Zhongyuan Li, Lin Lu, Yuren Xia, Qiang Zhao, Baocheng Gong
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The relationship between the ER stress risk score and clinicopathological features, immune infiltration, and drug sensitivity was evaluated. A predictive nomogram was developed for prognostic accuracy. Immunohistochemistry (IHC) validated the hub gene using NB clinical specimens.</p><p><strong>Results: </strong>A five-gene signature (<i>PINK1</i>, <i>IL7</i>, <i>CDKN3</i>, <i>C1S</i>, <i>MMP9</i>) was established, effectively stratifying patients into high- and low-risk groups with significant differences in overall survival. The model demonstrated robust predictive performance in training and testing datasets. High-risk NB patients exhibited poorer clinicopathological characteristics and a higher likelihood of being unresponsive to immunotherapy. Specific targeted agents were identified for high-risk patients. A nomogram integrating the gene signature and clinical variables enhanced prognostic accuracy. IHC analysis of CDKN3 supported its role as a biomarker for poor prognosis in NB.</p><p><strong>Conclusions: </strong>This five-gene model linked to ER stress can independently forecast NB prognosis and correlates with immune and antitumor agent susceptibility, providing a basis for personalized treatment strategies.</p>","PeriodicalId":23294,"journal":{"name":"Translational pediatrics","volume":"14 7","pages":"1471-1488"},"PeriodicalIF":1.7000,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12336884/pdf/","citationCount":"0","resultStr":"{\"title\":\"Novel endoplasmic reticulum stress-related gene signature unveils CDKN3 as a prognosticator in neuroblastoma.\",\"authors\":\"Zhongyuan Li, Lin Lu, Yuren Xia, Qiang Zhao, Baocheng Gong\",\"doi\":\"10.21037/tp-2025-142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Neuroblastoma (NB) is the most common extracranial solid tumor in children and a major cause of pediatric cancer mortality. 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Immunohistochemistry (IHC) validated the hub gene using NB clinical specimens.</p><p><strong>Results: </strong>A five-gene signature (<i>PINK1</i>, <i>IL7</i>, <i>CDKN3</i>, <i>C1S</i>, <i>MMP9</i>) was established, effectively stratifying patients into high- and low-risk groups with significant differences in overall survival. The model demonstrated robust predictive performance in training and testing datasets. High-risk NB patients exhibited poorer clinicopathological characteristics and a higher likelihood of being unresponsive to immunotherapy. Specific targeted agents were identified for high-risk patients. A nomogram integrating the gene signature and clinical variables enhanced prognostic accuracy. IHC analysis of CDKN3 supported its role as a biomarker for poor prognosis in NB.</p><p><strong>Conclusions: </strong>This five-gene model linked to ER stress can independently forecast NB prognosis and correlates with immune and antitumor agent susceptibility, providing a basis for personalized treatment strategies.</p>\",\"PeriodicalId\":23294,\"journal\":{\"name\":\"Translational pediatrics\",\"volume\":\"14 7\",\"pages\":\"1471-1488\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12336884/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational pediatrics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21037/tp-2025-142\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"PEDIATRICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational pediatrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tp-2025-142","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/28 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PEDIATRICS","Score":null,"Total":0}
引用次数: 0
摘要
背景:神经母细胞瘤(NB)是儿童最常见的颅外实体瘤,也是儿童癌症死亡率的主要原因之一。本研究旨在建立基于内质网应激的风险模型,以评估患者预后,确定新的治疗靶点,并预测免疫治疗反应。方法:从Gene Expression Omnibus (GEO)和ArrayExpress数据库中获取NB病例的转录组和临床数据。从GeneCards中提取内质网应激相关基因。鉴定差异表达基因(DEGs),构建内质网应激相关基因标记,用于预测预后。使用生存分析、受试者工作特征(ROC)曲线和统计工具评估预测能力。评估内质网应激风险评分与临床病理特征、免疫浸润、药物敏感性的关系。为了预测的准确性,我们开发了一个预测图。免疫组织化学(IHC)利用NB临床标本验证了hub基因。结果:建立了五基因标记(PINK1、IL7、CDKN3、C1S、MMP9),有效地将患者分为高危组和低危组,总生存期差异显著。该模型在训练和测试数据集上表现出稳健的预测性能。高危NB患者表现出较差的临床病理特征和对免疫治疗无反应的可能性较高。确定了针对高危患者的特异性靶向药物。整合基因特征和临床变量的nomogram提高了预后的准确性。CDKN3的免疫组化分析支持其作为NB不良预后的生物标志物的作用。结论:内质网应激相关的五基因模型可独立预测NB预后,并与免疫和抗肿瘤药物敏感性相关,为制定个性化治疗策略提供依据。
Novel endoplasmic reticulum stress-related gene signature unveils CDKN3 as a prognosticator in neuroblastoma.
Background: Neuroblastoma (NB) is the most common extracranial solid tumor in children and a major cause of pediatric cancer mortality. This study aims to develop an endoplasmic reticulum (ER) stress-based risk model to evaluate patient prognosis, identify novel therapeutic targets, and predict immunotherapy responses.
Methods: NB cases with transcriptome and clinical data were obtained from Gene Expression Omnibus (GEO) and ArrayExpress databases. ER stress-related genes were extracted from GeneCards. Differentially expressed genes (DEGs) were identified to construct an ER stress-related gene signature for prognosis prediction. The predictive ability was assessed using survival analysis, receiver operating characteristic (ROC) curves, and statistical tools. The relationship between the ER stress risk score and clinicopathological features, immune infiltration, and drug sensitivity was evaluated. A predictive nomogram was developed for prognostic accuracy. Immunohistochemistry (IHC) validated the hub gene using NB clinical specimens.
Results: A five-gene signature (PINK1, IL7, CDKN3, C1S, MMP9) was established, effectively stratifying patients into high- and low-risk groups with significant differences in overall survival. The model demonstrated robust predictive performance in training and testing datasets. High-risk NB patients exhibited poorer clinicopathological characteristics and a higher likelihood of being unresponsive to immunotherapy. Specific targeted agents were identified for high-risk patients. A nomogram integrating the gene signature and clinical variables enhanced prognostic accuracy. IHC analysis of CDKN3 supported its role as a biomarker for poor prognosis in NB.
Conclusions: This five-gene model linked to ER stress can independently forecast NB prognosis and correlates with immune and antitumor agent susceptibility, providing a basis for personalized treatment strategies.