Identification of Immune-Related Prognostic Genes and LncRNAs Biomarkers Associated With Osteosarcoma Microenvironment

Frontiers in Oncology

Tao Zhang¹  Xiangdong Chen¹  Haifa Xia¹  Yingli Nie²  Kailin Cai³  Jiliang Wang³  Huili Li³  Yanbin Zhang⁴ 

[1] Department of Anesthesiology, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, Wuhan, China;Department of Dermatology, Tongji Medical College, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Huazhong University of Science and Technology, Wuhan, China;Department of Gastrointestinal Surgery, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, Wuhan, China;Department of Orthopaedics, Tongji Medical College, Union Hospital, Huazhong University of Science and Technology, Wuhan, China;

关键词: osteosarcoma;    immune;    prognosis;    biomarker;    tumor microenvironment;   

DOI  :  10.3389/fonc.2020.01109

来源: DOAJ

【 摘 要 】

Osteosarcoma (OS) is the most common malignancy of the bone that occurs majorly in young people and adolescents. Although the survival of OS patients markedly improved by complete surgical resection and chemotherapy, the outcome is still poor in patients with recurrent and/or metastasized OS. Thus, identifying prognostic biomarkers that reflect the biological heterogeneity of OS could lead to better interventions for OS patients. Increasing studies have indicated the association between immune-related genes (IRGs) and cancer prognosis. In the present study, based on the data concerning OS obtained from TARGET (Therapeutically Applicable Research to Generate Effective Treatments) database, we constructed a classifier containing 12 immune-related (IR) long non-coding RNAs (lncRNAs) and 3 IRGs for predicting the prognosis of OS by using the least absolute shrinkage and selection operation Cox regression. Besides, based on the risk score calculated by the classifier, the samples were divided into high- and low-risk groups. We further investigated the tumor microenvironment of the OS samples by ESTIMATE and CIBERSORT algorithms between the two groups. Finally, we identified three small molecular drugs with potential therapeutic value for OS patients with high-risk score. Our results suggest that the IRGs and IR-lncRNAs–based classifier could be used as a reliable prognostic predictor for OS survival.

【 授权许可】

Unknown