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Research Paper|Volume 12, Issue 19|pp 19022—19044

Target RNA modification for epigenetic drug repositioning in neuroblastoma: computational omics proximity between repurposing drug and disease

Pei Ma1,2, Lifeng Yue3, Sen Zhang2, Dacheng Hao4, Zhihong Wu5, Lijia Xu1, Guanhua Du2, Peigen Xiao1
  • 1Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100193, China
  • 2State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
  • 3Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China
  • 4Biotechnology Institute, School of Environment and Chemical Engineering, Dalian Jiaotong University, Dalian 116021, China
  • 5Department of Orthopedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
Received: December 4, 2019Accepted: June 29, 2020Published: October 12, 2020
https://doi.org/10.18632/aging.103671

Copyright: © 2020 Ma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

RNA modifications modulate most steps of gene expression. However, little is known about its role in neuroblastoma (NBL) and the inhibitors targeting it. We analyzed the RNA-seq (n=122) and CNV data (n=78) from NBL patients in Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. The NBL sub-clusters (cluster1/2) were identified via consensus clustering for expression of RNA modification regulators (RNA-MRs). Cox regression, principle component analysis and chi-square analysis were used to compare differences of survival, transcriptome, and clinicopathology between clusters. Cluster1 showed significantly poor prognosis, of which RNA-MRs’ expression and CNV alteration were closely related to pathologic stage. RNA-MRs and functional related prognostic genes were obtained using spearman correlation analysis, and queried in CMap and L1000 FWD database to obtain 88 inhibitors. The effects of 5 inhibitors on RNA-MRs were confirmed in SH-SY5Y cells. The RNA-MRs exhibited two complementary regulation functions: one conducted by TET2 and related to translation and glycolysis; another conducted by ALYREF, NSUN2 and ADARB1 and related to cell cycle and DNA repair. The perturbed proteomic profile of HDAC inhibitors was different from that of others, thus drug combination overcame drug resistance and was potential for NBL therapy with RNA-MRs as therapeutic targets.