Department of Orthopedics, The Fourth Hospital of Hebei Medical University, 12 Health Road, Shijiazhuang, Hebei, 050011, People's Republic of China.
Department of CT Scan, The Fourth Hospital of Hebei Medical University, 12 Health Road, Shijiazhuang, Hebei, 050011, People's Republic of China.
Sci Rep. 2022 Mar 23;12(1):5029. doi: 10.1038/s41598-022-09080-5.
Osteosarcoma (OS) is the most common bone-derived tumor, and chemoresistance is a pivotal factor in the poor prognosis of patients with OS. Ferroptosis, as an emerging modality of regulated cell death, has demonstrated potential value in tumor chemoresistance studies. Through the gene expression omnibus database in conjunction with the FerrDb database, we identified novel ferroptosis-related differentially expressed genes (DEGs) involving chemoresistance in OS patients. Subsequently, enrichment analysis, protein-protein interaction network analysis and survival analysis were performed sequentially to recognize the hub genes and ultimately to construct a predictive model. The model constructed from the TARGET database was exhibited in a nomogram and assessed by calibration curves. The prognostic value of the model and hub genes was validated separately by an independent cohort. Twenty-two ferroptosis-related DEGs were identified, including 16 up-regulated and 6 down-regulated. Among them, expressions of CBS, COCS1, EGFR, as hub genes, were significantly associated with the prognosis of OS patients and were evidenced as independent prognostic factors. An efficient prognostic model covering hub gene expressions and clinical variables was developed and validated. Combining the results of hub genes in differential analysis, the actions of hub genes in ferroptosis, and the prognostic relevance of hub genes in patients, we revealed that CBS, SOCS1 and EGFR might play essential roles in OS and its chemoresistance with potential research and clinical value.
骨肉瘤(OS)是最常见的骨源性肿瘤,化疗耐药是骨肉瘤患者预后不良的关键因素。铁死亡作为一种新的细胞死亡方式,在肿瘤化疗耐药研究中显示出了潜在的价值。我们通过基因表达综合数据库(GEO)联合 FerrDb 数据库,鉴定了与骨肉瘤患者化疗耐药相关的新型铁死亡相关差异表达基因(DEGs)。随后,我们进行了富集分析、蛋白质-蛋白质相互作用网络分析和生存分析,以识别关键基因,并最终构建了一个预测模型。该模型是基于 TARGET 数据库构建的,并通过校准曲线进行评估。该模型和关键基因的预后价值分别通过独立队列进行了验证。鉴定出 22 个与铁死亡相关的 DEGs,其中包括 16 个上调基因和 6 个下调基因。在这些基因中,CBS、COCS1 和 EGFR 的表达与骨肉瘤患者的预后显著相关,并且被证实是独立的预后因素。我们开发并验证了一个包含关键基因表达和临床变量的有效的预后模型。结合差异分析中关键基因的结果、关键基因在铁死亡中的作用以及关键基因在患者中的预后相关性,我们揭示了 CBS、SOCS1 和 EGFR 可能在骨肉瘤及其化疗耐药中发挥重要作用,具有潜在的研究和临床价值。