Background
As a common malignant bone tumor, osteosarcoma (OS) progresses rapidly and recurs easily. This study is aimed to build a risk score system for OS patients.
Methods
From The Cancer Genome Atlas and Gene Expression Omnibus databases, the RNA-seq data of OS (the training set) and GSE39055 (the validation sets) separately were obtained. Combined with limma package, the differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) between recurrence and non-recurrence groups were analyzed. After the RNAs correlated with independent prognosis were screened using survival package, risk score systems were constructed and the optimal one was selected. For the independent clinical prognostic factors identified by survival package, stratification analysis was conducted. Using Gene Set Enrichment Analysis, pathways were enriched for the differentially expressed genes (DEGs) between high and low risk groups.
Results
For recurrence and non-recurrence groups, 319 DE-mRNAs and 14 DE-lncRNAs were identified. Subsequently, 10 DE-mRNAs (including ALDH1A1, CA9, GMDS, LCMT2, LRRC75A, METTL1, RAB29, TADA2B, TDRD7, and TIGD2) and eight DE-lncRNAs were found to be correlated with independent prognosis. From the four risk score systems, the mRNA expression status-based risk score system was selected as the optimal one. Among the three independent clinical prognostic factors, age and recurrence were significantly related to overall survival in high risk group. Additionally, vascular smooth muscle contraction, and glycine, serine and threonine metabolism were enriched for the DEGs between high and low risk groups.
Conclusion
The mRNA expression status-based risk score system might be devoted to predict the prognosis of OS patients.