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Updated: Feb 8, 2026

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Exploring the key genes and pathways of side population cells in human osteosarcoma using gene expression array

Yi-Ming Ren1, Yuan-Hui Duan1, Yun-Bo Sun1

  • 1Department of Joint and Sport Medicine, Tianjin Union Medical Center, Jieyuan Road 190, Hongqiao District, Tianjin, 300121, People's Republic of China.

Journal of Orthopaedic Surgery and Research
|June 21, 2018
PubMed
Abstract

Insights

This study identified differentially expressed genes (DEGs) between side population (SP) and non-SP cells in human osteosarcoma (OS). Key genes and the EIF4E/mTOR pathway were highlighted as potential therapeutic targets for OS.

Area of Science:

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background:

  • Human osteosarcoma (OS) is a prevalent bone cancer with high metastasis and limited treatment options.
  • Side population (SP) cells in OS are implicated in tumor growth and self-renewal.
  • Identifying genes regulated by SP cells is crucial for understanding OS development.

Purpose of the Study:

  • To identify differentially expressed genes (DEGs) between SP and non-SP cells in primary human OS.
  • To elucidate the functions and molecular pathways associated with these DEGs in OS.
  • To uncover potential therapeutic targets for OS based on gene expression differences.

Main Methods:

  • Downloaded and analyzed the gene expression profile GSE63390.
  • Performed bioinformatics analysis, including gene ontology (GO) and pathway enrichment.
  • Utilized gene-gene interaction network analysis to identify core genes.

Main Results:

  • Identified 141 DEGs, with 72 overexpressed and 69 underexpressed.
  • Discovered core genes like EIF4E, FAU, HSPD1, IL-6, and KISS1 potentially involved in OS development.
  • Highlighted the EIF4E/mTOR signaling pathway as a potential target for OS therapy and tumorigenesis.

Conclusions:

  • This study offers insights into the role of DEGs from SP cells in OS development.
  • Identified key genes and pathways that warrant further investigation.
  • The findings suggest potential new avenues for OS treatment strategies.
Keywords:
Bioinformatics analysisDifferentially expressed genesOsteosarcomaSide population cells

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