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具有预后价值的神经母细胞瘤微环境相关生物标志物的生物信息学鉴定

Bioinformatic Identification of Neuroblastoma Microenvironment-Associated Biomarkers with Prognostic Value.

作者信息

Wang Yi, Luo Huan, Cao Jing, Ma Chao

机构信息

Department of Neonatology and Neonatal Intensive Care, Zhumadian Central Hospital, Zhumadian, China.

Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and the Berlin Institute of Health, Berlin, Germany.

出版信息

J Oncol. 2020 Sep 10;2020:5943014. doi: 10.1155/2020/5943014. eCollection 2020.

Abstract

The microenvironment plays a vital role in the tumor recurrence of neuroblastoma. This research aimed at exploring prognostic genes that are involved in neuroblastoma microenvironment. We used "estimate" R package to calculate the immune/stromal/ESTIMATE scores of each sample of ArrayExpress dataset E-MTAB-8248 based on the ESTIMATE algorithm. Then we found that immune/stromal/ESTIMATE scores were not correlated with age/chromosome 11q, but tumor stage, MYCN gene amplifications, and chromosome 1p. Samples were then divided into high- and low-score groups, and 280 common differentially expressed genes (DEGs) were identified. 64 potential prognostic genes were harvested through overall survival analysis from the common DEGs. 14 prognostic genes (ABCA6, SEPP1, SLAMF8, GPR171, ABCA9, ARHGAP15, IL7R, HLA-DPB1, GZMA, GPR183, CCL19, ITK, FGL2, and CD1C) were obtained after screening in two independent cohorts. GO and KEGG analysis discovered that common DEGs and 64 potential prognostic genes are mainly involved in T-cell activation, lymphocyte activation regulation, leukocyte migration, and the interaction of cytokines and cytokine receptors. Correlation analysis showed that all prognostic genes were negatively correlated with MYCN amplification. Cox analysis identified 5 independent prognostic genes (ARHGAP15, ABCA9, CCL19, SLAMF8, and CD1C).

摘要

微环境在神经母细胞瘤的肿瘤复发中起着至关重要的作用。本研究旨在探索参与神经母细胞瘤微环境的预后基因。我们使用“estimate”R包,基于ESTIMATE算法计算ArrayExpress数据集E-MTAB-8248每个样本的免疫/基质/ESTIMATE评分。然后我们发现免疫/基质/ESTIMATE评分与年龄/11号染色体q臂、肿瘤分期、MYCN基因扩增和1号染色体p臂无关。样本随后被分为高分和低分两组,并鉴定出280个常见的差异表达基因(DEG)。通过对常见DEG进行总生存分析,收获了64个潜在的预后基因。在两个独立队列中筛选后,获得了14个预后基因(ABCA6、SEPP1、SLAMF8、GPR171、ABCA9、ARHGAP15、IL7R、HLA-DPB1、GZMA、GPR183、CCL19、ITK、FGL2和CD1C)。GO和KEGG分析发现常见DEG和64个潜在预后基因主要参与T细胞活化、淋巴细胞活化调节、白细胞迁移以及细胞因子和细胞因子受体的相互作用。相关性分析表明,所有预后基因均与MYCN扩增呈负相关。Cox分析确定了5个独立的预后基因(ARHGAP15、ABCA9、CCL19、SLAMF8和CD1C)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46fd/7501561/bd3f2b2e2888/JO2020-5943014.001.jpg

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