Metal-dependent programmed cell death-related lncRNA prognostic signatures and natural drug sensitivity prediction for gastric cancer - Song, Xuesong; Hou, Lin; Zhao, Yuanyuan; Guan, Qingtian; Li, Zhiwen (Frontiers in Pharmacology, 2022)
Background: Gastric cancer is one of the most important malignancies with bad prognosis. Ferroptosis and cuproptosis are newly discovered metal-dependent programmed cell death, which may directly affect the outcome of gastric cancer. Long non-coding RNAs (lncRNAs) can affect the prognosis of cancer with stable structure, which could be potential prognostic prediction factors for gastric cancer. Methods: Differentially expressed metal-dependent PCD related lncRNAs were identified with DESeq2 and Pearson’s correlation analysis. Through GO, KEGG and GSEA analysis, we identified the potential effects of metal-dependent PCD-related lncRNAs towards prognosis. Using COX regression analysis with LASSO method, we constructed a 12 lncRNAs prognostic signature model. And we also evaluated the prognostic efficiency with Kaplan–Meier (K-M) survival curve, receiver operating characteristic (ROC) curve, as well as Decision Curve Analysis (DCA) methods. The sensitivities for anti-tumor drugs and were then predicted with pRRophetic method. And we discuss the Chinese patent medicines and plant extracts which could induce metal-dependent programmed cell death. Results: We constructed metal-dependent PCD-related lncRNA-genes co-expression network. And a metal-dependent PCD-related gastric cancer prognostic signature model, including 12 lncRNAs was constructed. And K-M survival curve revealed a worse prognosis in high-risk group. ROC curve analysis shown the AUC of our model is 0.766, which was better than other published models. And half-maximum inhibitory concentration (IC50) for dasatinib, lapatinb, sunitinib, cytarabine, saracatinib and vinorelbine were much lower among high-risk group. Conclusions: Our 12 metal-dependent PCD-related lncRNAs prognostic signature model may improve the OS prediction for gastric cancer. And anti-tumor drug sensitivity analysis results may also helpful for individualized chemotherapy regimens design.