Osteosarcoma (OS), a malignant primary bone tumor often seen in young adults, is highly aggressive. The improvements in high-throughput technologies have accelerated the identification of various prognostic biomarkers for cancer survival prediction. However, only few studies focus on the prediction of prognosis in OS patients using gene expression data due to small sample size and the lack of public datasets. In the present study, the RNA-seq data of 82 OS samples, along with their clinical information, were collected from the TARGET database. To identify the prognostic genes for the OS survival prediction, we selected the top 50 genes of contribution as the initial candidate genes of the prognostic risk model, which were ranked by random forest model, and found that the prognostic model with five predictors including CD180, MYC, PROSER2, DNAI1, and FATE1 was the optimal multivariable Cox regression model. Moreover, based on a multivariable Cox regression model, we also developed a scoring method and stratified the OS patients into groups of different risks. The stratification for OS patients in the validation set further demonstrated that our model has a robust performance. In addition, we also investigated the biological function of differentially expressed genes between two risk groups and found that those genes were mainly involved with biological pathways and processes regarding immunity. In summary, the identification of novel prognostic biomarkers in OS would greatly assist the prediction of OS survival and development of molecularly targeted therapies, which in turn benefit patients’ survival.

中文翻译：

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转录组分析确定骨肉瘤中的新预后基因

骨肉瘤（OS）是一种恶性原发性骨肿瘤，通常在年轻人中见到，具有很高的侵袭性。高通量技术的进步加速了用于癌症生存预测的各种预后生物标志物的鉴定。然而，由于样本量小和缺乏公共数据集，仅有少数研究集中在使用基因表达数据预测OS患者的预后。在本研究中，从TARGET数据库中收集了82个OS样品的RNA-seq数据及其临床信息。为了确定用于OS生存预测的预后基因，我们选择了前50个贡献基因作为预后风险模型的初始候选基因，并按随机森林模型对其进行了排序，发现该预后模型具有五个预测因子，包括CD180，MYC，PROSER2，DNAI1和FATE1是最优的多变量Cox回归模型。此外，基于多变量Cox回归模型，我们还开发了一种评分方法，将OS患者分为风险不同的人群。在验证集中对OS患者进行的分层进一步表明，我们的模型具有强大的性能。此外，我们还研究了两个风险组之间差异表达基因的生物学功能，发现这些基因主要与免疫相关的生物学途径和过程有关。总之，在OS中鉴定新的预后生物标志物将大大有助于OS生存的预测和分子靶向疗法的发展，从而有利于患者的生存。