Department of Spine Osteopathic Surgery, the First Affiliated Hospital of Guangxi Medical University, Nanning, P. R. China.
Department of Orthopedic, Nanyang Central Hospital, Nanyang, China.
Medicine (Baltimore). 2022 Sep 9;101(36):e30192. doi: 10.1097/MD.0000000000030192.
Prognostic biomarkers for osteosarcoma (OS) are still very few, and this study aims to examine 2 novel prognostic biomarkers for OS through combined bioinformatics and experimental approach.
Expression profile data of OS and paraneoplastic tissues were downloaded from several online databases, and prognostic genes were screened by differential expression analysis, Univariate Cox analysis, least absolute shrinkage and selection operator regression analysis, and multivariate Cox regression analysis to construct prognostic models. The accuracy of the model was validated using principal component analysis, constructing calibration plots, and column line plots. We also analyzed the relationship between genes and drug sensitivity. Gene expression profiles were analyzed by immunocytotyping. Also, protein expressions of the constructed biomarkers in OS and paraneoplastic tissues were verified by immunohistochemistry.
Heparan sulfate 2-O-sulfotransferase 1 (HS2ST1) and Syndecan 3 (SDC3, met all our requirements after screening. The constructed prognostic model indicated that patients in the high-risk group had a much lower patient survival rate than in the low-risk group. Moreover, these genes were closely related to immune cells (P < .05). Drug sensitivity analysis showed that the 2 genes modeled were strongly correlated with multiple drugs. Immunohistochemical analysis showed significantly higher protein expression of both genes in OS than in paraneoplastic tissues.
HS2ST1 and SDC3 are significantly dysregulated in OS, and the prognostic models constructed based on these 2 genes have much lower survival rates in the high-risk group than in the low-risk group. HS2ST1 and SDC3 can be used as glycolytic and immune-related prognostic biomarkers in OS.
骨肉瘤(OS)的预后生物标志物仍然很少,本研究旨在通过联合生物信息学和实验方法来研究 2 种新型 OS 预后生物标志物。
从多个在线数据库下载 OS 和副肿瘤组织的表达谱数据,通过差异表达分析、单因素 Cox 分析、最小绝对收缩和选择算子回归分析以及多因素 Cox 回归分析筛选预后基因,构建预后模型。使用主成分分析、构建校准图和列线图来验证模型的准确性。我们还分析了基因与药物敏感性之间的关系。通过免疫细胞化学分析基因表达谱。此外,通过免疫组织化学验证了构建的生物标志物在 OS 和副肿瘤组织中的蛋白表达。
硫酸乙酰肝素 2-O-磺基转移酶 1(HS2ST1)和连接蛋白 3(SDC3,经过筛选后符合我们所有的要求。构建的预后模型表明,高危组患者的生存率明显低于低危组。此外,这些基因与免疫细胞密切相关(P<0.05)。药物敏感性分析表明,所构建的 2 个基因模型与多种药物强烈相关。免疫组织化学分析显示,这 2 个基因在 OS 中的蛋白表达均显著高于副肿瘤组织。
HS2ST1 和 SDC3 在 OS 中显著失调,基于这 2 个基因构建的预后模型中,高危组的生存率明显低于低危组。HS2ST1 和 SDC3 可作为 OS 中与糖酵解和免疫相关的预后生物标志物。