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Single-cell sequencing provides clues about the developmental genetic basis of evolutionary adaptations in syngnathid fishes.
Seahorses, pipefishes, and seadragons are fishes from the family Syngnathidae that have evolved extraordinary traits including male pregnancy, elongated snouts, loss of teeth, and dermal bony armor. The developmental genetic and cellular changes that led to the evolution of these traits are largely unknown. Recent syngnathid genome assemblies revealed suggestive gene content differences and provided the opportunity for detailed genetic analyses. We created a single-cell RNA sequencing atlas of Gulf pipefish embryos to understand the developmental basis of four traits: derived head shape, toothlessness, dermal armor, and male pregnancy. We completed marker gene analyses, built genetic networks, and examined the spatial expression of select genes. We identified osteochondrogenic mesenchymal cells in the elongating face that express regulatory genes bmp4, sfrp1a, and prdm16. We found no evidence for tooth primordia cells, and we observed re-deployment of osteoblast genetic networks in developing dermal armor. Finally, we found that epidermal cells expressed nutrient processing and environmental sensing genes, potentially relevant for the brooding environment. The examined pipefish evolutionary innovations are composed of recognizable cell types, suggesting that derived features originate from changes within existing gene networks. Future work addressing syngnathid gene networks across multiple stages and species is essential for understanding how the novelties of these fish evolved.
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Single-Cell Transcriptome Atlas Reveals the Underlying Mechanism of Kynurenic Acid in the Regulation of Tumor Immune Microenvironment in Glioblastoma.
Tryptophan metabolism plays a critical role in glioblastoma (GBM), however, the regulatory functions of kynurenic acid (KYNA) in this context remain poorly understood. Using an in-house clinical cohort, targeted metabolomic analysis revealed significantly downregulated KYNA levels in GBM tissues compared to non-tumor brain tissues. Further investigation demonstrated that KYNA administration markedly reduced tumor burden in an orthotopic GBM mouse model. Through integrated cytometry by time-of-fight (CyTOF), single-cell RNA sequencing (scRNA-seq), proteome, and flow cytometry analyses, this study delineated the alterative tumor immune landscape following KYNA treatment. Specifically, KYNA remodeled the immunosuppressive myeloid compartment within the GBM microenvironment. Additionally, KYNA reversed T cell exhaustion signatures, enhanced cytotoxic function, thereby augmented anti-tumor T cell responses. Notably, the anti-tumor effects of KYNA are abrogated in T cell-deficient mouse models (nude and Rag2-/-), confirming its dependence on adaptive immunity. In summary, this study highlights the therapeutic potential of KYNA in GBM and provides a comprehensive, multi-omics-based understanding of its immunomodulatory mechanisms.
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A Novel Artificial Neural Network Prognostic Model Based on a Cancer-Associated Fibroblast Activation Score System in Hepatocellular Carcinoma.
INTRODUCTION: Hepatocellular carcinoma (HCC) ranks fourth as the most common cause of cancer-related death. It is vital to identify the mechanism of progression and predict the prognosis for patients with HCC. Previous studies have found that cancer-associated fibroblasts (CAFs) promote tumor proliferation and immune exclusion. However, the information about CAF-related genes is still elusive. METHODS: The data were obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus databases. On the basis of single-cell transcriptome and ligand-receptor interaction analysis, CAF-related genes were selected. By performing Cox regression and random forest, we filtered 12 CAF-related prognostic genes for the construction of the ANN model based on the CAF activation score (CAS). Then, functional, immune, mutational, and clinical analyses were performed. RESULTS: We constructed a novel ANN prognostic model based on 12 CAF-related prognostic genes. Cancer-related pathways were enriched, and higher activated cell crosstalk was identified in high-CAS samples. High immune activity was observed in high-CAS samples. We detected three differentially mutated genes (NBEA, RYR2, and FRAS1) between high- and low-CAS samples. In clinical analyses, we constructed a nomogram to predict the prognosis of patients with HCC. 5-Fluorouracil had higher sensitivity in high-CAS samples than in low-CAS samples. Moreover, some small-molecule drugs and the immune response were predicted. CONCLUSION: We constructed a novel ANN model based on CAF-related genes. We revealed information about the ANN model through functional, mutational, immune, and clinical analyses.
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A multi-tissue single-cell expression atlas in cattle.
Systematic characterization of the molecular states of cells in livestock tissues is essential for understanding the cellular and genetic mechanisms underlying economically and ecologically important physiological traits. Here, as part of the Farm Animal Genotype-Tissue Expression (FarmGTEx) project, we describe a comprehensive reference map including 1,793,854 cells from 59 bovine tissues in calves and adult cattle, spanning both sexes, which reveals intra-tissue and inter-tissue cellular heterogeneity in gene expression, transcription factor regulation and intercellular communication. Integrative analysis with genetic variants that underpin bovine monogenic and complex traits uncovers cell types of relevance, such as spermatocytes, responsible for sperm motility and excitatory neurons for milk fat yield. Comparative analysis reveals similarities in gene expression between cattle and humans, allowing for the detection of relevant cell types to study human complex phenotypes. This Cattle Cell Atlas will serve as a key resource for cattle genetics and genomics, selective breeding and comparative biology.
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Identification of key molecules in the formation of portal vein tumor thrombus in hepatocellular carcinoma based on single cell transcriptomics and in vitro experiments.
BACKGROUND: The presence of portal vein tumor thrombus (PVTT) is a significant indicator of advanced-stage hepatocellular carcinoma (HCC). Unfortunately, the prediction of PVTT occurrence remains challenging, and there is a lack of comprehensive research exploring the underlying mechanisms of PVTT formation and its association with immune infiltration. METHODS: Our approach involved analyzing single-cell sequencing data, applying high dimensional weighted gene co-expression network analysis (hdWGCNA), and identifying key genes associated with PVTT development. Furthermore, we constructed competing endogenous RNA (ceRNA) networks and employed weighted gene co-expression network analysis (WGCNA), as well as three machine-learning techniques, to identify the upstream regulatory microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) of the crucial mRNAs. We employed fuzzy clustering of time series gene expression data (Mfuzz), gene set variation analysis (GSVA), and cell communication analysis to uncover significant signaling pathways involved in the activation of these important mRNAs during PVTT development. In addition, we conducted immune infiltration analysis, survival typing, and drug sensitivity analysis using The Cancer Genome Atlas (TCGA) cohort to gain insights into the two patient groups under study. RESULTS: Through the implementation of hdWGCNA, we identified 110 genes that was closely associated with PVTT. Among these genes, TMEM165 emerged as a crucial candidate, and we further investigated its significance using COX regression analysis. Furthermore, through machine learning techniques and survival analysis, we successfully identified the upstream regulatory miRNA (hsa-miR-148a) and lncRNA (LINC00909) that targeted TMEM165. These findings shed light on the complex regulatory network surrounding TMEM165 in the context of PVTT. Moreover, we conducted CIBERSORT analysis, which unveiled correlations between TMEM165 and immune infiltration in HCC patients. Specifically, TMEM165 exhibited associations with various immune cell populations, including memory B cells and CD8+ T cells. Additionally, we observed implications for immune function, particularly in relation to immune checkpoints, within the context of HCC. CONCLUSIONS: The regulatory axis involving TMEM165, hsa-miR-148a, and LINC00909 emerges as a crucial determinant in the development of PVTT in HCC patients, and it holds significant implications for prognosis. Furthermore, alterations in the TMEM165/hsa-miR-148a/LINC00909 regulatory axis exhibit a strong correlation with immune infiltration within the HCC tumor microenvironment, leading to immune dysfunction and potential failure of immunotherapy.
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Multidimensional Analysis of PANoptosis-Related Molecule CASP8: Prognostic Significance, Immune Microenvironment Effect, and Therapeutic Implications in Hepatocellular Carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) presents significant challenges in diagnosis and treatment. Understanding the role of PANoptosis-related molecules in HCC is crucial for advancing therapeutic strategies. METHODS: We conducted a comprehensive analysis using public data from the Cancer Genome Atlas, Human Protein Atlas, Tumor Immune Single Cell Hub, and STRING databases. Techniques included Kaplan-Meier survival curves, Cox regression, LASSO analysis, and various computational methods for understanding the tumor microenvironment. We also employed ClueGO, gene set enrichment analysis, and other algorithms for biological enrichment analysis. RESULTS: CASP8 emerged as a significant molecule in HCC, correlated with poor survival outcomes. Its expression was predominant in the nucleoplasm and cytosol and varied across different cancer types. Biological enrichment analysis revealed CASP8's association with critical cellular activities and immune responses. In the tumor microenvironment, CASP8 showed correlations with various immune cell types. A nomogram plot was developed for better clinical prognostication. Mutation analysis indicated a higher frequency of TP53 mutations in patients with elevated CASP8 expression. In addition, CASP8 was found to regulate YEATS2 in HCC, highlighting a potential pathway in tumor progression. CONCLUSIONS: Our study underscores the multifaceted role of CASP8 in HCC, emphasizing its prognostic and therapeutic significance. The regulatory relationship between CASP8 and YEATS2 opens new avenues for understanding HCC pathogenesis and treatment strategies.
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Relationship between Macrophage and Radiosensitivity in Human Primary and Recurrent Glioblastoma: In Silico Analysis with Publicly Available Datasets.
The glioblastoma microenvironment predominantly contains tumor-associated macrophages that support tumor growth and invasion. We investigated the relationship between tumor radiosensitivity and infiltrating M1/M2 macrophage profiles in public datasets of primary and recurrent glioblastoma. We estimated the radiosensitivity index (RSI) score based on gene expression rankings. Macrophages were profiled using the deconvolution algorithm CIBERSORTx. Samples from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), the Ivy Glioblastoma Atlas Project dataset, a single-cell RNA sequencing dataset (GSE84465), Glioma Longitudinal Analysis Consortium (GLASS), and an immunotherapy trial dataset (GSE121810) were included. RSI-high radioresistant tumors were associated with worse overall survival in TCGA and CGGA than RSI-low tumors. M1/M2 macrophage ratios and RSI scores were inversely associated, indicating that radioresistant glioblastoma tumor microenvironments contain more M2 than M1 macrophages. In the single-cell RNA sequencing dataset, the mean RSI of neoplastic cells was positively correlated with high M2 macrophages proportions. A favorable response to programmed cell death protein 1 (PD-1) therapy was observed in recurrent glioblastomas with high M1/M2 macrophage ratios and low RSI scores. In patients with recurrent glioblastoma, fewer M2 macrophages and low RSI scores were associated with improved overall survival. High M2 macrophage proportions may be involved in radioresistant glioblastoma.
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Single-cell transcriptomics in bone marrow delineates CD56dimGranzymeK+ subset as intermediate stage in NK cell differentiation.
Human natural killer (NK) cells in lymphoid tissues can be categorized into three subsets: CD56brightCD16+, CD56dimCD16+ and CD69+CXCR6+ lymphoid tissue-resident (lt)NK cells. How the three subsets are functionally and developmentally related is currently unknown. Therefore, we performed single-cell RNA sequencing combined with oligonucleotide-conjugated antibodies against CD56, CXCR6, CD117 and CD34 on fresh bone marrow NK cells. A minor CD56dimGzmK+ subset was identified that shared features with CD56bright and CD56dimGzmK- NK cells based on transcriptome, phenotype (NKG2AhighCD16lowKLRG1highTIGIThigh) and functional analysis in bone marrow and blood, supportive for an intermediate subset. Pseudotime analysis positioned CD56bright, CD56dimGzmK+ and CD56dimGzmK- cells in one differentiation trajectory, while ltNK cells were developmentally separated. Integrative analysis with bone marrow cells from the Human Cell Atlas did not demonstrate a developmental connection between CD34+ progenitor and NK cells, suggesting absence of early NK cell stages in bone marrow. In conclusion, single-cell transcriptomics provide new insights on development and differentiation of human NK cells.
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TranDep: a transcriptomics atlas of depression.
Depression is a severe mental illness that poses substantial burdens on public health. Given that depression research is still challenged by its multifaceted pathogenesis, depicting the depression associated genetic regulatory networks is essential for understanding its mechanism, optimizing diagnosis, and developing targeted therapies. However, a comprehensive panoramic view of transcriptional alterations in depression remains lacking. By leveraging the available transcriptomic studies from the National Center for Biotechnology Information (NCBI), China National Center for Bioinformatics (CNCB), European Bioinformatics Institute (EBI), and our laboratory, we compiled an extensive set of depression related datasets, encompassing 4 species, 31 types of brain and peripheral tissues, 35 categories of antidepressant interventions, and 6391 samples. Furthermore, a unified pipeline for raw data preprocessing and differential expression analysis was employed to identify differentially expressed genes (DEGs). A total of 631882 molecules entries were obtained, including 190366 entries from humans, 6612 from non-human primates, 332780 from mice, and 102124 from rats. Additionally, 15 single-cell and single-nucleus transcriptomic datasets, including 164 samples, and 78536 molecular entries were also included. Notably, we developed the TranDep database ( http://www.depression-atlas.cn/ ) for the depression research community, which provided a user-friendly web interface for browsing, and searching these molecules. To demonstrate the utility of TranDep, a case study was presented to identify robust DEGs, and explore its biological functions in the prefrontal cortex of patients with depression. Overall, TranDep is a comprehensive cross-species resource developed to provide a transcriptional atlas of depression, which may shed light on the identification and validation of diagnostic and therapeutic markers for depression.
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Single-cell insights into epithelial morphogenesis in the neonatal mouse uterus.
The uterus is vital for successful reproduction in mammals, and two different types of epithelia (luminal and glandular) are essential for embryo implantation and pregnancy establishment. However, the essential cellular and molecular factors and pathways governing postnatal epithelium maturation, determination, and differentiation in developing uterus are yet to be elucidated. Here, the epithelium of the neonatal mouse uterus was isolated and subjected to single-cell transcriptome (scRNA-seq) analysis. Both the undifferentiated epithelium and determined luminal epithelium were heterogeneous and contained several different cell clusters based on single-cell transcription profiles. Substantial gene expression differences were evident as the epithelium matured and differentiated between postnatal days 1 to 15. Two new glandular epithelium-expressed genes (Gas6 and Cited4) were identified and validated by in situ hybridization. Trajectory analyses provided a framework for understanding epithelium maturation, lineage bifurcation, and differentiation. A candidate set of transcription factors and gene regulatory networks were identified that potentially direct epithelium lineage specification and morphogenesis. This atlas provides a foundation important to discover intrinsic cellular and molecular mechanisms directing uterine epithelium morphogenesis during a critical window of postnatal development.