Comprehensive Analysis of Key Genes and Regulatory Elements in Osteosarcoma Affected by Bone Matrix Mineral With Prognostic Values

Comprehensive Analysis of Key mRNAs and lncRNAs in Osteosarcoma Response to Preoperative Chemotherapy with Prognostic Values

OBJECTIVE

Osteosarcoma is one of the most common types of bone sarcoma with a poor prognosis. However, identifying the predictive factors that contribute to the response to neoadjuvant chemotherapy remains a significant challenge.

METHODS

A public data series (GSE87437) was downloaded to identify differentially expressed genes (DEGs) and differentially expressed lncRNAs (DElncRNAs) between osteosarcoma patients that do and do not respond to preoperative chemotherapy. Subsequently, functional analysis of the transcriptome expression profile, regulatory networks of DEGs and DElncRNAs, competing endogenous RNAs (ceRNA) and protein-protein interaction networks were performed. Furthermore, the function, pathway, and survival analysis of hub genes was performed and drug and disease relationship prediction of DElncRNA was carried out.

RESULTS

A total of 626 DEGs, 26 DElncRNAs, and 18 hub genes were identified. However, only one gene and two lncRNAs were found to be suitable as candidate gene and lncRNAs respectively.

CONCLUSION

The DEGs, hub genes, candidate gene, and candidate lncRNAs screened out in this context were considered as potential biomarkers for the response to neoadjuvant chemotherapy of osteosarcoma.

Prognostic Value of the Preoperative Lymphocyte-to-C-Reactive Protein Ratio and Albumin-to-Globulin Ratio in Patients with Osteosarcoma

Purpose

Growing evidence indicates that preoperative biomarkers could be identified as independent prognostic factors in various cancers. The purpose of this study was to assess prognostic value of the preoperative lymphocyte-to-C-reactive protein ratio (LCR), albumin-to-globulin ratio (AGR), lymphocyte-monocyte ratio (LMR), and C-reactive protein to albumin ratio (CAR) in patients with osteosarcoma.

Methods

A total of 137 osteosarcoma patients treated at our hospital between 2011 and 2019 were enrolled in the study. Patient demographics, clinical characteristics, and laboratory data were collected and analyzed. The optimal cutoff values of LCR, AGR, LMR, and CAR were assessed with receiver operating characteristic (ROC) analysis. Kaplan-Meier analysis was performed to estimate overall survival (OS). Univariate and multivariate Cox regression models were employed to determine the independent prognostic factors. The hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated to evaluate relative risk.

Results

The optimal cutoff values of LCR, AGR, LMR, and CAR were 0.14, 1.79, 3.05 and 0.24, respectively. According to the univariate analysis, OS was remarkably associated with neoadjuvant chemotherapy (P < 0.001), pathological fracture (P < 0.001), local recurrence (P = 0.020), metastasis (P < 0.001), LCR (P = 0.035), AGR (P = 0.028), LMR (P = 0.010), and CAR (P = 0.004). In multivariate analyses, pathological fracture (P = 0.025), metastasis (P < 0.001), LCR (P = 0.012), and AGR (P = 0.001) were identified as independent risk predictors for OS.

Conclusion

The present study provides new evidence that the preoperative LCR and AGR could serve as independent prognostic factors for patients with osteosarcoma. These findings will help physicians to stratify patients for appropriate treatment protocols and facilitate decision-making so as to improve the patients' survival condition.