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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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In vivo human embryonic spinal cord atlas validates stem cell-derived human dorsal interneurons and reveals ASD spinal signatures.
Spinal cord injuries (SCI) result in the loss of motor and sensory function. We are working towards restoring sensation by developing directed differentiation protocols to generate dorsal spinal interneurons (dIs; dI1-dI6) from human embryonic stem cells (hESCs). Here, we present an improved method that produces human dIs via a neuromesodermal progenitor state, the physiological intermediate for spinal cord development. We show that retinoic acid (RA), bone morphogenetic protein 4 (BMP4) and growth differentiation factor (GDF) 11 direct dI identity, while GDF11 and extended time in culture promotes posterior spinal identities. Together, these protocols generate the full complement of dorsal subtypes along the entire anterior-posterior axis of the spinal cord. To benchmark in vitro-derived dIs, we constructed a single-cell RNA-Seq atlas of the human embryonic spinal cord and used it to show that hESC-derived dIs closely match their endogenous counterparts. The atlas also reveals that the dI4/dI5 populations dramatically expand in comparison with the other spinal lineages. Moreover, they have mechanosensory circuit signatures linked to autism spectrum disorder, implicating spinal circuits in autistic phenotypes.
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MIF-mediated intercellular crosstalk drives antigen-presenting-like cancer-associated fibroblast differentiation in triple-negative breast cancer via TGF-β signaling.
BACKGROUND: Triple-negative breast cancer (TNBC) is characterized by an aggressive tumor microenvironment (TME) in which cancer-associated fibroblasts (CAFs) play a pivotal role. However, the molecular mechanisms governing the transformation of quiescent fibroblasts into distinct CAF subtypes within TNBC remain poorly understood. This study aimed to elucidate the molecular mechanisms underlying fibroblast-to-CAF subtype transition in TNBC and identify key signaling pathways involved in TNBC-driven CAF activation. METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA)-TNBC were analyzed using weighted gene co-expression network analysis (WGCNA). CAF-related scores and TNBC scores were computed via single-sample gene set enrichment analysis (ssGSEA). CAF infiltration was assessed using Estimating the Proportion of Immune and Cancer cells (EPIC). Survival and correlation analyses were validated in the Gene Expression Omnibus (GEO) dataset GSE58812. Single-cell RNA sequencing (scRNA-seq) data (GSE176078) were employed for cell-type annotation, pseudotime trajectory inference, and cell-cell communication analysis. Cell experiments were further performed to explore the mechanisms of fibroblast activation in TNBC. RESULTS: TNBC score was significantly associated with poor prognosis and positively correlated with CAF score/infiltration. Single-cell analysis revealed antigen-presenting CAFs (apCAFs) as the predominant CAF subtype in TNBC. Pseudotime trajectory analysis showed that 96 genes uniquely involved in quiescent-to-apCAF-like differentiation were enriched in TGF-β signaling. Cell-cell communication analysis identified macrophage migration inhibitory factor (MIF)-(CD74 + CXCR4) as significantly enhanced during TNBC-apCAF interactions but absent in TNBC-myofibroblastic CAF (myCAF) crosstalk. Four hub genes, including CNTN4, NLGN1, NLGN4X, and SEMA5A, were identified as associated with the differentiation stage: CNTN4/NLGN1 in MIF-mediated signal initiation and NLGN4X/SEMA5A in the intracellular TGF-β execution phase. Cell experiments revealed that the MIF-CD74/CXCR4 axis promotes apCAF-like differentiation via the TGF-β pathway and enhances malignant phenotypes of TNBC cells. CONCLUSIONS: A TNBC-to-apCAF signaling axis was identified wherein TNBC-secreted MIF activates CD74/CXCR4 on fibroblasts, engaging TGF-β signaling to drive apCAF-like differentiation. These findings offer potential therapeutic targets for disrupting the pro-tumorigenic microenvironment in TNBC.
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A single cell atlas of the mouse seminal vesicle.
During mammalian reproduction, sperm are delivered to the female reproductive tract bathed in a complex medium known as seminal fluid, which plays key roles in signaling to the female reproductive tract and in nourishing sperm for their onwards journey. Along with minor contributions from the prostate and the epididymis, the majority of seminal fluid is produced by a somewhat understudied organ known as the seminal vesicle. Here, we report the first single-cell RNA-seq atlas of the mouse seminal vesicle, generated using tissues obtained from 23 mice of varying ages, exposed to a range of dietary challenges. We define the transcriptome of the secretory cells in this tissue, identifying a relatively homogeneous population of the epithelial cells which are responsible for producing the majority of seminal fluid. We also define the immune cell populations - including large populations of macrophages, dendritic cells, T cells, and NKT cells - which have the potential to play roles in producing various immune mediators present in seminal plasma. Together, our data provide a resource for understanding the composition of an understudied reproductive tissue with potential implications for paternal control of offspring development and metabolism.
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MIF as a potential diagnostic and prognostic biomarker for triple-negative breast cancer that correlates with the polarization of M2 macrophages.
Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that plays a crucial role in antitumor immunity. However, the role of MIF in influencing the tumor microenvironment (TME) and prognosis of triple-negative breast cancer (TNBC) remains to be elucidated. Using R, we analyzed single-cell RNA sequencing (scRNA-seq) data of 41 567 cells from 10 TNBC tumor samples and spatial transcriptomic data from two patients. Relationships between MIF expression and immune cell infiltration, clinicopathological stage, and survival prognosis were determined using samples from The Cancer Genome Atlas (TCGA) and validated in a clinical cohort using immunohistochemistry. Analysis of scRNA-seq data revealed that MIF secreted by epithelial cells in TNBC patients could regulate the polarization of macrophages into the M2 phenotype, which plays a key role in modulating the TME. Spatial transcriptomic data also showed that epithelial cells (tumor cells) and MIF were proximally located. Analysis of TCGA samples confirmed that tumor tissues of patients with high MIF expression were enriched with M2 macrophages and showed a higher T stage. High MIF expression was significantly associated with poor patient prognosis. Immunohistochemical staining showed high MIF expression was associated with younger patients and worse clinicopathological staging. MIF secreted by epithelial cells may represent a potential biomarker for the diagnosis and prognosis of TNBC and may promote TNBC invasion by remodeling the tumor immune microenvironment.
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Coordinated single-cell tumor microenvironment dynamics reinforce pancreatic cancer subtype.
Bulk analyses of pancreatic ductal adenocarcinoma (PDAC) samples are complicated by the tumor microenvironment (TME), i.e. signals from fibroblasts, endocrine, exocrine, and immune cells. Despite this, we and others have established tumor and stroma subtypes with prognostic significance. However, understanding of underlying signals driving distinct immune and stromal landscapes is still incomplete. Here we integrate 92 single cell RNA-seq samples from seven independent studies to build a reproducible PDAC atlas with a focus on tumor-TME interdependence. Patients with activated stroma are synonymous with higher myofibroblastic and immunogenic fibroblasts, and furthermore show increased M2-like macrophages and regulatory T-cells. Contrastingly, patients with 'normal' stroma show M1-like recruitment, elevated effector and exhausted T-cells. To aid interoperability of future studies, we provide a pretrained cell type classifier and an atlas of subtype-based signaling factors that we also validate in mouse data. Ultimately, this work leverages the heterogeneity among single-cell studies to create a comprehensive view of the orchestra of signaling interactions governing PDAC.
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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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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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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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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.