Urinary extracellular vesicles (uEVs) have emerged as promising non-invasive molecular carriers for biomarker discovery, yet the physiological variability and tissue-associated characteristics of uEV RNA cargo in healthy individuals remain poorly defined. This knowledge gap limits the interpretation, normalization, and clinical translation of uEV-based transcriptomic studies. Here, we performed a longitudinal RNA-sequencing analysis of uEVs from 12 healthy donors, of whom six contributed complete longitudinal sample sets, to establish a molecular reference framework for physiological uEV transcriptomes. We systematically characterized inter- and intra-individual variation in uEV RNA cargo and found substantial transcriptomic heterogeneity despite relatively stable extracellular vesicle secretion levels over time. A conserved set of highly expressed genes was significantly enriched in ribosomal function and oxidative phosphorylation, indicating their role in fundamental cellular maintenance. Importantly, we identified 12 protein-coding genes that showed consistently low expression variance both across individuals and within individuals over time. Cross-dataset analyses using independent external and pan-cancer datasets further supported their potential utility as candidate reference transcripts for uEV RNA studies. Computational tissue deconvolution inferred predominant kidney- and bladder-associated transcriptomic signatures, while cell-type enrichment analysis showed relatively high enrichment scores for smooth muscle cells and mesenchymal stem cells. Together, this study defines the physiological landscape of healthy uEV transcriptomes, delineates key sources of biological variation, and provides candidate reference transcripts and tissue-associated molecular profiles to support the standardization and translational application of uEV-based molecular biomarker research.

Colorectal cancer progression and therapeutic response are determined not only by tumor-intrinsic programs but also by neural, stromal, and immune components of the tumor microenvironment. However, biologically interpretable transcriptomic scores that jointly capture neural/stromal remodeling and immune activation remain limited. We developed a neuro-immune score (NIS), defined as the neural/stromal module score minus the immune activation module score. NIS was constructed using the combined TCGA-COAD/READ colorectal cancer cohort and externally evaluated in independent Gene Expression Omnibus (GEO) datasets. Single-cell RNA sequencing, focused ligand-receptor analysis, and spatial transcriptomics were further integrated to characterize the cellular origins, spatial organization, and potential mechanisms underlying NIS-associated biology. A high NIS (NIS-high) was associated with adverse prognosis in bulk transcriptomic cohorts. External validation demonstrated that a high NIS was significantly associated with worse disease-free survival/relapse-free survival (DFS/RFS) in GSE39582 and worse overall survival in GSE17536. A multi-cohort meta-analysis further supported a consistent association between NIS-high and poor clinical outcomes. Single-cell analysis localized the NIS-high signal mainly to glial-like cells, fibroblasts, pericytes, endothelial cells, and malignant epithelial cells, whereas CD8+ T cells and natural killer cells exhibited low NIS. Focused ligand-receptor analysis suggested that NIS-high cellular compartments may communicate with immune and tumor compartments through MIF-CD74/CXCR4, SPP1-CD44, extracellular matrix (ECM)-integrin, TGF-β, and immune checkpoint-related axes. Spatial transcriptomics further demonstrated that NIS-high regions were enriched in stromal, neural/glial-like, vascular/pericyte, and tumor-stromal niches, whereas NIS-low regions were associated with immune-activated and cytotoxic T/NK cell-rich areas. NIS captures a spatially organized state of the colorectal cancer microenvironment characterized by neural/stromal remodeling, activation of ECM and vascular/pericyte niches, and relatively reduced or spatially segregated immune activation. NIS may serve as a biologically interpretable microenvironment stratification score associated with adverse outcomes. It also provides a framework for future studies targeting stromal remodeling, myeloid-mediated immune regulation, neural-associated signaling, and antitumor immunity.

Motivation Large-scale omics resources, including The Cancer Genome Atlas, Genomics of Drug Sensitivity in Cancer, and the Cancer Dependency Map, have become essential for cancer research. However, these datasets are distributed across different platforms, formats and analysis frameworks, which limits their practical use by researchers without extensive computational expertise.Results We developed CancerOmicsStudio (CoS), a web server for integrative and interpretable analysis of multi-omics cancer data across 33 cancer types. CoS provides five major modules: CosAI, Traditional Analysis, Drug Sensitivity, CRISPR Dependency and Single-Cell Tumor Microenvironment. The Traditional Analysis module supports expression comparison, diagnostic evaluation, survival analysis, enrichment analysis and gene correlation. The Drug Sensitivity and CRISPR Dependency modules enable systematic evaluation of gene-drug response associations and gene essentiality in cancer cell lines. The Single-Cell Tumor Microenvironment module supports tumor microenvironment analysis at single-cell resolution. In total, approximately 1.23 million results have been precomputed to enable rapid retrieval. CosAI further allows users to submit natural-language queries and obtain results through a Real-time Analysis as Retrieval framework, with responses summarized by a lightweight language model.Availability and implementation CancerOmicsStudio is freely available at Zenodo (doi: 10.5281/zenodo.18744990) and https://cos.wanglab.bio.

Severe fever with thrombocytopenia syndrome virus (SFTSV) infection is associated with poor clinical outcomes and defective humoral immunity yet the immunometabolic mechanisms underlying B cell dysfunction remain incompletely defined. Through integrated single-cell RNA sequencing and B cell receptor (BCR) repertoire profiling of peripheral B cells from SFTS patients, we dissected the molecular signatures between survivors and fatal cases. Functional validation and metabolic flux analysis were further performed. Seven transcriptionally distinct B cell subsets were identified. Fatal cases exhibited a marked expansion of CXCR3+Ki-67+CXCR5- extrafollicular plasmablasts, coupled with depletion of naïve and memory B cells. These plasmablasts exhibited hyperactivation of interferon-response genes (IFI27, ISG15), upregulation of inflammatory mediators (S100A8/A9), and contraction of BCR diversity, with skewed usage of λ-light chains. Pseudotime trajectory analysis and metabolic scoring revealed progressive upregulation of oxidative phosphorylation, glycolysis and endoplasmic reticulum stress during terminal differentiation. In fatal cases, B cells exhibited suppressed antigen presentation capacity and impaired immunoglobulin gene expression, alongside heightened oxidative stress and elevated CD39 levels. Furthermore, analysis of SFTSV-infected versus uninfected B cells revealed that infected plasmablasts displayed enhanced inflammatory and migratory features, including upregulated CXCR3 and CCR10 expression, suggesting direct viral modulation of B cell function and trafficking. Our study reveals that dysfunctional, metabolically reprogrammed plasmablasts underlie humoral immune failure in fatal SFTS. These findings provide mechanistic insight into B cell-mediated immunopathogenesis and highlight potential targets for prognostic evaluation and immunomodulatory intervention.

BACKGROUND:Although metabolic reprogramming in colorectal cancer (CRC) has been studied, the changes in metabolic pathways and cellular communication from a healthy colon to precancerous adenoma and CRC remain poorly understood. MATERIALS AND METHODS:Here, we utilized single-cell transcriptome data including normal, polyp, and tumor colon tissues to construct the epithelial cell differentiation trajectory during CRC progression. We scored pathway and lactylation activities using AUCell to analyze changes in CRC progression and the trajectory. We explored the cell communication between epithelial cells and other stromal cells during the process from polyps to CRC through cell communication analysis. Based on the transcription factor-gene-pathway regulatory network analysis, potential regulatory mechanisms were inferred. RESULTS:We demonstrated that epithelial cell subpopulations dominate the malignant transformation process of CRC. The malignant trajectory of epithelial cell is accompanied by significant dysregulation of fatty acid and bile acid metabolism pathways, which may contribute to early CRC development. Additionally, this trajectory was associated with increased stemness, metastatic potential, and lactylation activity. The communication between myofibroblasts/endothelial and enterocytes subpopulations was established in the early CRC stages. Continuously altered genes (RUNX1, SOX4 STAT3, FOXO1) during CRC progression were closely related to metabolic regulations. Finally, seven dynamically changed lactylation-associated genes (HNRNPA1, PRPF6, PTMA, CALD1, FAM50A, RPL29, and RPL5) during CRC malignant transformation were identified as potential targets for metabolic intervention in CRC, highlighting a lactylation-related TF-gene-pathway regulatory network driving metabolic reprogramming. CONCLUSION:This study elucidates the malignant evolution of epithelial cells, along with changes in metabolic pathway activity and key regulators, jointly promote CRC development. This research provides new insights into early CRC detection from the perspective of metabolic reprogramming, while nominating candidate targets worthy of further investigation for precise treatment strategies.

Serum urate is the most abundant antioxidant molecule in human blood and may play a role in cancer prevention. However, the association between serum urate levels and colorectal cancer (CRC) risk remains inconclusive, with the underlying causal mechanisms still undefined. In the UK Biobank (UKB) cohort, we investigated the prospective association between serum urate levels and the risk of CRC. We used Cox proportional hazards models to estimate the multivariable hazard ratios (HR) for CRC. Subgroup analyses were performed based on anatomical subsite and sex. Additionally, two-sample Mendelian randomization (MR) analysis was conducted to assess the potential causal effect of genetically determined urate levels on CRC risk. During a median follow-up of 11.58 years, 1960 CRC events were recorded among 180,480 participants without baseline CRC in the UKB. Higher urate levels were associated with a decreased risk of CRC (HR = 0.85, 95

BACKGROUND:Lactylation, a recently discovered post-translational modification, has emerged as a critical regulator in cancer biology. Although chemotherapy remains the first-line treatment for metastatic colorectal cancer (CRC), only a subset of patients responds to it. This study aimed to identify key lactylation-related genes in CRC and evaluate their potential as predictive biomarkers for chemotherapy response. METHOD:Gene expression profiles and corresponding clinical data from CRC patients were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were identified using the limma R package, and key modules were selected through weighted gene co-expression network analysis (WGCNA). Intersecting genes were determined by aligning DEGs with WGCNA module genes. A predictive model was developed utilizing 11 machine learning algorithms and 92 algorithm combinations. Furthermore, the correlation between lactylation-related gene score and immune infiltration as well as drug sensitivity in CRC were also investigated with "CIBERSORT" and "oncoPredict" package. RESULTS:Eight lactylation-related genes in CRC were identified and used to construct a predictive model employing Random Forest (RF) and Gradient Boosting Machine (GBM) algorithms. The model demonstrated strong predictive efficacy for chemotherapy response in CRC patients. Using lactylation gene scores, we effectively stratified patients into high- and low-score groups, which showed distinct patterns in immune cell infiltration, tumor mutational profile, and response to conventional antitumor drugs. Notably, the high-lactylation score group exhibited reduced Treg immune characteristics and increased sensitivity to 5-Fluorouracil. CONCLUSIONS:In summary, our findings demonstrate that machine learning-driven analysis of lactylation biomarkers represents a promising approach for advancing personalized therapy and optimizing clinical management in CRC.

Chimeric antigen receptor T (CAR-T) cell therapy targeting T cell tumors still faces many challenges, one of which is its fratricide due to the target gene expressed on CAR-T cells. Despite this, these CAR-T cells can be expanded in vitro by extending the culture time and effectively eliminating malignant T cells. However, the mechanisms underlying CAR-T cell survival in cell subpopulations, the molecules involved, and their regulation are still unknown. We performed single-cell transcriptome profiling to investigate the fratricidal CAR-T products (CD26 CAR-Ts and CD44v6 CAR-Ts) targeting T cells, taking CD19 CAR-Ts targeting B cells from the same donor as a control. Compared with CD19 CAR-Ts, fratricidal CAR-T cells exhibit no unique cell subpopulation, but have more exhausted T cells, fewer cytotoxic T cells, and more T cell receptor (TCR) clonal amplification. Furthermore, we observed that fratricidal CAR-T cell survival was accompanied by target gene expression. Gene expression results suggest that fratricidal CAR-T cells may downregulate their human leukocyte antigen (HLA) molecules to evade T cell recognition. Single-cell regulatory network analysis and suppression experiments revealed that exhaustion mediated by critical regulatory factors may contribute to fratricidal CAR-T cell survival. Together, these data provide valuable and first-time insights into the survival of fratricidal CAR-T cells.

Objective: Metabolic reprogramming serves as a distinctive feature of cancer, impacting proliferation and metastasis, with aberrant glycosphingolipid expression playing a crucial role in malignancy. Nevertheless, limited research has investigated the connection between glycosphingolipid metabolism and pancreatic cancer. Methods: This study utilized a single-cell sequencing dataset to analyze the cell composition in pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational pipeline called scMetabolism. A gene signature developed from the differential expressed genes (DEGs), related to epithelial cell glycosphingolipid metabolism, was established to forecast patient survival, immune response, mutation status, and reaction to chemotherapy with pancreatic adenocarcinoma (PAAD). Results: The single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with high glycosphingolipid metabolism occurring in the cancerous tissue. A six-gene signature prognostic model based on abnormal epithelial glycosphingolipid metabolism was created and confirmed using publicly available databases. Patients with PAAD were divided into high- and low-risk categories according to the median risk score, with those in the high-risk group demonstrating a more unfavorable survival outcome in all three cohorts, with higher rates of gene mutations (e.g., KRAS, CDKN2A), increased levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and heightened sensitivity to Acetalax and Selumetinlb. Conclusions: Abnormal metabolism of glycosphingolipids in epithelial cells may promote the development of PAAD. A model utilizing a gene signature associated with epithelial glycosphingolipids metabolism has been established, serving as a valuable indicator for the prognostic stratification of patients with PAAD.

Supplementary Table S2. Summary of gene and miRNA expression by different expression level

Supplementary Tables 1,4 and Figures.docx Supplementary Table S1: Summary of RNA-seq and smRNA-seq data Supplementary Table S4: The information of cancer related pathways Supplementary Figure S1: Project design and flowchart of the study Supplementary Figure S2: Cluster of differentially expressed genes Supplementary Figure S3: Heatmap of the expression of key TFs and miRNAs in the transformation Supplementary Figure S4: Regulatory network for K562-MVs highly expressed TFs and miRNAs Supplementary Figure S5: Expression of miR-146b-5p in K562-MVs after infection Supplementary Figure S6: Level of NUMB mRNA in the recipient cells when NUMB-lentivirus was transfected

Proteostasis is fundamental for maintaining organismal health. However, the mechanisms underlying its dynamic regulation and how its disruptions lead to diseases are largely unclear. Here, we conduct in-depth propionylomic profiling in Drosophila, and develop a small-sample learning framework to prioritize the propionylation at lysine 17 of H2B (H2BK17pr) to be functionally important. Mutating H2BK17 which eliminates propionylation leads to elevated total protein level in vivo. Further analyses reveal that H2BK17pr modulates the expression of 14.7-16.3% of genes in the proteostasis network, and determines global protein level by regulating the expression of genes involved in the ubiquitin-proteasome system. In addition, H2BK17pr exhibits daily oscillation, mediating the influences of feeding/fasting cycles to drive rhythmic expression of proteasomal genes. Our study not only reveals a role of lysine propionylation in regulating proteostasis, but also implements a generally applicable method which can be extended to other issues with little prior knowledge.

BACKGROUND:Synaptic degeneration occurs in the early stage of Alzheimer's disease (AD) before devastating symptoms, strongly correlated with cognitive decline. Circular RNAs (circRNAs) are abundantly enriched in neural tissues, and aberrant expression of circRNAs precedes AD symptoms, significantly correlated with clinical dementia severity. However, the direct relationship between circRNA dysregulation and synaptic impairment in the early stage of AD remains poorly understood.METHODS:Hippocampal whole-transcriptome sequencing was performed to identify dysregulated circRNAs and miRNAs in 4-month-old wild-type and APP/PS1 mice. RNA antisense purification and mass spectrometry were utilized to unveil interactions between circRIMS2 and methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit (METTL3). The roles of circRIMS2/miR-3968 in synaptic targeting of UBE2K-mediated ubiquitination of GluN2B subunit of NMDA receptor were evaluated via numerous lentiviruses followed by morphological staining, co-immunoprecipitation and behavioral testing. Further, a membrane-permeable peptide was used to block the ubiquitination of K1082 on GluN2B in AD mice.RESULTS:circRIMS2 was significantly upregulated in 4-month-old APP/PS1 mice, which was mediated by METTL3-dependent N6-methyladenosine (m6A) modification. Overexpression of circRIMS2 led to synaptic and memory impairments in 4-month-old C57BL/6 mice. MiR-3968/UBE2K was validated as the downstream of circRIMS2. Elevated UBE2K induced synaptic dysfunction of AD through ubiquitinating K1082 on GluN2B. Silencing METTL3 or blocking the ubiquitination of K1082 on GluN2B with a short membrane-permeable peptide remarkably rescued synaptic dysfunction in AD mice.CONCLUSIONS:In conclusion, our study demonstrated that m6A-modified circRIMS2 mediates the synaptic and memory impairments in AD by activating the UBE2K-dependent ubiquitination and degradation of GluN2B via sponging miR-3968, providing novel therapeutic strategies for AD.

BackgroundThe immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are crucial in maintaining a delicate balance between protective effects and harmful pathological reactions that drive the progression of coronavirus disease 2019 (COVID-19). T cells play a significant role in adaptive antiviral immune responses, making it valuable to investigate the heterogeneity and diversity of SARS-CoV-2-specific T cell responses in COVID-19 patients with varying disease severity.MethodsIn this study, we employed high-throughput T cell receptor (TCR) β repertoire sequencing to analyze TCR profiles in the peripheral blood of 192 patients with COVID-19, including those with moderate, severe, or critical symptoms, and compared them with 81 healthy controls. We specifically focused on SARS-CoV-2-associated TCR clonotypes.ResultsWe observed a decrease in the diversity of TCR clonotypes in COVID-19 patients compared to healthy controls. However, the overall abundance of dominant clones increased with disease severity. Additionally, we identified significant differences in the genomic rearrangement of variable (V), joining (J), and VJ pairings between the patient groups. Furthermore, the SARS-CoV-2-associated TCRs we identified enabled accurate differentiation between COVID-19 patients and healthy controls (AUC > 0.98) and distinguished those with moderate symptoms from those with more severe forms of the disease (AUC > 0.8). These findings suggest that TCR repertoires can serve as informative biomarkers for monitoring COVID-19 progression.ConclusionsOur study provides valuable insights into TCR repertoire signatures that can be utilized to assess host immunity to COVID-19. These findings have important implications for the use of TCR β repertoires in monitoring disease development and indicating disease severity.

Supplementary Table S6. TF and miRNA co-regulatory network for the Cell cycle and DNA repair pathways.

Supplementary methods for sequencing, regular data analysis and routine experimental methods including primer sequences.

Supplementary Table S5. GO enrichment for 8 cluters of DEGs