ArticleDiscover oncology2025
Identification of endothelial INSR as an osteosarcoma-related biomarker and therapeutic target based on weighted gene co-expression network analysis.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A comprehensive analysis of ferroptosis-related metastasis genes in osteosarcoma.Discover oncology · 2026Article
- Pan-cancer analysis of role of LOXL4 and experiment validation in osteosarcoma.Discover oncology · 2025Article
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5 authors.
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Abstract
backgroundOsteosarcoma (OS) is the most common primary malignant bone tumor characterized by a high rate of metastasis. The clinical efficacy of current targeted drugs for OS is limited, highlighting the urgent need to identify novel therapeutic targets. The study aimed to identify potential drug targets for OS by combining weighted gene co-expression network analysis (WGCNA) with single-cell analysis.
methodsOS-related genes were obtained from the osteosarcoma database, and prognosis-related genes were identified using The Cancer Genome Atlas (TCGA) data. Gene expression profiles and corresponding clinical data were extracted from TCGA, Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox analyses were used to screen the genes associated with OS prognosis. WGCNA was applied to detect genes linked to clinical characteristics in OS patients. Differentially expressed genes (DEGs) were analyzed using the GEO dataset. Single-cell RNA sequencing (scRNA-seq) data were employed to assess the expression pattern of the crucial genes in different types of cells in the tumor microenvironment.
resultsA total of 911 OS-related genes were retrieved from the osteosarcoma database. Prognosis analysis identified 110 prognosis-associated genes (P < 0.05). WGCNA revealed 295 genes related to OS clinical characteristics within the turquoise module. DEG analysis across GEO datasets (GSE12865, GSE16088, and GSE14359) identified 220 DEGs (|log2 (FC)| >1 and P < 0.05). Integration of these analyses identified 16 key genes in OS. Based on the expression profiles of these genes, OS patients were classified into three distinct clusters that exhibited significant differences in survival time, immune scores, and T-cell CD4 memory resting levels (P < 0.05). Insulin receptor (INSR) was identified as an independent risk factor predominantly expressed in endothelial cells.
conclusionINSR expression in OS tissues is associated with poor clinical outcomes. Activation or dysregulation of endothelial INSR contributes to OS progression, suggesting that endothelial INSR may represent a novel therapeutic target for OS.
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