Prognostic significance and identification of m6A regulator genes and hub genes associated with m6A in breast cancer.

IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Discover. Oncology Pub Date : 2024-11-12 DOI:10.1007/s12672-024-01521-z
Longjie Xia, Runchun Huang, Yingxiong Huang, Huixian Huang, Yunxiang Luo, Yixuan Qin, Shaoliang Zhu, Fanbiao Kong, Weiwei Miao
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Abstract

This research endeavors to investigate the functions of N6-methyladenosine (m6A) regulatory genes and key genes linked to m6A modifications within the context of breast cancer (BC). The objective is to identify a promising predictive biomarker related to m6A modifications and validate its significance in BC through experimental methodologies. Utilizing data from The Cancer Genome Atlas (TCGA) database, a model for predicting prognosis was developed. Key genes connected to m6A modifications were discerned using weighted gene co-expression network analysis (WGCNA) coupled with LASSO and Cox regression analyses, which were then utilized to construct a predictive model. The influence of ZNF260 within BC was probed experimentally. The predictive model formulated using m6A regulatory genes and key m6A-associated genes demonstrated the capability to categorize BC patients into distinct risk groups effectively (all P < 0.001). Clinical sample analyses revealed notably elevated expression levels of ZNF260 in hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR + /HER2-) BC tissues compared to adjacent non-tumor tissues (all P < 0.001). Reduction in ZNF260 expression was shown to inhibit the proliferation, clonogenicity, migration, and invasiveness of MCF-7 cells while concomitantly enhancing apoptosis (all P < 0.001).This investigation uniquely uncovered ZNF260 as a novel key gene, suggesting its potential utility as a predictive biomarker associated with m6A modifications specifically in HR + /HER2- BC.

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乳腺癌 m6A 调节基因和与 m6A 相关的枢纽基因的预后意义和鉴定。
本研究致力于研究乳腺癌(BC)中 N6-甲基腺苷(m6A)调控基因的功能以及与 m6A 修饰相关的关键基因。研究的目的是找出与 m6A 修饰相关的有前景的预测性生物标志物,并通过实验方法验证其在乳腺癌中的意义。利用癌症基因组图谱(TCGA)数据库中的数据,建立了一个预测预后的模型。通过加权基因共表达网络分析(WGCNA)以及LASSO和Cox回归分析,发现了与m6A修饰相关的关键基因,并以此构建了预测模型。实验探究了 ZNF260 在 BC 中的影响。利用 m6A 调控基因和关键 m6A 相关基因建立的预测模型显示,该模型能有效地将 BC 患者分为不同的风险组(所有 P
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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