Background: The development of HCC is often associated with extensive metabolic disturbances. Single cell RNA sequencing (scRNA-seq) provides a better understanding of cellular behavior in the context of complex tumor microenvironments by analyzing individual cell populations. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data was employed to investigate the metabolic pathways in HCC. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were applied to identify six cell subpopulations, namely, T/NK cells, hepatocytes, macrophages, endothelial cells, fibroblasts, and B cells. The gene set enrichment analysis (GSEA) was performed to explore the existence of pathway heterogeneity across different cell subpopulations. Univariate Cox analysis was used to screen genes differentially related to The Overall Survival in TCGA-LIHC patients based on scRNA-seq and bulk RNA-seq datasets, and LASSO analysis was used to select significant predictors for incorporation into multivariate Cox regression. Connectivity Map (CMap) was applied to analysis drug sensitivity of risk models and targeting of potential compounds in high risk groups.Results: Analysis of TCGA-LIHC survival data revealed the molecular markers associated with HCC prognosis, including MARCKSL1, SPP1, BSG, CCT3, LAGE3, KPNA2, SF3B4, GTPBP4, PON1, CFHR3, and CYP2C9. The RNA expression of 11 prognosis-related differentially expressed genes (DEGs) in normal human hepatocyte cell line MIHA and HCC cell lines HCC-LM3 and HepG2 were compared by qPCR. Higher KPNA2, LAGE3, SF3B4, CCT3 and GTPBP4 protein expression and lower CYP2C9 and PON1 protein expression in HCC tissues from Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. The results of target compound screening of risk model showed that mercaptopurine is a potential anti-HCC drug.Conclusion: The prognostic genes associated with glucose and lipid metabolic changes in a hepatocyte subpopulation and comparison of liver malignancy cells to normal liver cells may provide insight into the metabolic characteristics of HCC and the potential prognostic biomarkers of tumor-related genes and contribute to developing new treatment strategies for individuals.

O-GlcNAcylation is a ubiquitous, dynamic and reversible post-translational protein modification in metazoans, and it is catalysed and removed by O-GlcNAc transferase (OGT) and O-GlcNAcase, respectively. Prokaryotes lack endogenous OGT activity. It has been reported that coexpression of mammalian OGT with its target substrates in Escherichia coli produce O-GlcNAcylated recombinant proteins, but the plasmids used were not compatible, and the expression of both OGT and its target protein were induced by the same inducer. Here, we describe a compatible dual plasmid system for coexpression of OGT and its target substrate for O-GlcNAcylated protein production in E. coli. The approach was validated using the CKII and p53 protein as control. This compatible dual plasmid system contains an arabinose-inducible OGT expression vector with a pUC origin and an isopropyl β-d-thiogalactopyranoside-inducible OGT target substrate expression vector bearing a p15A origin. The dual plasmid system produces recombinant proteins with varying O-GlcNAcylation levels by altering the inducer concentration. More importantly, the O-GlcNAcylation efficiency was much higher than the previously reported system. Altogether, we established an adjustable compatible dual plasmid system that can effectively yield O-GlcNAcylated proteins in E. coli.

Corrigendum: Single-cell transcriptome analysis reveals the metabolic changes and the prognostic value of malignant hepatocyte subpopulations and predict new therapeutic agents for hepatocellular carcinoma

The major liver cancer subtype is hepatocellular carcinoma (HCC). Studies have indicated that a better prognosis is related to the presence of tumor-infiltrating lymphocytes (TILs) in HCC. However, the molecular pathways that drive immune cell variation in the tumor microenvironment (TME) remain poorly understood. Glycosylation (GLY)-related genes have a vital function in the pathogenesis of numerous tumors, including HCC. This study aimed to develop a GLY/TME classifier based on glycosylation-related gene scores and tumor microenvironment scores to provide a novel prognostic model to improve the prediction of clinical outcomes. The reliability of the signatures was assessed using receiver operating characteristic (ROC) and survival analyses and was verified with external datasets. Furthermore, the correlation between glycosylation-related genes and other cells in the immune environment, the immune signature of the GLY/TME classifier, and the efficacy of immunotherapy were also investigated. The GLY score low/TME score high subgroup showed a favorable prognosis and therapeutic response based on significant differences in immune-related molecules and cancer cell signaling mechanisms. We evaluated the prognostic role of the GLY/TME classifier that demonstrated overall prognostic significance for prognosis and therapeutic response before treatment, which may provide new options for creating the best possible therapeutic approaches for patients.

Clear cell renal cell carcinoma (ccRCC), the most common RCC subtype, displays significant intratumoral heterogeneity driven by metabolic reprogramming, which complicates our understanding of disease progression and limits treatment efficacy. This study aimed to construct a comprehensive cellular and transcriptional landscape of ccRCC, with emphasis on gene expression dynamics during malignant progression. An integrated analysis of 90 scRNA-seq samples comprising 534,227 cells revealed a progressive downregulation of sodium ion transport-related genes, particularly CHP1 (calcineurin B homologous protein isoform 1), which is predominantly expressed in epithelial cells. Reduced CHP1 expression was confirmed at both mRNA and protein levels using bulk RNA-seq, CPTAC proteomics, immunohistochemistry, and ccRCC cell lines. Survival analysis showed that high CHP1 expression correlated with improved prognosis. Functional analyses, including pseudotime trajectory, Mfuzz clustering, and cell–cell communication modeling, indicated that CHP1⁺ epithelial cells engage in immune interaction via PPIA–BSG signaling. Transcriptomic profiling and molecular docking suggested that CHP1 modulates amino acid transport through SLC38A1. ZNF460 was identified as a potential transcription factor of CHP1. Virtual screening identified arbutin and imatinib mesylate as candidate CHP1-targeting compounds. These findings establish CHP1 downregulation as a novel molecular feature of ccRCC progression and support its utility as a prognostic biomarker.

Introduction: Calcineurin B homologous protein 1 (CHP1), a crucial cofactor of the sodium–hydrogen exchanger 1 (NHE1), plays a pivotal role in triglyceride synthesis and storage within the endoplasmic reticulum. Increasing evidence suggests that CHP1 participates in biological processes central to tumorigenesis. Objective: This study aims to systematically investigate the expression profile of CHP1 across multiple human cancers through a pan-cancer analysis and evaluate its associations with clinical outcomes and immune cell infiltration through integrated bioinformatics approaches. Methods: Expression and clinical data from 33 cancer types were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression (GTEx) databases. Analyses of CHP1 expression levels, tissue distribution, stage-specific variation, prognostic value, diagnostic performance, gene alterations, immune infiltration, protein–protein interactions, and enrichment pathways were performed using the Human Protein Atlas, Gene Expression Profiling Interactive Analysis 2, Tumor Immune Estimation Resource 2, and Search Tool for the Retrieval of Interacting Genes/Proteins platforms. Results: CHP1 expression was significantly downregulated in 11 tumor types compared with corresponding adjacent normal tissues. Higher CHP1 expression was associated with a favorable prognosis in several cancer types and demonstrated high diagnostic accuracy. Conclusion: CHP1 is frequently downregulated across multiple cancers and is closely linked to patient survival, supporting its potential as a prognostic biomarker. Its significant association with immune infiltration suggests a potential role in modulating the tumor immune microenvironment, highlighting CHP1 as a promising therapeutic target in pan-cancer settings.