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一种用于预测乙型肝炎病毒相关性肝细胞癌预后的新型铜死亡相关长链非编码RNA模型及LINC01269的实验验证

A New Cuproptosis-Related lncRNAs Model for Predicting the Prognosis of Hepatitis B Virus-Associated Hepatocellular Carcinoma and Experimental Validation of LINC01269.

作者信息

Shi Chuanbing, Sun Yintao, Sha Ling, Gu Xuefeng

机构信息

Department of Pathology, Nanjing Pukou People's Hospital, Nanjing, Jiangsu, People's Republic of China.

Department of Imaging, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, People's Republic of China.

出版信息

Int J Gen Med. 2024 Dec 10;17:6009-6027. doi: 10.2147/IJGM.S489059. eCollection 2024.

Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) triggered by Hepatitis B virus (HBV) remains a significant clinical challenge, necessitating novel therapeutic interventions. Copper ionophores, recognized for introducing an innovative type of programmed cell death termed cuproptosis, present promising potentials for cancer therapy. Nevertheless, The role of cuproptosis-related lncRNAs (CRLRs) in HBV-HCC has not been clearly elucidated.

METHODS

This study utilised univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariable Cox regression analyses to establish a signature for CRLRs in HBV-HCC. This prognostic model was validated with an independent internal validation cohort, combined with clinical parameters, and used to construct a nomogram for patient survival predictions. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were employed to explore associated biological pathways. Additionally, a protein-protein interaction (PPI) network was developed, and implications for tumour mutational burden (TMB) and drug response were examined. A comprehensive bioinformatics analysis of these hub CRLRs was performed, followed by experimental validation through quantitative real-time PCR (qRT-PCR) and functional cellular assays.

RESULTS

The nomogram showed high predictive accuracy for HBV-HCC patient survival. GO and GSEA analyses indicated that these lncRNAs are involved in pathways related to cancer and oestrogen metabolism. A PPI network consisting of 201 nodes and 568 edges was developed, and the TMB and drug response differed significantly between high- and low-risk groups. Analyses identified three hub CRLRs, SOS1-IT1, AC104695.3, and LINC01269, which were significantly differentially expressed in HCC tissues. In vitro, LINC01269 was found to enhance HCC cell proliferation, invasion, and migration.

CONCLUSION

The first systematic exploration of the roles of CRLRs in HBV-HCC demonstrates their critical involvement in the disease's pathogenesis and possible therapeutic implication. The distinct expression patterns and significant biological pathways suggest that these lncRNAs may facilitate novel therapeutic targets.

摘要

背景

由乙型肝炎病毒(HBV)引发的肝细胞癌(HCC)仍然是一项重大的临床挑战,需要新的治疗干预措施。铜离子载体因引入一种名为铜死亡的新型程序性细胞死亡而闻名,在癌症治疗方面具有广阔的潜力。然而,铜死亡相关长链非编码RNA(CRLRs)在HBV-HCC中的作用尚未明确阐明。

方法

本研究采用单变量Cox、最小绝对收缩和选择算子(LASSO)以及多变量Cox回归分析,建立HBV-HCC中CRLRs的特征。该预后模型在独立的内部验证队列中结合临床参数进行验证,并用于构建患者生存预测的列线图。采用基因本体论(GO)和基因集富集分析(GSEA)来探索相关的生物学途径。此外,构建了蛋白质-蛋白质相互作用(PPI)网络,并研究了其对肿瘤突变负担(TMB)和药物反应的影响。对这些核心CRLRs进行了全面的生物信息学分析,随后通过定量实时PCR(qRT-PCR)和细胞功能实验进行实验验证。

结果

列线图对HBV-HCC患者生存具有较高的预测准确性。GO和GSEA分析表明,这些长链非编码RNA参与了与癌症和雌激素代谢相关的途径。构建了一个由201个节点和568条边组成的PPI网络,高风险组和低风险组之间的TMB和药物反应存在显著差异。分析确定了三个核心CRLRs,即SOS1-IT1、AC104695.3和LINC01269,它们在HCC组织中显著差异表达。在体外,发现LINC01269可增强HCC细胞的增殖、侵袭和迁移能力。

结论

首次对CRLRs在HBV-HCC中的作用进行系统探索,证明它们在该疾病发病机制中起关键作用,并具有潜在的治疗意义。独特的表达模式和重要的生物学途径表明,这些长链非编码RNA可能有助于发现新的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8840/11645962/775710c98cef/IJGM-17-6009-g0001.jpg

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