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探索AKR1B10P1、RP11-465B22.3、WASH8P和NPM1P25的非编码RNA表达谱作为肝细胞癌患者生存的预测模型。

Exploring non-coding RNA expression profiles of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 as a predictive model for hepatocellular carcinoma patient survival.

作者信息

Firouzi-Farsani Khatereh, Dehghani-Samani Mina, Gerami Razieh, Sadat Moosavi Reihaneh, Gerami Marzieh, Mahdevar Mohammad

机构信息

Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran.

Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

出版信息

Discov Oncol. 2025 May 15;16(1):771. doi: 10.1007/s12672-025-02475-6.

Abstract

The primary aim of the study was to analyze novel long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC) to assess their roles as potential oncogenes and tumor suppressors and to develop a survival prediction model based on their expression levels. Data from The Cancer Genome Atlas, GSE135631, and GSE214846, were utilized to evaluate changes in lncRNA expression in HCC and their associations with patient prognosis. A risk model was created based on lncRNA expression to predict patient mortality. The co-expression network was employed to identify associated pathways, and the results were subsequently validated using the RT-qPCR method. The findings indicated that 14 lncRNAs were down-regulated in HCC, and their increased expression was associated with a favorable prognosis. Additionally, eight lncRNAs were overexpressed and correlated with poorer patient outcomes. The multivariate Cox regression analysis demonstrated that overexpression of AKR1B10P1, RP11-465B22.3, WASH8P, and the downregulation of NPM1P25 could independently predict patient survival, irrespective of clinical variables. The risk score model based on these lncRNAs effectively stratified patients by their mortality risk. Furthermore, the co-expression network analysis revealed that the identified lncRNAs might be involved in various pathways, including fatty acid metabolism, mTOR signaling, glycolysis, angiogenesis, Wnt-β-catenin pathway, and DNA repair. RT-qPCR results validated the significant increase in the expression level of WASH8P in cancer specimens compared to normal tissues. Our results unveiled that changes in the expression levels of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 were significantly and independently associated with prognosis. Moreover, the patient mortality risk model constructed using these four lncRNAs exhibited a robust capacity to accurately predict patients' survival rates.

摘要

本研究的主要目的是分析肝细胞癌(HCC)中的新型长链非编码RNA(lncRNA),以评估它们作为潜在癌基因和肿瘤抑制因子的作用,并基于其表达水平建立生存预测模型。利用来自癌症基因组图谱、GSE135631和GSE214846的数据,评估HCC中lncRNA表达的变化及其与患者预后的关联。基于lncRNA表达创建了一个风险模型来预测患者死亡率。利用共表达网络来识别相关通路,随后使用RT-qPCR方法对结果进行验证。研究结果表明,14种lncRNA在HCC中表达下调,其表达增加与预后良好相关。此外,8种lncRNA过表达且与患者较差的预后相关。多变量Cox回归分析表明,AKR1B10P1、RP11-465B22.3、WASH8P的过表达以及NPM1P25的下调可独立预测患者生存情况,而不受临床变量影响。基于这些lncRNA的风险评分模型有效地根据患者的死亡风险进行了分层。此外,共表达网络分析显示,所鉴定的lncRNA可能参与多种通路,包括脂肪酸代谢、mTOR信号传导、糖酵解、血管生成、Wnt-β-连环蛋白通路和DNA修复。RT-qPCR结果证实,与正常组织相比,癌组织中WASH8P的表达水平显著升高。我们的结果表明,AKR1B10P1、RP11-465B22.3、WASH8P和NPM1P25表达水平的变化与预后显著且独立相关。此外,使用这四种lncRNA构建的患者死亡风险模型具有强大的能力,能够准确预测患者的生存率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/957c/12081793/e746f06bf025/12672_2025_2475_Fig1_HTML.jpg

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