Department of Radiology, The First Hospital of Jilin University, Changchun, China.
Department of Nuclear Medicine, The First Hospital of Jilin University, Changchun, China.
J Cell Mol Med. 2023 Dec;27(23):3827-3838. doi: 10.1111/jcmm.17958. Epub 2023 Oct 18.
To develop and validate the predictive effects of stable ferroptosis- and pyroptosis-related features on the prognosis and immune status of breast cancer (BC). We retrieved as well as downloaded ferroptosis- and pyroptosis-related genes from the FerrDb and GeneCards databases. The minimum absolute contraction and selection operator (LASSO) algorithm in The Cancer Genome Atlas (TCGA) was used to construct a prognostic classifier combining the above two types of prognostic genes with differential expression, and the Integrated Gene Expression (GEO) dataset was used for validation. Seventeen genes presented a close association with BC prognosis. Thirteen key prognostic genes with prognostic value were considered to construct a new expression signature for classifying patients with BC into high- and low-risk groups. Kaplan-Meier analysis revealed a worse prognosis in the high-risk group. The receiver operating characteristic (ROC) curve and multivariate Cox regression analysis identified its predictive and independent features. Immune profile analysis showed that immunosuppressive cells were upregulated in the high-risk group, and this risk model was related to immunosuppressive molecules. We successfully constructed combined features of ferroptosis and pyroptosis in BC that are closely related to prognosis, clinicopathological and immune features, chemotherapy efficacy and immunosuppressive molecules. However, further experimental studies are required to verify these findings.
为了开发和验证稳定的铁死亡和细胞焦亡相关特征对乳腺癌（BC）预后和免疫状态的预测效果。我们从 FerrDb 和 GeneCards 数据库中检索并下载了铁死亡和细胞焦亡相关基因。使用癌症基因组图谱（TCGA）中的最小绝对收缩和选择算子（LASSO）算法构建了一个预后分类器，该分类器结合了上述两种预后基因和差异表达，并用集成基因表达（GEO）数据集进行验证。有 17 个基因与 BC 预后密切相关。考虑到 13 个具有预后价值的关键预后基因，构建了一个新的表达特征，用于将 BC 患者分为高风险和低风险组。Kaplan-Meier 分析显示高危组预后较差。ROC 曲线和多变量 Cox 回归分析确定了其预测和独立特征。免疫特征分析显示高危组中免疫抑制细胞上调，该风险模型与免疫抑制分子有关。我们成功构建了与 BC 预后、临床病理和免疫特征、化疗疗效和免疫抑制分子密切相关的铁死亡和细胞焦亡联合特征。然而，需要进一步的实验研究来验证这些发现。
