Cancer Management and Research (Oct 2021)
Circular RNA-Related CeRNA Network and Prognostic Signature for Patients with Osteosarcoma
Abstract
Gu Man,1,* Ao Duan,2,* Wanshun Liu,2,* Jiangqi Cheng,2 Yu Liu,3 Jiahang Song,4 Haisen Zhou,5 Kai Shen2 1Department of Orthopedics, Nanjing Lishui District Traditional Chinese Medicine Hospital, Nanjing, Jiangsu, People’s Republic of China; 2Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 3Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 4Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 5Department of Pathology, Nanjing Lishui District Traditional Chinese Medicine Hospital, Nanjing, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Kai ShenDepartment of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of ChinaTel +86-15152639976Email [email protected] ZhouDepartment of Pathology, Nanjing Lishui District Traditional Chinese Medicine Hospital, Nanjing, Jiangsu, People’s Republic of ChinaTel +86-13915913055Email [email protected]: Osteosarcoma (OSA) is characterized by its relatively high morbidity in children and adolescents. Patients usually have advanced disease at the time of diagnosis, resulting in poor outcomes. This study focused on building a circular RNA-based ceRNA network to develop a reliable model for OSA risk prediction.Methods: We used the Gene Expression Omnibus (GEO) datasets to explore the expression patterns of circRNA, miRNA, and mRNA in OSA. The prognostic value of circRNA host genes was assessed with data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database using Kaplan–Meier survival analysis. We established a circRNA-related ceRNA network and annotated its biological functions. Next, we developed a prognostic risk signature based on mRNAs extracted from the ceRNA network. We also developed a prognostic model and constructed a nomogram to enhance the prediction of OSA prognosis.Results: We identified 166 DEcircRNAs, 233 DEmiRNAs, and 1317 DEmRNAs and used them to create a circRNA-related ceRNA network. We then established a prognostic risk model consisting of four genes (MLLT11, TNFRSF11B, SLC7A7, and PARVA). Moreover, we found that inhibition of MLLT11 and SLC7A7 blocked OSA cell proliferation and migration in in vitro experiments.Conclusion: Our study identifies crucial prognostic genes and provides a circRNA-related ceRNA network for OSA, which will contribute to the elucidation of the molecular mechanisms underlying the oncogenesis and development of OSA.Keywords: osteosarcoma, ceRNA network, prognosis, nomogram, TARGET
