背景：一种特定类型的细胞死亡，称为铁死亡，是由于过度脂质过氧化引起的。它是一种调节型的细胞死亡，可以影响肿瘤细胞的反应。目前不清楚这种情况的存在是否会影响多发性骨髓瘤（MM）患者的预后。方法：在本研究中，我们研究了MM中铁死亡相关基因（FRG）的表达差异和预后价值，并建立了一个铁死亡风险评分模型。为了提高预测准确性和临床适用性，我们还建立了一个判定图。通过基因富集分析，确定了与高风险组密切相关的通路。然后，我们探索了药物敏感性和免疫模式中的风险分层差异，并评估了它们在预后预测和治疗反应中的价值。最后，我们收集了MM细胞系和患者样本，使用定量实时聚合酶链式反应（qRT-PCR）验证了标记性FRG的表达。结果：预测MM患者的生存能力是一个具有挑战性的问题。通过使用从铁死亡中得出的风险模型，我们能够更准确地预测疾病的预后。通过统计分析对其进行了验证，结果显示该模型是MM预后的独立因子。高风险得分的患者与低风险组相比，生存机会更差。判定图的校准和能力也很强。我们注意到，铁死亡风险评分与临床治疗之间的联系是通过FRG与免疫检查点基因和药物敏感性的显著相关来建议的。我们使用qRT-PCR验证了预测模型。结论：我们证明了FRG与MM的关联，并为MM患者的预后开发了一种新的风险模型。我们的研究揭示了铁死亡在MM中的潜在临床相关性，并强调其作为该疾病患者治疗靶点的潜力。Copyright © 2023 Wang, Zhao, Zhang, Zhang, Zheng, Lin, Zhou, Zheng, Chen, Zheng, Zhang, Lin, Dong, Chen, Qian, Hu, Zhuang, Zhang, Jiang and Ma.

Background: One particular type of cellular death that is known as ferroptosis is caused by the excessive lipid peroxidation. It is a regulated form of cell death that can affect the response of the tumor cells. Currently, it is not known if the presence of this condition can affect the prognosis of patients with multiple myeloma (MM). Methods: In this study, we studied the expression differences and prognostic value of ferroptosis-related genes (FRGs) in MM, and established a ferroptosis risk scoring model. In order to improve the prediction accuracy and clinical applicability, a nomogram was also established. Through gene enrichment analysis, pathways closely related to high-risk groups were identified. We then explored the differences in risk stratification in drug sensitivity and immune patterns, and evaluated their value in prognostic prediction and treatment response. Lastly, we gathered MM cell lines and samples from patients to confirm the expression of marker FRGs using quantitative real-time PCR (qRT-PCR). Results: The ability to predict the survival of MM patients is a challenging issue. Through the use of a risk model derived from ferroptosis, we were able to develop a more accurate prediction of the disease's prognosis. They were then validated by a statistical analysis, which showed that the model is an independent factor in the prognosis of MM. Patients of high ferroptosis risk scores had a much worse chance of survival than those in the low-risk groups. The calibration and power of the nomogram were also strong. We noted that the link between the ferroptosis risk score and the clinical treatment was suggested by the FRG's significant correlation with the immune checkpoint genes and the medication sensitivity. We validated the predictive model using qRT-PCR. Conclusion: We demonstrated the association between FRGs and MM, and developed a new risk model for prognosis in MM patients. Our study sheds light on the potential clinical relevance of ferroptosis in MM and highlights its potential as a therapeutic target for patients with this disease.Copyright © 2023 Wang, Zhao, Zhang, Zhang, Zheng, Lin, Zhou, Zheng, Chen, Zheng, Zhang, Lin, Dong, Chen, Qian, Hu, Zhuang, Zhang, Jiang and Ma.