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Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies.
Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression and cellular heterogeneity within tissues and have enabled the construction of transcriptomic cell atlases. However, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM enables positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that TaG-EM barcodes can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to multiplex and reliably annotate single-cell transcriptomic experiments.
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Spatiotemporal and single-cell atlases to dissect regional specific cell types of the developing ovary.
Characterization of cellular heterogeneity and molecular diversity greatly enhances our understanding of the ovary differentiation process. However, regional specification remains largely unexplored during ovary development. Here, we combine spatial transcriptomics and single-cell RNA sequencing to build a spatiotemporal developmental atlas of ovaries from the fetal stage through adulthood. We construct the developmental trajectory of female germ cells and identify key genes essential for primordial follicle assembly. Specifically, we characterize the regional heterogeneity of granulosa cell subtypes contributing to the folliculogenesis, and analyze the molecular distinctions between healthy and atretic follicles. Notably, we discover that Onecut2-positive luteal cells exhibit a specific spatial distribution. Furthermore, lineage tracing reveals that these Onecut2-positive luteal cells originate from Foxl2-positive granulosa cells and Cyp17a1-positive theca cells. Collectively, this study provides a comprehensive delineation of ovary development and regional specificity of ovarian cell types.
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PRMT5/WDR77 Enhances the Proliferation of Squamous Cell Carcinoma via the ΔNp63α-p21 Axis.
Protein arginine methyltransferase 5 (PRMT5) is a critical oncogenic factor in various cancers, and its inhibition has shown promise in suppressing tumor growth. However, the role of PRMT5 in squamous cell carcinoma (SCC) remains largely unexplored. In this study, we analyzed SCC patient data from The Cancer Genome Atlas (TCGA) and the Cancer Dependency Map (DepMap) to investigate the relationship between PRMT5 and SCC proliferation. We employed competition-based cell proliferation assays, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assays, flow cytometry, and in vivo mouse modeling to examine the regulatory roles of PRMT5 and its binding partner WDR77 (WD repeat domain 77). We identified downstream targets, including the p63 isoform ΔNp63α and the cyclin-dependent kinase inhibitor p21, through single-cell RNA-seq, RT-qPCR, and Western blot analyses. Our findings demonstrate that upregulation of PRMT5 and WDR77 correlates with the poor survival of head and neck squamous cell carcinoma (HNSCC) patients. PRMT5/WDR77 regulates the HNSCC-specific transcriptome and facilitates SCC proliferation by promoting cell cycle progression. The PRMT5 and WDR77 stabilize the ΔNp63α Protein, which in turn, inhibits p21. Moreover, depletion of PRMT5 and WDR77 repress SCC in vivo. This study reveals for the first time that PRMT5 and WDR77 synergize to promote SCC proliferation via the ΔNp63α-p21 axis, highlighting a novel therapeutic target for SCC.
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AI-driven body composition atlas reveals its association with NSCLC immunotherapy outcome and molecular background: a multicenter study.
Although previous studies have linked body composition to immunotherapy efficacy, comprehensive multidimensional analyses with biological explanations remain lacking. This study integrated eight independent cohorts comprising 2,132 non-small cell lung cancer (NSCLC) patients, including five immune checkpoint inhibitor prognostic cohorts (n = 1,919), two bulk RNA-seq cohorts (n = 190), and one prospective single-cell RNA-seq cohort (n = 23). Using deep learning algorithms, we automatically extracted 92 body composition parameters from computed tomography images. The AI-based segmentation system demonstrated high consistency with manual measurements (intraclass correlation coefficient >0.87) with significantly improved efficiency. In male patients, higher intermuscular fat volume (IMFV) and 14 other indicators were independent predictors of overall survival; in female patients, T12 subcutaneous fat density and 6 other indicators showed potential associations with survival. Male patients with high IMFV exhibited significant upregulation of interferon-related pathways in CD8 + T cells and NK cells, along with lower exhaustion scores, while female patients with high T12 subcutaneous fat density showed macrophage polarization toward the M1 phenotype. This study underscores the importance of multidimensional body composition in NSCLC patient management, demonstrating that specific parameters are not only closely related to survival outcomes but also exhibit unique gender differences and location variations, providing new insights for optimizing immunotherapy strategies.
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Utilizing a novel mitochondrial-related gene signature for predicting the prognosis and immunological impact in bladder cancer.
BACKGROUND: Mounting evidence highlights the critical role of mitochondrial dysfunction, driven by mitochondrial-related genes (MTRGs), in the development, progression, and therapeutic response of cancer. However, a comprehensive analysis linking specific Mitochondria-Related Gene Signature (MTRGS) to Bladder Cancer (BLCA) prognosis and immunotherapy efficacy remains largely unexplored. Therefore, this study aims to investigate the role of MTRGs in BLCA, construct and validate a novel MTRGs-based prognostic signature, and explore its potential for guiding personalized treatment strategies. MATERIALS AND METHODS: Leveraging transcriptomic and clinical data from The Cancer Genome Atlas (TCGA-BLCA) cohort, we constructed a mitochondrial-related risk score model using LASSO, univariate and multivariate Cox regression analyses. This model was subsequently validated in an independent Gene Expression Omnibus (GEO) dataset. We then employed integrated bioinformatics approaches (implemented in R with online databases) to characterize features of the tumor microenvironment (TME), immune cell infiltration, Gene Set Enrichment Analysis (GSEA), tumor mutational burden (TMB), and drug sensitivity across different risk groups. Additionally, using data from public databases, we further verified our findings through single-cell RNA sequencing (scRNA-seq) analyses. RESULTS: Using 104 mitochondria-related differentially expressed genes (MTR-DEGs), unsupervised non-negative matrix factorization (NMF) clustering stratified BLCA patients into three molecular subtypes (Clusters 1-3). Survival analysis revealed that patients in Cluster 3 had significantly longer overall survival than those in Clusters 1 and 2. Our mitochondrial-related risk model incorporating six core genes (MAP1B, PYCR1, HSD3B1, KLK6, AKR1B15, and TAT) - exhibited robust prognostic capability (3-years AUC = 0.695 in TCGA-BLCA, 0.798 in GEO-GSE32894, 0.703 in GSE13507). The risk model revealed distinct immune infiltration patterns between high- and low-risk groups. Furthermore, Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenotype score (IPS) analyses demonstrated that integrating risk scores with stromal/immune signatures significantly enhanced immunotherapy benefit prediction across BLCA risk-subgroups. Crucially, the model demonstrated predictive power for therapy response: low-risk patients showed potential benefit from immune checkpoint inhibitors, while high-risk patients exhibited heightened sensitivity to specific chemotherapy agents or targeted therapies (e.g., Tozasertib, Gemcitabine) and may require intensified regimens. CONCLUSION: This validated mitochondrial risk model delivers a clinically actionable biomarker for BLCA prognosis stratification and guides personalized therapeutic selection, enabling precision treatment intensification.
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Serglycin secreted by late-stage nucleus pulposus cells is a biomarker of intervertebral disc degeneration.
Intervertebral disc degeneration is a natural process during aging and a leading cause of lower back pain. Here, we generate a comprehensive atlas of nucleus pulposus cells using single-cell RNA-seq analysis of human nucleus pulposus tissues (three males and four females, age 41.14 ± 18.01 years). We identify fibrotic late-stage nucleus pulposus cells characterized by upregulation of serglycin expression which facilitate the local inflammatory response by promoting the infiltration of inflammatory cytokines and macrophages. Finally, we discover that daphnetin, a potential serglycin ligand, substantially mitigates the local inflammatory response by downregulating serglycin expression in an in vivo mouse model, thus alleviating intervertebral disc degeneration. Taken together, we identify late-stage nucleus pulposus cells and confirm the potential mechanism by which serglycin regulates intervertebral disc degeneration. Our findings indicate that serglycin is a latent biomarker of intervertebral disc degeneration and may contribute to development of diagnostic and therapeutic strategies.
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Intercellular communication atlas reveals Oprm1 as a neuroprotective factor for retinal ganglion cells.
Previous studies of neuronal survival have primarily focused on identifying intrinsic mechanisms controlling the process. This study explored how intercellular communication contributes to retinal ganglion cell (RGC) survival following optic nerve crush based on single-cell RNA-seq analysis. We observed transcriptomic changes in retinal cells in response to the injury, with astrocytes and Müller glia having the most interactions with RGCs. By comparing RGC subclasses characterized by distinct resilience to cell death, we found that the high-survival RGCs tend to have more ligand-receptor interactions with neighboring cells. We identified 47 interactions stronger in high-survival RGCs, likely mediating neuroprotective effects. We validated one identified target, the μ-opioid receptor (Oprm1), to be neuroprotective in three retinal injury models. Although the endogenous Oprm1 is preferentially expressed in intrinsically photosensitive RGCs, its neuroprotective effect can be transferred to other subclasses by pan-RGC overexpression of Oprm1. Lastly, manipulating the Oprm1 activity improved visual functions in mice.
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A succinylation-based classifier predicts chemotherapy response in prostate cancer and reveals KAT2A as a therapeutic target.
BACKGROUND: Chemotherapy resistance remains a critical hurdle in advanced prostate cancer (PCa). Succinylation, an essential post-translational modification linking cellular metabolism with epigenetic regulation, has been implicated in tumour progression; however, its contribution to PCa chemoresistance remains poorly defined. OBJECTIVE: This study aimed to evaluate the prognostic significance of succinylation in PCa, develop a succinylation-based biomarker, and elucidate the mechanisms driving chemotherapy resistance. METHODS: We generated a succinylation score (SS) by applying single-sample gene set enrichment analysis (ssGSEA) to transcriptomic profiles from the TCGA-PRAD cohort. Its relationships with survival, the tumour microenvironment (TME), and treatment susceptibility were examined using CIBERSORT, GSEA, TIDE, oncoPredict, and single-cell RNA sequencing (scRNA-seq). Findings were functionally validated in patient-derived organoids, PCa cell lines, and xenograft models through genetic manipulation, chemosensitivity assays, and mechanistic studies. RESULTS: High SS correlated with favourable prognosis, lower Gleason scores, absent lymph node metastasis, and an immune-active TME enriched in CD8+ precursor exhausted T cells. High-SS tumours showed enhanced sensitivity to docetaxel and cisplatin. scRNA‑seq identified KAT2A as a key driver in low‑SS malignant clusters with chemoresistance features. KAT2A was elevated in chemoresistant tissues, cell lines, and organoids. KAT2A knockout sensitised cells to chemotherapy, while ectopic expression promoted resistance in vitro and in vivo. Mechanistically, KAT2A-mediated succinylation of PIK3R2 at K477 and K564 inhibited its ubiquitination and proteasomal degradation, stabilising PIK3R2 to drive chemoresistance. The KAT2A inhibitor Butyrolactone 3 synergised with standard chemotherapy to suppress tumour growth. CONCLUSION: The succinylation score serves as a robust prognostic biomarker integrating metabolic and immunological features in PCa. The KAT2A-PIK3R2 succinylation pathway represents a newly defined driver of chemoresistance and points to MB-3-based combination therapy as a potential strategy for resistant advanced disease. KEY POINTS: A transcriptome-based succinylation score (SS) stratifies prostate cancer by prognosis, immune contexture, and chemotherapy sensitivity. KAT2A is enriched in low-SS, chemoresistant tumours and promotes resistance by succinylating PIK3R2. KAT2A-mediated succinylation competitively inhibits PIK3R2 ubiquitination, stabilising PIK3R2 and driving chemoresistance. The KAT2A inhibitor MB-3 synergises with chemotherapy to suppress tumour growth in both chemoresistant and chemosensitive models.
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Spatial microbiome-metabolic crosstalk drives CD8+ T-cell exhaustion through the butyrate-HDAC axis in colorectal cancer.
BACKGROUND: The spatial organization of intratumoral microbiota and its metabolic impact on immunotherapy response in colorectal cancer (CRC) is unclear, limiting targeted interventions. METHODS: We integrated single-cell RNA-seq, spatial transcriptomics, and microbial multi-omics from a discovery cohort of 23 treatment-naïve CRC patients. Findings were validated in an independent validation cohort from The Cancer Genome Atlas (TCGA-CRC, n = 159). RESULTS: Spatial depletion of Streptococcus and Acetivibrio in tumor niches disrupts butyrate-histone deacetylase (HDAC) signaling, leading to programmed cell death 1 (PDCD1) hyperacetylation and CD8+ T-cell exhaustion. The Colorectal Cancer Microbiome Score (CMS) may serve as a predictive biomarker for immunotherapy response and HDAC inhibitor-based combination therapy. We developed the CMS, a spatial biomarker that stratifies patients by microbial-metabolic dysfunction, predicting immunotherapy resistance (e.g., higher tumor immune dysfunction and exclusion (TIDE) scores; p < 0.01) and guiding combinatorial HDAC inhibition for CMS-defined subgroups. In silico fecal microbiota transplantation (FMT) validated CMS as an actionable target for microbiota modulation. Butyrate supplementation in vitro restored HDAC activity and reduced PD-1 expression on CD8+ T cells, validating the proposed mechanism. CONCLUSION: Our study unveils a spatially defined, microbiome-driven metabolic niche that epigenetically programs CD8+ T-cell exhaustion via the butyrate-HDAC axis, revealing a targetable mechanism to overcome immunotherapy resistance in CRC.
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MIR4435-2HG: A novel biomarker for triple-negative breast cancer diagnosis and prognosis, activating cancer-associated fibroblasts and driving tumor invasion through EMT associated with JNK/c-Jun and p38 MAPK signaling pathway activation.
BACKGROUND: Breast cancer has the highest incidence rate and causes the most fatalities among all female cancers worldwide. Triple-negative breast cancer (TNBC) is known for its strong invasiveness and higher rates of recurrence. In this research, we aimed to identify MIR4435-2HG as a promising long non-coding RNA (lncRNA) biomarker and therapeutic target for TNBC. METHODS: Utilizing clinicopathological information and transcriptome data from The Cancer Genome Atlas (TCGA) database, we assessed the clinical relevance of MIR4435-2HG in breast cancer through univariate and multivariate COX regression, receiver operating characteristic (ROC) analysis, as well as Kaplan-Meier survival analysis. To investigate the biological role of MIR4435-2HG in TNBC, we conducted gene set enrichment analysis (GSEA), as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Additionally, we constructed and validated a nomogram to predict disease-free survival (DFS). Both the R package "pRRophetic" and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were employed to forecast the sensitivity to different therapeutics between the high- and low-MIR4435-2HG groups. We employed single-cell RNA sequencing analysis and tumor microenvironment infiltration analysis to investigate the potential involvement of MIR4435-2HG in the TNBC tumor microenvironment. Cellular biological behaviors were assessed utilizing CCK-8, transwell assays, and wound-healing assays. Furthermore, we performed RNA-seq, qRT-PCR, and western blotting analyses to elucidate and confirm the specific mechanisms underlying the role of MIR4435-2HG in TNBC. RESULTS: In our study, we have identified MIR4435-2HG as a significant diagnostic and prognostic factor for TNBC. We observed that MIR4435-2HG is widely expressed and might have a significant impact on the reshaping of the TNBC tumor microenvironment. Patients with TNBC in the high-MIR4435-2HG group may show reduced sensitivity to cisplatin, doxorubicin, and gemcitabine and have an increased propensity for immune escape. Knockdown of MIR4435-2HG inhibits cancer-associated fibroblasts (CAFs) activation. Notably, MIR4435-2HG predominantly enhances the migratory and invasive capabilities of TNBC cells through the epithelial-mesenchymal transition (EMT) process. Mechanistically, we validated that MIR4435-2HG activates the JNK/c-Jun and p38 non-classical MAPK signaling pathway in TNBC cells. CONCLUSIONS: Our findings highlight the significant potential of MIR4435-2HG as a highly promising biomarker for TNBC. Targeting MIR4435-2HG could represent an appealing therapeutic approach for TNBC.