A four-lncRNA risk signature for prognostic prediction of osteosarcoma - Liu, Huanlong; Chen, Chao; Liu, Long; Wang, Zengtao (Frontiers in Genetics, 2023)
Aim: Osteosarcoma is the most common primary malignant tumor of bone. However, our understanding of the prognostic indicators and the genetic mechanisms of the disease progression are still incomplete. The aim of this study was to identify a long noncoding RNA (lncRNA) risk signature for osteosarcoma survival prediction. Methods: RNA sequencing data and relevant clinical information of osteosarcoma patients were downloaded from Therapeutically Applicable Research To Generate Effective Treatments database and we further analyzed differential expressed lncRNAs between dead and alive patients. Then, these lncRNAs were analyzed by univariate and multivariate Cox regression analysis to identify a risk signature. We calculated prognostic risk score for each sample according to this prognosis signature, and divided patients into high-risk and low-risk groups according to the median value of the risk score (0.975). Kaplan–Meier analysis and receiver operating characteristic (ROC) curve were used to evaluate the performance of the signature. Next, we analyze the signature’s potential function through Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG) and gene set enrichment analysis (GSEA). Finally, qRT-PCR was used to validate the expression level of the four lncRNAs in clinical samples. Results: 26 differentially expressed lncRNAs were identified between dead and alive groups. Furthermore, 4 lncRNAswere identified as independent remarkable prognostic factors and a four-lncRNAs risk signature for osteosarcoma survival prediction was constructed. Kaplan–Meier analysis showed that the 5-year survival time in high-risk and low-risk groups was 33.1% and 82.5%, and the area under the curve (AUC) of the ROC was 0.784, which demonstrated that the prognostic signature was convincible and had the potential to evaluate the survival of patients with osteosarcoma. The expression of the four lncRNAs were validated by qRT-PCR in osteosarcoma tissues and cells.Functional enrichment analysis suggested that the signature might influence osteosarcoma through regulating MAPK signaling pathway, PI3K-Akt signaling pathway and extracellular matrix, and also provided several new insights into the study of osteosarcoma, including the role of papillomavirus infection, olfactory receptor activity and olfactory transduction in osteosarcoma. Conclusions: We constructed a novel risk signature, and that would act as an independent prognostic biomarker to predict prognosis of osteosarcoma patients.