Браузер не даёт сохранять данные (например, приватный режим): закладки пропадут после закрытия вкладки.
Поиск статей PubMed
Ключевые слова, автор, журнал, годы — результаты из PubMed, аннотации с переводом на русский, закладки в браузере.
Найдено: 4 915
Страница 140 из 492-
CXCL11 Correlates With Antitumor Immunity and an Improved Prognosis in Colon Cancer.
The chemokine ligand C-X-C motif chemokine ligand 11 (CXCL11) is involved in the progression of various cancers, but its biological roles in colorectal cancer (CRC) remain confused. Therefore, the prognostic value and underlying mechanism of CXCL11 in CRC were preliminarily evaluated. Three independent datasets were used for mRNA-related analysis: one dataset from the Cancer Genome Atlas (TCGA, n = 451) and two single-cell RNA sequencing (scRNA-seq) datasets from Gene Expression Omnibus (GEO): GSE146771 and GSE132465. In addition, a colon adenocarcinoma (COAD) patient cohort (the Yijishan Hospital cohort, YJSHC, n = 108) was utilized for analysis of cell infiltration by immunohistochemistry. We determined the distribution of CXCL11 in tumor tissue across all TCGA cancers and found that CXCL11 expression was significantly upregulated in both COAD and rectal adenocarcinoma (READ). However, the upregulation of CXCL11 mRNA was associated with a better prognosis in COAD, but not in READ. Within the YJSHC, the patients with a high abundance of intratumoral CXCL11+ cells had prolonged survival (p = 0.001). Furthermore, we found that the high CXCL11 expression group had a higher proportion of antitumor immune cells, and a lower proportion of protumor immune cells. Additionally, we discovered the changes of gene expression and enriched immune pathway network mediated by CXCL11. Interestingly, both cytotoxic genes (IFNG, GZMA, GZMB, GZMK, GZMM, and PRF1) and immunosuppressive molecules, including PD-L1, were positively correlated with CXCL11 expression. CXCL11, which promoted antitumor immunity to benefit survival, was identified as an independent prognostic biomarker in patients with COAD.
-
A single-cell transcriptomic atlas of human stem cells from apical papilla during the committed differentiation.
AIM: Human stem cells derived from the apical papilla (SCAPs) are recognized for their multilineage differentiation potential and their capacity for functional tooth root regeneration. However, the molecular mechanisms underlying odonto/osteogenic differentiation remain largely unexplored. In this study, we utilized single-cell RNA sequencing (scRNA-seq) to conduct an in-depth analysis of the transcriptional changes associated with chemically induced osteogenesis in SCAPs. METHODOLOGY: scRNA-seq identified SCAPs as distinct subpopulations. Differentially expressed genes (DEGs) and Gene Ontology (GO) analyses were conducted to evaluate the potential function of each cluster. Pseudotime trajectory analysis was employed to elucidate the potential differentiation processes of the identified SCAP populations. To investigate the osteo/odontogenic potential of Deiodinase Iodothyronine Type 2 (DIO2) on SCAPs, we performed alkaline phosphatase staining, western blot analysis, Alizarin Red S staining and immunofluorescence staining. Additionally, SCAP components were transplanted into mouse calvarial defects to evaluate osteogenesis in vivo. RESULTS: The analysis of cell clusters derived from our scRNA-seq data revealed a significant shift in cellular composition when cells were cultured in a mineralization induction medium compared to those cultured in a complete medium. Both groups exhibited heterogeneity, with some cells intrinsically predisposed to osteogenesis and others appearing to be primed for proliferative functions. Notably, we identified a subpopulation characterized by high expression of DIO2, which exhibited pronounced osteogenic activity during differentiation. CONCLUSIONS: Our study is the first to reveal a shift in the cellular composition of SCAPs when cultured in a mineralization induction medium compared to a complete medium. Following both in vitro and in vivo validation, the DIO2+ subpopulation exhibited the highest transcriptional similarity to osteogenic function, suggesting its potential utility in tissue regeneration applications.
-
Identification and validation of a novel innate lymphoid cell-based signature to predict prognosis and immune response in liver cancer by integrated single-cell RNA analysis and bulk RNA sequencing.
BACKGROUND: Innate lymphoid cells (ILCs) exert tumor suppressive and tumor promoting effects. However, the prognostic significance of ILC-associated genes remains unclear in hepatocellular carcinoma (HCC). Hence, the aim of this research was to develop an innovative predictive risk classification system using bioinformatics examination. METHODS: We explored the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to gather data pertaining to HCC and its clinical details. Significantly different ILC-associated genes were investigated by Seurat analysis. The number of signaling interactions of ILCs with other cells was discovered by CellPhoneDB analysis. ClusterProfiler and Metascape were utilized to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on ILC genes. In order to identify potential ILC predictors, we utilized univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses, subsequently validating these predictors in TCGA and GEO groups. The multi-omics ILC signature model's clinical predictive capabilities, along with drug sensitivity and immune factor relations, were assessed using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and pRRophetic. We investigated the possible molecular pathways in our predictive ILC signature through the utilization of gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Five key genes were screened out by constructing a competing endogenous RNA (ceRNA) network using Cytoscape and their values in clinical indexes were demonstrated. Immunohistochemistry (IHC) in HCC cases confirmed the expression of these genes. RESULTS: ILC cell subsets were identified, and cell-cell communication analysis revealed that the signaling pathways involving ILC cell subsets were mostly abundant in the HCC microenvironment. Subsequently, 270 marker genes of the ILC clusters were subjected to GO and KEGG enrichment analysis. Furthermore, a total of 58 prognostically relevant genes were screened as features for prognostic prediction models. Next, the models were validated and clinically evaluated (P values of Kaplan-Meier survival curves below 0.05). Five key genes (C2, STK4, CALM1, IL7R, and RORA) were further screened by multi omics analysis of immune cell and factor and drug sensitivity and correlation analysis of tumor regulatory genes in liver cancer. Furthermore, the potential clinical value of the 5 key genes was confirmed in HCC patients. Finally, the IHC results confirmed the expression of C2, STK4, CALM1, IL7R, and RORA in HCC. Our experimental results provided preliminary evidence supporting the oncogenic roles of STK4 and CALM1, as well as the tumor-suppressive roles of C2, RORA, and IL7R in HCC. CONCLUSIONS: A novel prognostic feature of ILC potentially involved in HCC was discovered. It showed high values in predicting patient overall survival (OS) as well as good differences in immunity and drug sensitivity. Therefore, targeting these ILC signatures may be a potential effective approach in HCC treatment.
-
Single-cell RNA sequencing reveals transcriptomic landscape and potential targets for human testicular ageing.
STUDY QUESTION: What is the molecular landscape underlying the functional decline of human testicular ageing? SUMMARY ANSWER: The present study provides a comprehensive single-cell transcriptomic atlas of testes from young and old humans and offers insights into the molecular mechanisms and potential targets for human testicular ageing. WHAT IS KNOWN ALREADY: Testicular ageing is known to cause male age-related fertility decline and hypogonadism. Dysfunction of testicular cells has been considered as a key factor for testicular ageing. STUDY DESIGN, SIZE, DURATION: Human testicular biopsies were collected from three young individuals and three old individuals to perform single-cell RNA sequencing (scRNA-seq). The key results were validated in a larger cohort containing human testicular samples from 10 young donors and 10 old donors. PARTICIPANTS/MATERIALS, SETTING, METHODS: scRNA-seq was used to identify gene expression signatures for human testicular cells during ageing. Ageing-associated changes of gene expression in spermatogonial stem cells (SSCs) and Leydig cells (LCs) were analysed by gene set enrichment analysis and validated by immunofluorescent and functional assays. Cell-cell communication analysis was performed using CellChat. MAIN RESULTS AND THE ROLE OF CHANCE: The single-cell transcriptomic landscape of testes from young and old men was surveyed, revealing age-related changes in germline and somatic niche cells. In-depth evaluation of the gene expression dynamics in germ cells revealed that the disruption of the base-excision repair pathway is a prominent characteristic of old SSCs, suggesting that defective DNA repair in SSCs may serve as a potential driver for increased de novo germline mutations with age. Further analysis of ageing-associated transcriptional changes demonstrated that stress-related changes and cytokine pathways accumulate in old somatic cells. Age-related impairment of redox homeostasis in old LCs was identified and pharmacological treatment with antioxidants alleviated this cellular dysfunction of LCs and promoted testosterone production. Lastly, our results revealed that decreased pleiotrophin signalling was a contributing factor for impaired spermatogenesis in testicular ageing. LARGE SCALE DATA: The scRNA-seq sequencing and processed data reported in this paper were deposited at the Genome Sequence Archive (https://ngdc.cncb.ac.cn/), under the accession number HRA002349. LIMITATIONS, REASONS FOR CAUTION: Owing to the difficulty in collecting human testis tissue, the sample size was limited. Further in-depth functional and mechanistic studies are warranted in future. WIDER IMPLICATIONS OF THE FINDINGS: These findings provide a comprehensive understanding of the cell type-specific mechanisms underlying human testicular ageing at a single-cell resolution, and suggest potential therapeutic targets that may be leveraged to address age-related male fertility decline and hypogonadism. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Key Research and Development Program of China (2022YFA1104100), the National Natural Science Foundation of China (32130046, 82171564, 82101669, 82371611, 82371609, 82301796), the Natural Science Foundation of Guangdong Province, China (2022A1515010371), the Major Project of Medical Science and Technology Development Research Center of National Health Planning Commission, China (HDSL202001000), the Open Project of NHC Key Laboratory of Male Reproduction and Genetics (KF202001), the Guangdong Province Regional Joint Fund-Youth Fund Project (2021A1515110921, 2022A1515111201), and the China Postdoctoral Science Foundation (2021M703736). The authors declare no conflict of interest.
-
GeneSurfer Enables Transcriptome-wide Exploration and Functional Annotation of Gene Co-expression Modules in 3D Spatial Transcriptomics Data.
Gene co-expression provides crucial insights into biological functions, however, there is a lack of exploratory analysis tools for localized gene co-expression in large-scale datasets. We present GeneSurfer, an interactive interface designed to explore localized transcriptome-wide gene co-expression patterns in the 3D spatial domain. Key features of GeneSurfer include transcriptome-wide gene filtering and gene clustering based on spatial local co-expression within transcriptomically similar cells, multi-slice 3D rendering of average expression of gene clusters, and on-the-fly Gene Ontology term annotation of co-expressed gene sets. Additionally, GeneSurfer offers multiple linked views for investigating individual genes or gene co-expression in the spatial domain at each exploration stage. Demonstrating its utility with both spatial transcriptomics and single-cell RNA sequencing data from the Allen Brain Cell Atlas, GeneSurfer effectively identifies and annotates localized transcriptome-wide co-expression, providing biological insights and facilitating hypothesis generation and validation.
-
STING signalling compensates for low tumour mutation burden to drive anti-tumour immunity.
BACKGROUND: While mutation-derived neoantigens are well recognized in generating anti-tumour T cell response, increasing evidences highlight the complex association between tumour mutation burden (TMB) and tumour infiltrating lymphocytes (TILs). The exploration of non-TMB determinants of active immune response could improve the prognosis prediction and provide guidance for current immunotherapy. METHODS: The transcriptomic and whole exome sequence data in The Cancer Genome Atlas were used to examine the relationship between TMB and exhausted CD8+ T cells (Tex), as an indicator of tumour antigen-specific T cells across nine major cancer types. Computational clustering analysis was performed on 4510 tumours to identify different immune profiles. NanoString gene expression analysis and single cell RNA-seq analysis using fresh human breast cancer were performed for finding validation. FINDINGS: TMB was found to be poorly correlated with active immune response in various cancer types. Patient clustering analysis revealed a group of tumours with abundant Tex but low TMB. In those tumours, we observed significantly higher expression of the stimulator of interferon genes (STING) signalling. Dendritic cells, particularly those of BATF3+ lineage, were also found to be essential for accumulation of Tex within tumours. Mechanistically, loss of genomic and cellular integrity, marked by decreased DNA damage repair, defective replication stress response, and increased apoptosis were shown to drive STING activation. INTERPRETATION: These results highlight that TMB alone does not fully predict tumour immune profiles, with STING signalling compensating for low TMB in non-hypermutated tumours to enhance anti-tumour immunity. Translating these results, STING agonists may benefit patients with non-hypermutated tumours. STING activation may serve as an additional biomarker to predict response to immune checkpoint blockades alongside TMB. Our research also unravelled the interplay between genomic instability and STING activation, informing potential combined chemotherapy targeting the axis of genomic integrity and immunotherapy. FUNDING: City of Hope Christopher Family Endowed Innovation Fund for Alzheimer's Disease and Breast Cancer Research in honor of Vineta Christopher; Breast Cancer Alliance Early Career Investigator Award; National Cancer Institute of the National Institutes of Health under award number R01CA256989 and R01CA240392.
-
Single-Cell Analysis of Target Antigens of CAR-T Reveals a Potential Landscape of "On-Target, Off-Tumor Toxicity".
Cellular immunotherapy represented by CD19-directed chimeric antigen receptor T (CAR-T) cells has achieved great success in recent years. An increasing number of CAR-T therapies are being developed for cancer treatment, but the frequent and varied adverse events, such as "on-target, off-tumor toxicity", limit CAR-T application. Here, we identify the target antigen expression patterns of CAR therapies in 18 tissues and organs (peripheral blood mononuclear cells, bone marrow, lymph nodes, spleen, heart, ascending aortic tissue, trachea, lung, skin, kidney, bladder, esophagus, stomach, small intestine, rectum, liver, common bile duct, and pancreas) from healthy human samples. The atlas determines target antigens expressed on some normal cell types, which facilitates elucidating the cause of "on-target, off-tumor toxicity" in special tissues and organs by targeting some antigens, but not others. Moreover, we describe the target antigen expression patterns of B-lineage-derived malignant cells, acute myeloid leukemia (AML), and solid tumors. Overall, the present study indicates the pathogenesis of "on-target, off-tumor toxicity" during CAR therapies and provides guidance on taking preventive measures during CAR treatment.
-
Computational Drug Repurposing for Alzheimer's Disease via Sheaf Theoretic Population-Scale Analysis of snRNA-seq Data.
Single-cell and single-nucleus RNA sequencing (scRNA-seq /snRNA-seq) are widely used to reveal heterogeneity in cells, showing a growing potential for precision and personalized medicine. Nonetheless, sustainable drug discovery must be based on a population-level understanding of molecular mechanisms, which calls for the population-scale analysis of scRNA-seq/snRNA-seq data. This work introduces a sequential target-drug selection model for drug repurposing against Alzheimer's Disease (AD) targets inferred from population-level snRNA-seq studies of AD progression in microglia cells as well as different cell types taken from an AD affected brain vascular tissue atlas, involving hundreds of thousands of nuclei from multi-patient and multi-regional studies. We utilize Persistent Sheaf Laplacians (PSL) to facilitate a Protein-Protein Interaction (PPI) analysis of AD targets inferred from differential gene expression (DEG), and then use a machine learning models to predict repurpose-able DrugBank compounds for molecular targeting. We screen the efficacy of different DrugBank small compounds and further examine their central nervous system (CNS)-relevant ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity), resulting in a list of lead candidates for AD treatment. The list of significant genes establishes a target domain for effective machine learning based AD drug repurposing analysis of DrugBank small compounds to treat AD related molecular targets.
-
Identification of Regulatory RNA-Binding Proteins Associated with Immune Infiltration in Laryngeal Squamous Cell Carcinoma.
We analyzed bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) data to identify alternative splicing (AS) events and regulatory RNA-binding proteins (RBPs) associated with immune infiltration in human laryngeal squamous cell carcinoma (LSCC). Whole-transcriptome sequencing data of 20 human laryngeal cancer and paracancerous tissues were downloaded from the Gene Expression Omnibus public database, using newly published splicing-site usage variation analysis software to obtain highly conserved regulated AS (RAS) events, and scientific reverse convolution algorithm analysis was used to identify significantly different immune cells and perform a correlation analysis between the two. The software package edgeR was used to identify differentially expressed RBPs and the immune infiltration-related LSCC-RAS they may regulate. Finally, we present the expression profiles and survival curves of 117 human laryngeal cancer samples from The Cancer Genome Atlas dataset for the identified RBPs and LSCC-RAS. We also downloaded the gene set enrichment 150321 scRNA-seq data for two human LSCC tissue samples. The RBP expression pattern and the expression of prophase RBP genes were analyzed in different LSCC cell populations. RNA-binding motif protein 47 (RBM47) and filamin A, as well as the RBP-RAS events that were screened in both the fibulin 2 and fibronectin 1 genes, were all significantly associated with the prognosis, and the RBM47 gene was upregulated in myeloid cells. Because the prognosis was significantly associated with two RBP regulators and two LSCC-RAS events, they may be critical regulators of immune cell survival during laryngeal cancer progression, and RBM47 may regulate macrophage-associated AS and affect immunity.
-
Widespread sex dimorphism across single-cell transcriptomes of adult African turquoise killifish tissues.
The African turquoise killifish (Nothobranchius furzeri), the shortest-lived vertebrate that can be bred in captivity, is an emerging model organism for aging research. Here, we describe a multitissue, single-cell gene expression atlas of female and male blood, kidney, liver, and spleen. We annotate 22 cell types, define marker genes, and infer differentiation trajectories. We find pervasive sex-dimorphic gene expression across cell types. Sex-dimorphic genes tend to be linked to lipid metabolism, consistent with clear differences in lipid storage in female vs. male turquoise killifish livers. We use machine learning to predict sex using single-cell gene expression and identify potential markers for molecular sex identity. As a proof of principle, we show that our atlas can be used to deconvolute existing bulk RNA sequencing (RNA-seq) data to obtain accurate estimates of cell type proportions. This atlas can be a resource to the community that could be leveraged to develop cell-type-specific expression in transgenic animals.