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Machine learning reveals the role of telomerase activation-related genes in the prognosis of neuroblastoma

端粒酶 神经母细胞瘤 基因 计算生物学 生物 癌症研究 遗传学 细胞培养
作者
Chen Renhai,Fan Kaisi,Li Jinhao,Zhao Qianyun,Ding Xiaoting,Yongteng Li,Wang Jianjun,Daiyue Yu,Yang Liucheng,Kai Wu
出处
期刊:Cancer Biomarkers [IOS Press]
卷期号:42 (5)
标识
DOI:10.1177/18758592241306263
摘要

Background Neuroblastoma (NB) development is significantly impacted by telomere maintenance where telomerase activation acts as the triggering factor. The study demonstrated the practical use of telomerase activation-related genes in the diagnosis and prognosis of NB. Methods Weighted Gene Co-expression Network Analysis (WGCNA) and differential analysis were used to screen for prognostic-related genes in NB. Telomerase activation-related genes (TARG) were identified using Genecard and then intersected with the prognostic-related genes to obtain telomerase activation-related NB prognostic genes. The key prognosis genes were pinpointed by random forest and Lasso Cox analysis and confirmed by bioinformatics methods. Then RT-PCR experiments were employed to verify the differences in WNT4 and RPL22L1 gene expressions in tissue samples. The impact of the risk gene on NB cell proliferation, migration, and invasion was confirmed using CCK-8, Wound-healing assay, and Transwell assay. Results PRPH, RPL22L1, ODC1, ALK, NTRK1, ALCAM, and WNT4 were the seven key telomerase prognostic genes that were found by Lasso cox analysis and confirmed by external datasets in NB. Their expression levels varied in INSS stages, age, and high-risk and low-risk groups, as indicated by the validation results. Subsequently, two previously unverified genes, RPL22L1 and WNT4, were selected to construct a multifactor regression model combined with various clinical features to predict the mortality risk. RPL22L1 was ultimately chosen and confirmed to promote NB cell proliferation, migration, and invasion in vitro . Conclusion Telomerase activation is strongly linked to the onset and progression of NB. A multivariate regression model using the genes RPL22L1 and WNT4 proved effective in evaluating the prognosis of NB. The new molecular marker RPL22L1 can inhibit the NB cell proliferation, migration, and invasion, making it beneficial for the early diagnosis of high-risk NB.

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