A Super-Enhancer-Related Ferroptosis Signature Predicts Survival and Immune Microenvironment in Colon Cancer Based on Bioinformatics Analyses and Experimental Validation
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引用次数: 0
Abstract
Although immunotherapy has revolutionised cancer treatment, its benefits remain restricted to a minority of patients with colon cancer. Emerging evidence implicates super-enhancer (SE) networks and ferroptosis dysregulation as key oncogenic drivers, though their synergistic prognostic and immune microenvironment implications are unexplored. Super-enhancer-related ferroptosis genes (SEFGs) were identified by intersecting SE-associated and ferroptosis-related genes. Using TCGA-COAD (training) and GSE39582 (validation) cohorts, we established an 8-gene prognostic signature via LASSO Cox regression. This signature formed the basis of a clinical nomogram with robust calibration and discrimination (C-index = 0.813). High-risk patients exhibited significantly reduced overall survival. Elevated risk scores correlated with advanced stage, consensus molecular subtypes (CMS1/CMS4), high tumour mutation burden (TMB), high-level microsatellite instability (MSI) and enhanced immune cell infiltration, paradoxically coupled with immunosuppressive phenotypes including increased immune checkpoint gene expression and reduced immunotherapy responsiveness, alongside increased sensitivity to SE inhibitors. JQ-1 RNA-Seq profiling revealed three core SE-driven genes, TRIB2, CAV1 and ENO3, which were significantly downregulated upon SE inhibition. Among them, TRIB2 was distinguished by its SE recurrence, tumour overexpression, prognostic value and JQ-1 suppression. The SEFG signature facilitates simultaneous prediction of prognosis and assessment of the immune microenvironment, providing a potential tool for colon cancer management.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.