背景：免疫和铁死亡在肝细胞癌（HCC）的进展和治疗中通常起着协同作用。然而，少有研究关注鉴定与免疫相关的铁死亡基因生物标志物。方法：我们进行了加权基因共表达网络分析（WGCNA）和随机森林分析，分别鉴定与HCC高度相关的预后差异表达免疫相关基因（PR-DE-IRGs）和具有特征性的预后差异表达铁死亡相关基因（PR-DE-FRGs），以进行共表达分析，得到预后差异表达免疫相关铁死亡特征基因（PR-DE-IRFeCGs）。最后，运用套索回归法确认了3个PR-DE-IRFeCGs，并构建了预测模型。基于共享数据和多种实验手段的差异表达和预后分析进一步验证了这3个模型基因在HCC中的生物学价值。我们运行了各种性能测试方法来测试模型的性能，并与其他类似标记进行比较。最后，我们融合了复合因素，构建了综合定量预测图，以实现准确的预后预测，并评估了其性能。结果：基于筛选的17个PR-DE-FRGs和34个PR-DE-IRGs之间的共表达分析，确定了17个PR-DE-IRFeCGs。多源测序数据、QRT-PCR、免疫组化染色和测试方法充分证实了这三个PR-DE-IRFeCGs在HCC中的上调表达和显著的预后影响。该模型在基于5个队列的多种方法性能测试中表现良好。此外，我们的模型在各种性能测试中优于其他相关模型。我们的标记的免疫疗法和化疗指导价值以及综合预测图的出色性能也经受住了考验。结论：我们鉴定了一种在HCC中具有优异预后预测和临床指导价值的新型PR-DE-IRFeCGs标记。Copyright © 2023 Jiang, Wang, Zhang and Li.

Background: Immunity and ferroptosis often play a synergistic role in the progression and treatment of hepatocellular carcinoma (HCC). However, few studies have focused on identifying immune-related ferroptosis gene biomarkers. Methods: We performed weighted gene co-expression network analysis (WGCNA) and random forest to identify prognostic differentially expressed immune-related genes (PR-DE-IRGs) highly related to HCC and characteristic prognostic differentially expressed ferroptosis-related genes (PR-DE-FRGs) respectively to run co-expression analysis for prognostic differentially expressed immune-related ferroptosis characteristic genes (PR-DE-IRFeCGs). Lasso regression finally identified 3 PR-DE-IRFeCGs for us to construct a prognostic predictive model. Differential expression and prognostic analysis based on shared data from multiple sources and experimental means were performed to further verify the 3 modeled genes' biological value in HCC. We ran various performance testing methods to test the model's performance and compare it with other similar signatures. Finally, we integrated composite factors to construct a comprehensive quantitative nomogram for accurate prognostic prediction and evaluated its performance. Results: 17 PR-DE-IRFeCGs were identified based on co-expression analysis between the screened 17 PR-DE-FRGs and 34 PR-DE-IRGs. Multi-source sequencing data, QRT-PCR, immunohistochemical staining and testing methods fully confirmed the upregulation and significant prognostic influence of the three PR-DE-IRFeCGs in HCC. The model performed well in the performance tests of multiple methods based on the 5 cohorts. Furthermore, our model outperformed other related models in various performance tests. The immunotherapy and chemotherapy guiding value of our signature and the comprehensive nomogram's excellent performance have also stood the test. Conclusion: We identified a novel PR-DE-IRFeCGs signature with excellent prognostic prediction and clinical guidance value in HCC.Copyright © 2023 Jiang, Wang, Zhang and Li.