A Novel Predictive Model Associated with Osteosarcoma Metastasis

Abstract

Purpose

Long non-coding RNAs (lncRNAs) have diverse roles in modulating gene expression on both transcriptional and translational levels, but their involvement in osteosarcoma (OS) metastasis remains unknown.

Patients and Methods

Transcriptional and clinical data were downloaded from TARGET datasets. A total of seven lncRNAs screened by univariate cox regression, lasso regression, and multivariate cox regression analysis were used to establish the OS metastasis model. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model.

Results

The established model showed exceptional predictive performance (1 year: AUC = 0.92, 95% Cl = 0.83–0.99; 3 years: AUC = 0.87, 95% Cl = 0.79–0.96; 5 years: AUC = 0.86, 95% Cl = 0.76–0.96). Patients in the high group had a poor survival outcome than those in the low group (p < 0.0001). GSEA analysis revealed that “NOTCH_SIGNALING” and “WNT_BETA_CATENIN_SIGNALING” were significantly enriched and that resting dendritic cells were associated with AL512422.1, AL357507.1, and AC006033.2 (p < 0.05).

Conclusion

Based on seven prognosis-related lncRNAs, we constructed a novel model with high reliability and accuracy for predicting metastasis in OS patients.

Keywords:

• lncRNAs
• osteosarcoma
• tumor metastasis
• prognosis

Abbreviation

AUC, area under receiver operating characteristic curve; BP, biological processes; CC, cellular components; EMT, epithelial–mesenchymal transition; FDR, false discovery rate; GSEA, Gene set enrichment analysis; GSVA, Gene Set Variation Analysis; KM, Kaplan–Meier; LASSO, least absolute shrinkage and selection operator; lncRNAs, long non-coding RNAs; MsigDB, Molecular Signatures Database; OS, osteosarcoma; ROS, reactive oxygen species; TF, transcription factor; Tregs, T cells regulatory.

Data Sharing Statement

Publicly available datasets from the TARGET datasets (https://ocg.cancer.gov/programs/target) were analyzed in this study. The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Ethics Statement

The study was approved by the Ethical Committee of the Affiliated Hospital of Qingdao University and experiments were performed in accordance with the Ethical Committee’s guidelines and regulations. The study complies with guidelines by the Declaration of Helsinki.

Author Contributions

Zhang H, Chen GH and Lyu CY designed the study, acquired the data, and wrote the manuscript. Xu Y reviewed the manuscript. Lyu XJ and Rong C contributed to the Statistical analysis and graphing. Wang YZ and Lyu CY supervised the study. Zhang H and Chen GH contribute equally to this paper. All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

Authors declare that they have no conflict of interest.