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构建新型失巢凋亡相关预后模型并分析其与神经母细胞瘤免疫细胞浸润的相关性。

Construction of a novel anoikis-related prognostic model and analysis of its correlation with infiltration of immune cells in neuroblastoma.

机构信息

Department of General Surgery, Children's Hospital of Nanjing Medical University, Nanjing, China.

Department of Hematology and Oncology, Children's Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Front Immunol. 2023 Apr 4;14:1135617. doi: 10.3389/fimmu.2023.1135617. eCollection 2023.

Abstract

BACKGROUND

Anoikis resistance (AR) plays an important role in the process of metastasis, which is an important factor affecting the risk stage of neuroblastoma (NB). This study aims to construct an anoikis-related prognostic model and analyze the characteristics of hub genes, important pathways and tumor microenvironment of anoikis-related subtypes of NB, so as to provide help for the clinical diagnosis, treatment and research of NB.

METHODS

We combined transcriptome data of GSE49710 and E-MTAB-8248, screened anoikis-related genes (Args) closely related to the prognosis of NB by univariate cox regression analysis, and divided the samples into anoikis-related subtypes by consistent cluster analysis. WGCNA was used to screen hub genes, GSVA and GSEA were used to analyze the differentially enriched pathways between anoikis-related subtypes. We analyzed the infiltration levels of immune cells between different groups by SsGSEA and CIBERSORT. Lasso and multivariate regression analyses were used to construct a prognostic model. Finally, we analyzed drug sensitivity through the GDSC database.

RESULTS

721 cases and 283 Args were included in this study. All samples were grouped into two subtypes with different prognoses. The analyses of WGCNA, GSVA and GSEA suggested the existence of differentially expressed hub genes and important pathways in the two subtypes. We further constructed an anoikis-related prognostic model, in which 15 Args participated. This model had more advantages in evaluating the prognoses of NB than other commonly used clinical indicators. The infiltration levels of 9 immune cells were significantly different between different risk groups, and 13 Args involved in the model construction were correlated with the infiltration levels of immune cells. There was a relationship between the infiltration levels of 6 immune cells and riskscores. Finally, we screened 15 drugs with more obvious effects on NB in high-risk group.

CONCLUSION

There are two anoikis-related subtypes with different prognoses in the population of NB. The anoikis-related prognostic model constructed in this study can accurately predict the prognoses of children with NB, and has a good guiding significance for clinical diagnosis, treatment and research of NB.

摘要

背景

失巢凋亡抵抗(AR)在转移过程中起着重要作用,是影响神经母细胞瘤(NB)危险分期的重要因素。本研究旨在构建失巢凋亡相关预后模型,并分析 NB 失巢凋亡相关亚型的关键基因、重要通路和肿瘤微环境特征,为 NB 的临床诊断、治疗和研究提供帮助。

方法

我们结合 GSE49710 和 E-MTAB-8248 的转录组数据,通过单因素 cox 回归分析筛选与 NB 预后密切相关的失巢凋亡相关基因(Args),并通过一致性聚类分析将样本分为失巢凋亡相关亚型。采用 WGCNA 筛选关键基因,GSVA 和 GSEA 分析失巢凋亡相关亚型间差异富集通路。通过 SsGSEA 和 CIBERSORT 分析不同组别间免疫细胞浸润水平。采用 Lasso 和多因素回归分析构建预后模型。最后,通过 GDSC 数据库分析药物敏感性。

结果

本研究共纳入 721 例病例和 283 个 Args。所有样本分为预后不同的两种亚型。WGCNA、GSVA 和 GSEA 分析提示两种亚型间存在差异表达的关键基因和重要通路。我们进一步构建了一个失巢凋亡相关的预后模型,其中 15 个 Args 参与了模型的构建。与其他常用的临床指标相比,该模型在评估 NB 预后方面具有更大的优势。不同风险组间 9 种免疫细胞浸润水平存在显著差异,模型构建中涉及的 13 个 Args 与免疫细胞浸润水平相关。有 6 种免疫细胞的浸润水平与风险评分存在关系。最后,我们筛选出高风险组中对 NB 作用更明显的 15 种药物。

结论

NB 人群中存在两种预后不同的失巢凋亡相关亚型。本研究构建的失巢凋亡相关预后模型能准确预测 NB 患儿的预后,对 NB 的临床诊断、治疗和研究具有良好的指导意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a2c/10111050/454052732c6e/fimmu-14-1135617-g001.jpg

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