LncRNA-Associated ceRNA Network Revealing the Potential Regulatory Roles of Ferroptosis and Immune Infiltration in Osteosarcoma as well as Construction of the Prognostic Model.

Abstract

Background: Osteosarcoma (OS) is the most common primary bone malignancy in the world. Increasing studies indicate that long non-coding RNAs (lncRNAs) are involved in ferroptosis and OS progression. Therefore, this study aims to identify ferroptosis- related lncRNAs (frlncRNAs), explore potential competing endogenous RNA (ceRNA) networks, and establish a new model for predicting OS prognosis.

Methods: Firstly, we downloaded data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), University of California, Santa Cruz (UCSC), and FerrDB, and screened for differentially expressed FRlncRNAs (DEFRlncRNAs) between OS patients and healthy controls. Then, we constructed the ceRNA network using the Lncbase 3.0, starBase, miRDB, miRTarBase, and TargetScan databases. Subsequently, prognosis- related DEFRlncRNAs were selected through Cox analysis, and a prognostic model was constructed. Next, the proportions of different immune cells in high and low-risk groups were quantified and evaluated using the "CIBERSORT" algorithm. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on prognosis-related DEFRlncRNAs to identify topranked biological processes and pathways.

Results: We identified 247 DEFRlncRNAs and constructed the ceRNA network comprising 37 lncRNAs, 84 microRNAs (miRNAs), and 865 messenger RNAs (mRNAs). Subsequently, we obtained 8 prognosis-related DEFRlncRNAs (AL645728.1, AL161785.1, LINC00539, AL590764.1, OLMALINC, AC110995.1, AC091180.2, and AL160006.1) and constructed a prognostic model, where metastasis and risk score were identified as important clinical factors for predicting OS prognosis. Additionally, only OLMALINC and AL160006.1 had corresponding target miRNAs in the prognosis-related ceRNA network. Lastly, we revealed the infiltration proportions of different immune cells in OS, with higher proportions of macrophages (M0 and M2 subgroups) and T cells (T cells CD4 memory resting and T cells CD8) observed.

Conclusion: This study explored the ferroptosis-related lncRNA-miRNA-mRNA regulatory network in OS, constructed a ferroptosis-related prognostic model, and characterized its association with immune infiltration, providing new insights into the pathological mechanisms and targeted therapy development for OS.