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Exercise reprograms the inflammatory landscape of multiple stem cell compartments during mammalian aging.
Exercise has the ability to rejuvenate stem cells and improve tissue regeneration in aging animals. However, the cellular and molecular changes elicited by exercise have not been systematically studied across a broad range of cell types in stem cell compartments. We subjected young and old mice to aerobic exercise and generated a single-cell transcriptomic atlas of muscle, neural, and hematopoietic stem cells with their niche cells and progeny, complemented by whole transcriptome analysis of single myofibers. We found that exercise ameliorated the upregulation of a number of inflammatory pathways associated with old age and restored aspects of intercellular communication mediated by immune cells within these stem cell compartments. Exercise has a profound impact on the composition and transcriptomic landscape of circulating and tissue-resident immune cells. Our study provides a comprehensive view of the coordinated responses of multiple aged stem cells and niche cells to exercise at the transcriptomic level.
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Single-Cell Transcriptomic Analyses of Brain Parenchyma in Patients With New-Onset Refractory Status Epilepticus (NORSE).
BACKGROUND AND OBJECTIVES: New-onset refractory status epilepticus (NORSE) occurs in previously healthy children or adults, often followed by refractory epilepsy and poor outcomes. The mechanisms that transform a normal brain into an epileptic one capable of seizing for prolonged periods despite treatment remain unclear. Nonetheless, several pieces of evidence suggest that immune dysregulation could contribute to hyperexcitability and modulate NORSE sequelae. METHODS: We used single-nucleus RNA sequencing to delineate the composition and phenotypic states of the CNS of 4 patients with NORSE, to better understand the relationship between hyperexcitability and immune disturbances. We compared them with 4 patients with chronic temporal lobe epilepsy (TLE) and 2 controls with no known neurologic disorder. RESULTS: Patients with NORSE and TLE exhibited a significantly higher proportion of excitatory neurons compared with controls, with no discernible difference in inhibitory GABAergic neurons. When examining the ratio between excitatory neurons and GABAergic neurons for each patient individually, we observed a higher ratio in patients with acute NORSE or TLE compared with controls. Furthermore, a negative correlation was found between the ratio of excitatory to GABAergic neurons and the proportion of GABAergic neurons. The ratio between excitatory neurons and GABAergic neurons correlated with the proportion of resident or infiltrating macrophages, suggesting the influence of microglial reactivity on neuronal excitability. Both patients with NORSE and TLE exhibited increased expression of genes associated with microglia activation, phagocytic activity, and NLRP3 inflammasome activation. However, patients with NORSE had decreased expression of genes related to the downregulation of the inflammatory response, potentially explaining the severity of their presentation. Microglial activation in patients with NORSE also correlated with astrocyte reactivity, possibly leading to higher degrees of demyelination. DISCUSSION: Our study sheds light on the complex cellular dynamics in NORSE, revealing the potential roles of microglia, infiltrating macrophages, and astrocytes in hyperexcitability and demyelination, offering potential avenues for future research targeting the identified pathways.
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Brain-wide correspondence of neuronal epigenomics and distant projections.
Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.
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The impact of glucocorticoid receptor transactivation on context-dependent cell migration dynamics.
The glucocorticoid receptor (GR) plays a significant role in breast cancer cell behaviour, although data on its effects are conflicting. The impact of GR agonist dexamethasone (dex) and antagonist mifepristone (mif) on oestrogen-positive (ER+) and triple-negative (TN) breast cancer cell lines in both 2D and 3D cultures was studied using multiple in vitro functional assays and transcriptome sequencing. GR activation increased cell motility in TN but not in ER + tumour cells, as observed in both collective and single-cell migration tests. Time-lapse analysis showed enhanced motility after 4-6 h in wound healing, despite dex inhibiting migration initially. This inhibition was observed at 2 h in single-cell tracking migration assays. Cell proliferation increased in TN and decreased in ER + cells upon GR activation, reversed by GR antagonist. RNA sequencing revealed dex's impact on cell adhesion and extracellular matrix signalling in TN cells and on DNA replication in ER + cells. Based on data from 1085 human breast cancer specimens, GR pathway expression correlated with migratory, extracellular matrix, and angiogenesis gene signatures. Additionally, higher expression of GR and increased GR signature were observed in fast-migrating cells compared to slow-migrating ones. Positive correlation between the GR signature and migration signature at the single-cell level indicated an association between GR activity and cell migration. For the first time, we assessed altered time-lapse migration dynamics in TN breast cancer cells, potentially contributing to cancer progression and prognosis, highlighting that the effects of dexamethasone on breast cancer cell migration are influenced by ER status and treatment duration.
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Integrated spatial multi-omics delineates fatty acid degradation fuels malignant evolution at the tumour periphery in cervical squamous cell carcinoma.
BACKGROUND: Cervical squamous cell carcinoma (CSCC) exhibits profound spatial heterogeneity in evolutionary trajectories across distinct tumour foci, yet the underlying mechanisms remain poorly understood. METHODS: In this study, we performed an integrated spatial transcriptomic and metabolomic analysis of six CSCC and two normal cervical samples, supported by single-cell RNA sequencing (n = 20) and validated in an independent spatial enhanced resolution omics-sequencing cohort (n = 15), to map the spatial tumour architecture and cellular heterogeneity of CSCC. Findings were functionally confirmed using cell lines, patient-derived organoids, and mouse models. FINDINGS: We identified that tumour foci with high spatial continuity demonstrated elevated cancer cell purity and exhibited distinct spatial stratification. The peripheral tumour foci (layer 3) exhibited enhanced proliferative capacity and aggressive traits characterised by elevated epithelial-to-mesenchymal transition (EMT) activity compared to core foci (layer 1), which correlated with advanced evolutionary states. A layer 3-specific gene signature predicted poorer overall survival in both the Cancer Genome Atlas (TCGA) and Tongji Hospital (TJH) cohorts. Spatial multi-omics uncovered progressive metabolic reprogramming along the core-to-periphery axis, with activation of fatty acid degradation emerging as a hallmark of layer 3 aggression. Genetic knockdown (HADH, HADHA and ECHS1) and pharmacological inhibition (mitotane and perhexiline) of fatty acid degradation attenuated malignant phenotypes of layer 3, including proliferation and EMT-driven invasion. INTERPRETATION: Our work establishes spatially resolved activation of the fatty acid degradation as a key evolutionary engine fuelling the malignant phenotypes of peripheral tumour foci, and nominates stratification-targeted metabolic disruption as a spatially promising therapeutic strategy for CSCC. FUNDING: Noncommunicable Chronic Diseases-National Science and Technology Major Project (2025ZD0544100), National Natural Science Foundation of China (82372929, 82503148, 32300460, 32400555 and 82472696), China Postdoctoral Science Foundation (2025M772119), Hubei Provincial Natural Science Foundation (JCZRQN202500308).
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Aberrant p53 fuels macrophage immunoregulatory polarization and refractory clinical outcome in urothelial carcinoma.
BACKGROUND: Urothelial carcinoma (UC) exhibits extensive infiltration of tumor-associated macrophages (TAMs). As the most frequently altered gene in UC, TP53 is recognized not only as a guardian of genomic integrity, but also as a potential architect of the tumor immune microenvironment (TIME). However, how aberrant p53 status, comprising TP53 mutation (TP53 Mut) and p53 abnormal expression (p53Abn), correlates with TAM phenotypic and functional heterogeneity and their reciprocal interactions within the TIME landscape remains incompletely defined. METHODS: This study integrated single-cell RNA sequencing, immunohistochemistry, and flow cytometry to delineate TAM phenotypes and map distinct immune landscapes stratified by p53 status. Clinical relevance was assessed in a multicohort dataset of 962 patients with UC with comprehensive clinicopathological annotations. RESULTS: Single-cell profiling revealed distinct TAM subsets closely linked to p53 status. Interferon-primed TAMs, marked by CXCL9, CXCL10, CXCL11 and IDO1, predominated in p53 wild-type (p53WT) tumors, whereas immune regulatory TAMs (Reg-TAMs), marked by SPP1, MARCO, SLC2A1 and INHBA, were enriched in p53Abn tumors. This divergent distribution highlighted a profound, p53-associated TAM heterogeneity. Clinically, high TAMs infiltration was consistently associated with worse overall survival predominantly in p53Abn or TP53 Mutpatients across three independent cohorts (Zhongshan Hospital, Fudan University Shanghai Cancer Center and The Cancer Genome Atlas). Furthermore, high TAMs infiltration correlated with poorer responses to both platinum-based chemotherapy and anti-programmed cell death-ligand 1 immunotherapy specifically in the p53Abn or TP53 Mut subgroup. Notably, aberrant p53 status was strongly coupled with a distinct metabolic reprogramming in TAMs, favoring lipid catabolism and immunoregulatory polarization. Trajectory analysis revealed a skewed differentiation axis in p53Abn tumors toward terminally differentiated Reg-TAMs. Immunohistochemistry and flow cytometry validated increased immunosuppressive TAM subsets in p53Abn UC. Additionally, p53Abn tumors exhibited an altered CD4+ T-cell landscape, enriched for suppressive subsets (regulatory, exhausted, and metallothionein-expressing T cells) coexisting with Reg-TAMs, potentially associated with immune suppression via the predicted SPP1-CD44 axis. CONCLUSIONS: In UC, aberrant p53 status correlates with a remodeled TIME, characterized by metabolically reprogrammed, immunosuppressive TAMs. These TAMs co-evolve with suppressive CD4+ T cells, suggesting a coordinated immunosuppressive network potentially involving SPP1-CD44 signaling. Together, this specific genotype-phenotype coupling delineates a profoundly immunosuppressive ecosystem that likely impedes immune clearance and limits therapeutic efficacy.
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Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer.
As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including SERPINE1, FEN1, PDGFRB, SNCG, TCF3, and APOC3. The TCGA-STAD cohort was utilized as a training set while the GSE84437 and GSE13861 cohorts were analyzed for validation. Immune cell infiltration and immunotherapy efficacy were investigated in the PRJEB25780 cohort. Data from the genomics of drug sensitivity in cancer (GDSC) database revealed pharmacological response. The GSE13861 and GSE54129 cohorts, single-cell dataset GSE134520, and The Human Protein Atlas (THPA) database were utilized for localization of the key senescence-related genes. Association of a higher risk-score with worse overall survival (OS) was identified in the training cohort (TCGA-STAD, P<0.001; HR = 2.03, 95% CI, 1.45-2.84) and the validation cohorts (GSE84437, P = 0.005; HR = 1.48, 95% CI, 1.16-1.95; GSE13861, P = 0.03; HR = 2.23, 95% CI, 1.07-4.62). The risk-score was positively correlated with densities of tumor-infiltrating immunosuppressive cells (P < 0.05) and was lower in patients who responded to pembrolizumab monotherapy (P = 0.03). Besides, patients with a high risk-score had higher sensitivities to the inhibitors against the PI3K-mTOR and angiogenesis (P < 0.05). Expression analysis verified the promoting roles of FEN1, PDGFRB, SERPINE1, and TCF3, and the suppressing roles of APOC3 and SNCG in GC, respectively. Immunohistochemistry staining and single-cell analysis revealed their location and potential origins. Taken together, the senescence gene-based model may potentially change the management of GC by enabling risk stratification and predicting response to systemic therapy.
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FSTL4 interaction with Gαi proteins activates the Akt-mTOR pathway to drive malignant phenotypes in non-small cell lung cancer.
Non-small cell lung cancer (NSCLC) presents a critical challenge clinically; thus, identifying novel drivers and reliable prognostic biomarkers is imperative. Here, we investigated the clinical relevance, cell-type-specific localization, and mechanistic role of Follistatin-like 4 (FSTL4) in NSCLC. Analysis of The Cancer Genome Atlas (TCGA) and local resected tissue samples show that FSTL4 expression is significantly elevated in NSCLC tissues compared to normal lung tissues, and serves as an independent prognostic indicator for reduced overall survival. Single-cell RNA sequencing confirmed that FSTL4 expression is predominantly and consistently localized to the malignant epithelial cell population across primary tumors and metastatic niches in lung adenocarcinoma (LUAD). Functionally, stable knockdown or CRISPR/Cas9-mediated knockout of FSTL4 across multiple NSCLC cell types suppressed key malignant phenotypes, including cell proliferation, and migration, and inducing G1-phase cell cycle arrest and triggering intrinsic apoptosis. This cytotoxic dependency was selective to malignant cells, as normal lung epithelial cells remained unaffected. Conversely, ectopic overexpression of FSTL4 enhanced these aggressive characteristics. Mechanistically, FSTL4 exerts its pro-oncogenic effects through regulating the Akt-mTOR signaling cascade. FSTL4 physically interacts with the inhibitory G-protein subunits Gɑi1 and Gɑi3, and the co-depletion of these subunits inhibited FSTL4-mediated Akt-mTOR activation. Crucially, the functional effects of FSTL4 silencing in primary human NSCLC cells were rescued by the introduction of a constitutively active Akt1 (caAkt1, S473D) construct, confirming Akt as the essential required downstream transducer. In vivo validation further demonstrated that FSTL4 silencing profoundly attenuated NSCLC xenograft tumor growth by reducing proliferation and accelerating apoptosis, mirroring the diminished Akt-mTOR activation observed in vitro. Collectively, these comprehensive findings unequivocally establish that elevated FSTL4 expression promotes malignant phenotypes of NSCLC possibly by activating Gɑi1/3-Akt-mTOR cascade.
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Characterizing the key genes of COVID-19 that regulate tumor immune microenvironment and prognosis in hepatocellular carcinoma.
Hepatocellular carcinoma (HCC), a highly heterogeneous malignant tumor associated with a poor prognosis, is a common cause of cancer-related deaths worldwide, with a limited survival benefit for patients despite ongoing therapeutic breakthroughs. Coronavirus disease 2019 (COVID-19), a severe infectious disease caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), is a global pandemic and a serious threat to human health. The increased susceptibility to SARS-CoV-2 infection and a poor prognosis in patients with cancer necessitate the exploration of the potential link between the two. No studies have investigated the relationship of COVID-19 genes with the prognosis and tumor development in patients with HCC. We screened prognosis-related COVID-19 genes in HCC, performed molecular typing, developed a stable and reliable COVID-19 genes signature for predicting survival, characterized the immune microenvironment in HCC patients, and explored new molecular therapeutic targets. Datasets of HCC patients, including RNA sequencing data and clinical information, were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Prognosis-related COVID-19 genes were identified by univariate Cox analysis. Molecular typing of HCC was performed using the consensus non-negative matrix factorization method (cNMF), followed by the analysis of survival, tumor microenvironment, and pathway enrichment for each subtype. Prognostic signatures were constructed using LASSO-Cox regression models, and receiver operating characteristic (ROC) curves were used to validate the predictive performance of the signature. The same approach was used for the test and external validation sets. Seven software packages were applied to determine the abundance of immune infiltration in HCC patients and investigate its relationship with the risk scores. Gene set enrichment analysis (GSEA) was used to explore the potential mechanisms by which the COVID-19 genes affect hepatocarcinogenesis and prognosis. Three types of machine learning methods were combined to identify the most critical genes in the signature and localize their expression at the single cell level. We identified 53 prognosis-related COVID-19 genes and classified HCC into two molecular subtypes (C1, C2) by using the NMF method. The prognosis of C2 was significantly better than that of C1, and the two subtypes differed remarkably in terms of the tumor immune microenvironment and biological functions. The 17 COVID-19 genes were screened using the LASSO regression method to develop a 17 COVID-19 genes signature, which demonstrated a good predictive performance for 1-, 2- and 3-year OS of patients with HCC. The risk score as an independent prognostic factor for HCC has better predictive accuracy than traditional clinical variables. Patients in the TCGA cohort were categorized by risk score into the high- and low-risk groups, with the high-risk group mainly enriched in the immune modulation-related pathways and the low-risk group mainly enriched in the metabolism-related pathways, suggesting that the COVID-19 genes may affect disease progression and prognosis by regulating the tumor immune microenvironment and metabolism in HCC. NOL10 was identified as the most critical gene in the signature and hypothesized to be a potential therapeutic target for HCC. Objectively, the COVID-19 genes signature developed in this study, as an independent prognostic factor in HCC patients, is closely associated with the prognosis and tumor immune microenvironment of HCC patients and indicates that they may regulate the development of HCC in multiple ways, providing us with new perspectives for understanding the molecular mechanisms of HCC and finding effective therapeutic targets.
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Senescent fibroblasts secrete CTHRC1 to promote cancer stemness in hepatocellular carcinoma.
BACKGROUND: Cellular senescence plays a significant role in tumorigenesis and tumor progression. Substantial evidence indicates that senescence occurs in cancer-associated fibroblasts (CAFs), the predominant stromal component within the tumor microenvironment (TME), which profoundly impacts tumor biology. However, despite growing evidence of stromal cell involvement in cancer progression, the specific mechanisms and clinical implications of senescent CAFs (SCAFs) in hepatocellular carcinoma (HCC) have not been fully elucidated. METHODS: The senescence signature was utilized to evaluate the senescence status of cell types within the TME of HCC using the GSE149614 dataset. The CytoTRACE and cell-cell communication analysis were used to find the correlation between cancer stemness and SCAFs. A risk prediction model associated with SCAFs was constructed to investigate potential mechanisms by which SCAFs promote tumor progression. Single-cell RNA sequencing data was used to identify senescent CAF-related genes. Gene expression and clinical data for HCC were obtained from the Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and National Omics Data Encyclopedia (NODE) databases. Using four machine-learning algorithms, crucial genes were identified to develop a CAF-senescence-related risk model, predicting prognosis, cancer stemness, immune infiltration, tumor mutation burden, and therapeutic responses in HCC patients. Next, we explored the role of Collagen Triple Helix Repeat Containing-1 (CTHRC1) in cancer stemness using both in vitro and in vivo experiments. Through various functional experiments, we elucidated the downstream signaling pathways of CTHRC1. Additionally, chromatin immunoprecipitation experiments were used to verify that key transcription factors bind to the CTHRC1 promoter region. RESULTS: CAFs exhibited high senescence status and a strong correlation with cancer stemness in HCC. A novel CAF-senescence-score (CSscore) prognostic model was established for HCC based on 10 genes: CTHRC1, SERPINE1, RNF11, ENG, MARCKSL1, ASAP1, FHL3, LAMB1, CD151, and OLFML2B. The survival prediction performance was validated on TCGA, ICGC, and NODE cohorts. Immune analysis revealed that the CSscore was positively correlated with immunosuppressive immune cell populations, including M2 macrophages and regulatory T cells. Conversely, a negative correlation was observed between the CSscore and anti-tumor immune cells such as CD8 + T cells, dendritic cells, and B cells HCC patients with a low CSscore had a lower tumor mutation burden and showed improved responsiveness to immunotherapy and transarterial chemoembolization. In vitro experiments and bioinformatics analysis further revealed that CTHRC1 was significantly elevated in SCAFs promoted cancer stemness and metastasis via the SRY-box transcription factor 4 (SOX4)-CTHRC1-Notch1 axis in HCC. CONCLUSION: Our study revealed that SCAFs were strongly correlated with cancer stemness in HCC. A novel machine learning model based on senescent CAF-related genes was constructed to accurately predict prognosis in HCC patients. Furthermore, CTHRC1 was identified as a novel prognostic and therapeutic biomarker to predict poor prognosis in HCC and promote cancer stemness and metastasis through the Notch signaling pathway, with its expression being transcriptionally regulated by SOX4.