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Comprehensive analysis of basement membrane-related gene based on single-cell and bulk RNA sequencing data to predict prognosis and evaluate immune characteristics in colorectal cancer.
AIMS: Basement membrane-related genes (BMs) participate in regulating cell polarity, invasion, metastasis, and survival across different tumor types. Nevertheless, the specific functions of BMs in colorectal cancer (CRC) remain uncertain. METHODS: To investigate the clinical relevance of BMs in CRC, we retrieved both gene expression and clinical data from The Cancer Genome Atlas (TCGA) datasets for subsequent analysis. The Kaplan-Meier (K-M) survival curve was employed to evaluate prognosis in high- and low-risk groups. Furthermore, additional analyses, including nomogram construction, functional enrichment, examination of the tumor immune microenvironment, prediction of small-molecule drugs, and more, were conducted to delve into the significance of BM-related signatures in CRC. Single-cell data from seven CRC patients were obtained from the TISCH2 database, and expression validation and cell source exploration of BM-related signatures were performed. Lastly, the expression and function of TIMP1, a key gene in BMs that may play a role in the progression of CRC, was validated in vitro through a series of basic experiments. RESULTS: We constructed a seven BMs-based model to categorize CRC patients into high-risk and low-risk groups. K-M survival analysis indicated a poorer prognosis for high-risk CRC patients. Cox regression analysis further identified the risk score as an independent prognostic factor for CRC patients. The nomogram model exhibited superior discrimination and calibration abilities of CRC patients. Based on the results from GO/KEGG and GSEA, genes in the high-risk subgroup were implicated in immune-related pathways and exhibited a positive correlation with immune checkpoints. In single-cell data, we found that TIMP1 is highly expressed in many cells, especially in malignant tumor cells. We also observed up-regulation of TIMP1 in CRC cell lines, promoting cancer invasion and migration in vitro. CONCLUSIONS: Our study has discovered a novel prognostic index derived from BM-related genes in CRC patients. Specifically, the new model enables patient stratification, improving the selection of individuals likely to benefit from immunotherapy.
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Single-Cell and Spatial Transcriptomics Reveals a Stereoscopic Response of Rice Leaf Cells to Magnaporthe oryzae Infection.
Infection by the fungal pathogen Magnaporthe oryzae elicits dynamic responses in rice. Utilizing an integrated approach of single-cell and spatial transcriptomics, a 3D response is uncovered within rice leaf cells to M. oryzae infection. A comprehensive rice leaf atlas is constructed from 236 708 single-cell transcriptomes, revealing heightened expression of immune receptors, namely Pattern Recognition Receptors (PRRs) and Nucleotide-binding site and leucine-rich repeat (NLRs) proteins, within vascular tissues. Diterpene phytoalexins biosynthesis genes are dramatically upregulated in procambium cells, leading to an accumulation of these phytoalexins within vascular bundles. Consistent with these findings, microscopic observations confirmed that M. oryzae is prone to target leaf veins for invasion, yet is unable to colonize further within vascular tissues. Following fungal infection, basal defenses are extensively activated in rice cells, as inferred from trajectory analyses. The spatial transcriptomics reveals that rice leaf tissues toward leaf tips display stronger immunity. Characterization of the polarity gene OsHKT9 suggests that potassium transport plays a critical role in resisting M. oryzae infection by expression along the longitudinal axis, where the immunity is stronger toward leaf tip. This work uncovers that there is a cell-specific and multi-dimensional (local and longitudinal) immune response to a fungal pathogen infection.
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The role of immune- and lipid metabolism-related genes in macrophage polarization and prognosis of glioblastoma.
OBJECTIVE: To investigate the roles of immune- and lipid metabolism-related genes in macrophage polarization and their prognostic and therapeutic implications in glioblastoma (GBM). METHODS: A total of 655 GBM samples from The Cancer Genome Atlas (TCGA) were stratified into immune and non-immune groups based on immune scores. Differentially expressed genes (DEGs) were identified, and their intersection with 859 lipid metabolism-related genes yielded 26 candidates. A 10-gene prognostic signature was constructed using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses and validated in both internal (TCGA) and independent (Chinese Glioma Genome Atlas, CGGA) cohorts. Functional enrichment, single-cell transcriptomic analysis, experimental validation, and drug sensitivity profiling were performed to assess the biological and therapeutic relevance of the identified genes. RESULTS: Ten immune- and lipid metabolism-related genes were significantly associated with GBM prognosis. Key genes such as LGALS1, PLA2G5, and FABP5 were upregulated in high-risk patients and enriched in M2-like tumor-associated macrophages. Enrichment analyses indicated their involvement in immune regulation and lipid metabolic pathways. Their elevated expression in GBM tissues was confirmed by qRT-PCR and Western blot. Drug sensitivity analysis demonstrated a correlation between LGALS1 expression and the response to agents such as zoledronate and staurosporine. CONCLUSIONS: Immune- and lipid metabolism-related genes contribute to macrophage polarization and are closely linked to GBM prognosis. The identified gene signature provides prognostic value and potential therapeutic targets for immunometabolic modulation in GBM.
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Dynamic DNA methylation across diverse human cell lines and tissues.
As studies of DNA methylation increase in scope, it has become evident that methylation has a complex relationship with gene expression, plays an important role in defining cell types, and is disrupted in many diseases. We describe large-scale single-base resolution DNA methylation profiling on a diverse collection of 82 human cell lines and tissues using reduced representation bisulfite sequencing (RRBS). Analysis integrating RNA-seq and ChIP-seq data illuminates the functional role of this dynamic mark. Loci that are hypermethylated across cancer types are enriched for sites bound by NANOG in embryonic stem cells, which supports and expands the model of a stem/progenitor cell signature in cancer. CpGs that are hypomethylated across cancer types are concentrated in megabase-scale domains that occur near the telomeres and centromeres of chromosomes, are depleted of genes, and are enriched for cancer-specific EZH2 binding and H3K27me3 (repressive chromatin). In noncancer samples, there are cell-type specific methylation signatures preserved in primary cell lines and tissues as well as methylation differences induced by cell culture. The relationship between methylation and expression is context-dependent, and we find that CpG-rich enhancers bound by EP300 in the bodies of expressed genes are unmethylated despite the dense gene-body methylation surrounding them. Non-CpG cytosine methylation occurs in human somatic tissue, is particularly prevalent in brain tissue, and is reproducible across many individuals. This study provides an atlas of DNA methylation across diverse and well-characterized samples and enables new discoveries about DNA methylation and its role in gene regulation and disease.
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Mapping the immune cells of the testis: Key insights into sexual maturation.
BACKGROUND: The testicular immune microenvironment sustains homeostasis and immune privilege. However, the presence and functional significance of B cells within this specialized niche remain poorly characterized. Furthermore, the intricate crosstalk between resident immune populations and testicular stromal cells that may orchestrate the immunological and endocrine microenvironment during sexual maturation warrants systematic investigation. OBJECTIVE: To systematically delineate the immune cell atlas and developmental trajectory of testicular leukocytes before and after sexual maturation. MATERIALS AND METHODS: An integrated analysis of leukocytes in post-sexual maturity (8-week-old) and pre-sexual maturity (2-week-old) mouse testes using single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF), was performed. Magnetic-activated cell sorting (MACS) isolated immune subsets, followed by bioinformatics interrogation of cellular heterogeneity and ligand-receptor network analysis to map intercellular communication pathways. RESULTS: Through scRNA-seq clustering analysis, we resolved 18 distinct leukocyte populations (11 lymphoid and seven myeloid lineages), which were further validated and expanded to 17 phenotypically discrete subsets (eight lymphoid and nine myeloid) via high-dimensional CyTOF profiling. Notably, we identified a rare but functionally significant B lymphocyte population within the testicular compartment. The myeloid compartment exhibited pronounced developmental plasticity, marked by progressive Il1b+Macrophages diminution and regulatory T cell expansion during maturation. Cell communication network analysis revealed intensified ligand-receptor cross-talk between androgen-producing Leydig cells and CD8+ T lymphocytes in post-pubertal testes, providing mechanistic insights into age-dependent immune privilege establishment. DISCUSSION AND CONCLUSIONS: Multi-omics integration reveals dynamic immune remodeling during testicular maturation. These findings underscore the potential involvement of B cells in local immune surveillance while identifying maturation-associated signaling axes between stromal and immune cells. This comprehensive mapping of testicular leukocyte dynamics significantly advances our understanding of reproductive immunology and lays foundation for investigating immune-mediated testicular pathologies.
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Protein large language model-assisted one-to-one gene homology mapping in cross-species single-cell transcriptome integration.
Cross-species integration of single-cell transcriptomes requires establishing gene correspondences to enable comparative analysis of expression profiles across organisms. Current approaches predominantly rely on Ensembl homology tables; although gene-family expansion and contraction can reflect biologically meaningful evolutionary divergence, default many-to-many mappings can overweight expanded gene-family signals during integration and generate mapping-associated microclusters that lack clear cell-type identity, thereby complicating direct cell-type alignment. Although restricting mappings to a one-to-one scheme suppresses such artifacts, it reduces the number of homology gene pairs by ∼8% (about 900 pairs). To address this limitation, we develop a protein large language model (pLLM)-based gene homology mapping strategy that boosts the number of homology gene pairs. By enforcing a one-to-one mapping constraint and integrating pLLM-derived representations with sequence similarity, we construct a fused mapping approach, which achieves top performance in a comprehensive benchmark based on a curated cross-species atlas spanning nine data sets, 11 species, and more than 3.2 million cells. Our method further identifies previously unannotated cell-type marker pairs, facilitating novel cross-species marker discovery. These results establish a robust framework for gene homology mapping in cross-species transcriptome integration, improving both accuracy and biological interpretability.
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A Meta-Atlas of the Developing Human Cortex Identifies Modules Driving Cell Subtype Specification.
Human brain development requires the generation of hundreds of diverse cell types, a process targeted by recent single-cell transcriptomic profiling efforts. Through a meta-analysis of seven of these published datasets, we have generated 225 meta-modules - gene co-expression networks that can describe mechanisms underlying cortical development. Several meta-modules have potential roles in both establishing and refining cortical cell type identities, and we validated their spatiotemporal expression in primary human cortical tissues. These include meta-module 20, associated with FEZF2+ deep layer neurons. Half of meta-module 20 genes are putative FEZF2 targets, including TSHZ3, a transcription factor associated with neurodevelopmental disorders. Human cortical organoid experiments validated that both factors are necessary for deep layer neuron specification. Importantly, subtle manipulations of these factors drive slight changes in meta-module activity that cascade into strong differences in cell fate - demonstrating how of our meta-atlas can engender further mechanistic analyses of cortical fate specification.
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Turkey oviduct epithelial organoids express region-associated markers and avian influenza virus receptors†.
The turkey reproductive tract is a notable point of entry for low pathogenic avian influenza virus (AIV), largely due to the widespread use of artificial insemination. Despite this relevance, in vitro models to investigate AIV infectivity remain limited. To address this, we recently developed region-specific turkey oviduct epithelial organoids; however, comprehensive characterization of these models requires identification and validation of regional markers. This study aimed to validate the soundness of these organoid models. To achieve this, single-cell ribonucleic acid sequencing (scRNA-seq) was performed on six oviductal regions: infundibulum (INF), magnum (Mag), isthmus, uterus (Utr), uterovaginal junction (UVJ), and vagina, collected from two sexually mature hens (Meleagris gallopavo), to identify cell-type specific markers. Sub-clustering of epithelial cells suggested region-associated gene expression profiles. Bulk RNA sequencing (n = 2) and immunofluorescence staining (n = 4) of organoids derived from INF, Mag, Utr, and UVJ indicated the expression and localization of WT1, OVAL, BGLAP, and PSCA, respectively, consistent with the respective tissues. Notably, organoids expressed AIV-associated genes and displayed comparable distributions of SA α2,3-gal receptors (AIV receptors) in tissues and organoids. These findings suggest that turkey oviduct epithelial organoids appear to retain region-associated molecular identities and AIV receptor expression, supporting their application as in vitro models. This exploratory niche study presents the first initial framework for a single-cell atlas of the turkey reproductive tract and provides a foundational resource for further reproductive physiology, AIV infectivity, and preventive research using organoid systems.
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Construction of the Single-Cell Landscape of Hashimoto's Thyroiditis Tissue and Peripheral Blood by Single-Cell RNA Sequencing.
BACKGROUND: Hashimoto's thyroiditis (HT) is the most common organ-specific autoimmune disease, and its etiology may be related to genetic, environmental, and epigenetic factors. However, its exact pathogenesis remains elusive. METHODS: In this study, single-cell transcriptomic sequencing and bioinformatics analysis were performed on the thyroid tissues of six HT patients, peripheral blood mononuclear cells (PBMCs) of four HT patients, and normal thyroid tissue of one healthy control. A panoramic single-cell atlas of HT was constructed to explore changes in the abundance of different cell subsets in the states of the disease. RESULTS: A single-cell atlas of HT was constructed, and eight cell types were defined based on the marker genes. Subsequent clustering analysis of T cells, B cells, myeloid, and thyroid follicular cells revealed that the abundance rates of the CD8+T_CCL4L2, B_MEF2B_BCL6, Mac_APOE, Mac_IL1B, and TFC_PAX8_NKX2-1 subgroups were elevated in thyroid tissues of HT patients. However, the abundance rate of the NKT_KLRD1_KLRC2 subgroup was risen in the PBMCs of HT patients. Ig-producing plasma cells were specifically enriched in the B-cell subgroup. CONCLUSION: The present study further validated the role of immune cells in the pathogenesis of HT at the cellular level. In addition, a new cell subset B_MEF2B_BCL6 was found. It could be speculated that MEF2B mainly transactivates the expression level of the transcriptional repressor BCL6, leading to the development of HT. A new cell subset TFC_PAX8_NKX2-1 was also identified, in which the specific transcription factors PAX8 and NKX2-1 were highly expressed in HT tissues.
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Integrated immunogenomic analysis of single-cell and bulk profiling reveals novel tumor antigens and subtype-specific therapeutic agents in lung adenocarcinoma.
BACKGROUND: In recent years, mRNA-based vaccines with promising safety and functional characteristics have gained significant momentum in cancer immunotherapy. However, stable immunological molecular subtypes of lung adenocarcinoma (LUAD) and novel tumor antigens for LUAD mRNA vaccine development remain elusive. Therefore, a novel approach is urgently needed to identify suitable LUAD subtypes and potential tumor antigens. METHODS: The Cancer Genome Atlas (TCGA), the Genotype Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases were utilized to retrieve gene expression data. The LUAD Immunological Multi-Omics Classification (LIMOC) system was developed using seven machine learning (ML) algorithms by performing integrative immunogenomic analysis of single-cell and bulk tissue transcriptome profiling. Subsequently, a panel of approaches was applied to identify novel tumor antigens. RESULTS: First, the LIMOC system was construct to identify three subtypes: LIMOC1, LIMOC2, and LIMOC3. Second, we identified CHIT1, LILRA4, and MEP1A as novel tumor antigens in LUAD; these genes were up-regulated, amplified, and mutated, and showed a positive association with APC infiltration, making them promising candidates for designing mRNA vaccines. Notably, the LIMOC2 subtype had the worst prognosis and could benefit most from mRNA immunization. Furthermore, we performed a comprehensive in silico screening of approximately 2000 compounds and identified Sorafenib and Azacitidine as potential subtype-specific therapeutic agents. CONCLUSIONS: Overall, our study established a robust LIMOC system and identified CHIT1, LILRA4, and MEP1A as promising tumor antigen candidates for development of anti-LUAD mRNA vaccines, particularly for the LIMOC2 subtype.