基于肿瘤浸润调节性T细胞的乳腺癌分子亚型和预后特征鉴定

IF 1.9 4区 医学 Q3 OBSTETRICS & GYNECOLOGY
Breast Journal Pub Date : 2025-03-05 DOI:10.1155/tbj/6913291
Jianying Ma, Gang Hu, Lianghong Kuang, Zhongzhong Zhu
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引用次数: 0

摘要

背景:T调节性细胞(Tregs)对维持免疫耐受至关重要。它们在许多肿瘤中大量存在,阻碍了潜在的有益抗肿瘤反应。然而,它们对乳腺癌(BC)的预测意义仍不明确。本研究旨在探索与Tregs相关的基因,并开发与Tregs相关的预后特征。方法:从Cancer Genome Atlas (TCGA)和gene expression Omnibus (GEO)数据库中获取BC的基因表达和临床资料。结合CIBERSORT和加权相关网络分析(WGCNA)算法,识别与treg相关的模块。利用共识聚类算法创建由Tregs相关基因决定的分子亚型。然后,构建与Tregs相关的预后特征,并评估其与肿瘤免疫和预后的关系。结果:蓝色模块基因与Tregs相关性最显著,共获得1080个与Tregs相关的基因。从TCGA数据集中共发现93个基因对患者预后有显著影响。通过一致聚类分析,将BC省样本分为两类。总生存率、免疫检查点基因、分子亚型和生物学行为在这两种亚型之间存在显著差异。在TCGA和GEO数据集中,从两种亚型之间的差异表达基因开发的10个基因特征显示出一致的预后准确性。它作为BC患者的独立预后指标。此外,低风险患者更倾向于表现出更高的免疫细胞浸润、TME评分和肿瘤突变负担(TMB)。与此同时,与高风险组相比,低风险组的个体对免疫疗法表现出更好的反应。结论:由tregs相关基因衍生的预后模型有助于评估预后,指导个性化治疗,并有可能提高BC患者的临床预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Identification of the Molecular Subtype and Prognostic Characteristics of Breast Cancer Based on Tumor-Infiltrating Regulatory T Cells

Identification of the Molecular Subtype and Prognostic Characteristics of Breast Cancer Based on Tumor-Infiltrating Regulatory T Cells

Background: T regulatory cells (Tregs) are essential for preserving immune tolerance. They are present in large numbers in many tumors, hindering potentially beneficial antitumor responses. However, their predictive significance for breast cancer (BC) remains ambiguous. This study aimed to explore genes associated with Tregs and develop a prognostic signature associated with Tregs.

Methods: The gene expression and clinical data on BC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The integration of CIBERSORT and weighted correlation network analysis (WGCNA) algorithms was utilized to identify modules associated with Tregs. The consensus cluster algorithm was utilized to create molecular subtypes determined by genes associated with Tregs. Then, a prognostic signature associated with Tregs was constructed and its relationship to tumor immunity and the prognosis was evaluated.

Results: The blue module genes exhibited the most significant correlation with Tregs, and 1080 genes related to Tregs were acquired. A total of 93 genes from the TCGA dataset were found to have a significant impact on patient prognosis. Samples from BC were categorized into two clusters by consensus cluster analysis. The overall survival, immune checkpoint genes, molecular subtype, and biological behaviors varied significantly between these two subtypes. A 10-gene signature developed from differentially expressed genes between two subtypes demonstrated consistent prognostic accuracy in both TCGA and GEO datasets. It functioned as a standalone prognostic marker for individuals with BC. In addition, patients with low risk are more inclined to exhibit increased immune cell infiltration, TME score, and tumor mutation burden (TMB). Meanwhile, Individuals classified within the low-risk group showed better responses to immunotherapies compared to their counterparts in the high-risk group.

Conclusions: The prognostic model derived from Tregs-related genes could aid in assessing the prognosis, guiding personalized treatment, and potentially enhancing the clinical outcomes for patients with BC.

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来源期刊
Breast Journal
Breast Journal 医学-妇产科学
CiteScore
4.00
自引率
0.00%
发文量
47
审稿时长
4-8 weeks
期刊介绍: The Breast Journal is the first comprehensive, multidisciplinary source devoted exclusively to all facets of research, diagnosis, and treatment of breast disease. The Breast Journal encompasses the latest news and technologies from the many medical specialties concerned with breast disease care in order to address the disease within the context of an integrated breast health care. This editorial philosophy recognizes the special social, sexual, and psychological considerations that distinguish cancer, and breast cancer in particular, from other serious diseases. Topics specifically within the scope of The Breast Journal include: Risk Factors Prevention Early Detection Diagnosis and Therapy Psychological Issues Quality of Life Biology of Breast Cancer.
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