列线图
肝细胞癌
基因签名
肿瘤科
免疫疗法
基因
比例危险模型
多元分析
受体
单变量
生物
内科学
医学
癌症研究
生物信息学
计算生物学
基因表达
癌症
多元统计
遗传学
计算机科学
机器学习
作者
Chong Yau Fu,Cheng Chen,Yanping Zhang
出处
期刊:Heliyon
[Elsevier BV]
日期:2023-09-01
卷期号:9 (9): e19502-e19502
标识
DOI:10.1016/j.heliyon.2023.e19502
摘要
BackgroudWe aimed to explore the prognostic features of ligand and receptor genes associated with disulfidoptosis in hepatocellular carcinoma (HCC) and establish a risk signature utilizing these genes to predict the prognosis of HCC patients.MethodsWe used scRNA-seq data from GSE166635 to differentiate malignant cells from normal cells using “copykat”.The study thoroughly examined the disparities in disulfidoptosis scores and the associated gene expressions between malignant and normal cells.We identified key ligand and receptor genes that are specific to HCC cells.Subsequently, Correlation analysis was conducted to ascertain the ligand and receptor genes associated with disulfidoptosis.We performed univariate Cox regression analysis to identify prognostic ligand and receptor genes associated with disulfidoptosis.We employed LASSO to construct a risk signature using prognostic ligand and receptor genes associated with disulfidoptosis.Lastly, we developed a nomogram model that integrates the risk signature with clinicopathological characteristics.ResultsMalignant cells displayed a marked increase in disulfidoptosis scores and the expression of associated genes compared to normal cells.We identified 110 receptor and ligand genes significantly associated with disulfidoptosis, and narrowed them down to create a risk signature comprising eight genes.Multivariate analysis confirmed the risk signature as an independent prognostic factor for HCC and validated its predictive value for immunotherapy outcomes.A novel nomogram was developed, incorporating stage information and the risk signature derived from disulfidoptosis-related receptor and ligand genes, demonstrating excellent predictive accuracy and reliability in HCC prognosis prediction.ConclusionRisk signatures based on disulfidoptosis-associated ligand and receptor genes can effectively predict HCC prognosis and may inform immunotherapy strategies.
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