Integrative multi-omics and experimental validation reveal UBE2C as a central hub gene and prognostic biomarker in hepatocellular carcinoma.
Summary
This multi-omics and experimental study identifies Ubiquitin-conjugating enzyme E2 C (UBE2C) as a central hub gene and a key prognostic biomarker in hepatocellular carcinoma (HCC). UBE2C is significantly upregulated in HCC, predominantly in hepatocytes, and its knockdown suppresses tumor proliferation and growth. The study reveals that UBE2C-high regions are associated with an immunosuppressive microenvironment, characterized by TGFB1 enrichment and cytotoxic T-cell exclusion. A nomogram integrating UBE2C expression, T stage, and tumor stage was developed to predict patient survival and stratify immunotherapy response.
Analysis
CLINIQUE: This research positions UBE2C as a prognostic and predictive biomarker for immunotherapy response in hepatocellular carcinoma. The nomogram, based on UBE2C, T stage, and tumor stage, provides a robust tool for predicting patient survival, which could guide clinical decisions and patient stratification for immunotherapy trials. Validation of this nomogram in prospective cohorts could justify a change in clinical practice, allowing for better selection of patients for existing or future treatments. Clinical impact could be seen in the medium term (3-5 years) if validation studies are conducted promptly. BIOMOL: The study discovered UBE2C as a significantly upregulated hub gene in HCC, playing a crucial role in tumor progression by promoting proliferation and inhibiting apoptosis. Single-cell transcriptomics revealed its predominant expression in hepatocytes and dynamic upregulation. Spatial transcriptomics highlighted the link between UBE2C-high regions and an immunosuppressive microenvironment, involving TGFB1 enrichment and impaired CXCL9-CXCR3 signaling, leading to cytotoxic T-cell exclusion. These findings, validated by qPCR and immunoblotting in HCC tissues and cell lines, identify UBE2C as a potential target for novel therapies aimed at modulating the tumor immune microenvironment. BIOINFO: The integrative bioinformatics approach combined co-expression networks and protein-protein interaction analyses from public databases (TCGA, GEO, CPTAC) to identify hub genes. Analysis of single-cell and spatial transcriptomics data allowed for characterization of UBE2C expression and its impact on the tumor microenvironment with spatial and cellular resolution. The construction of a prognostic nomogram via multivariate Cox regression demonstrates a direct clinical application of bioinformatics data for survival prediction. These reproducible methods, leveraging public data, could be integrated into clinical workflows for patient stratification.