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Increased IL4I1 expression predicts poor survival and modulates the immune microenvironment in acute myeloid leukemia.
BACKGROUND: The immunometabolic enzyme Interleukin-4-induced-1 (IL4I1) is implicated in cancer pathogenesis, yet its specific function and clinical relevance in acute myeloid leukemia (AML) remain unclear. METHODS: Comparative analysis of IL4I1 mRNA levels between AML patients and normal controls was performed using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The Kaplan–Meier survival analysis was conducted to evaluate the prognostic value of IL4I1. Functional insights were derived from analyses of differentially expressed genes (DEGs), Gene Set Enrichment Analysis (GSEA), and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Immune infiltration was evaluated using the ssGSEA, ESTIMATE, quanTIseq and single-cell RNA sequencing (scRNA-seq) analysis. Finally, in vitro and in vivo functional experiments were perfromed to explore the impact of IL4I1 on AML progression and immunoregulation. RESULTS: IL4I1 expression was significantly elevated in AML compared to normal controls (p = 0.0004) and associated with poorer overall survival (p = 0.003). Bioinformatic analysis revealed that IL4I1 was linked to immune-related pathways—including humoral immune response, leukocyte interactions, and chemokine signaling—and to cellular amino acid metabolism. Its expression correlated with immune cell infiltration and checkpoint molecule expression. Experimentally, IL4I1 promoted leukemia cell proliferation in vitro and in vivo (p < 0.05). Furthermore, silencing IL4I1 suppressed M2 macrophage polarization and reduced secretion of inflammatory factors (p < 0.05). CONCLUSIONS: IL4I1 may serve as a potential biomarker for poor prognosis and an attractive target for immune-based therapeutic interventions in AML.
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Heterogeneity and Differentiation Trajectories of Infiltrating CD8+ T Cells in Lung Adenocarcinoma.
CD8+ T cells infiltrating the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) are critical for establishing antitumor immunity. Nevertheless, the global landscape of their numbers, functional status, and differentiation trajectories remains unclear. In the single-cell RNA-sequencing (scRNA-seq) dataset GSE131907 of LUAD, the CD8+T cells were selected for TSNE clustering, and the results showed that they could be divided into ten subsets. The cell differentiation trajectory showed the presence of abundant transition-state CD8+ T cells during the differentiation of naive-like CD8+ T cells into cytotoxic CD8+ T cells and exhausted CD8+ T cells. The differentially expressed marker genes among subsets were used to construct the gene signature matrix, and the proportion of each subset was identified and calculated in The Cancer Genome Atlas (TCGA) samples. Survival analysis showed that the higher the proportion of the exhausted CD8+ T lymphocyte (ETL) subset, the shorter the overall survival (OS) time of LUAD patients (p = 0.0098). A total of 61 genes were obtained by intersecting the differentially expressed genes (DEGs) of the ETL subset, and the DEGs of the TCGA samples were divided into a high and a low group according to the proportion of the ETL subset. Through protein interaction network analysis and survival analysis, four hub genes that can significantly affect the prognosis of LUAD patients were finally screened, and RT-qPCR and Western blot verified the differential expression of the above four genes. Our study further deepens the understanding of the heterogeneity and functional exhaustion of infiltrating CD8+ T cells in LUAD. The screened prognostic marker genes provide potential targets for targeted therapy and immunotherapy in LUAD patients.
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Temporal specificity and heterogeneity of Drosophila immune cells.
Immune cells provide defense against non-self and have recently been shown to also play key roles in diverse processes such as development, metabolism, and tumor progression. The heterogeneity of Drosophila immune cells (hemocytes) remains an open question. Using bulk RNA sequencing, we find that the hemocytes display distinct features in the embryo, a closed and rapidly developing system, compared to the larva, which is exposed to environmental and metabolic challenges. Through single-cell RNA sequencing, we identify fourteen hemocyte clusters present in unchallenged larvae and associated with distinct processes, e.g., proliferation, phagocytosis, metabolic homeostasis, and humoral response. Finally, we characterize the changes occurring in the hemocyte clusters upon wasp infestation, which triggers the differentiation of a novel hemocyte type, the lamellocyte. This first molecular atlas of hemocytes provides insights and paves the way to study the biology of the Drosophila immune cells in physiological and pathological conditions.
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Targeting the TREM1-positive myeloid microenvironment in glioblastoma.
BACKGROUND: Tumor cellular and molecular heterogeneity is a hallmark of glioblastoma and underlies treatment resistance and recurrence. This manuscript investigated the myeloid-derived microenvironment as a driver of glioblastoma heterogeneity and provided a pharmacological pathway for its suppression. METHODS: Transcriptomic signatures of glioblastoma infiltrated myeloid-derived cells were assessed using R2: genomic platform, Ivy Glioblastoma Spatial Atlas, and single-cell RNA-seq data of primary and recurrent glioblastomas. Myeloid-derived cell prints were evaluated in five PDX cell lines using RNA-seq data. Two immunocompetent mouse glioblastoma models were utilized to isolate and characterize tumor-infiltrated myeloid-derived cells and glioblastoma/host cell hybrids. The ability of an inhibitor of HuR dimerization SRI42127 to suppress TREM1+-microenvironment and glioblastoma/myeloid-derived cell interaction was assessed in vivo and in vitro. RESULTS: TREM1+-microenvironment is enriched in glioblastoma peri-necrotic zones. TREM1 appearance is enhanced with tumor grade and associated with poor patient outcomes. We confirmed an expression of a variety of myeloid-derived cell markers, including TREM1, in PDX cell lines. In mouse glioblastoma models, we demonstrated a reduction in the TREM1+-microenvironment and glioblastoma/host cell fusion after treatment with SRI42127. In vitro assays confirmed inhibition of cell fusion events and reduction of myeloid-derived cell migration towards glioblastoma cells by SRI42127 and TREM1 decoy peptide (LP17) versus control treatments. CONCLUSIONS: TREM1+-myeloid-derived microenvironment promulgates glioblastoma heterogeneity and is a therapeutic target. Pharmacological inhibition of HuR dimerization leads to suppression of the TREM1+-myeloid-derived microenvironment and the neoplastic/non-neoplastic fusogenic cell network.
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Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features.
Cancer arises from extensive genetic and epigenetic alterations that reshape chromatin, transcriptional regulation, and malignant cell states. To systematically chart cancer-intrinsic regulatory programs, we constructed a pan-cancer single-cell transcriptomic and epigenomic atlas encompassing 60 human cell lines representing 16 tissue origins and 20 cancer types, comprising 240,957 single-nucleus RNA-seq and 223,347 single-nucleus ATAC-seq profiles. Integrative analyses revealed extensive pan-cancer cell-state heterogeneity, core gene-regulatory networks, and a conserved epithelial-mesenchymal transition (EMT) axis that transcends tissue of origin. Copy-number variation analysis identified transcription factor amplification and downstream hyperactivation as key drivers of cancer cell-state reprogramming. To further examine how regulatory programs diverge within a cancer lineage and contribute to clinically divergent outcomes, we performed a focused comparison of cutaneous melanoma with acral melanoma, a rare, UV-independent subtype underrepresented in existing pan-cancer atlases. The comparison uncovered a universal inflammation-suppressive program in acral melanoma and an inflamed regulatory landscape in cutaneous melanoma, with the JAK-STAT pathway and downstream transcriptional responses as central discriminators. Integration of single-cell and bulk datasets across models and patient cohorts further linked in vitro tumor-intrinsic gene regulations with in vivo microenvironmental composition and immunotherapy responses. Together, by extending single-cell multi-omic profiling to rare alongside common cancer subtypes, this atlas offers a resource for mapping pan-cancer and subtype-specific gene-regulatory programs that shape cancer cell-state plasticity.
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A spatially mapped gene expression signature for intestinal stem-like cells identifies high-risk precursors of gastric cancer.
OBJECTIVE: Gastric intestinal metaplasia (GIM) is a precancerous lesion that increases gastric cancer (GC) risk. The Operative Link on GIM (OLGIM) is a combined clinical-histopathologic system to risk-stratify patients with GIM. The identification of molecular biomarkers that are indicators for advanced OLGIM lesions may improve cancer prevention efforts. METHODS: This study was based on clinical and genomic data from four cohorts: 1) GAPS, a GIM cohort with detailed OLGIM severity scoring (N=303 samples); 2) the Cancer Genome Atlas (N=198); 3) a collation of in-house and publicly available scRNA-seq data (N=40), and 4) a spatial validation cohort (N=5) consisting of annotated histology slides of patients with either GC or advanced GIM. We used a multi-omics pipeline to identify, validate and sequentially parse a highly-refined signature of 26 genes which characterize high-risk GIM. RESULTS: Using standard RNA-seq, we analyzed two separate, non-overlapping discovery (N=88) and validation (N=215) sets of GIM. In the discovery phase, we identified 105 upregulated genes specific for high-risk GIM (defined as OLGIM III-IV), of which 100 genes were independently confirmed in the validation set. Spatial transcriptomic profiling revealed 36 of these 100 genes to be expressed in metaplastic foci in GIM. Comparison with bulk GC sequencing data revealed 26 of these genes to be expressed in intestinal-type GC. Single-cell profiling resolved the 26-gene signature to both mature intestinal lineages (goblet cells, enterocytes) and immature intestinal lineages (stem-like cells). A subset of these genes was further validated using single-molecule multiplex fluorescence in situ hybridization. We found certain genes (TFF3 and ANPEP) to mark differentiated intestinal lineages, whereas others (OLFM4 and CPS1) localized to immature cells in the isthmic/crypt region of metaplastic glands, consistent with the findings from scRNAseq analysis. CONCLUSIONS: using an integrated multi-omics approach, we identified a novel 26-gene expression signature for high-OLGIM precursors at increased risk for GC. We found this signature localizes to aberrant intestinal stem-like cells within the metaplastic microenvironment. These findings hold important translational significance for future prevention and early detection efforts.
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Mapping human development at single-cell resolution.
Human development is regulated by spatiotemporally restricted molecular programmes and is pertinent to many areas of basic biology and human medicine, such as stem cell biology, reproductive medicine and childhood cancer. Mapping human development has presented significant technological, logistical and ethical challenges. The availability of established human developmental biorepositories and the advent of cutting-edge single-cell technologies provide new opportunities to study human development. Here, we present a working framework for the establishment of a human developmental cell atlas exploiting single-cell genomics and spatial analysis. We discuss how the development atlas will benefit the scientific and clinical communities to advance our understanding of basic biology, health and disease.
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Single-cell RNA sequencing reveals peripheral immunological features in Parkinson's Disease.
Although many researchers of Parkinson's disease (PD) have shifted their focus from the central nervous system (CNS) to the peripheral blood, a significant knowledge gap remains between PD severity and the peripheral immune response. In the current study, we aimed to map the peripheral immunity atlas in peripheral blood mononuclear cells (PBMCs) from PD patients and healthy controls using single-cell RNA sequencing (scRNA-seq). Our study employed scRNA-seq analysis to map the peripheral immunity atlas in PD by profiling PBMCs from PD-Early, PD-Late patients and matched controls. By enlarging the blood sample size, we validated the roles of NK cells in numerous immune-related biological processes. We also detected the infiltration of NK cells into the cerebral motor cortex as the disease progressed, using human brain sections, and elucidated the communication between the periphery and CNS and its implications for PD. As a result, cell subpopulation atlases in PBMCs from PD patients and healthy controls along with differentially expressed genes in NK cells were identified by scRNA-seq analysis, representing 6 major immune cell subsets among which NK cells declined in the progression of PD. We further validated NK cell reduction in increasing samples and found that they participated in numerous immune-related biological processes and infiltration into the cerebral motor cortex as the disease proceeded, evidencingd the close communication between the peripheral immune response and CNS. Strikingly, XCL2 positively correlated with PD severity, with good predictive performance of PD and specific expression in subclusters C2 and C5 of NK cells. All these findings delineated the critical role of peripheral immune response mediated by NK cells in the pathogenesis of PD. NK cell-specific XCL2 could be used as a diagnostic marker for treating PD. The indispensable function of NK cells and NK cell-specific molecular biomarkers highlighted the implication of the peripheral immune response in PD progression. Trial registration: ChiCTR, ChiCTR1900023975. Registered 20 June 2019 - Retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=31035 .
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A test metric for assessing single-cell RNA-seq batch correction.
Single-cell transcriptomics is a versatile tool for exploring heterogeneous cell populations, but as with all genomics experiments, batch effects can hamper data integration and interpretation. The success of batch-effect correction is often evaluated by visual inspection of low-dimensional embeddings, which are inherently imprecise. Here we present a user-friendly, robust and sensitive k-nearest-neighbor batch-effect test (kBET; https://github.com/theislab/kBET ) for quantification of batch effects. We used kBET to assess commonly used batch-regression and normalization approaches, and to quantify the extent to which they remove batch effects while preserving biological variability. We also demonstrate the application of kBET to data from peripheral blood mononuclear cells (PBMCs) from healthy donors to distinguish cell-type-specific inter-individual variability from changes in relative proportions of cell populations. This has important implications for future data-integration efforts, central to projects such as the Human Cell Atlas.
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Breaking barriers: improving time and space resolution of arbuscular mycorrhizal symbiosis with single-cell sequencing approaches.
The cell and molecular bases of arbuscular mycorrhizal (AM) symbiosis, a crucial plant-fungal interaction for nutrient acquisition, have been extensively investigated by coupling traditional RNA sequencing techniques of roots sampled in bulk, with methods to capture subsets of cells such as laser microdissection. These approaches have revealed central regulators of this complex relationship, yet the requisite level of detail to effectively untangle the intricacies of temporal and spatial development remains elusive.The recent adoption of single-cell RNA sequencing (scRNA-seq) techniques in plant research is revolutionizing our ability to dissect the intricate transcriptional profiles of plant-microbe interactions, offering unparalleled insights into the diversity and dynamics of individual cells during symbiosis. The isolation of plant cells is particularly challenging due to the presence of cell walls, leading plant researchers to widely adopt nuclei isolation methods. Despite the increased resolution that single-cell analyses offer, it also comes at the cost of spatial perspective, hence, it is necessary the integration of these approaches with spatial transcriptomics to obtain a comprehensive overview.To date, few single-cell studies on plant-microbe interactions have been published, most of which provide high-resolution cell atlases that will become crucial for fully deciphering symbiotic interactions and addressing future questions. In AM symbiosis research, key processes such as the mutual recognition of partners during arbuscule development within cortical cells, or arbuscule senescence and degeneration, remain poorly understood, and these advancements are expected to shed light on these processes and contribute to a deeper understanding of this plant-fungal interaction.