIBERSORT, QUANTISEQ, MCP counter, ssGSEA, and TIMER) were then utilized to examine the immune landscape and activity across high- and low-risk groups. We also analyzed Tumor Mutation Burden (TMB) values, Tumor Immune Dysfunction and Exclusion (TIDE) scores, mutation frequency, and immune checkpoint gene expression to evaluate immune treatment sensitivity. We analyzed integrin subunit alpha 3 (ITGA3) expression in HCC by performing single-cell RNA sequencing (scRNA-seq) analysis using the TISCH 2.0 database. Lastly, wound healing and transwell assays were conducted to elucidate the role of ITGA3 in tumor metastasis. RESULTS: Patients with HCC were categorized into high- and low-risk groups based on the median values, with higher risk scores indicating worse overall survival. Five immune-related algorithms revealed that the abundance of immune cells, particularly T cells, was greater in the high-risk group than in the low-risk group. The high-risk group also exhibited a higher TMB value, mutation frequency, and immune checkpoint gene expression and a lower tumor TIDE score, suggesting the potential for better immunotherapy outcomes. Additionally, scRNA-seq analysis revealed higher ITGA3 expression in tumor cells compared with normal hepatocytes. Wound healing scratch and transwell cell migration assays revealed that overexpression of the MBRG ITGA3 enhanced migration of HCC HepG2 cells. CONCLUSION: This study established a direct molecular correlation between metastasis and BM, encompassing clinical features, tumor microenvironment, and immune response, thereby offering valuable insights for predicting clinical outcomes and immunotherapy responses in HCC.
-
Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD), the most common histological subtype of lung cancer, demonstrates significant intertumoral heterogeneity. While dendritic cells (DCs) are essential mediators of antitumor immunity, their transcriptional diversity and prognostic value in LUAD remain underexplored. METHODS: We constructed a cellular atlas by integrating single-cell RNA sequencing (scRNA-seq) data from LUAD and normal tissues, emphasizing dendritic cells. High-dimensional weighted gene co-expression network analysis (hdWGCNA) and pseudotime analysis were utilized to identify functional modules and lineage trajectories. A dendritic cell-related signature (DCRS) was constructed using multiple machine learning algorithms (Lasso-Cox, RSF, CoxBoost, Stepwise-Cox), and its prognostic performance was validated in seven external cohorts. Immune landscape, genomic instability, drug sensitivity, and immunotherapy response were further analyzed. The functional role of PLEK2, a DCRS hub gene, was validated in clinical samples and LUAD cell lines. RESULTS: We identified six DC clusters with distinct developmental states and transcriptional programs. The M2 module was enriched in prognostically relevant clusters and used to derive the DCRS. Patients in the high-DCRS group exhibited worse prognosis, lower immune infiltration, higher chromosomal instability and tumor mutation burden, and reduced responsiveness to immunotherapy. Drug sensitivity analysis revealed that the low-DCRS group was more responsive to multiple chemotherapeutic agents. Functional validation confirmed that PLEK2 was overexpressed in LUAD tissues and promoted tumor cell proliferation, migration, and colony formation. CONCLUSION: We established a novel DCRS with robust prognostic and predictive value in LUAD. This work highlights the pivotal role of dendritic cell programs in shaping the tumor microenvironment and provides potential targets for improving precision immunotherapy.