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Updated: Dec 8, 2025

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
Bioinformatic Identification of Neuroblastoma Microenvironment-Associated Biomarkers with Prognostic Value
Yi Wang1, Huan Luo2,3, Jing Cao4
1Department of Neonatology and Neonatal Intensive Care, Zhumadian Central Hospital, Zhumadian, China.
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).
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