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Single-cell transcriptomics reveals the impact of sex and age in the healthy human liver.
BACKGROUND & AIMS: The liver is a vital organ composed of parenchymal, non-parenchymal, and immune cell populations. Single-cell sequencing approaches now provide the opportunity to understand how sex and age influence gene expression and cellular function across cell types within the liver. METHODS: We analyzed the cellular composition and intercellular interactions of the human liver through single-nucleus RNA sequencing, incorporating insights from 37 healthy liver samples. The dataset contains cells from female and male donors spanning more than seven decades of life, and analysis was performed to evaluate the impact of sex and age on differential gene expression, pathway enrichment, and predicted ligand-receptor and protein-protein interactions. RESULTS: Excluding the X and Y chromosomes, we identified 374 genes uniquely enriched in cells of the female liver and 520 genes enriched in cells of the male liver. Differential expression analysis defined unique circuitries enriched within each cell type between females and males and their impact on cell-cell communication and response to external signals, including enrichment of cholesterol metabolism (p <1.64 x 10-3), TGF-β receptor signaling (p <5.69 x 10-3), and fibronectin production (p <1.04 x 10-8) in female cells and bone morphogenic protein signaling (p <7.62 × 10-6) in male cells. With increasing age, we observe a greater diversity in gene expression, including enrichment of genes that regulate neuregulin signaling (p <7.81 × 10-3) at older ages, while genes regulating insulin growth factor signaling (p <2.44 × 10-3) are enriched at younger ages. Senescence signatures were also identified for each cell type within the liver. CONCLUSIONS: These results define the activities of healthy cell types within the liver across sex and age, providing a foundation for studies to examine how ancestry, geography, and disease states influence liver function within these contexts. IMPACT AND IMPLICATIONS: Our study provides a comprehensive single-cell analysis of 37 healthy human liver samples, revealing how sex and age influence gene expression profiles, cellular interactions, and signaling responses across liver cell types and subtypes. These insights are of particular significance for researchers investigating the influence of sex and age on cellular responses to injury and treatment of injury. Furthermore, this dataset serves as a healthy reference, enabling future studies to understand how ancestry, geography, and disease states shape liver biology in the context of age and sex.
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A gene expression atlas for kiwifruit (Actinidia chinensis) and network analysis of transcription factors.
BACKGROUND: Transcriptomic studies combined with a well annotated genome have laid the foundations for new understanding of molecular processes. Tools which visualise gene expression patterns have further added to these resources. The manual annotation of the Actinidia chinensis (kiwifruit) genome has resulted in a high quality set of 33,044 genes. Here we investigate gene expression patterns in diverse tissues, visualised in an Electronic Fluorescent Pictograph (eFP) browser, to study the relationship of transcription factor (TF) expression using network analysis. RESULTS: Sixty-one samples covering diverse tissues at different developmental time points were selected for RNA-seq analysis and an eFP browser was generated to visualise this dataset. 2839 TFs representing 57 different classes were identified and named. Network analysis of the TF expression patterns separated TFs into 14 different modules. Two modules consisting of 237 TFs were correlated with floral bud and flower development, a further two modules containing 160 TFs were associated with fruit development and maturation. A single module of 480 TFs was associated with ethylene-induced fruit ripening. Three "hub" genes correlated with flower and fruit development consisted of a HAF-like gene central to gynoecium development, an ERF and a DOF gene. Maturing and ripening hub genes included a KNOX gene that was associated with seed maturation, and a GRAS-like TF. CONCLUSIONS: This study provides an insight into the complexity of the transcriptional control of flower and fruit development, as well as providing a new resource to the plant community. The Actinidia eFP browser is provided in an accessible format that allows researchers to download and work internally.
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Canine peripheral blood TCRαβ T cell atlas: Identification of diverse subsets including CD8A+ MAIT-like cells by combined single-cell transcriptome and V(D)J repertoire analysis.
The dog is valued as a companion animal and increasingly recognized as a model for human disorders. Given the importance of T cells in health and disease, comprehensive knowledge of canine T cells can contribute to our understanding of pathogenesis mechanisms and inform the development of new treatment strategies. However, the diversity of canine T cells is still poorly understood mainly due to the lack of species-reactive antibodies for use in flow cytometry. The aim of this study was to generate a detailed atlas of peripheral blood TCRαβ+ T cells of healthy dogs using single-cell RNA-sequencing (scRNAseq) combined with immune repertoire sequencing. A total of 22 TCRαβ+ T cell clusters were identified, which were classified into three major groups: CD4-dominant (11 clusters), CD8A-dominant (8 clusters), and CD4/CD8A-mixed (3 clusters). Based on differential gene expression, distinct differentiation states (naïve, effector, memory, exhausted) and lineages (e.g. CD4 T helper and regulatory T cells) could be distinguished. Importantly, several T cell populations were identified, which have not been described in dogs before. Of particular note, our data provide first evidence for the existence of canine mucosa-associated invariant T cell (MAIT)-like cells, representing one of three newly identified FCER1G+ innate-like CD8A+ T cell populations in the peripheral blood of healthy dogs. In conclusion, using scRNAseq combined with immune repertoire sequencing we were able to resolve canine TCRαβ+ T cell populations at unprecedented resolution. The peripheral blood TCRαβ+ T cell atlas of healthy dogs generated here represents an important reference data set for future studies and is of relevance for identifying new targets for T cell-specific therapies.
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Gene signatures of palmitoylation and fatty acid metabolism predict prognosis and immunotherapy response in breast cancer patients by machine learning, single-cell analysis, and experimental validation.
BACKGROUND: Palmitoylation and dysregulated fatty acid metabolism are key components of tumor metabolic reprogramming and play important roles in the initiation, progression, and immune regulation of breast cancer (BRCA). However, their systemic molecular characteristics and clinical predictive value remain incompletely understood. METHODS: This study integrated transcriptomic and clinical data from The Cancer Genome Atlas, GTEx, and Gene Expression Omnibus databases to identify genes associated with fatty acid metabolism and palmitoylation that are aberrantly expressed in tumors. Using Cox and LASSO regression analyses, we constructed a prognostic risk model to stratify patients into distinct risk groups and evaluated differences in survival outcomes, immune profiles, and predicted therapeutic responses. Furthermore, we performed additional analyses, including pan-cancer analysis, tumor microenvironment characterization, drug sensitivity prediction, single-cell RNA sequencing analysis, and in vitro and in vivo functional experiments, to investigate the potential biological and clinical relevance of these findings. RESULTS: This study identified a set of genes associated with palmitoylation and fatty acid metabolism that are significantly linked to BRCA prognosis, and constructed a prognostic risk model to stratify patients into distinct risk groups. Significant differences were observed between the high- and low-risk groups regarding overall survival, immune cell infiltration, immune checkpoint expression, and predicted immunotherapy efficacy. Further analysis identified G6PD as a key gene associated with poor prognosis. Epithelial cells with high G6PD expression exhibited enhanced activity in palmitoylation and fatty acid metabolism pathways, accompanied by altered intercellular communication within the TME. Knockdown of G6PD inhibited the proliferation and migration of BRCA cells and suppressed tumor growth in vivo. Potential interactions between G6PD and candidate compounds suggest its therapeutic potential. CONCLUSION: This study indicates that gene signatures associated with palmitoylation and fatty acid metabolism may be relevant to prognostic stratification and the prediction of immunotherapy efficacy in BRCA. Furthermore, the study identifies G6PD as a key metabolic gene linked to tumor progression; this finding not only offers potential insights into the molecular mechanisms of BRCA but also supports further exploration of metabolism-related therapeutic strategies.
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Identification of RAC1 in promoting brain metastasis of lung adenocarcinoma using single-cell transcriptome sequencing.
This study aims to give a new perspective to the biomarkers in the lung adenocarcinoma (LUAD) brain metastasis, pathways involved and potential therapeutics. We performed a comprehensive single-cell level transcriptomic analysis on one LUAD patient with circulating tumor cells (CTCs), primary tumor tissue and metastatic tumor tissue using scRNA-seq approach to identify metastasis related biomarkers. Further scRNA-seq were performed on 7 patients to validate the cancer metastatic hallmark. with single cells collected from either metastatic or primary LUAD tissues. Pathological and functional studies were also performed to evidence the critical role of RAC1 in the LUAD metastasis. Hallmark gene was verified based on immunohistochemistry staining, cytological experiment, survival information from The Cancer Genome Atlas (TCGA), and staining results from Human Protein Atlas (HPA) databases. PCA analysis revealed that CTCs were in the intermediate place between the metastatic group and primary group. In the unsupervised clustering analysis CTCs were closer to one of the metastatic tumor cells, implying heterogeneity of the metastatic tumor and origin of the CTCs were from metastatic site. Transitional phase related gene analysis identified RAC1 was enriched in metastatic tumor tissue (MTT) preferred gene set functioning as regulated cell death and apoptosis as well as promoted macromolecule organization. Compared with normal tissue, expression levels of RAC1 increased significantly in LUAD tissue based on HPA database. High expression of RAC1 predicts worse prognosis and higher-risk. EMT analysis identified the propensity of mesenchymal state in primary cells while epithelial signals were higher in the metastatic site. Functional clustering and pathway analyses suggested genes in RAC1 highly expressed cells played critical roles in adhesion, ECM and VEGF signaling pathways. Inhibition of RAC1 attenuates the proliferation, invasiveness and migration ability of lung cancer cells. Besides, through MRI T2WI results, we proved that RAC1 can promote brain metastasis in the RAC1-overexpressed H1975 cell burden nude mouse model. RAC1 and its mechanisms might promote drug design against LUAD brain metastasis.
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HSP70-Mediated Macrophage-Stromal Crosstalk is an Immunopathogenic Driver of Recurrent Implantation Failure.
BACKGROUND: Recurrent implantation failure (RIF) remains a major challenge in assisted reproductive technology (ART), affecting a considerable proportion of patients despite multiple transfers of high-quality embryos. Although impaired endometrial receptivity is recognized as a critical contributor to RIF, the molecular mechanisms responsible for establishing a non-receptive endometrial microenvironment remain incompletely understood. The proliferative phase precedes decidualization and subsequent embryo implantation, representing a critical period for endometrial preparation. The endometrium is a highly dynamic tissue composed of diverse epithelial, stromal, vascular, and immune cell populations that undergo coordinated remodeling throughout the menstrual cycle; however, the cell type-specific alterations and pathogenic immune-stromal interactions during this phase have not been comprehensively characterized. OBJECTIVE: This study aimed to dissect the transcriptional landscape of the proliferative-phase endometrium in RIF patients, and validate the key pathways through experimental approaches. STUDY DESIGN: We for the first time performed single-cell RNA sequencing (scRNA-seq) of proliferative-phase endometrial tissues from RIF patients and control subjects to characterize cell-type-specific transcriptional alterations and intercellular communication patterns. Peripheral blood scRNA-seq was additionally performed to determine whether immune alterations were tissue-specific or systemic. The impact of HSP70 on the transcriptome of endometrial stromal cells was investigated using RNA sequencing. The production of HSP70 and CCL7 in RIF patients was measured by enzyme-linked immunosorbent assay (ELISA). The HSP70/CCL7 axis-mediated functional crosstalk between macrophages and endometrial stromal cells was investigated using Transwell assay, QPCR, and SA-β-Gal staining. HSP70-induced activation of PI3K signaling was predicted using RNA sequencing data, then validated through Western blot, ELISA, and Transwell assay. RESULTS: We identified excessive inflammatory immune infiltration as a microenvironmental hallmark of RIF endometrium, as reflected by increased percentages of T cells, monocytes, and NK cells. This alteration is associated with pathogenic macrophage - stromal crosstalk. Mechanistically, an inflammatory milieu promotes the expression of 70-kDa heat shock protein (HSP70) in macrophages, which stimulates CCL7 production in endometrial stromal cells via PI3K signaling. CCL7 drives the recruitment of multiple types of immune cells that further amplify the inflammation. Neutralization of CCL7 or inhibition of PI3K signaling prevented this pro-inflammatory infiltration. The HSP70-CCL7 axis facilitates endometrial stromal cell senescence and leads to impaired decidualization. CONCLUSION: This study provides the first single-cell transcriptomic atlas of proliferative-phase endometrium in RIF and identifies a pathogenic macrophage-stromal communication network associated with HSP70/CCL7 axis. Our findings reveal that inflammatory microenvironmental remodeling occurs before the window of implantation and contributes to subsequent endometrial dysfunction. Targeting HSP70/CCL7-mediated immune-stromal crosstalk may represent a promising therapeutic strategy for early intervention and prevention of RIF.
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Integrative Analysis Identified MCT4 as an Independent Prognostic Factor for Bladder Cancer.
BACKGROUND: Bladder cancer is the 10th most common cancer and most common urothelial malignancy worldwide. Prognostic biomarkers for bladder cancer patients are required for individualized treatment. Monocarboxylate transporter 4 (MCT4), encoded by SLC16A3 gene, is a potential biomarker for bladder cancer because of its crucial role in the lactate efflux in the aerobic glycolysis process. We aimed to study the association between MCT4 expression and the overall survival (OS) of bladder cancer patients. METHODS: The published single-cell RNA sequencing data of 49,869 bladder cancer cells and 15,827 normal bladder mucosa cells and The Cancer Genome Atlas (TCGA) bladder cancer cohort data were used to explore the mRNA expression of SLC16A3 in bladder cancer. Eighty-nine consecutive bladder cancer patients who had undergone radical cystectomy were enrolled as a validation cohort. The expression of MCT4 proteins in bladder cancer specimens was detected using immunohistochemistry staining. The Kaplan-Meier survival analysis and Cox regression were performed to analyze the association between MCT4 protein expression and OS in bladder cancer patients. RESULTS: SLC16A3 mRNA was upregulated in bladder cancer cells. The upregulated genes in SLC16A3-positive epithelial cells were enriched in the glycolysis process pathway and monocarboxylic acid metabolic process pathway. Patients with high SLC16A3 mRNA expression showed significantly poor OS (p = 0.016). High MCT4 protein expression was also found to be an independent predictor for poor OS in bladder cancer patients (HR: 2.462; 95% CI: 1.202~5.042, p = 0.014). A nomogram was built based on the results of the multivariate Cox analysis. CONCLUSION: Bladder cancer with high SLC16A3 mRNA expression has a poor OS. High MCT4 protein expression is an independent prognostic factor for bladder cancer patients who had undergone radical cystectomy.
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Dissecting the Single-Cell Transcriptome Network Underlying Gastric Premalignant Lesions and Early Gastric Cancer.
Intestinal-type gastric cancer is preceded by premalignant lesions, including chronic atrophic gastritis and intestinal metaplasia. In this study, we constructed a single-cell atlas for 32,332 high-quality cells from gastric antral mucosa biopsies of patients spanning a cascade of gastric premalignant lesions and early gastric cancer (EGC) using single-cell RNA sequencing. We then constructed a single-cell network underlying cellular and molecular characteristics of gastric epithelial cells across different lesions. We found that gland mucous cells tended to acquire an intestinal-like stem cell phenotype during metaplasia, and we identified OR51E1 as a marker for unique endocrine cells in the early-malignant lesion. We also found that HES6 might mark the pre-goblet cell cluster, potentially aiding identification of metaplasia at the early stage. Finally, we identified a panel of EGC-specific signatures, with clinical implications for the precise diagnosis of EGC. Our study offers unparalleled insights into the human gastric cellulome in premalignant and early-malignant lesions.
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Circulating and tumor-infiltrating immune cell profiles in cervical cancer checkpoint blockade: multi-omics biomarkers of response and resistance.
Immune checkpoint blockade has changed the therapeutic landscape of cervical cancer, but clinical benefit remains heterogeneous and difficult to predict with single biomarkers. Cervical cancer is a particularly suitable setting for immune-cell profiling because HPV-driven antigenicity, chemoradiotherapy-induced tissue remodeling, anti-angiogenic combinations, and repeated exposure to PD-1/PD-L1 inhibitors all shape the blood-tumor immune axis. This Mini Review discusses how circulating immune cells and tumor-infiltrating immune cells can be jointly interrogated by multi-omics technologies to identify biomarkers of response and resistance. We focus on single-cell RNA sequencing, T-cell receptor/B-cell receptor (TCR/BCR) profiling, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), flow cytometry, spatial transcriptomics, high-plex spatial proteomics, bulk transcriptomics, cytokine profiling, and circulating tumor DNA (ctDNA)-informed longitudinal designs. Recent cervical cancer atlases suggest that response is unlikely to be explained by total immune infiltration alone, but instead reflects the spatial organization and functional states of cytotoxic T cells, NK cells, antigen-presenting cells, tertiary lymphoid structure (TLS) programs, regulatory T cells, myeloid cells, and cancer-associated fibroblasts (CAFs). We propose a blood-to-tumor framework in which dynamic peripheral phenotypes may monitor systemic immune competence, while tissue multi-omics may identify local immune exclusion, terminal exhaustion, and myeloid suppression. Prospective paired sampling and interpretable, externally validated AI-assisted computational integration are needed before these biomarkers can guide treatment selection.
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HCNetlas: A reference database of human cell type-specific gene networks to aid disease genetic analyses.
Cell type-specific actions of disease genes add a significant layer of complexity to the genetic architecture underlying diseases, obscuring our understanding of disease mechanisms. Single-cell omics have revealed the functional roles of genes at the cellular level, identifying cell types critical for disease progression. Often, a gene impact on disease through its altered network within specific cell types, rather than mere changes in expression levels. To explore the cell type-specific roles of disease genes, we developed HCNetlas (human cell network atlas), a resource cataloging cell type-specific gene networks (CGNs) for various healthy tissue cells. We also devised 3 network analysis methods to investigate cell type-specific functions of disease genes. These methods involve comparing HCNetlas CGNs with those derived from disease-affected tissue samples. These methods find that systemic lupus erythematosus genes predominantly function in myeloid cells, and Alzheimer's disease genes mainly play roles in inhibitory and excitatory neurons. Additionally, they suggest that many lung cancer-related genes may exert their roles in immune cells. These findings suggest that HCNetlas has the potential to link disease-associated genes to cell types of action, facilitating development of cell type-resolved diagnostics and therapeutic strategies for complex human diseases.