摘要
出身背景
骨肉瘤是一种常见的儿童恶性肿瘤，死亡率和致残率很高。自噬是调节肿瘤细胞凋亡和侵袭的重要过程，因此构建OS自噬相关基因（ARGs）的风险评分模型将有利于评估治疗和预后。
方法
我们从产生有效治疗的治疗应用研究（TARGET）数据库下载了一个OS数据集，并通过人类自噬数据库（HADb）发现了与OS相关的ARG。使用多变量Cox回归模型获得五种中枢ARG（CCL2、AMBRA1、VEGFA、MYC和EGFR）。然后，我们生成了风险评分，并构建了一个预测模型。从基因表达综合数据库（GEO）获得的另一个数据集用于测试准确性和有效性。系统地探讨了免疫细胞浸润的作用，并评估了对靶向药物反应的预测。进行免疫组织化学以验证关键ARGs的表达。
后果
基于五个中枢ARG，我们建立了一个与操作系统相关的风险评分模型。从地球观测组织下载的数据集证明了高准确性和有效性。这五种ARG在PI3K和MAPK通路中发挥作用。靶向药物敏感性分析的结果与通路分析一致。免疫组织化学显示，OS组和癌旁组之间五种ARG的表达差异显著。
结论
我们构建了一个与OS自噬相关的风险评分模型，探讨了ARGs的诊断价值，并提出了可能的治疗靶点。
Abstract
Background
Osteosarcoma (OS) is a common pediatric malignancy with high mortality and disability rates. Autophagy is an essential process in regulating the apoptosis and invasion of tumor cells, so constructing a risk score model of OS autophagy-related genes (ARGs) will bring benefit to the evaluation of both treatment and prognosis.

Methods
We downloaded a dataset of OS from the Therapeutically Applicable Research To Generate Effective Treatments (TARGET) database, and found OS-related ARGs through the Human Autophagy Database (HADb). Five hub ARGs (CCL2, AMBRA1, VEGFA, MYC and EGFR) were obtained using a multivariate Cox regression model. We then generated the risk scores and constructed a prediction model. Another dataset obtained from the Gene Expression Omnibus (GEO) was used to test accuracy and validity. The role of immune cell infiltration was systematically explored, and prediction of response to targeted drugs was assessed. Immunohistochemistry was carried out to verify the expression of the key ARGs.

Results
Based on the five hub ARGs, we established a risk score model related to OS. High accuracy and validity were demonstrated by datasets downloaded from the GEO. The five ARGs played a role in the PI3K and MAPK pathways. Results from targeted drug sensitivity analyses were consistent with pathway analyses. Immunohistochemistry demonstrated that the expression differences of the five ARGs were significant between the OS group and the paracancerous group.

Conclusions
We constructed a risk score model related to autophagy of OS, explored the diagnostic value of ARGs, and present possible therapeutic targets.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987880/