Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi‐Omics Analysis

Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemotherapy and surgical resection. This treatment is effective for early osteosarcoma. However, the effect declines as the disease progresses. Currently, our research on osteosarcoma is not enough to meet the clinical needs. Exosomes play a critical role in osteosarcoma progression by mediating intercellular communication. They carry molecular signals, including miRNAs and proteins, which can influence tumor growth, metastasis, and drug resistance. Recent studies have shown that exosomes from osteosarcoma cells can promote cell proliferation and migration, making them potential biomarkers for early diagnosis and therapeutic targets in osteosarcoma. This opens up new possibilities for the research of osteosarcoma. The combined genes of exosomes and DEGs were identified by searching GeneCards and GEO databases. Subsequent analyses included GO and KEGG Enrichment, GSEA. The core gene set was derived from the intersection of LASSO and SVM-RFE outputs, ensuring minimal redundancy through dimensionality reduction. Osteosarcoma was diagnosed and predicted by differential expression levels, ROC curve analysis, and nomogram. Immune cell infiltration in osteosarcoma was evaluated by the ssGSEA algorithm. Drug enrichment analysis and molecular docking simulations were conducted to discover the most promising drug leads. In vitro experiments included Wound Healing Assay and qRT-PCR to detect the therapeutic effect of the drug. Through multiple analyses and dimensionality reduction of the data set, six genes were selected (WNT5A, GCA, ANXA6, BIRC5, IL1β, and ARPC3). We examined differential expression in the control and tumor groups and made a gene prediction nomogram. Analysis of immune cell infiltration revealed significant alterations in the composition of immune cell subsets. Drug enrichment analysis and molecular docking of these six core genes were conducted to screen out the most suitable candidate drug: Mifepristone. Finally, Mifepristone was proved to inhibit the growth of osteosarcoma cells in vitro. Bioinformatics analysis identified six exosome-associated osteosarcoma genes (WNT5A, GCA, ANXA6, BIRC5, IL1β, and ARPC3) that could serve as potential biomarkers. Through screening, Mifepristone, which can act on BIRC5 and IL1β at the same time, has a very effective osteosarcoma treatment effect.

Authors

Institutions

Publication Details

Journal
The FASEB Journal
Published
2025-07-05
DOI
https://doi.org/10.1096/fj.202501151rr
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi‐Omics Analysis

Ronghan Liu, Yunpeng Zou, Kai Zhao, Shengbo Zhu et al.
The FASEB Journal
Extracellular vesicles in disease
article

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi‐Omics Analysis

Ronghan Liu, Yunpeng Zou, Kai Zhao, Shengbo Zhu, Wenqi Ma, Zheng Li, Jie Guo, Jianzhao Niu
article en

Abstract

Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemotherapy and surgical resection. This treatment is effective for early osteosarcoma. However, the effect declines as the disease progresses. Currently, our research on osteosarcoma is not enough to meet the clinical needs. Exosomes play a critical role in osteosarcoma progression by mediating intercellular communication. They carry molecular signals, including miRNAs and proteins, which can influence tumor growth, metastasis, and drug resistance. Recent studies have shown that exosomes from osteosarcoma cells can promote cell proliferation and migration, making them potential biomarkers for early diagnosis and therapeutic targets in osteosarcoma. This opens up new possibilities for the research of osteosarcoma. The combined genes of exosomes and DEGs were identified by searching GeneCards and GEO databases. Subsequent analyses included GO and KEGG Enrichment, GSEA. The core gene set was derived from the intersection of LASSO and SVM-RFE outputs, ensuring minimal redundancy through dimensionality reduction. Osteosarcoma was diagnosed and predicted by differential expression levels, ROC curve analysis, and nomogram. Immune cell infiltration in osteosarcoma was evaluated by the ssGSEA algorithm. Drug enrichment analysis and molecular docking simulations were conducted to discover the most promising drug leads. In vitro experiments included Wound Healing Assay and qRT-PCR to detect the therapeutic effect of the drug. Through multiple analyses and dimensionality reduction of the data set, six genes were selected (WNT5A, GCA, ANXA6, BIRC5, IL1β, and ARPC3). We examined differential expression in the control and tumor groups and made a gene prediction nomogram. Analysis of immune cell infiltration revealed significant alterations in the composition of immune cell subsets. Drug enrichment analysis and molecular docking of these six core genes were conducted to screen out the most suitable candidate drug: Mifepristone. Finally, Mifepristone was proved to inhibit the growth of osteosarcoma cells in vitro. Bioinformatics analysis identified six exosome-associated osteosarcoma genes (WNT5A, GCA, ANXA6, BIRC5, IL1β, and ARPC3) that could serve as potential biomarkers. Through screening, Mifepristone, which can act on BIRC5 and IL1β at the same time, has a very effective osteosarcoma treatment effect.

The FASEB JournalVol. 39(13)
Weifang Medical University (CN), Jinan Central Hospital (CN), Shandong First Medical University (CN)
Jinan Science and Technology Bureau, National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 85%
Extracellular vesicles in disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.