To identify metastasis-associated prognostic genes and construct a robust molecular signature for survival prediction in uveal melanoma (UVM) patients. Transcriptomic data and clinical information from 80 UVM patients in the Cancer Genome Atlas (TCGA)-UVM cohort and an external Gene Expression Omnibus (GEO) microarray dataset (GSE73652; 8 non-metastatic vs 5 metastatic cases) were analyzed to identify differentially expressed genes (DEGs). Functional enrichment, protein-protein interaction (PPI) network construction, and survival analyses identified seven metastasis- and prognosis-related genes. Their expression was further examined using public single-cell RNA-seq data (GSE139829; 11 tumors). Experimental validation was performed in UVM cell lines (92.1, OMM1, MEL270) and adult retinal pigment epithelial (ARPE-19) cells using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting to confirm transcriptomic trends. A LASSO Cox model was applied to construct a metastasis-related risk Score signature. Tumor immune microenvironment characteristics were evaluated via single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE. Somatic mutation and copy number variation (CNV) profiles were also examined. Seven key genes (UBE2T, KIF20A, DLGAP5, KLC3, TPX2, UBE2C, AURKA) were significantly associated with overall survival and used to construct a metastasis-related riskScore signature, which effectively stratified patients into high- and low-risk groups and served as an independent prognostic factor. qRT-PCR and Western blot results confirmed that the expression levels of selected key genes in UVM cell lines showed significant differences compared to ARPE-19 cells, which were largely consistent with the transcriptomic findings. The high-risk group exhibited reduced immune infiltration and stromal activity. Single-cell analysis revealed these genes were predominantly expressed in a tumor cell cluster characterized by BAP1 loss and high metastatic potential. Mutation and CNV analyses further supported the relevance of these genes to UVM progression. This study establishes and validates a seven-gene signature associated with metastasis and prognosis in UVM. The findings provide a framework for understanding molecular determinants of tumor progression and immune microenvironment alterations, and may offer guidance for future mechanistic studies and therapeutic exploration.

Acute-on-chronic liver failure (ACLF) is a life-threatening syndrome involving dysfunction of multiple immune cell types. This study aimed to comprehensively depict the dynamic trajectory of immune responses throughout the disease course of HBV-related ACLF (HBV-ACLF). Single-cell RNA sequencing and single-cell proteomics were performed on the peripheral blood mononuclear cells of 45 samples from 17 patients who were hospitalised (progressive/stable/recovering course of HBV-ACLF, 6/5/6) and 15 control subjects (liver cirrhosis, chronic hepatitis B and healthy controls, 5/5/5). Functional and mechanistic experiments were validated in vivo and in vitro. Single-cell multiomics analysis revealed specific changes in the peripheral immune response in ACLF. VCAN+CD14+-monocytes with activated interferon-stimulated genes and enhanced inflammatory functions, stimulated by HBV relapse and expanded in ACLF-1, fuelling early inflammatory storm. The subsequent apoptotic hepatocytes predominantly induce hyperinflammatory C-X-C motif chemokine receptor 2 (CXCR2)+-neutrophils and CD163+-monocytes, enriching in patients with progressive ACLF and serving as significant markers of disease deterioration. Cytotoxic T-cells were functionally impaired and significantly decreased in progressive patients. CXCR2+-neutrophils exhibited immunosuppressive activity and induced the exhaustion of cytotoxic T-cells. Pharmacological inhibition of CXCR2 significantly reduced neutrophils infiltration, restored cytotoxic T-cells and showed therapeutic effect in ACLF mice. Six immune cellular modules (CMs) were identified for patient stratification, with CM2 and CM6 showing strong predictive value for disease outcomes, and CM3 indicating a potential early therapeutic window. Our longitudinal multiomics study revealed the dynamic evolution of the immune response in HBV-ACLF and characterised diverse immune patterns for the future precise management and therapeutic intervention.

Dissecting the immune pathogenesis of HBV-ACLF through single-cell multimodal analysis.

Digital twins for in vivo metabolic flux estimations in patients with brain cancer.

The role of androgen receptor (AR) signaling in modulating antitumor immune responses has received increasing attention in recent years; however, its broader impact across diverse cancer types and between sexes remains largely unexplored. In this study, we investigated how AR activity correlates with tumor-infiltrating leukocytes, patient prognosis, and immunotherapy response across cancers and sexes. We inferred AR activity using a network-based approach across bulk RNA sequencing [RNA-seq; The Cancer Genome Atlas (TCGA)], single-cell RNA-seq (prostate cancer meta-atlas), and immunotherapy cohorts. Pathway analysis and Cox regression assessed mechanisms and survival. Immune infiltration and signatures were evaluated via TIMER and single-sample gene set enrichment analysis. Key findings were validated using digital spatial profiling and IHC. Our pan-cancer analysis of 33 TCGA cancer types revealed broad variability in AR activity, with highest observed in prostate adenocarcinoma. Genes significantly correlated with AR activity showed negative associations and were enriched in immune activation pathways. Notably, AR activity inversely correlated with leukocyte abundance and IFNγ pathway activity across tumors and sexes—unlike estrogen or progesterone receptors. Longitudinal biopsy analysis in metastatic prostate cancer showed that AR inhibition enhanced immune cell and IFNγ signatures. Single-cell analysis confirmed that tumor-intrinsic AR activity inversely correlates with immune infiltration in prostate cancer. Furthermore, low AR activity is significantly associated with favorable immunotherapy responses in hormone-independent cohorts. Spatial proteomics showed a negative correlation between AR and CD45 protein in sarcoma and ovarian cancers. These findings suggest AR activity as a pan-cancer predictive biomarker of immunotherapy response and support that AR blockade in immunotherapy-refractory tumors represents a promising treatment strategy, regardless of tumor type or patient sex.Significance:Tumor-associated AR activity negatively correlates with immune infiltration and immunotherapy response across cancers, independent of sex, suggesting that combining AR inhibitors with checkpoint blockade may benefit patients with immunotherapy-refractory tumors.

Aging cells in the bone marrow contribute to bone aging and related diseases. By combining single-cell and bulk RNA analysis, we aim to better understand the changes in the bone marrow micro-environment caused by aging. We established single-cell profiles of bone marrow from young and aging mice to identify cell types that exhibited significant aging-related changes. And differential gene enrichment analysis and cell-cell communication analysis were conducted on cells with significant changes. Then, we validated the enrichment analysis results using bulk RNA sequencing. Based on sequencing data and machine learning, we identified key genes involved in cellular aging. And the best anti-aging drugs were screened through molecular docking. Finally, the communication between cells, effectiveness of drugs and key genes were validated through experiments. In the aged bone marrow, the content of mesenchymal stem cells (BMSCs) and macrophages (BMMs) significantly increases. The aging of bone marrow is related to cellular fibrosis, immune inflammatory response, resulting in reduced ossification and enhanced osteoclast differentiation. Aging BMSCs secrete various cytokines to promote the aging of BMMs, such as adiponectin, annexin, and galectin. The effect of aging BMMs on BMSCs is relatively small. CADM1 and FAP may be key targets for BMSCs and BMMs aging. Rapamycin has the highest binding affinity with target gene and can to some extent reverse the aging of bone marrow cells. Aged bone marrow cells can further spread aging, and the interaction between bone marrow cells helps us better understand bone aging.

Stress induces a neutrophil subtype in the lungs that secretes CCL3 and CCL4 to stimulate metastasis of breast cancer cells by activating CCR1, offering potential strategies for preventing or treating metastasis.

Single-cell analysis integrated with RNA-Sequencing uncovers new action of Patchoulol on adipose tissue remodeling in obesity.

Dissecting macrophage heterogeneity in ulcerative colitis: Single-cell analysis and functional validation of S100A4 as a therapeutic target.

Metabolic analysis of tumor cells is crucial for understanding tumor metabolic reprogramming, and single-cell metabolic accumulation studies provide precise insights into tumor biology. In this work, we established a microfluidic assay for single-cell metabolic accumulation analysis by combining droplet-generated hydrogel microspheres for single-cell encapsulation with a microchamber culture chip for microsphere isolation and 3D cultivation. This system enables efficient accumulation of secreted metabolites from individual cells for downstream analysis. Coupled with mass spectrometry, this system revealed metabolic accumulation heterogeneity among individual cells of the same tumor type. Moreover, metabolic profiling of different tumor types, including A549, HepG2, and HCT116, demonstrated distinct metabolic patterns, enabling cell classification based on accumulation differences. The method supports high-throughput, multiplexed, and dynamic metabolic analysis in a 3D single-cell context, offering a scalable strategy for decoding tumor heterogeneity with potential application in cell-state characterization and advancing oncology research.

Postinfarct myocardial remodeling is modulated by myeloid-derived cells; however, the precise mechanism remains to be fully elucidated. Here, by the targeted single-cell RNA sequence (scRNA-Seq) analysis, we newly identified a myeloid cell population that specifically expresses glycoprotein A repetition-predominant (GARP), a docking receptor and activator of latent transforming growth factor βs (TGF-βs). GARP-expressing myeloid (GEM) cells exhibited the gene expression profile characteristic of fibrocytes, fibroblast-like myeloid cells. Myeloid cell-specific GARP-null mice (GARP-CKO mice) showed ameliorated cardiac fibrosis and improved cardiac function after myocardial infarction (MI). Myeloid-specific GARP gene ablation resulted in the suppression of TGF-β signaling in cardiomyocytes and reduced the neutrophil infiltration into infarct myocardium, accompanied by decreased neutrophil chemotaxis cytokine production. In addition, cardiomyocyte apoptosis decreased in GARP-CKO mice, proposing that myeloid GARP/TGF-β axis is involved in cardiomyocyte loss. Comprehensive scRNA-Seq data, combined with the published dataset of healthy heart cells, revealed that GEM cells were derived from heart-resident fibrocytes. Finally, the Visium data of patients with MI suggested the existence of GARP+CD11b+ cells in postinfarct myocardium. Collectively, GARP-expressing fibrocytes deteriorate cardiac remodeling by regulating neutrophil infiltration and cardiomyocyte apoptosis. The blockade of the transition from fibrocytes to GEM cells could be a therapeutic strategy against postinfarct heart failure.NEW & NOTEWORTHY Myeloid cells are known to contribute to the progression of myocardial infarction. However, the precise roles of these cells have not been fully elucidated. Single-cell RNA sequencing analysis demonstrated a population of glycoprotein A repetition-predominant (GARP)-expressing myeloid cells (GEM cells) that were derived from heart-resident fibrocytes. GEM cells were found to regulate neutrophil infiltration and cardiomyocyte apoptosis, resulting in detrimental cardiac remodeling. Spatial transcriptomics suggests that GEM cells are also present in human infarcted myocardium.

Technology-enabled integration of single-cell transcriptomics and microbiome data identifies RNA-targetable host-microbiota networks in colorectal adenoma.

Combining single-cell analysis and Mendelian randomization to elucidate the molecular mechanisms of fibronectin-related genes in multiple sclerosis.

hepatocellular carcinoma (HCC) is a major cancer, and PTTG1 alters asparagine metabolism to promote HCC progression, but its diagnostic and prognostic significance in HCC remains unclear. This study aimed to evaluate the prognostic value of PTTG1-related genes in hepatocellular carcinoma by integrating Mendelian randomization, transcriptomic analysis, and single-cell sequencing approaches. This study identified PTTG1-interacting differential genes (PTTG1-IDGs) through differential analysis and protein network construction, then applied Mendelian randomization (MR) to assess their causal relationship with HCC. Univariate Cox regression and machine learning methods screened prognostic genes and constructed prognostic model. CDC45 and CENPE were prognostic genes with a causal relationship to HCC. Notably, the odds ratios (ORs) of these prognostic genes were close to 1, indicating that although the two genes had a statistically significant causal association with HCC, the independent effect of each allele on HCC risk was weak. This reflected that PTTG1-related genes played a subtle regulatory role rather than a strong direct causal role in the pathogenesis of HCC. nomogram analysis indicated that risk score and pathological T-stage were independent prognostic factors. Immune infiltration and molecular network analysis highlighted the biological value of CDC45 and CENPE. Single-cell analysis demonstrated the key role of hepatocytes in HCC, while pseudotime analysis revealed the distribution of different cell subtypes. Cell communication analysis showed enhanced interactions between PTTG1-highly expressed cells and fibroblasts, myeloid cells, and endothelial cells; experimental validation confirmed elevated expression of CDC45 and CENPE in the HCC group in addition to PTTG1. Overall, CDC45 and CENPE, as prognostic genes related to PTTG1, provided new research perspectives and potential therapeutic targets for HCC treatment.

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

Technologic advances in flow cytometry.

Insights and advancements in molecular biology techniques in ophthalmology.

Gene expression and protein abundance: Just how associated are these molecular traits?

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited treatment options and poor prognosis. This study aimed to identify novel prognostic markers within the tumor microenvironment, particularly focusing on lipid-associated macrophages (LAMs). Using single-cell RNA sequencing (scRNA-seq) and transcriptome analysis, LGALS3BP was identified as a key lipid-related macrophage marker with significant prognostic value in TNBC. Our findings demonstrate that LGALS3BP is strongly associated with immune infiltration, particularly in influencing T cells and macrophages, and correlates positively with immune checkpoint expression. Furthermore, high LGALS3BP expression is linked to enhanced sensitivity to chemotherapeutic agents and improved outcomes in immunotherapy. These results highlight LGALS3BP as a potential biomarker for predicting TNBC prognosis and guiding personalized therapeutic strategies.

Background: The expression levels of the programmed death-ligand 1 (PD-L1) protein serves as a prognostic indicator for patients with colorectal cancer (CRC). Advancement of CRC is facilitated by deubiquitinating enzymes (DUBs), which regulate oncoprotein levels via the ubiquitin-proteasomal pathway. The post-translational regulatory mechanisms governing PD-L1 protein abundance on CRC, in relation to different tumor grades and their clinical relevance, remains unknown. Methods: We analyzed single-cell RNA sequencing (scRNA-seq) data to identify DUB genes associated with PD-L1 expression in CRC. We used a loss-of-function-based CRISPR/Cas9 library to identify putative DUB genes that regulate the PD-L1 protein level. Immunoprecipitation was used to confirm the interaction between the USP32 and PD-L1 along with its ubiquitination status. A series of in vitro and in vivo carcinogenesis-related experiments were conducted to determine the clinical relevance between USP32 and PD-L1 expression in CRC progression. Results: In this study, we analyzed scRNA-seq data from extensive cohorts of human and mice at the single-cell level to identify DUB genes associated with PD-L1 expression in CRC. Our analysis identified multiple putative DUBs, including USP32 and USP12, as prognostic markers associated with PD-L1 expression, which was found to be elevated in T cells, macrophages, and classical monocytes cell types in patients with CRC. A secondary screening using CRISPR/Cas9-mediated loss-of-function analysis for DUBs found that USP32 modulates PD-L1 protein levels in CRC. Furthermore, we demonstrated that USP32 interacts with, stabilizes, and extends the half-life of PD-L1 by preventing its K-48-linked polyubiquitination as an underlying mechanism that contributes for tumorigenesis. Conclusion: A combination of scRNA-seq analysis and wet-lab experimental validation confirmed that USP32 mediates PD-L1 protein stabilization in colon cancer, identifying it as a potential therapeutic target for CRC. CRISPR/Cas9-mediated targeted knockout of the USP32 gene reduced PD-L1 protein levels and significantly mitigated colorectal cell proliferation and tumorigenesis, both in vitro and in vivo, in a xenograft mouse model, underscoring a novel and alternative approach to the treatment of CRC.