Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients.

IF 2.7 4区 医学 Q3 ONCOLOGY Technology in Cancer Research & Treatment Pub Date : 2024-01-01 DOI:10.1177/15330338241241484
Chen Yi, Jun Yang, Ting Zhang, Liu Qin, Dongjuan Chen
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Abstract

Introduction: Endoplasmic reticulum stress (ERS) was a response to the accumulation of unfolded proteins and plays a crucial role in the development of tumors, including processes such as tumor cell invasion, metastasis, and immune evasion. However, the specific regulatory mechanisms of ERS in breast cancer (BC) remain unclear. Methods: In this study, we analyzed RNA sequencing data from The Cancer Genome Atlas (TCGA) for breast cancer and identified 8 core genes associated with ERS: ELOVL2, IFNG, MAP2K6, MZB1, PCSK6, PCSK9, IGF2BP1, and POP1. We evaluated their individual expression, independent diagnostic, and prognostic values in breast cancer patients. A multifactorial Cox analysis established a risk prognostic model, validated with an external dataset. Additionally, we conducted a comprehensive assessment of immune infiltration and drug sensitivity for these genes. Results: The results indicate that these eight core genes play a crucial role in regulating the immune microenvironment of breast cancer (BRCA) patients. Meanwhile, an independent diagnostic model based on the expression of these eight genes shows limited independent diagnostic value, and its independent prognostic value is unsatisfactory, with the time ROC AUC values generally below 0.5. According to the results of logistic regression neural networks and risk prognosis models, when these eight genes interact synergistically, they can serve as excellent biomarkers for the diagnosis and prognosis of breast cancer patients. Furthermore, the research findings have been confirmed through qPCR experiments and validation. Conclusion: In conclusion, we explored the mechanisms of ERS in BRCA patients and identified 8 outstanding biomolecular diagnostic markers and prognostic indicators. The research results were double-validated using the GEO database and qPCR.

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根据内质网应激相关基因鉴定乳腺癌亚型并分析乳腺癌患者的预后和免疫微环境
导言:内质网应激(ERS)是对未折叠蛋白积累的一种反应,在肿瘤的发展过程中起着至关重要的作用,包括肿瘤细胞的侵袭、转移和免疫逃避等过程。然而,ERS在乳腺癌(BC)中的具体调控机制仍不清楚。研究方法在这项研究中,我们分析了癌症基因组图谱(TCGA)中的乳腺癌 RNA 测序数据,并确定了 8 个与 ERS 相关的核心基因:ELOVL2、IFNG、MAP2K6、MZB1、PCSK6、PCSK9、IGF2BP1 和 POP1。我们评估了它们在乳腺癌患者中的个体表达、独立诊断和预后价值。多因素 Cox 分析建立了一个风险预后模型,并通过外部数据集进行了验证。此外,我们还对这些基因的免疫浸润和药物敏感性进行了全面评估。结果结果表明,这八个核心基因在调节乳腺癌(BRCA)患者的免疫微环境中起着至关重要的作用。同时,基于这八个基因表达的独立诊断模型显示出的独立诊断价值有限,其独立预后价值也不理想,时间 ROC AUC 值普遍低于 0.5。根据逻辑回归神经网络和风险预后模型的结果,当这八个基因协同作用时,它们可以作为乳腺癌患者诊断和预后的优秀生物标志物。此外,研究结果还通过 qPCR 实验和验证得到了证实。结论总之,我们探索了 BRCA 患者 ERS 的发生机制,并确定了 8 个优秀的生物分子诊断标志物和预后指标。研究结果通过 GEO 数据库和 qPCR 进行了双重验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.40
自引率
0.00%
发文量
202
审稿时长
2 months
期刊介绍: Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.
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