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一种新型的与超级增强子相关的风险模型,用于预测肝细胞癌的预后并指导个体化治疗。

A novel super-enhancer-related risk model for predicting prognosis and guiding personalized treatment in hepatocellular carcinoma.

机构信息

Department of Oncology, The First Affiliated Hospital of Fujian Medical University, No. 20 Chazhong Road, Fuzhou, 350005, China.

Department of Oncology, National Regional Medical Center, Binhai Campus of The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.

出版信息

BMC Cancer. 2024 Sep 2;24(1):1087. doi: 10.1186/s12885-024-12874-7.

Abstract

BACKGROUND

Our research endeavored to develop a robust predictive signature grounded in super-enhancer-related genes (SERGs), with the dual objectives of forecasting survival outcomes and evaluating the tumor immune microenvironment (TiME) in hepatocellular carcinoma (HCC).

METHODS

HCC RNA-sequencing data were retrieved from The Cancer Genome Atlas (TCGA), and 365 patients were randomly assigned to training or testing sets in 1:1 ratio. SERGs of HCC were downloaded from Super-Enhancer Database (SEdb). On the basis of training set, a SERGs signature was identified, and its prognostic value was confirmed by internal and external validation (GSE14520) sets. We subsequently examined the model for potential functional enrichment and the degree of tumor immune infiltration. Additionally, we carried out in vitro experiments to delve into the biological functions of CBX2 gene.

RESULTS

An SE-related prognostic model including CBX2, TPX2, EFNA3, DNASE1L3 and SOCS2 was established and validated. According to this risk model, patients in the high-risk group had a significantly worse prognosis, and their immune cell infiltration was significantly different from that of low-risk group. Moreover, the high-risk group exhibited a significant enrichment of tumor-associated pathological pathways. The SERGs signature can generally be utilized to screen HCC patients who are likely to respond to immunotherapy, as there is a positive correlation between the risk score and the Tumor Immune Dysfunction and Exclusion (TIDE) score. Furthermore, the downregulation of the CBX2 gene expression was found to inhibit HCC cell viability, migration, and cell cycle progression, while simultaneously promoting apoptosis.

CONCLUSIONS

We developed a novel HCC prognostic model utilizing SERGs, indicating that patients with high-risk score not only face a poorer prognosis but also may exhibit a diminished therapeutic response to immune checkpoint inhibitors (ICIs). This model is designed to tailor personalized treatment strategies to the individual needs of each patient, thereby improving the overall clinical outcomes for HCC patients. Furthermore, CBX2 is a promising candidate for therapeutic intervention in HCC.

摘要

背景

本研究旨在构建基于超级增强子相关基因(SERGs)的稳健预测标志物,以期同时预测肝细胞癌(HCC)患者的生存结局和评估肿瘤免疫微环境(TiME)。

方法

从癌症基因组图谱(TCGA)中获取 HCC 的 RNA-seq 数据,并按照 1:1 的比例将 365 名患者随机分配到训练集或测试集中。从超级增强子数据库(SEdb)中下载 HCC 的 SERGs。基于训练集,确定 SERGs 标志物,并通过内部和外部验证集(GSE14520)验证其预后价值。随后,我们研究了模型的潜在功能富集和肿瘤免疫浸润程度。此外,我们还进行了体外实验以深入研究 CBX2 基因的生物学功能。

结果

建立并验证了一个包含 CBX2、TPX2、EFNA3、DNASE1L3 和 SOCS2 的 SE 相关预后模型。根据该风险模型,高风险组患者的预后明显较差,且其免疫细胞浸润与低风险组有显著差异。此外,高风险组表现出与肿瘤相关的病理性途径的显著富集。该 SERGs 标志物通常可用于筛选可能对免疫治疗有反应的 HCC 患者,因为风险评分与肿瘤免疫功能障碍和排除(TIDE)评分之间存在正相关。此外,下调 CBX2 基因表达可抑制 HCC 细胞活力、迁移和细胞周期进程,同时促进细胞凋亡。

结论

我们开发了一种新的基于 SERGs 的 HCC 预后模型,表明高风险评分的患者不仅预后较差,而且对免疫检查点抑制剂(ICIs)的治疗反应可能减弱。该模型旨在根据每个患者的个体需求制定个性化治疗策略,从而改善 HCC 患者的总体临床结局。此外,CBX2 是 HCC 治疗干预的一个有前途的候选基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c04e/11370013/2e67342817a9/12885_2024_12874_Fig1_HTML.jpg

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