Newly Established Anoikis-Associated Genes Predict the Prognosis of Hepatocellular Carcinoma.

IF 3.4 3区 医学 Q2 ONCOLOGY
Journal of Hepatocellular Carcinoma Pub Date : 2025-09-03 eCollection Date: 2025-01-01 DOI:10.2147/JHC.S533398
Yuyao Li, Er Li, Wenlan Zheng, Jia Shi, Shihan Yu, Xuemei Zhang, Liming Zheng, Wurong Du, Hao Liu, Hai Feng, Jianfeng Guo, Zhuo Yu
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引用次数: 0

Abstract

Objective: Anoikis is an anchorage-dependent programmed cell death implicated in multiple pathological processes of cancers; however, the prognostic value of anoikis-related genes (ANRGs) in hepatocellular carcinoma (HCC) remains unclear. Our study aims to develop an ANRGs-based prediction model to improve prognostic assessment in HCC patients.

Methods: The RNA-seq profile was performed to estimate the expression of ANRGs in HCC patients. The univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were applied in the model construction to predict the prognosis in terms of differentially expressed ANRGs in the Cancer Genome Atlas (TCGA) training cohort. The TCGA test cohort and the International Cancer Genome Consortium (ICGC)-originated cohort were set to verify the predictive capacity. Nomogram was built on the basis of risk score (RS), gender, age, grade, and T_stage, with the hope of extending the predictive ability of ANRGs to evaluate the HCC prognosis. The expression of differentially expressed ANRGs was assessed in HCC cell lines and orthotopic tumor-bearing mice.

Results: Six ANRGs (ANXA5, BIRC5, BSG, DAP3, SKP2 and CDKN3) demonstrated the critical prognostic significance in HCC patients. The prognostic RS model on the basis of these ANRGs was capable of properly predicting 1-, 3-, and 5-year survivals. The Kaplan-Meier results displayed the increased death and decreased survival in the high-risk group. The RS acted as the independent factor for the survival evaluation. Our nomogram model was able to directly reflect the survival probabilities of each patient, which was confirmed through various validations. The transcription and translation of six ANRGs were significantly enhanced in HCC cell lines and tumor tissues.

Conclusion: Despite the lack of mechanistic validation, our anoikis-linked RS model serves as a promising tool for predicting HCC prognosis in clinical practice, and provides valuable insights into the decision of individualized therapeutic approaches.

新发现的嗜酸相关基因预测肝细胞癌的预后。
目的:Anoikis是一种锚定依赖性程序性细胞死亡,涉及多种癌症病理过程;然而,嗜酸相关基因(ANRGs)在肝细胞癌(HCC)中的预后价值尚不清楚。我们的研究旨在建立一个基于anrgs的预测模型,以改善HCC患者的预后评估。方法:采用RNA-seq谱法估计HCC患者中ANRGs的表达。采用单变量Cox回归和最小绝对收缩和选择算子(LASSO) Cox回归分析进行模型构建,预测肿瘤基因组图谱(TCGA)培训队列中差异表达ANRGs的预后。设置TCGA测试队列和国际癌症基因组联盟(ICGC)发起的队列来验证预测能力。以风险评分(RS)、性别、年龄、分级、T_stage为基础构建Nomogram,以期扩大ANRGs对HCC预后的预测能力。在HCC细胞系和原位荷瘤小鼠中评估差异表达的ANRGs的表达。结果:6个ANRGs (ANXA5、BIRC5、BSG、DAP3、SKP2和CDKN3)在HCC患者中具有重要的预后意义。基于这些ANRGs的预后RS模型能够正确预测1年、3年和5年生存率。Kaplan-Meier结果显示,高危组的死亡率增加,生存率降低。RS作为生存评价的独立因素。我们的nomogram模型能够直接反映每个患者的生存概率,这一点通过各种验证得到了证实。6种ANRGs的转录和翻译在HCC细胞系和肿瘤组织中显著增强。结论:尽管缺乏机制验证,但我们的anoiisk -linked RS模型在临床实践中可以作为预测HCC预后的有希望的工具,并为个性化治疗方法的决策提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.50
自引率
2.40%
发文量
108
审稿时长
16 weeks
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