Prognostic value and immune infiltration of anoikis-related genes in osteosarcoma
Jianming Mo, Hening Li, Hui Wang, Xu Fang, Jie Ma, Kaiwei Chen

TL;DR
This study builds a model using genes related to anoikis to predict osteosarcoma prognosis and immune response, validated with single-cell RNA sequencing and experiments.
Contribution
The novel contribution is a prognostic model for osteosarcoma based on anoikis-related genes and single-cell RNA sequencing data.
Findings
A four-gene model (MYC, BNIP3, IGFBP5, SPP1) accurately predicts osteosarcoma prognosis with AUC values of 0.836 for 1-, 3-, and 5-year survival.
The model shows significant differences in immune cell infiltration between risk groups and correlates with immune checkpoint expression.
qRT-PCR and immunohistochemistry confirmed elevated gene expression in osteosarcoma cells and poor prognosis patients.
Abstract
Currently, there is no research on building osteosarcoma (OS) prognostic models based on single-cell RNA sequencing (scRNA-seq) and anoikis-related genes (ARGs). Differential genes between osteoblasts cells and osteosarcoma cells were identified using scRNA-seq, and ARGs were determined by Genecard database. Lasso regression was employed to investigate hub genes and construct the model based on TARGET. Kaplan-Meier survival analysis was applied to compare the survival differences. ROC curves were used to evaluate the predictive performance of the model. CIBERSORT and ESTIMATE algorithms were conducted to calculate immune cell infiltration abundance. Finally, qRT-PCR and immunohistochemistry experiments were conducted to validate the results. A predictive model containing four modeling genes (MYC, BNIP3, IGFBP5, and SPP1) was successfully constructed, with AUC values of 0.836, 0.837,…
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Taxonomy
TopicsSarcoma Diagnosis and Treatment · Ferroptosis and cancer prognosis · Bone Tumor Diagnosis and Treatments
