Institute of Health Service and Transfusion Medicine, Beijing 100850, P.R. China.
Beijing Key Laboratory of Blood Safety and Supply Technologies, Beijing 100850, P.R. China.
Aging (Albany NY). 2024 Aug 29;16(16):11939-11954. doi: 10.18632/aging.206068.
Immune-associated ferroptosis plays an important role in the progression of acute myeloid leukemia (AML); however, the targets that play key roles in this process are currently unknown. This limits the development of mRNA vaccines based on immune-associated ferroptosis for clinical therapeutic applications. In this study, based on the rich data resources of the TCGA-LAML cohort, we analyzed the tumor mutational burden (TMB), gene mutation status, and associations between immune and ferroptosis genes to reveal the disease characteristics of AML patients. To gain a deeper understanding of differentially expressed genes, we applied the Limma package for differential expression analysis and integrated data sources such as ImmPort Shared Data and FerrDb V2. Moreover, we established gene modules related to TMB according to weighted gene coexpression network analysis (WGCNA) and explored the functions of these modules in AML and their relationships with TMB. We focused on the top 30 most frequent genes through a detailed survey of missense mutations and single nucleotide polymorphisms (SNPs) and selected potentially critical gene targets for subsequent analysis. Based on the expression of these genes, we successfully subgrouped AML patients and found that the subgroups associated with TMB (C1 and C2) exhibited significant differences in survival. The differences in the tumor microenvironment and immune cells between C1 and C2 patients were investigated with the ESTIMATE and MCP-counter algorithms. A predictive model of TMB-related genes (TMBRGs) was constructed, and the validity of the model was demonstrated by categorizing patients into high-risk and low-risk groups. The differences in survival between the high-risk patients and high-TMB patients were further investigated, and potential vaccine targets were identified via immune cell-level analysis. The identification of immunity- and ferroptosis-associated signature genes is an independent predictor of survival in AML patients and provides new information on immunotherapy for AML.
免疫相关的铁死亡在急性髓细胞白血病（AML）的进展中起着重要作用；然而，目前尚不清楚在这个过程中起关键作用的靶点。这限制了基于免疫相关铁死亡的 mRNA 疫苗在临床治疗应用中的发展。在这项研究中，基于 TCGA-LAML 队列的丰富数据资源，我们分析了肿瘤突变负担（TMB）、基因突变状态以及免疫和铁死亡基因之间的关联，以揭示 AML 患者的疾病特征。为了更深入地了解差异表达基因，我们应用 Limma 包进行差异表达分析，并整合了 ImmPort Shared Data 和 FerrDb V2 等数据源。此外，我们根据加权基因共表达网络分析（WGCNA）建立了与 TMB 相关的基因模块，并探讨了这些模块在 AML 中的功能及其与 TMB 的关系。我们通过详细调查错义突变和单核苷酸多态性（SNP），重点关注前 30 个最常见的基因，并选择潜在的关键基因靶点进行后续分析。基于这些基因的表达，我们成功地对 AML 患者进行了亚组分类，发现与 TMB 相关的亚组（C1 和 C2）在生存方面存在显著差异。使用 ESTIMATE 和 MCP-counter 算法研究了 C1 和 C2 患者之间肿瘤微环境和免疫细胞的差异。构建了 TMB 相关基因（TMBRGs）的预测模型，并通过将患者分为高风险和低风险组来验证该模型的有效性。进一步研究了高风险患者和高 TMB 患者之间的生存差异，并通过免疫细胞水平分析确定了潜在的疫苗靶点。鉴定出的免疫和铁死亡相关特征基因是 AML 患者生存的独立预测因子，为 AML 的免疫治疗提供了新的信息。
