Ferroptosis is a form of regulated cell death initiated by oxidative perturbations that can be blocked by iron chelators and lipophilic antioxidants, and ferroptosis may be the silver bullet treatment for multiple cancers, including immunotherapy- and chemotherapy-insensitive cancers such as pancreatic ductal adenocarcinoma (PDAC). Numerous studies have noted that long non-coding RNAs (lncRNAs) regulate the biological behaviour of cancer cells by binding to DNA, RNA and protein. However, few studies have reported the role of lncRNAs in ferroptosis processes and the function of ferroptosis-associated lncRNAs. The primary objective of the present study was to identify ferroptosis-related lncRNAs using bioinformatic approaches combined with experimental validation. The second objective was to construct a prognostic model to predict the overall survival of patients with PDAC. The present study identified ferroptosis-related lncRNAs using a bioinformatic approach and validated them in an independent pancreatic cancer cohort from Fudan University Shanghai Cancer Center. The lncRNA SLCO4A1-AS1 was identified as a novel molecule mediating ferroptosis resistance in vitro. A novel algorithm was used to construct a ‘0 or 1’ matrix-based prognosis model, which showed promising diagnostic accuracy for potential clinical translation (area under the curve = 0.89 for the 2-year survival rate). Notably, molecular subtypes classified by the risk scores of the model did not belong to any previously reported subtypes of PDAC. The immune microenvironment, metabolic activities, mutation landscape and ferroptosis sensitivity were significantly distinct between patients with different risk scores. Sensitivity (IC50) to 30 common anticancer drugs was analysed between patients with different risks, and imatinib and axitinib were found to be potential drugs for the treatment of patients with lower risk scores. Overall, we developed an accurate prognostic model based on the expression patterns of ferroptosis lncRNAs, which may contribute greatly to the evaluation of patient prognosis, molecular characteristics and treatment modalities and could be further translated into clinical applications.

中文翻译：

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铁死亡相关 lncRNA 对预测胰腺导管腺癌的临床结果和分子特征

铁死亡是一种由氧化扰动引发的受调节的细胞死亡形式，可以被铁螯合剂和亲脂性抗氧化剂阻断，铁死亡可能是多种癌症的灵丹妙药，包括免疫治疗和化疗不敏感的癌症，如胰腺导管腺癌 (PDAC) ）。大量研究指出，长链非编码 RNA (lncRNA) 通过与 DNA、RNA 和蛋白质结合来调节癌细胞的生物学行为。然而，很少有研究报道lncRNA在铁死亡过程中的作用以及与铁死亡相关的lncRNA的功能。本研究的主要目的是使用生物信息学方法结合实验验证来鉴定与铁死亡相关的 lncRNA。第二个目标是构建一个预后模型来预测 PDAC 患者的总生存期。本研究使用生物信息学方法鉴定了与铁死亡相关的 lncRNA，并在复旦大学上海癌症中心的独立胰腺癌队列中对其进行了验证。lncRNA SLCO4A1-AS1被鉴定为一种在体外介导铁死亡抗性的新分子。一种新的算法用于构建基于“0 或 1”矩阵的预后模型，该模型显示了潜在临床转化的有希望的诊断准确性（曲线下面积 = 2 年生存率的 0.89）。值得注意的是，按模型风险评分分类的分子亚型不属于任何先前报道的 PDAC 亚型。免疫微环境、代谢活动、具有不同风险评分的患者之间的突变情况和铁死亡敏感性显着不同。分析了不同风险患者对 30 种常见抗癌药物的敏感性（IC50），发现伊马替尼和阿西替尼是治疗风险评分较低患者的潜在药物。总体而言，我们基于铁死亡 lncRNA 的表达模式开发了一个准确的预后模型，这可能有助于评估患者预后、分子特征和治疗方式，并可以进一步转化为临床应用。发现伊马替尼和阿西替尼是治疗风险评分较低患者的潜在药物。总体而言，我们基于铁死亡 lncRNA 的表达模式开发了一个准确的预后模型，这可能有助于评估患者预后、分子特征和治疗方式，并可以进一步转化为临床应用。发现伊马替尼和阿西替尼是治疗风险评分较低患者的潜在药物。总体而言，我们基于铁死亡 lncRNA 的表达模式开发了一个准确的预后模型，这可能有助于评估患者预后、分子特征和治疗方式，并可以进一步转化为临床应用。