Department of General Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
IET Syst Biol. 2024 Apr;18(2):55-75. doi: 10.1049/syb2.12089. Epub 2024 Mar 8.
The main objective was to establish a prognostic model utilising long non-coding RNAs associated with disulfidptosis and cuproptosis. The data for RNA-Sequence and clinicopathological information of Colon adenocarcinoma (COAD) were acquired from The Cancer Genome Atlas. A prognostic model was constructed using Cox regression and the Least Absolute Shrinkage and Selection Operator method. The model's predictive ability was assessed through principal component analysis, Kaplan-Meier analysis, nomogram etc. The ability of identifying the rates of overall survival, infiltration of immune cells, and chemosensitivity was also explored. In vitro experiments were conducted for the validation of differential expression and function of lncRNAs. A disulfidptosis and cuproptosis-related lncRNA prognostic model was constructed. The prognostic model exhibits excellent independent predictive capability for patient outcomes. Based on the authors' model, the high-risk group exhibited higher tumour mutation burdened worse survival. Besides, differences in immune cell infiltration and responsiveness to chemotherapeutic medications exist among patients with different risk scores. Furthermore, aberrant expressions in certain lncRNAs have been validated in HCT116 cells. In particular, FENDRR and SNHG7 could affect the proliferation and migration of colorectal cancer cells. Our study developed a novel prognostic signature, providing valuable insights into prognosis, immune infiltration, and chemosensitivity in COAD patients.
本研究的主要目的是建立一个基于与二硫键凋亡和铜死亡相关的长非编码 RNA 的预后模型。从癌症基因组图谱(TCGA)中获取了 RNA 测序和结直肠腺癌(COAD)临床病理信息的数据。使用 Cox 回归和最小绝对值收缩和选择算子(LASSO)方法构建了预后模型。通过主成分分析、Kaplan-Meier 分析、列线图等评估模型的预测能力。还探索了识别总生存率、免疫细胞浸润和化疗敏感性的能力。进行了体外实验以验证 lncRNAs 的差异表达和功能。构建了一个与二硫键凋亡和铜死亡相关的 lncRNA 预后模型。该预后模型对患者的预后具有出色的独立预测能力。根据作者的模型,高风险组的肿瘤突变负担更高,生存状况更差。此外,不同风险评分的患者之间存在免疫细胞浸润和对化疗药物反应性的差异。此外,在 HCT116 细胞中验证了某些 lncRNAs 的异常表达。特别是,FENDRR 和 SNHG7 可以影响结直肠癌细胞的增殖和迁移。我们的研究开发了一种新的预后标志物,为 COAD 患者的预后、免疫浸润和化疗敏感性提供了有价值的见解。