PDF(Pubmed)
Abstract：
Osteosarcoma (OS) is the most common primary malignant tumour of the bone with high mortality. Here, we comprehensively analysed the hypoxia signalling in OS and further constructed novel hypoxia-related gene signatures for OS prediction and prognosis. This study employed Gene Set Enrichment Analysis (GSEA), Weighted correlation network analysis (WGCNA) and Least absolute shrinkage and selection operator (LASSO) analyses to identify Stanniocalcin 2 (STC2) and Transmembrane Protein 45A (TMEM45A) as the diagnostic biomarkers, which further assessed by Receiver Operating Characteristic (ROC), decision curve analysis (DCA), and calibration curves in training and test dataset. Univariate and multivariate Cox regression analyses were used to construct the prognostic model. STC2 and metastasis were devised to forge the OS risk model. The nomogram, risk score, Kaplan Meier plot, ROC, DCA, and calibration curves results certified the excellent performance of the prognostic model. The expression level of STC2 and TMEM45A was validated in external datasets and cell lines. In immune cell infiltration analysis, cancer-associated fibroblasts (CAFs) were significantly higher in the low-risk group. And the immune infiltration of CAFs was negatively associated with the expression of STC2 (P < 0.05). Pan-cancer analysis revealed that the expression level of STC2 was significantly higher in Esophageal carcinoma (ESCA), Head and Neck squamous cell carcinoma (HNSC), Kidney renal clear cell carcinoma (KIRC), Lung squamous cell carcinoma (LUSC), and Stomach adenocarcinoma (STAD). Additionally, the higher expression of STC2 was associated with the poor outcome in those cancers. In summary, this study identified STC2 and TMEM45A as novel markers for the diagnosis and prognosis of osteosarcoma, and STC2 was shown to correlate with immune infiltration of CAFs negatively.
摘要：
骨肉瘤（OS）是骨最常见的原发性恶性肿瘤，死亡率高。这里,我们全面分析了OS中的缺氧信号,并进一步构建了用于OS预测和预后的新型缺氧相关基因特征.本研究采用基因集富集分析(GSEA)，加权相关网络分析（WGCNA）和最小绝对收缩和选择操作符（LASSO）分析，以鉴定斯ninocalcin2（STC2）和跨膜蛋白45A（TMEM45A）作为诊断生物标志物，通过接收器工作特性(ROC)进一步评估，决策曲线分析(DCA)，以及训练和测试数据集中的校准曲线。单因素和多因素Cox回归分析用于构建预后模型。设计STC2和转移以伪造OS风险模型。列线图，风险评分，KaplanMeier情节,ROC,DCA,和校准曲线结果证明了预后模型的出色性能。在外部数据集和细胞系中验证STC2和TMEM45A的表达水平。在免疫细胞浸润分析中，在低危组中,癌相关成纤维细胞(CAFs)显著升高.而CAFs的免疫浸润与STC2的表达呈负相干(P<0.05)。全癌分析显示STC2在食管癌(ESCA)中的表达水平明显增高,头颈部鳞状细胞癌（HNSC），肾透明细胞癌（KIRC），肺鳞状细胞癌（LUSC），胃腺癌（STAD）。此外,在这些癌症中,STC2的高表达与不良预后相关.总之,这项研究确定STC2和TMEM45A是骨肉瘤诊断和预后的新标志物，STC2与CAFs的免疫浸润呈负相关。
