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Analyzing the Interactions of mRNAs and ncRNAs to Predict Competing Endogenous RNA Networks in Osteosarcoma

Kun-Peng Zhu1, Chun-Lin Zhang1, Xiao-Long Ma1

  • 1Department of Orthopedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, PR China; Institute of Bone Tumor, Tongji University, School of Medicine, Shanghai 200072, PR China.

Molecular Therapy : the Journal of the American Society of Gene Therapy
|January 30, 2019
PubMed

Insights

Chemo-resistance in osteosarcoma (OS) is a major challenge. This study identifies novel competing RNA networks (ceRNAs) involving long non-coding RNAs, circular RNAs, and messenger RNAs, offering potential targets to overcome drug resistance in OS.

Area of Science:

  • Molecular Biology
  • Genomics
  • Cancer Research

Background:

  • Chemo-resistance significantly hinders osteosarcoma (OS) treatment outcomes.
  • Both protein-coding messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) regulate cancer biology, but their roles in OS chemo-resistance are not fully understood.
  • The comprehensive expression profiles and competing endogenous RNA (ceRNA) regulatory networks in chemo-resistant OS remain largely unelucidated.

Purpose of the Study:

  • To comprehensively identify differentially expressed long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and mRNAs in chemo-resistant versus chemo-sensitive osteosarcoma (OS) cell lines.
  • To construct and analyze the competing endogenous RNA (ceRNA) regulatory network underlying OS chemo-resistance.
  • To identify potential novel therapeutic targets for reversing chemo-resistance in osteosarcoma.

Main Methods:

  • Whole-transcriptome RNA sequencing (RNA-seq) was performed on paired chemo-resistant and chemo-sensitive OS cell lines.
  • Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted on differentially expressed mRNAs.
  • ceRNA networks were predicted using miRanda and TargetScan databases, integrating drug resistance-related genes and pathways. Validation involved real-time qPCR, RNA immunoprecipitation (RIP), RNA pull-down, and dual luciferase reporter assays.

Main Results:

  • Identification of differentially expressed lncRNAs, circRNAs, miRNAs, and mRNAs between chemo-resistant and chemo-sensitive OS cells.
  • Construction of comprehensive ceRNA networks, revealing complex regulatory interactions.
  • Validation of two specific ceRNA pathways (lncRNAMEG3/hsa-miR-200b-3p/AKT2 and hsa_circ_0001258/hsa-miR-744-3p/GSTM2) providing mechanistic insights.

Conclusions:

  • The study elucidates the complex molecular landscape of chemo-resistance in osteosarcoma through comprehensive transcriptomic analysis.
  • Identified ceRNA networks offer novel insights into the mechanisms driving drug resistance in OS.
  • The findings suggest potential therapeutic targets for overcoming chemo-resistance and improving osteosarcoma treatment outcomes.
Keywords:
ceRNAchemo-resistancemRNAncRNAosteosarcoma

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