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Single-Cell Transcriptional Profiling Reveals Signatures of Helper, Effector, and Regulatory MAIT Cells during Homeostasis and Activation.
Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant TCR, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during early and prolonged Ag-specific activation with the MR1 ligand 5-OP-RU and nonspecific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4+ or CD8+ coexpression. During early activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF In contrast, prolonged stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. We further demonstrate a FOXP3 expressing MAIT cell subset that phenotypically resembles conventional regulatory T cells. Moreover, scRNAseq-defined MAIT cell subpopulations were also detected in individuals recently exposed to Mycobacterium tuberculosis, confirming their presence during human infection. To our knowledge, our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease.
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Circulating immune cells exhibit distinct traits linked to metastatic burden in breast cancer.
BACKGROUND: Circulating immune cells play a crucial role in the anti-tumour immune response, yet the systemic immune system in metastatic breast cancers is not fully characterised. Investigating the cellular and molecular changes in peripheral blood mononuclear cells (PBMCs) from breast cancer patients could elucidate the role of circulating immune cells in metastasis and aid in identifying biomarkers for disease burden and progression. METHODS: In this study, we characterised the systemic immune landscape associated with varying levels of metastatic burden by analysing the single-cell transcriptomes of PBMCs from breast cancer patients and healthy controls. Our research focused on identifying changes in immune cell composition, transcriptional programs, and immune-cell communication networks linked to metastatic burden. Additionally, we compared these PBMC features onto a single-cell atlas of primary breast tumours to study corresponding traits in tumour-infiltrating immune cells. RESULTS: In metastatic breast cancer, PBMCs exhibit a significant downregulation of the adaptive immune system and a decreased number and activity of unconventional T cells, such as γδ T cells. Additionally, metastatic burden is associated with impaired cell communication pathways involved in immunomodulatory functions. We also identified a gene signature derived from myeloid cells shared between tumour immune infiltrates and circulating immune cells in breast cancer patients. CONCLUSIONS: Our study provides a comprehensive single-cell molecular profile of the peripheral immune system in breast cancer, offering a valuable resource for understanding metastatic disease in terms of tumour burden. By identifying immune traits linked to metastasis, we have unveiled potential new biomarkers of metastatic disease.
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Multi-stage transcriptome analysis reveals genetic orchestration of rat testis development.
BACKGROUND: Testicular development is a highly orchestrated process essential for male fertility, but its temporal genetic regulation remains incompletely resolved in many mammalian models. This study re-analyses rat testis transcriptomes across 15 stages from embryonic day 12 to postnatal week 16 using bulk RNA-sequencing data from a multispecies organ development atlas, generating a continuous, testis-focused temporal framework, and pinpointing key developmental transition windows and regulatory modules. RESULTS: Of 23,748 annotated genes, 17,717 were differentially expressed (DEGs), and hierarchical plus co-expression analyses identified four principal expression modules and five clusters capturing spermatogenic, morphogenetic, immune, and neurone-like programs. Four major transcriptional transition windows, embryonic day 14, embryonic day 19, postnatal week 2, and postnatal week 6, were defined, with the largest remodeling between 2 and 6 weeks coinciding with the onset of robust spermatogenesis and marking a particularly vulnerable window for environmental or toxicant-induced perturbation. Stage-specific spermatogenesis-associated gene sets at embryonic day 19 (n = 28), postnatal week 2 (n = 61), and week 6 (n = 735) showed minimal overlap, supporting sequential regulatory waves driving germ cell commitment, early meiosis, and terminal differentiation. Target enrichment analyses highlighted five conserved microRNAs (rno-miR-151-5p, rno-miR-29b-3p, rno-miR-384-5p, rno-miR-500-5p, rno-miR-672-5p) whose predicted and validated targets form modules related to extracellular matrix remodeling, apoptosis and cell-cycle control, ion-channel signaling, and neuronal-like pathways, with high sequence conservation to human homologs. Immune-related genes and blood-testis barrier components displayed coordinated expression dynamics, and a conserved core of 487 spermatogenesis genes showed strong cross-mammalian orthology, indicating a deeply shared transcriptional backbone on which species-specific regulatory nuances are layered. CONCLUSIONS: This multistage transcriptomic analysis delineates major developmental transitions, co-expression modules, and regulatory miRNA-mRNA networks that orchestrate rat testis maturation and highlight a critical P2W-P6W transition window. The resource complements existing multiorgan and single-cell datasets by providing a testis-focused temporal framework and identifies conserved gene sets and regulatory candidates of direct relevance to male infertility, toxicology, and cross-species translational studies.
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Macrophage migration inhibitory factor-CD74 axis drives vascular smooth muscle cell-induced M1 macrophage polarization to exacerbate intracranial aneurysm inflammation.
BACKGROUND: Intracranial aneurysms (IAs) develop and progress through pathological processes, including inflammation and abnormal changes in the vascular structure. The cytokine Macrophage Migration Inhibitory Factor (MIF) is implicated in the pathology of vascular diseases. However, the role of MIF in IAs remains to be elucidated. METHODS: Transcriptomic data from IA and normal arteries were analyzed to quantify MIF expression and immune infiltration (CIBERSORT). Methylation sequencing assessed MIF promoter methylation. Single-cell RNA sequencing (scRNA-seq) defined secretory vascular smooth muscle cell (sVSMC) and M1-like macrophage proportions and MIF expression. Intercellular communication via the MIF-CD74 axis was evaluated using CellChat. In vitro functional experiments validated sVSMC-induced macrophage M1 polarization mechanisms. RESULTS: MIF mRNA was significantly upregulated in IAs (diagnostic AUC = 0.89) and correlated with increased M1-like macrophage infiltration (r = 0.783, p = 0.008). Hypomethylation of MIF was observed in IAs. scRNA-seq revealed expanded secretory VSMCs and M1-like macrophages, with elevated MIF in secretory VSMCs. CellChat confirmed enhanced MIF-CD74 signaling. In vitro, secretory VSMCs induced M1 polarization (iNOS/CD86↑, Arg1↓) via MIF-CD74; this effect was reversed by MIF knockdown or CD74 inhibition. CONCLUSION: We provide a comprehensive single-cell atlas of IAs and identify the sVSMC-derived MIF-CD74 axis as a novel mechanism driving macrophage M1 polarization and IA inflammation. This uncovers previously unrecognized sVSMC-macrophage crosstalk, establishing the MIF-CD74 axis as a promising immunomodulatory target for IA therapy.
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Liquid-liquid phase separation-related gene in gliomas: FABP5 is a potential prognostic marker.
BACKGROUND: The glioma is the most malignant human brain tumor. Early glioma detection and treatment are still difficult. New biomarkers are desperately required to aid in the evaluation of diagnosis and prognosis. METHODS: The single cell sequencing dataset scRNA-6148 for glioblastoma was obtained from the Chinese Glioma Genome Atlas database. Data were gathered for the transcriptome sequencing project. Genes involved in liquid-liquid phase separation (LLPS) were taken out of the DrLLPS database. To find the modules connected to LLPS, the weighted co-expression network was analyzed. Differential expression analysis was used to identify the differentially expressed genes (DEGs) in gliomas. Pseudo-time series analysis, gene set enrichment analysis (GSEA) and immune cell infiltration analysis were used to investigate the role of important genes in the immunological microenvironment. We examined the function of key glioma genes using polymerase chain reaction (PCR) testing, CCK-8 assays, clone generation assays, transwell assays and wound healing assays. RESULTS: FABP5 was identified as a key gene in glioblastoma by multiomics research. Pseudo-time series analysis showed that FABP5 was highly linked with the differentiation of many different types of cells. GSEA revealed that FABP5 was strongly linked to several hallmark pathways in glioblastoma. We looked at immune cell infiltration and discovered a significant link between FABP5, macrophages and T cell follicular helpers. The PCR experiment results demonstrated that FABP5 expression was elevated in glioma samples. Cell experiments showed that FABP5 knockdown dramatically decreased the viability, proliferation, invasion and migration of the LN229 and U87 glioma cell lines. CONCLUSIONS: Our study provides a new biomarker, FABP5, for glioma diagnosis and treatment.
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Circadian-immune-related gene signature for lung squamous cell carcinoma: machine learning and multi-omics analysis.
BACKGROUND: Circadian disruption promotes tumor progression and therapy resistance, but its prognostic value and impact on the tumor immune microenvironment in lung squamous cell carcinoma (LUSC) remain unclear. This study aimed to develop a circadian-immune-related gene signature to improve LUSC risk stratification and therapy guidance. METHODS: We integrated multi-omics data from LUSC patients (n=494) across The Cancer Genome Atlas and Gene Expression Omnibus (GEO) database GSE73403 (n=69). A circadian-immune-related gene prognostic signature (CIGPS) was constructed from 1,677 circadian rhythm-related genes through weighted gene co-expression network analysis (WGCNA) and ten machine learning algorithms (StepCox + GBM optimized) and externally validated. Bioinformatics analyses assessed the tumor immune microenvironment, mutation landscape, and therapy response. Single-cell RNA sequencing data (GSE148071) explored gene expression at cellular resolution. RESULTS: A six-gene CIGPS was developed, comprising CLDN1, FGG, ALPL, TREM1, NKX2-1, and CLDN5. This signature stratified patients into high- and low-risk groups with divergent overall survival in both cohorts. Unsupervised clustering revealed C1/C2 subtypes: C1 displayed an immune-hot yet excluded phenotype with higher CD8+ T cell infiltration but elevated physical barriers; C2 exhibited an immune-cold phenotype with DNA replication and epigenetic machinery activation. Both subtypes demonstrated distinct therapeutic vulnerabilities and divergent drug sensitivity profiles. Single-cell profiling demonstrated heterogeneous spatial distribution of signature genes across distinct tumor microenvironmental compartments. CONCLUSIONS: The CIGPS serves as a potent prognostic tool that elucidates the heterogeneous tumor immune microenvironment in LUSC. It holds significant promise for guiding risk assessment and informing personalized therapeutic strategies based on distinct molecular subtypes.
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Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model.
BACKGROUND: Intra-tumor heterogeneity (ITH) encompasses cellular differences in tumors and is related to clinical outcomes such as drug resistance. However, little is known about the dynamics of ITH, owing to the lack of time-series analysis at the single-cell level. Mouse models that recapitulate cancer development are useful for controlled serial time sampling. RESULTS: We performed single-cell exome and transcriptome sequencing of 200 cells to investigate how ITH is generated in a mouse colorectal cancer model. In the model, a single normal intestinal cell is grown into organoids that mimic the intestinal crypt structure. Upon RNAi-mediated downregulation of a tumor suppressor gene APC, the transduced organoids were serially transplanted into mice to allow exposure to in vivo microenvironments, which play relevant roles in cancer development. The ITH of the transcriptome increased after the transplantation, while that of the exome decreased. Mutations generated during organoid culture did not greatly change at the bulk-cell level upon the transplantation. The RNA ITH increase was due to the emergence of new transcriptional subpopulations. In contrast to the initial cells expressing mesenchymal-marker genes, new subpopulations repressed these genes after the transplantation. Analyses of colorectal cancer data from The Cancer Genome Atlas revealed a high proportion of metastatic cases in human subjects with expression patterns similar to the new cell subpopulations in mouse. These results suggest that the birth of transcriptional subpopulations may be a key for adaptation to drastic micro-environmental changes when cancer cells have sufficient genetic alterations at later tumor stages. CONCLUSIONS: This study revealed an evolutionary dynamics of single-cell RNA and DNA heterogeneity in tumor progression, giving insights into the mesenchymal-epithelial transformation of tumor cells at metastasis in colorectal cancer.
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Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma.
Clear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We complemented our findings with single-cell sequencing data and employed the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and qRT-PCR to compare gene expression profiles between cancerous and paracancerous tissues. PRS serves as a valuable tool for prognostication, immune characterization, tumor mutation burden estimation, immunotherapy response prediction, and drug sensitivity assessment in ccRCC. We identify five genes with significant roles in cancer promotion and three genes with cancer-suppressive properties, further validated by qRT-PCR and CPTAC analyses, showcasing gene expression differences in ccRCC tissues. Our study introduces an innovative PCD model that amalgamates diverse cell death patterns to provide accurate predictions for clinical outcomes, mutational profiles, and immune characteristics in ccRCC. Our findings hold promise for advancing personalized treatment strategies in ccRCC patients.
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ECT2+ cell group acts as cancer stem cell in malignant pleomorphic adenoma.
Salivary carcinoma ex pleomorphic adenoma (CXPA) is a carcinoma that develops from benign pleomorphic adenoma, and it is characterized by aggressiveness and poor prognosis. Recent advancements in cancer stem cell (CSC) research have identified CSCs as critical contributors to tumor carcinogenesis due to their unlimited self-renewal ability. Single-cell RNA sequencing has enabled a comprehensive analysis of CSC heterogeneity. However, CSCs in CXPA remain largely unexplored. In this study, we constructed a comprehensive atlas of CXPA at single-cell resolution and demonstrated that CXPA exhibited intratumoral heterogeneity. We identified four tumor epithelial cell subgroups characterized by epithelial development, cell cycle, extracellular matrix remodeling, and salivary secretion signatures. ECT2+ tumor cells in the cell cycle cluster were identified as CSCs in CXPA. Analysis of tumor tissues from patients with CXPA revealed that ECT2 expression was strongly associated with invasiveness and prognosis. Targeting the ECT2 gene significantly inhibited tumor sphere formation and aggressiveness in CXPA cell lines. Our findings provide new insights into CXPA diversity and origin, with substantial clinical implications for targeting the ECT2 gene in CXPA treatment.
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Single-cell multiregion dissection of Alzheimer's disease.
Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1-3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer's disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer's disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer's disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer's disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer's disease pathology.