Identification of differentially expressed genes and fusion genes associated with malignant progression of spinal cord gliomas by transcriptome analysis

Sci Rep. 2019 Sep 19;9(1):13583. doi: 10.1038/s41598-019-50072-9.

Abstract

Glioma, the most common histological subtype of primary spinal cord tumors, is considered as a rare central nervous system neoplasm. In this study, 9 glioma samples (4 of grade II and 5 of grade IV with H3K27M positive) were analyzed to examine the molecular mechanisms underlying the malignant progression of gliomas, transcriptome sequencing. Differentially expressed genes (DEGs) in grade IV vs. grade II were analyzed by using the Limma package in R. Enrichment analysis was performed for the individual DEGs through VennPlex software and the Database for Annotation. Gene mutations and fusions were analyzed using the Genome Analysis Toolkit and STAR-Fusion. A total of 416 DEGs were identified in grade IV vs. grade II. Functional analysis of the DEGs showed that GALR1 and GRM5 of neuroactive ligand-receptor interactions signaling pathways may be relaed to malignant progression of gliomas. Further systematic transcriptional profiling identified 11 in-frame/frameshift gene fusions in the tumors. Notably, one novel gene fusions, GATSL2-GTF2I was detected in all of the grade II samples. In summary, the molecular alterations observed in glioma progression may improve the characterization of different human spinal cord glioma grades. The transcriptome analysis of intramedullary spinal cord glioma will provide a new candidate gene list for further mechanism research.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Biomarkers, Tumor / genetics*
  • Child
  • Child, Preschool
  • Disease Progression
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Neoplastic
  • Gene Fusion
  • Gene Regulatory Networks*
  • Glioma / genetics
  • Glioma / pathology*
  • Humans
  • Male
  • Middle Aged
  • Mutation
  • Neoplasm Grading
  • Sequence Analysis, RNA
  • Software
  • Spinal Cord Neoplasms / genetics
  • Spinal Cord Neoplasms / pathology*
  • Young Adult

Substances

  • Biomarkers, Tumor