Construction of an oxidative phosphorylation-related gene signature for predicting prognosis and identifying immune infiltration in osteosarcoma

Peng Zhou ^1,2, Jin Zhang ¹, Jinyan Feng ¹

⁰Department of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China.

Aging +

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March 20, 2024

View abstract on PubMed

Summary

This study identifies five oxidative phosphorylation genes that predict osteosarcoma prognosis. The developed risk model accurately predicts outcomes and reveals a link between these genes and immune infiltration in osteosarcoma.

Area Of Science

Oncology
Molecular Biology
Bioinformatics

Background

Osteosarcoma is a common bone cancer in children and adolescents, relying on oxidative phosphorylation for energy.
The prognostic role of oxidative phosphorylation-related genes in osteosarcoma remains underexplored.

Purpose Of The Study

To identify oxidative phosphorylation genes that predict osteosarcoma prognosis.
To develop a prognostic model for osteosarcoma based on these genes.
To investigate the relationship between these genes and immune infiltration in osteosarcoma.

Main Methods

Utilized data from UCSC Xena and GEO databases.
Employed univariate COX and LASSO regression analyses to identify prognostic genes.
Constructed a risk model and assessed its predictive accuracy using ROC curve analysis.
Analyzed survival and immune infiltration differences between high-risk and low-risk groups.
Performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA).

Main Results

Identified five key oxidative phosphorylation genes (ATP6V0D1, LHPP, COX6A2, MTHFD2, NDUFB9) associated with osteosarcoma prognosis.
Developed a risk prognostic model with superior predictive accuracy.
Observed adverse effects of immune infiltration in the high-risk group.
Validated the function of the identified gene set and confirmed the link between oxidative phosphorylation genes and osteosarcoma immune infiltration.

Conclusions

A robust prognostic model for osteosarcoma was successfully developed.
A significant correlation exists between oxidative phosphorylation-related genes and immune infiltration in osteosarcoma.
These findings offer potential biomarkers for osteosarcoma prognosis and immunotherapy targets.

Keywords:

gene immunity osteosarcoma oxidative phosphorylation prognosis