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Single-cell transcriptomic profiling of maize cell heterogeneity and systemic immune responses against Puccinia polysora Underw.
Southern corn rust (SCR), caused by Puccinia polysora Underw (P. polysora), is a catastrophic disease affecting maize, leading to significant global yield losses. The disease manifests primarily as pustules on the upper surface of corn leaves, obscuring our understanding of its cellular heterogeneity, the maize's response to its infection and the underlying gene expression regulatory mechanisms. In this study, we dissected the heterogeneity of maize's response to P. polysora infection using single-cell RNA sequencing. We delineated cell-type-specific gene expression alterations in six leaf cell types, creating the inaugural single-cell atlas of a maize leaf under fungal assault. Crucially, by reconstructing cellular trajectories in susceptible line N110 and resistant line R99 during infection, we identified diverse regulatory programs that fortify R99's resistance across different leaf cell types. This research uncovers an immune-like state in R99 leaves, characterized by the expression of various fungi-induced genes in the absence of fungal infection, particularly in guard and epidermal cells. Our findings also highlight the role of the fungi-induced glycoside hydrolase family 18 chitinase 7 protein (ZmChit7) in conferring resistance to P. polysora. Collectively, our results shed light on the mechanisms of maize resistance to fungal pathogens through comparative single-cell transcriptomics, offering a valuable resource for pinpointing novel genes that bolster resistance to P. polysora.
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Single-cell multi-omics reveals NUF2 as a potential biomarker associated with the high-lactylation malignant state in osteosarcoma.
BackgroundLactylation has emerged as a crucial post-translational modification that influences oncogenesis and tumor progression. However, its intratumoral heterogeneity in osteosarcoma is not well characterized.MethodsSingle-cell multi-omics data were retrieved from the Gene Expression Omnibus database. Lactylation heterogeneity was assessed, cell-cell communication networks were constructed, and transcription factor activity was analyzed to delineate differences among cell populations. Bioinformatics analysis coupled with experimental validation was employed to screen for potential targets.ResultsThe study revealed that the overall lactylation level was significantly elevated in osteosarcoma tissues compared to adjacent non-tumor tissues. At the single-cell level, osteosarcoma-derived osteoblastic cells exhibited markedly higher lactylation scores than their counterparts from adjacent non-tumor tissue. Bioinformatics analysis identified NUF2 as a potential biomarker associated with the high-lactylation malignant state. Subsequent experimental validation confirmed that NUF2 is overexpressed in osteosarcoma tissues and co-localizes with pan-Kla.ConclusionThis study presents a single-cell lactylation atlas of osteosarcoma, identifies NUF2 as a potential biomarker associated with the high-lactylation malignant state, and provides a novel theoretical basis for the clinical translation of lactylation-targeted therapies.
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Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies.
Glioblastoma multiforme (GBM) is one of the most aggressive cancers with a low overall survival rate. The treatment of GBM is challenging due to the presence of the blood-brain barrier (BBB), which hinders drug delivery. Invasive procedures alone are not effective at completely removing such tumors. Hence, identifying the crucial pathways and biomarkers for the treatment of GBM is of prime importance. We conducted this study to identify the pathways associated with GBM. We used The Cancer Genome Atlas (TCGA) GBM genomic dataset to identify differentially expressed genes (DEGs). We investigated the prognostic values of the guanine nucleotide-binding protein G(i) alpha subunit (GNAI) family of genes in GBM using a Chinese Glioma Genome Atlas (CGGA) dataset. Within this dataset, we observed the association in the tumor microenvironment between the gene expression of GNAI subunit 3 (GNAI3) and a poor prognosis. MetaCore and gene ontology (GO) analyses were conducted to explore the role of GNAI3 in co-expressed genes and associated signaling pathways using a transcript analysis. Notable pathways included "Cytoskeleton remodeling regulation of actin cytoskeleton organization by the kinase effectors of Rho GTPases" and "Immune response B cell antigen receptor (BCR) pathway". A single-cell analysis was used to assess GNAI3 expression in GBM. The results demonstrated that GNAI family genes, specifically GNAI3, were significantly associated with carcinogenesis and malignancy in GBM patients. Our findings suggest that the GNAI3 gene holds potential as a prognostic biomarker for GBM.
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A necroptosis-regulated model from single-cell analysis that predicts survival and identifies the Pivotal role of MAGEA6 in hepatocellular carcinoma.
OBJECTIVE: Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related deaths, constituting 75%-85 % of all primary liver cancers. The objective of this study was to develop a necroptosis-related gene signature using single-cell and bulk RNA sequencing to predict HCC patient prognoses. METHODS: A total of 25 key necroptosis regulators were identified from previous literature. We evaluated the necroptosis scores of different cell types using single-cell sequencing data from HCC and analyzed 168 necroptosis-related genes. The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset served as the training set for establishing a novel necroptosis-related gene risk signature, employing univariate and multivariate Cox regression analyses. Additionally, the study examined the model's relevance in immunity and immunotherapy, and predicted chemosensitivity in HCC patients based on the gene signature. The key genes were validated by the biological experiments. RESULTS: Compared to other cell types, hepatoma cells displayed the lowest necroptosis scores. A new six-gene necroptosis-related signature (S100A11, MAGEC2, MAGEA6, CTP2C9, SOX4, AKR1B10) was developed using the TCGA database and validated in the ICGC database. Patients in the high-risk category had poorer prognoses, with the risk score serving as an independent prognostic indicator beyond other clinical factors. These high-risk patients also exhibited greater immune infiltration but demonstrated a weaker anti-tumor response due to elevated expression of immune checkpoints. Pathways involving hypoxia, glycolysis, and P53, as well as the frequency of P53 somatic mutations, were notably heightened in the high-risk group. Additionally, the six genes in the model showed significantly different mRNA expression in hepatoma cell lines compared to normal hepatocytes, with the role of MAGEA6 in liver cancer being elucidated through critical experiments. CONCLUSIONS: This study successfully developed a six-gene necroptosis-related signature to predict prognoses in HCC patients. It further explored the roles of necroptosis in hepatoma cells and the tumor microenvironment.
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Single cell transcriptional analysis of human adenoids identifies molecular features of airway microfold cells.
The nasal, oropharyngeal, and bronchial mucosa are primary contact points for airborne pathogens like Mycobacterium tuberculosis (Mtb), SARS-CoV-2, and influenza virus. While mucosal surfaces can function as both entry points and barriers to infection, mucosa-associated lymphoid tissues (MALT) facilitate early immune responses to mucosal antigens. MALT contains a variety of specialized epithelial cells, including a rare cell type called a microfold cell (M cell) that functions to transport apical antigens to basolateral antigen-presenting cells, a crucial step in the initiation of mucosal immunity. M cells have been extensively characterized in the gastrointestinal (GI) tract in murine and human models. However, the precise development and functions of human airway M cells is unknown. Here, using single-nucleus RNA sequencing (snRNA-seq), we generated an atlas of cells from the human adenoid and identified 16 unique cell types representing basal, club, hillock, and hematopoietic lineages, defined their developmental trajectories, and determined cell-cell relationships. Using trajectory analysis, we found that human airway M cells develop from progenitor club cells and express a gene signature distinct from intestinal M cells. Surprisingly, we also identified a heretofore unknown epithelial cell type demonstrating a robust interferon-stimulated gene signature. Our analysis of human adenoid cells enhances our understanding of mucosal immune responses and the role of M cells in airway immunity. This work also provides a resource for understanding early interactions of pathogens with airway mucosa and a platform for development of mucosal vaccines.
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Ubiquitylation-oxaliplatin-related prognosis signature reveals the landscapes of immune responses, cell communication, and therapeutic sensitivity for colorectal cancer.
Ubiquitylation plays a crucial role in posttranslational modification, and its dysregulation is linked to chemosensitivity. However, its role in oxaliplatin (OXA) resistance in colorectal cancer (CRC) remains unclear. Transcriptomic data from the cancer genome atlas (TCGA) and Gene Expression Omnibus were used to develop a ubiquitylation-OXA resistance-related risk score (URGScore), integrating immunological, mutational, and clinical features. Single-cell RNA sequencing (scRNA-seq) identified OXA-resistant cell populations, and Genomics of Drug Sensitivity in Cancer predicted drug sensitivity. GSVA analyzed enriched pathways. Ubiquitin-specific protease 7 (USP7) expression and function were validated in CRC. A 10-gene OXA resistance signature effectively classified CRC patients into OXA-sensitive or -resistant groups. Low-URGScore patients showed greater benefit from immunotherapy. scRNA-seq highlighted the MK signaling pathway, particularly in dendritic cells and progenitors, with NCL as a key MK receptor directly interacting with USP7. Potential drugs for high-risk patients were identified. Functionally, USP7 promoted CRC proliferation, invasion, and OXA resistance in vitro. We generated an ubiquitylation-OXA-resistant CRC risk model that was employed to provide potential therapeutic targets and strategies for treating CRC patients exhibiting OXA-resistance.
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CAF signature predicts the prognosis of colorectal cancer patients: A retrospective study based on bulk RNA sequencing and single-cell RNA sequencing data.
The incidence rate and mortality rate of colorectal cancer (CRC) ranks third and second globally. Cancer-associated fibroblasts (CAFs) are the major constituent of the stromal cells in the tumor microenvironment (TME) and are closely associated with patients' prognoses. Our study intended to establish a prognostic model for CRC using hallmark genes of CAFs. The expression values of genes and clinicopathological characteristics of patients were enrolled from the cancer genome atlas database as well as the gene expression omnibus database. The single-cell RNA sequencing data were collected and analyzed in the deeply integrated human single-cell omics database and cancer single-cell expression map databases. The ESTIMATE algorithm was applied to access the infiltration levels of immune and stromal cells. The prognostic genes were selected by the Cox regression analysis and the prognostic signature was constructed by the least absolute shrinkage and selection operator algorithm. gene set enrichment analysis was used to explore the enriched gene sets. In this study, based on bulk RNA sequencing and single-cell RNA sequencing data, and we found that more CAFs were infiltrated in the tumor microenvironment and consisted of 3 subtypes. Then we constructed a prognostic signature for CRC using hallmark genes of CAFs and proved that this signature exhibited high values to predict the overall survival of CRC patients in independent training and validating cohorts. Besides, function enrichment analysis revealed that our prognostic model was significantly associated with immune regulation. Further analysis showed that the infiltrated levels of tumor-suppressing immune cells and the expression of higher immune checkpoint genes in CRC tissues were higher in patients with high-risk scores. Furthermore, immunohistochemistry analysis exhibited that these genes in our prognostic signature were markedly upregulated in CRC tissues. We first constructed a signature based on CAFs hallmark genes to predict the survival of CRC patients and further revealed that the tumor-suppressing microenvironment and dysregulated immune checkpoint genes in CRC tissues were partly responsible for the poor prognosis of patients.
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A Balancing Act in Corneal Epithelial Repair: A MAPK-JUN/EGR1/TFAP2A Network Regulates Ferroptotic Cell Fate.
OBJECTIVE: To explore the role of ferroptosis in the process of corneal epithelial repair and to elucidate the underlying molecular regulatory mechanisms. METHODS: This study performed transcriptomic analysis based on the zebrafish corneal epithelial repair dataset (GSE193784). We intersected differentially expressed genes with the core weighted gene co-expression network analysis (WGCNA) module, and integrated Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network construction, and cross-referencing with the FerrDb v2 database to screen for key ferroptosis-related molecules involved in the repair process. Subsequently, using an Erastin-induced ferroptosis model in human corneal epithelial cells (HCE-T), we performed in vitro validation via RT-qPCR. Additionally, we compared the identified transcriptomic signatures with the latest mammalian and human single-cell atlases to assess cross-species conservation. RESULTS: A total of 252 differentially expressed genes (DEGs) were identified, Intersection with the antiquewhite1 WGCNA module, which is most highly correlated with corneal epithelial repair, yielded 99 overlapping genes. Functional enrichment analysis revealed their significant roles in transcriptomic reprogramming, with a prominent enrichment in the MAPK signaling pathway. Further cross-screening using a PPI network and the FerrDb v2 database pinpointed three core biological factors: jun, egr1, and tfap2a. In vitro experimental verification revealed their differential expression patterns of JUN downregulation, EGR1 upregulation and TFAP2A downregulation under ferroptosis stress. Cross-species bioinformatic comparisons demonstrated that this MAPK-driven transcriptomic reprogramming is highly consistent with the hyper-proliferative and highly plastic cellular states observed during mammalian and human corneal repair. CONCLUSION: This study found that JUN, EGR1 and TFAP2A, the core biological factors in the corneal epithelial repair process, are closely related to ferroptosis. This suggests that key biological factors enriched in the MAPK pathway may affect corneal epithelial repair by regulating ferroptosis.
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NUP85 as a Pan-Cancer Immune Biomarker: Integrated Multi Omics and Functional Analyses Reveal Its Role in Tumor Prognosis.
PURPOSE: NUP85 encodes protein components of the Nup107-160 subunit of the nuclear pore complex, belonging to the Nucleoporins (NUPs) family, potentially implicating its role in human cancer. This study aims to elucidate the potential involvement of NUP85 in cancer pathogenesis. METHODS: Leveraging data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Clinical Proteomic Tumor Analysis Consortium (CPTAC), Cancer Cell Line Encyclopedia (CCLE), Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), CellMiner, and GeneMANIA databases, we investigated the role of NUP85 across various tumors. Correlations between NUP85 expression and pathological stage, histological grade, survival, immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), drug resistance, DNA methylation, copy number variation (CNV), and single-cell expression were analyzed. Gene functional enrichment analysis was conducted to explore NUP85-associated pathways. Molecular biology experiments including Western blotting, flow cytometry, trans-well migration, and invasion assays were performed to validate NUP85's oncogenic role in lung adenocarcinoma (LUAD) and oral squamous cell carcinoma (OSCC) cell lines. RESULTS: Our findings reveal up-regulated expression of NUP85 in most tumor tissues, with significant correlations observed with pathological stage, survival, immune infiltration, TMB, MSI, drug resistance, DNA methylation, and CNV. Molecular biology experiments confirm NUP85's tumor-promoting role in LUAD and OSCC cell lines. Single-cell sequencing data suggest elevated NUP85 expression primarily in proliferative T cells (Tprolif). CONCLUSION: NUP85 emerges as a potential tumor marker associated with tumor immunity and poor prognosis. These insights offer avenues for the development of novel therapeutic targets and anti-neoplastic drugs.
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Construction of a prognostic model related to copper dependence in breast cancer by single-cell sequencing analysis.
Purpose: To explore the clinical significance of copper-dependent-related genes (CDRG) in female breast cancer (BC). Methods: CDRG were obtained by single-cell analysis of the GSE168410 dataset in the Gene Expression Omnibus (GEO) database. According to a 1:1 ratio, the Cancer Genome Atlas (TCGA) cohort was separated into a training and a test cohort randomly. Based on the training cohort, the prognostic model was built using COX and Lasso regression. The test cohort was used to validate the model. The GSE20685 dataset and GSE20711 dataset were used as two external validation cohorts to further validate the prognostic model. According to the median risk score, patients were classified as high-risk or low-risk. Survival analysis, immune microenvironment analysis, drug sensitivity analysis, and nomogram analysis were used to evaluate the clinical importance of this prognostic model. Results: 384 CDRG were obtained by single-cell analysis. According to the prognostic model, patients were classified as high-risk or low-risk in both cohorts. The high-risk group had a significantly worse prognosis. The area under the curve (AUC) of the model was around 0.7 in the four cohorts. The immunological microenvironment was examined for a possible link between risk score and immune cell infiltration. Veliparib, Selumetinib, Entinostat, and Palbociclib were found to be more sensitive medications for the high-risk group after drug sensitivity analysis. Conclusion: Our CDRG-based prognostic model can aid in the prediction of prognosis and treatment of BC patients.