A Novel Ferroptosis-Related Gene Signature Predicts Overall Survival of Breast Cancer Patients.
A Novel Ferroptosis-Related Gene Signature Predicts Overall Survival of Breast Cancer Patients.
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一种新的铁死亡相关基因特征可预测乳腺癌患者的总体生存率
DOI：
10.3390/biology10020151
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发表时间：
2021-02-14
期刊：
影响因子：
4.2
通讯作者：
Shi Y
中科院分区：
文献类型：
--
作者：
Li H;Li L;Xue C;Huang R;Hu A;An X;Shi Y
铁死亡是一种铁依赖的细胞死亡形式，有别于常见的细胞死亡形式。越来越多的证据表明铁死亡与众多人类疾病密切相关。对于乳腺癌，一项相关研究表明，一些靶向药物可诱导铁死亡，此外，一些基础研究发现铁死亡相关基因与乳腺癌密切相关。然而，铁死亡相关基因与乳腺癌患者预后之间的相关性仍不明确。我们构建了一个8个铁死亡相关基因模型来预测乳腺癌患者的预后。该模型可将患者分为高风险组和低风险组。此外，肿瘤微环境分析显示这两组之间免疫细胞和免疫通路的富集情况不同。这个8基因模型被认为在预测乳腺癌患者预后方面具有重要价值。
乳腺癌是女性死亡的第二大原因，因此需要一个可靠的乳腺癌总生存期（OS）预后模型来改善治疗和护理。铁死亡是一种铁依赖的细胞死亡。已知西拉美新和拉帕替尼可诱导乳腺癌细胞发生铁死亡，并且一些铁死亡相关基因与乳腺癌治疗结果密切相关。这些基因与总生存期预后之间的关系尚不清楚。从公共数据库下载了基因表达数据和相关临床信息。基于癌症基因组图谱（TCGA） - 乳腺癌（BRCA）队列，采用最小绝对收缩和选择算子（LASSO）Cox回归建立了一个8基因预测模型，并在分子分类学乳腺癌国际协作组（METABRIC）队列患者中进行了验证。根据从8基因模型获得的中位风险评分，将患者分为高风险组和低风险组。Cox回归分析确定风险评分是总生存期的独立预测因子。CIBERSORT和单样本基因集富集分析（ssGSEA）的结果显示，上述两个风险组之间免疫细胞和通路的富集分数存在显著差异。综上所述，该预测模型有可能在未来的临床环境中得到广泛应用。
Simple Summary Ferroptosis is an iron-dependent cell death which is distinctive from common forms of cell death. Accumulating evidence indicated the close relationship between ferroptosis and numerous human diseases. Regarding breast cancer, a related study indicated that some targeted medicines could induce ferroptosis, furthermore, some basic research found that ferroptosis-related genes were closely related to breast cancer. However, the correlation between ferroptosis-related genes and breast cancer patients’ prognosis remains unknown. We built an 8-ferroptosis-related-gene model to predict breast cancer patients’ prognosis. This model could stratify patients into high- or low-risk groups. Additionally, tumor microenvironment analyses displayed differently enriched immune cells and immune pathways between these two groups. This 8-gene model is believed to be of great value in predicting prognosis for breast cancer patients. Abstract Breast cancer is the second leading cause of death in women, thus a reliable prognostic model for overall survival (OS) in breast cancer is needed to improve treatment and care. Ferroptosis is an iron-dependent cell death. It is already known that siramesine and lapatinib could induce ferroptosis in breast cancer cells, and some ferroptosis-related genes were closely related with the outcomes of treatments regarding breast cancer. The relationship between these genes and the prognosis of OS remains unclear. The data of gene expression and related clinical information was downloaded from public databases. Based on the TCGA-BRCA cohort, an 8-gene prediction model was established with the least absolute shrinkage and selection operator (LASSO) cox regression, and this model was validated in patients from the METABRIC cohort. Based on the median risk score obtained from the 8-gene model, patients were stratified into high- or low-risk groups. Cox regression analyses identified that the risk score was an independent predictor for OS. The findings from CIBERSORT and ssGSEA presented noticeable differences in enrichment scores for immune cells and pathways between the abovementioned two risk groups. To sum up, this prediction model has potential to be widely applied in future clinical settings.
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ACSL4 通过塑造细胞脂质成分来决定铁死亡敏感性。
影响因子：
14.8
作者：
Doll S;Proneth B;Tyurina YY;Panzilius E;Kobayashi S;Ingold I;Irmler M;Beckers J;Aichler M;Walch A;Prokisch H;Trümbach D;Mao G;Qu F;Bayir H;Füllekrug J;Scheel CH;Wurst W;Schick JA;Kagan VE;Angeli JP;Conrad M
通讯作者：
Conrad M
影响因子：
4.4
作者：
Martinez, Fernando O.;Gordon, Siamon;Mantovani, Alberto
通讯作者：
Mantovani, Alberto
铁死亡相关基因特征预测神经胶质瘤细胞死亡和神经胶质瘤患者进展
影响因子：
5.5
作者：
Liu, Han-jie;Hu, Hui-min;Jiang, Tao
通讯作者：
Jiang, Tao
影响因子：
0.7
作者：
Nucera, Silvia;Biziato, Daniela;De Palma, Michele
通讯作者：
De Palma, Michele
影响因子：
64.8
作者：
Jiang, Le;Kon, Ning;Li, Tongyuan;Wang, Shang-Jui;Su, Tao;Hibshoosh, Hanina;Baer, Richard;Gu, Wei
通讯作者：
Gu, Wei