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基于铁死亡相关基因特征的三阴性乳腺癌亚型鉴定以优化治疗策略

Ferroptosis-related gene signature-based subtype identification of triple-negative breast cancer to prioritize treatment strategies.

作者信息

Chen Yongzhen, Huang Xiaoying, Wang Junqi, Hu Chao, Zheng Yanan, Wang Yumeng, Zheng Shuqian, Ji Guozhong, You Qiang

机构信息

Department of General Practice, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Laboratory of Frontiers Science Center for Precision Oncology, Faculty of Health Sciences, University of Macau, Macau, Macau SAR, China.

出版信息

Front Oncol. 2025 May 20;15:1541119. doi: 10.3389/fonc.2025.1541119. eCollection 2025.

Abstract

PURPOSE

Ferroptosis, an iron-dependent form of regulated cell death (RCD), has been proven to affect the response to antineoplastic therapies. However, little is known about the role of ferroptosis in chemotherapy and immune checkpoint inhibitor (ICI) therapy responses, as well as the molecular subtype identification of triple-negative breast cancer (TNBC).

METHODS

We performed unsupervised clustering to stratify patients with TNBC in the Fudan University Shanghai Cancer Center (FUSCC) TNBC cohort into distinct ferroptosis-related subtypes according to the expression of eight ferroptosis-related genes (FRGs): EMC2, FTH1, HMOX1, LPCAT3, NOX4, SOCS1, BAP1, and ISCU. We conducted Gene Ontology (GO) analysis and gene set variation analysis (GSVA) to characterize the immune phenotype and enriched pathways of the distinct subtypes of TNBC. We constructed the FerrScore model to identify the most promising candidate compounds and predict ICI therapy benefits for patients with TNBC.

RESULTS

We identified two distinct ferroptosis-related subtypes with different overall survival (OS). Patients in cluster 1 exhibited better OS, which had a phenotype of a "hot" tumor with abundant immune cell infiltration and higher expression of immune checkpoints compared to cluster 2. We screened everolimus as the most promising candidate drug for patients with high FerrScore referring to comprehensive factors including CMap score, experimental evidence, and clinical trial status. Further, we confirmed that FerrScore was a potentially powerful metric to predict anti-PD-L1, anti-PD-1, and anti-PD-1 + CTLA-4 ICI therapy benefits.

CONCLUSIONS

Ferroptosis reprogrammed the tumor microenvironment (TME) and classified patients into distinct subgroups with significantly different OS. FerrScore was a potentially powerful metric to screen candidate compounds and predict ICI therapy benefits for patients with TNBC, which prioritized clinical treatment strategies.

摘要

目的

铁死亡是一种铁依赖性的程序性细胞死亡形式,已被证明会影响抗肿瘤治疗的反应。然而,关于铁死亡在化疗和免疫检查点抑制剂(ICI)治疗反应中的作用,以及三阴性乳腺癌(TNBC)的分子亚型鉴定,我们所知甚少。

方法

我们进行了无监督聚类,根据8个铁死亡相关基因(FRG):EMC2、FTH1、HMOX1、LPCAT3、NOX4、SOCS1、BAP1和ISCU的表达,将复旦大学附属肿瘤医院(FUSCC)TNBC队列中的患者分层为不同的铁死亡相关亚型。我们进行了基因本体(GO)分析和基因集变异分析(GSVA),以表征TNBC不同亚型的免疫表型和富集通路。我们构建了FerrScore模型,以识别最有前景的候选化合物,并预测TNBC患者的ICI治疗获益。

结果

我们鉴定出两种具有不同总生存期(OS)的铁死亡相关亚型。与第2组相比,第1组患者的OS更好,具有“热”肿瘤的表型,免疫细胞浸润丰富,免疫检查点表达更高。综合CMap评分、实验证据和临床试验状态等因素,我们筛选出依维莫司作为FerrScore高的患者最有前景的候选药物。此外,我们证实FerrScore是预测抗PD-L1、抗PD-1和抗PD-1+CTLA-4 ICI治疗获益的潜在有力指标。

结论

铁死亡重塑了肿瘤微环境(TME),并将患者分为具有显著不同OS的不同亚组。FerrScore是筛选候选化合物和预测TNBC患者ICI治疗获益的潜在有力指标,为临床治疗策略提供了优先次序。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/106e/12129930/a50d3ea2fd69/fonc-15-1541119-g001.jpg

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