A Super-Enhancer-Related Ferroptosis Signature Predicts Survival and Immune Microenvironment in Colon Cancer Based on Bioinformatics Analyses and Experimental Validation

IF 1.9 4区 生物学 Q4 CELL BIOLOGY
Luying Wan, Jingyi Li, Xianhe Xie
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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.

Abstract Image

Abstract Image

基于生物信息学分析和实验验证的超级增强子相关的铁下垂特征预测结肠癌的生存和免疫微环境。
尽管免疫疗法已经彻底改变了癌症治疗,但它的益处仍然局限于少数结肠癌患者。新出现的证据表明,超增强子(SE)网络和铁下沉失调是关键的致癌驱动因素,尽管它们的协同预后和免疫微环境影响尚未探索。超增强子相关铁下垂基因(SEFGs)是通过交叉se相关基因和铁下垂相关基因来鉴定的。使用TCGA-COAD(训练)和GSE39582(验证)队列,我们通过LASSO Cox回归建立了8基因预后特征。这一特征构成了具有稳健校准和鉴别的临床nomogram基础(C-index = 0.813)。高危患者的总生存率明显降低。升高的风险评分与晚期、一致分子亚型(CMS1/CMS4)、高肿瘤突变负担(TMB)、高微卫星不稳定性(MSI)和增强的免疫细胞浸润相关,矛盾地与免疫抑制表型相结合,包括免疫检查点基因表达增加、免疫治疗反应性降低,以及对SE抑制剂的敏感性增加。JQ-1 RNA-Seq分析显示,三个核心SE驱动基因TRIB2、CAV1和ENO3在SE抑制后显著下调。其中TRIB2以SE复发、肿瘤过表达、预后价值和JQ-1抑制等指标进行区分。SEFG标记有助于同时预测预后和评估免疫微环境,为结肠癌治疗提供了潜在的工具。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
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.
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