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Background <p>This study investigated endoplasmic reticulum(ER) stress mechanisms in Neuroblastoma(NB) progression using bioinformatics and experimental validation.</p> Methods <p>Using GSE49710 and E-MTAB-8248 datasets, ER stress related genes(ERSRGs) were analyzed. Consensus clustering identified ER stress related subtypes(ERSRsubtype). Integrated bioinformatic analyses identified key hub genes, dysregulated biological pathways, and significant alterations in immune cell infiltration within the studied context. A prognostic model was constructed via least absolute shrinkage and selection operator(LASSO)/multivariate regression and validated across multiple datasets. Drug sensitivity and microenvironment differences were assessed. Lentiviral knockdown, Cell Counting Kit-8(CCK8), 5-Ethynyl’-2-deoxyuridine(EdU), and Transwell assays evaluated <i>HIST1H1B</i>’s roles in NB cell lines.</p> Result <p>173 prognosis-linked ERSRGs were identified. The samples were stratified into two ERSRsubtypes with distinct prognoses. We obtained 4 hub genes and multiple differentially expressed pathways in the two subtypes. The ER stress related model accurately predicted survival. High-risk patients showed altered immune infiltration(8 cell types) and 149 differentially effective drugs(18 more effective in high-risk NB). <i>HIST1H1B</i>, upregulated in <i>MYCN</i>-amplified NB, enhanced proliferation, migration, and invasion of NB.</p> Conclusion <p>ERSRsubtypes were associated with NB prognosis and tumor microenvironment(TME) heterogeneity. The prognostic model and key genes identified provide crucial insights into ER stress mechanisms, offering potential targets for therapy and aiding in risk stratification and treatment strategy formulation.</p>

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Identification and validation of an endoplasmic reticulum stress related model to predict prognosis and tumor microenvironment in neuroblastoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月3日

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  • Ji Chen,
  • Baofeng Du,
  • Bin Jiang,
  • Lei Huang

摘要

Background

This study investigated endoplasmic reticulum(ER) stress mechanisms in Neuroblastoma(NB) progression using bioinformatics and experimental validation.

Methods

Using GSE49710 and E-MTAB-8248 datasets, ER stress related genes(ERSRGs) were analyzed. Consensus clustering identified ER stress related subtypes(ERSRsubtype). Integrated bioinformatic analyses identified key hub genes, dysregulated biological pathways, and significant alterations in immune cell infiltration within the studied context. A prognostic model was constructed via least absolute shrinkage and selection operator(LASSO)/multivariate regression and validated across multiple datasets. Drug sensitivity and microenvironment differences were assessed. Lentiviral knockdown, Cell Counting Kit-8(CCK8), 5-Ethynyl’-2-deoxyuridine(EdU), and Transwell assays evaluated HIST1H1B’s roles in NB cell lines.

Result

173 prognosis-linked ERSRGs were identified. The samples were stratified into two ERSRsubtypes with distinct prognoses. We obtained 4 hub genes and multiple differentially expressed pathways in the two subtypes. The ER stress related model accurately predicted survival. High-risk patients showed altered immune infiltration(8 cell types) and 149 differentially effective drugs(18 more effective in high-risk NB). HIST1H1B, upregulated in MYCN-amplified NB, enhanced proliferation, migration, and invasion of NB.

Conclusion

ERSRsubtypes were associated with NB prognosis and tumor microenvironment(TME) heterogeneity. The prognostic model and key genes identified provide crucial insights into ER stress mechanisms, offering potential targets for therapy and aiding in risk stratification and treatment strategy formulation.