Abstract

Background Improving the osteosarcoma (OS) patients' survival has long been a challenge, even though the disease's treatment is on the verge of progress. DNA damage response (DDR) has traditionally been associated with carcinogenesis, tumor growth, and genomic instability. No study has used DDR genes as a signature to identify the prognosis of OS. The goal of this work was to find an effective possible DDR gene biomarker for predicting OS prognosis, which may be useful in clinical diagnosis and therapy. Methods To assess gene methylation, univariate and multivariate cox regression analyses were performed on data from OS patients. The data were retrieved from public databases, including the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and the Gene Expression Omnibus (GEO). Results The DDR gene signature was chosen, which included seven genes (NHEJ1, RMI2, SWI5, ERCC2, CLK2, POLG, and MLH1). In the TARGET dataset, patients were categorized into two groups: high-risk and low-risk. Patients with a high-risk score revealed a shorter OS rate (hazard ratio (HR): 3.15, 95% confidence interval (CI): 1.38–4.34, P < 0.001) in comparison with the patients with a low-risk score in the TARGET as a training group. The validation of the prognostic signature accuracy was carried out in relapse and validation cohorts (TARGET, n = 75; GSE21257, n = 53). The signature was found to be an independent predictive factor for OS in multivariate cox regression analysis, and a nomogram model was developed to predict an individual's risk of OS. DDR gene signature involved in Fanconi anemia pathway, nonhomologous end−joining pathway, mismatch repair, and nucleotide excision repair pathway. Conclusions Our study suggests that the identified novel DDR genes could be a powerful prognostic tool for prognosis evaluation and a valuable tool in predicting the risk factors in OS patients.

Highlights

  • Improving the osteosarcoma (OS) patients’ survival has long been a challenge, even though the disease’s treatment is on the verge of progress

  • Univariate and multivariate cox regression analyses were performed on data from OS patients. e data were retrieved from public databases, including the erapeutically Applicable Research to Generate Effective Treatments (TARGET) and the Gene Expression Omnibus (GEO)

  • Dataset and Data Processing. e data generated by the OS project of the the e Cancer Genome Atlas (TARGET) were used as the training set. e TARGET osteosarcoma project was used for the important clinical information for osteosarcoma patients as well as level three RNA-Seq data

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Summary

Introduction

Improving the osteosarcoma (OS) patients’ survival has long been a challenge, even though the disease’s treatment is on the verge of progress. No study has used DDR genes as a signature to identify the prognosis of OS. Univariate and multivariate cox regression analyses were performed on data from OS patients. E data were retrieved from public databases, including the erapeutically Applicable Research to Generate Effective Treatments (TARGET) and the Gene Expression Omnibus (GEO). In the TARGET dataset, patients were categorized into two groups: high-risk and low-risk. E signature was found to be an independent predictive factor for OS in multivariate cox regression analysis, and a nomogram model was developed to predict an individual’s risk of OS. Our study suggests that the identified novel DDR genes could be a powerful prognostic tool for prognosis evaluation and a valuable tool in predicting the risk factors in OS patients

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