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The role of miR-21 in early-stage lung adenocarcinoma: clinical and bioinformatics insights.
Lung adenocarcinoma (LUAD) is one of the most common types of lung cancer and a leading cause of cancer-related mortality worldwide. This study aimed to identify key microRNAs (miRNAs) and genes involved in LUAD pathogenesis. We enrolled 50 patients diagnosed with early-stage LUAD between October 2021 and September 2023 as the observation group, along with 50 healthy individuals as the control group. Peripheral blood samples (5 mL) were collected from each participant for exosome isolation and quantitative analysis of miR-21. The results demonstrated that miR-21 expression was significantly higher in the observation group compared to the control group (P < 0.05). To further explore the molecular mechanisms underlying LUAD, publicly available RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) datasets were analyzed using bioinformatics approaches. Differential expression analysis of The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) datasets identified 296 differentially expressed miRNAs (192 upregulated, 104 downregulated) and 2942 differentially expressed genes (1691 upregulated, 1251 downregulated). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that miR-21 target genes are involved in critical biological processes, including cell proliferation, apoptosis, and signal transduction. A protein-protein interaction (PPI) network analysis revealed key protein modules associated with LUAD progression.Immunohistochemistry (IHC) confirmed the high expression of miR-21 target genes IL12A and TGFBI in LUAD tissues. Additionally, the interaction between miR-21 and long non-coding RNAs (lncRNAs) was explored, revealing complex regulatory networks. Gene co-expression analysis of the miR-21 target gene ZNF367 identified highly correlated genes associated with mitosis and DNA repair. Immune infiltration analysis using CIBERSORT demonstrated significant differences in immune cell composition between LUAD patients and healthy controls. Survival analysis further indicated that high miR-21 expression is associated with poorer prognosis, underscoring its potential as a prognostic biomarker.Furthermore, scRNA-seq provided insights into the dynamic molecular changes occurring during the transition from normal to malignant states. Collectively, these findings highlight the critical role of miR-21 in LUAD pathogenesis and suggest potential avenues for targeted therapies and personalized treatment strategies.
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Single-cell atlases link macrophages and CD8+ T-cell subpopulations to disease progression and immunotherapy response in urothelial carcinoma.
Rationale: Immune checkpoint inhibitors (ICIs) have revolutionized the management of locally advanced or metastatic urothelial carcinoma. Strikingly, compared to urothelial carcinoma of the bladder (UCB), upper tract urothelial carcinoma (UTUC) has a higher response rate to ICIs. The stratification of patients most likely to benefit from ICI therapy remains a major clinical challenge. Methods: In this study, we performed the first single-cell RNA sequencing (scRNA-seq) study of 13 surgical tissue specimens from 12 patients with UTUC. The key results were validated by the analysis of two independent cohorts with bulk RNA-seq data for UCB (n = 404) and UTUC (n = 158) and one cohort of patients with metastatic urothelial carcinoma (mUC) who were treated with atezolizumab (n = 348). Results: Using scRNA-seq, we observed a higher proportion of tumor-infiltrating immune cells in locally advanced UTUC. Similar prognostically relevant intrinsic basal and luminal-like epithelial subtypes were found in both UTUC and UCB, although UTUC is predominantly of the luminal subtype. We also discovered that immunosuppressive macrophages and exhausted T-cell subpopulations were enriched in the basal subtype and showed enhanced interactions. Furthermore, we developed a gene expression signature (Macro-C3 score) capturing the immunosuppressive macrophages that better predicts outcomes than the currently established subtypes. We also developed a computational method to model immune evasion, and the Macro-C3 score predicted therapeutic response of mUC treated with first-line anti-PD-L1 inhibitors in patients with lower basal scores. Conclusions: Overall, the distinct microenvironment and Macro-C3 score provide an explanation for ICI efficacy in urothelial carcinoma and reveal new candidate regulators of immune evasion, suggesting potential therapeutic targets for improving antitumor immunity in the basal subtype.
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Upregulation of MTA1 in Colon Cancer Drives A CD8+ T Cell-Rich But Classical Macrophage-Lacking Immunosuppressive Tumor Microenvironment.
BACKGROUND: The MTA1 protein encoded by metastasis-associated protein 1 (MTA1) is a key component of the ATP-dependent nucleosome remodeling and deacetylase (NuRD) complex, which is widely upregulated in cancers. MTA1 extensively affects downstream gene expression by participating in chromatin remodeling. Although it was defined as a metastasis-associated gene in first reports and metastasis is a process prominently affected by the tumor microenvironment, whether it affects the microenvironment has not been investigated. In our study, we elucidated the regulatory effect of MTA1 on tumor-associated macrophages (TAMs) and how this regulation affects the antitumor effect of cytotoxic T lymphocytes (CTLs) in the tumor microenvironment of colorectal cancer. METHODS: We detected the cytokines affected by MTA1 expression via a cytokine antibody array in control HCT116 cells and HCT116 cells overexpressing MTA1. Multiplex IHC staining was conducted on a colorectal cancer tissue array from our cancer cohort. Flow cytometry (FCM) was performed to explore the polarization of macrophages in the coculture system and the antitumor killing effect of CTLs in the coculture system. Bioinformatics analysis was conducted to analyze the Cancer Genome Atlas (TCGA) colorectal cancer cohort and single-cell RNA-seq data to assess the immune infiltration status of the TCGA colorectal cancer cohort and the functions of myeloid cells. RESULTS: MTA1 upregulation in colorectal cancer was found to drive an immunosuppressive tumor microenvironment. In the tumor microenvironment of MTA1-upregulated colorectal cancer, although CD8+ T cells were significantly enriched, macrophages were significantly decreased, which impaired the CTL effect of the CD8+ T cells on tumor cells. Moreover, upregulated MTA1 in tumor cells significantly induced infiltrated macrophages into tumor-associated macrophage phenotypes and further weakened the cytotoxic effect of CD8+ T cells. CONCLUSION: Upregulation of MTA1 in colorectal cancer drives an immunosuppressive tumor microenvironment by decreasing the microphages from the tumor and inducing the residual macrophages into tumor-associated microphage phenotypes to block the activation of the killing CTL, which contributes to cancer progression.
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Dysregulated Retinal DPP10 Expression with Single Cell-based Next Genomic Sequencing Profiling in X-linked Juvenile Retinoschisis.
X-linked juvenile retinoschisis (XLRS) is a hereditary retinal dystrophy resulting from mutations in the retinoschisin (RS1) gene, which lead to progressive structural abnormalities in the retina and consequent visual impairment. Despite this, the molecular mechanisms through which RS1 mutations induce cell type-specific transcriptional remodeling during disease progression remain inadequately elucidated. To delineate transcriptional changes associated with RS1 mutations, we conducted single-cell RNA sequencing (scRNA-seq) on a CRISPR/Cas9-engineered Rs1emR209C knock-in mouse model. Integrative analysis with the Mouse Retina Cell Atlas demonstrated that rod photoreceptors exhibited the most significant transcriptional dysregulation among retinal cell types. Notably, dipeptidyl peptidase-like protein 10 (DPP10) was progressively and markedly upregulated, predominantly within photoreceptors, as the disease advanced. These findings were corroborated by immunofluorescence staining, quantitative PCR, and western blot analyses, which confirmed increased retinal DPP10 expression concurrent with a gradual decline in RS1 levels. To explore the functional implications of DPP10 dysregulation, we developed Y79 retinal cell models expressing either wild-type RS1 or the XLRS-associated RS1 R209C variant. Cells expressing the RS1 R209C mutation exhibited elevated DPP10 expression alongside reduced viability. Crucially, siRNA-mediated knockdown of DPP10 partially rescued cell viability and was associated with reduced GRP78/BiP expression in RS1 R209C-expressing cells, supporting potential functional relevance between DPP10 upregulation and mutant RS1-induced cellular stress. Furthermore, circulating DPP10 concentrations were significantly increased in patients with XLRS compared to control subjects. Collectively, these results identify DPP10 as a molecular alteration associated with RS1 mutation and suggest its potential as a circulating biomarker candidate for XLRS.
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Single-Cell Atlas of Aging Human Skin Reveals FOSB-Related Transcriptional Programs and Druggable Targets.
BACKGROUND: While human skin aging involves complex transcriptional alterations, the cell-type-specific regulatory mechanisms and therapeutic targets remain incompletely defined. The study aims to investigate aging-associated transcriptional programs and drug-responsive signatures at single-cell resolution. METHOD: Here we performed a single-cell RNA sequencing of young and elder human skin cells and provided a comprehensive analysis of aging-related genes, a gene regulatory network with immunohistochemistry (IHC) validation, cell-cell interference as well as potential chemical reactions. RESULT: Total 10 distinct cell populations were analyzed based on the scRNA sequencing data. Gene regulatory network analysis showed decreased lactotransferrin gene expression and increased FOSB(+) and DDIT3(+) regulons' regulatory activity. IHC identified the FOSB as an aging-related transcription factor. Despite uniform MT1 protein distribution across epidermal layers, single-cell data revealed subcluster-specific MT1 mRNA dynamics linked to metal ion homeostasis. Drug response prediction experiments revealed possible drug targets and potential antiaging drugs for the skin. CONCLUSION: Our data showed the skin cell clusters presented distinct transcriptional signatures during skin aging. We highlighted the versatile expression profiles of metallothionein family genes and identified the aging-related signature FOSB in the aged skin. We also provided potential target resources for antiaging therapies.
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Bulk and single-cell RNA sequencing identify prognostic signatures related to FGFBP2+ NK cell in hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly aggressive malignancy. As a specific immune cell subpopulation, FGFBP2+ NK cells play a crucial part in immune surveillance of HCC progression. This study set out to identify prognostic signature related to FGFBP2+ NK cell in HCC. METHODS: Bulk and scRNA-seq data were derived from the public databases. The single cell atlas of HCC and heterogeneity of natural killer (NK) cells were delineated by "Seurat" package. Pseudo-time trajectory of FGFBP2+ NK cell was constructed by "Monocle2" package. Cell-cell interactions were analyzed by "CellChat" package. Prognostic signature was screened to develop a RiskScore model, and the prediction robustness was verified. Immune cell infiltration and immunotherapy response were assessed between different risk groups. Drug sensitivity was predicted by "oncoPredict" package. The expressions of the prognosis gene signature were detected by in vitro test utilizing HCC cells. The effects of key genes on the proliferative, migratory and invasive capacity of HCC cells were assessed by EdU assay, wound healing and Transwell assay. RESULTS: The proportion of NK cell in HCC samples was markedly decreased than that in healthy samples. NK cell was further divided into three cell subpopulations, and FGFBP2+ NK cell was associated with the prognosis of HCC patients. Pseudo-time trajectory analysis of FGFBP2+ NK cell revealed two differential expression gene clusters. FGFBP2+ NK cell exhibited extensive intercellular communication in HCC. Further, eight prognostic signatures were identified, including six "risk" genes (UBE2F, AHSA1, PTP4A2, CDKN2D, FTL, RGS2) and two "protective" genes (KLF2, GZMH). RiskScore model was established with good prognostic prediction performance. In comparison to low-risk group, high-risk group had poorer prognosis, lower immune cell infiltration, and higher TIDE score. Moreover, 16 drugs showed significant correlation with RiskScore. Additionally, the expressions of GZMH was downregulated while FTL, PTP4A2, UBE2F, CDKN2D, RGS2, and AHSA1 were up-regulated in HCC cells. FTL and PTP4A2 silencing could suppress the proliferation, migration and invasion abilities of HCC cells. CONCLUSION: This study identified eight prognostic gene signatures related to FGFBP2+ NK cell in HCC, which may serve as potential therapeutic targets for HCC.
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Ferroptosis-driven cell death perpetuates the chronic inflammatory cycle in periodontitis: a single-cell transcriptomic study.
BACKGROUND: Periodontitis represents one of the most prevalent chronic inflammatory diseases, characterized by progressive periodontal tissue destruction driven by immune dysregulation. Emerging evidence establishes ferroptosis-an iron-dependent, lipid-peroxidation-driven form of regulated cell death-as a pivotal but underexplored driver of the pathological "cell death-inflammation-re-death" cycle in periodontitis. Ferroptotic cells release damage-associated molecular patterns (DAMPs) including oxidized lipids, HMGB1, and iron species that amplify inflammation. The spatiotemporal heterogeneity of ferroptosis susceptibility among periodontal cell subtypes, the identity of DAMPs-mediated intercellular signaling networks, and the epigenetic mechanisms governing ferroptosis-susceptibility transitions remain incompletely characterized. METHODS: We employed a single-arm cross-sectional design: a prospective single-cell RNA sequencing (scRNA-seq) study of gingival tissue from 6 periodontitis patients and 4 controls, integrating UMAP clustering, pseudotime trajectory, RNA velocity, CellChat-based ligand-receptor analysis, pySCENIC regulon inference, and epigenetic landscape analysis via published ATAC-seq/methylation dataset integration from independent cohorts. To functionally validate key transcriptomic findings, LPS-stimulated human cementoblast (HCEM) in vitro experiments with Ferrostatin-1 rescue were performed, and gene expression was quantified by RT-qPCR. RESULTS: The scRNA-seq atlas resolved three cementoblast subtypes with distinct ferroptosis susceptibility profiles; ferroptosis-sensitive cementoblasts (FS-CEM) functioned as dominant DAMPs-releasing hubs engaging fibroblasts, endothelial cells, and immune cells via HMGB1-RAGE, IL-33-ST2, and MIF-CD74 axes that triggered secondary necroptotic and pyroptotic cascades. NFE2L2 (NRF2)-BACH1 was identified as the transcription factor master switch governing ferroptosis susceptibility. Epigenetic analysis, derived from integration with publicly available ATAC-seq and methylation datasets from independent cohorts (GEO: GSE194276; ENCODE), revealed hypermethylation of GPX4/SLC7A11 promoters and EZH2-mediated H3K27me3 enrichment at NFE2L2 target loci in ferroptosis-sensitive cells, representing hypothesis-generating epigenetic inferences requiring direct experimental validation. In vitro LPS stimulation of HCEM cells confirmed dose-dependent downregulation of GPX4 and SLC7A11 and upregulation of ACSL4, PTGS2, and HMGB1; these changes were significantly reversed by Ferrostatin-1 pre-treatment, validating the ferroptosis specificity of the identified molecular signatures. CONCLUSION: This study provides mechanistic evidence that ferroptosis drives the chronic inflammatory cycle in periodontitis, and proposes NFE2L2 activation, BACH1 inhibition, EZH2 inhibition, and HMGB1 neutralization as precision therapeutic targets to break the pathological cell death-inflammation cycle.
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Comprehensive analysis of single-cell and bulk RNA sequencing data reveals an EGFR signature for predicting immunotherapy response and prognosis in pan-cancer.
INTRODUCTION: Immune checkpoint inhibitors (ICIs) have changed the paradigm of cancer treatment, but their effectiveness in some patients with epidermal growth factor receptor (EGFR) mutations is unsatisfactory. Therefore, it is necessary to develop a new biomarker for combined immunotherapy strategies to maximize the clinical benefits. METHODS: We collected and investigated 34 pan-cancer scRNA-Seq cohorts from The Cancer Genome Atlas (TCGA) and 10 bulk RNA-Seq cohorts utilizing multiple machine learning (ML) algorithms to identify and verify a representative EGFR-related gene signature (EGFR.Sig) as a predictive biomarker for immunotherapy response. Core genes were identified as Hub-EGFR.Sig to predict the prognosis of cancers and to understand the crosstalk between EGFR and the tumor immune microenvironment (TIME). RESULTS: EGFR.Sig can accurately predict the ICI response with an AUC of 0.77, demonstrating superior predictive performance compared to previously established signatures. Twelve core genes in EGFR.Sig were identified as Hub-EGFR.Sig, of which 4 immune resistance genes were previously verified in different CRISPR cohorts. Notably, the prognosis most related to Hub-EGFR.Sig was bladder cancer, which can be divided into two clusters with different responses to immunotherapy based on Hub-EGFR.Sig. DISCUSSION: We developed a promising pan-cancer signature based on EGFR-related genes to serve as a biomarker for immunotherapy response and survival outcome prediction. Furthermore, core genes were identified for future targeting, which will pave the way for improving the effect of immunotherapy in the context of combination immunotherapies.
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ZMAP: A single-cell meta-atlas of zebrafish embryonic development reveals a consensus hierarchy of cell identities.
Single-cell RNA sequencing (scRNA-seq) efforts have generated large collections of high-resolution cellular atlases of embryonic development, providing unprecedented views of the dynamic gene expression programs that accompany cell fate specification. Alongside parallel efforts in other models, zebrafish has emerged as one of the most extensively profiled vertebrate embryonic systems, with numerous scRNA-seq atlases spanning both embryonic and early larval stages. Despite this progress, cross-study comparisons between datasets remain challenging due to differences in sample processing, mapping, and annotation conventions. Here we present ZMAP (Zebrafish Meta Atlas Project), a harmonized reference integrating 8 published whole-embryo zebrafish scRNA-seq datasets comprising 798,790 cells across 15 developmental time windows. ZMAP unifies component studies through a shared embedding, a standardized marker-gene discovery pipeline, and a hierarchical annotation ontology. Using ZMAP, we inferred "consensus identity programs" - marker gene signatures for each ontology group that were reproducibly detected across studies. To promote broad usage, we provide a Python-based API for automated annotation and retrieval of marker gene sets and reference objects, as well as a web portal that supports interactive 2D and 3D exploration of the UMAP embedding, gene and annotation-level queries, and access to consensus marker resources.
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Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.