异常的代谢紊乱和肿瘤组织和细胞中显著的糖酵解改变是乳腺癌进展的标志。该研究旨在利用生物信息学分析阐明介导乳腺癌异常糖酵解的关键生物标志物和途径。我们进行了差异基因表达分析、基因本体分析、京都基因和基因组百科全书分析、基因集富集分析以及相关性分析，以探索糖酵解相关基因的表达和预后意义。我们有效地整合了4个基因来构建一个对高风险与低风险组预后有较短存活时间的预测模型。预测模型表现出良好的预测价值，并且可能是乳腺癌预后的一部分。生存分析和受试者工作特征曲线表明，这个标记在癌症基因组图谱训练组和2个基因表达综合数据库验证组中具有良好的预测性能。多变量分析表明，这4个基因标记具有独立的预后价值。此外，所有校准曲线都表现出了在预测预后中的有效性。我们建立了一个优化的4个基因标记，以澄清糖酵解和乳腺癌之间的关联，并为乳腺癌患者的风险分层和预后预测提供了一个有吸引力的平台。版权所有 © 2023作者， Wolters Kluwer Health, Inc.出版。

Aberrant metabolic disorders and significant glycolytic alterations in tumor tissues and cells are hallmarks of breast cancer (BC) progression. This study aims to elucidate the key biomarkers and pathways mediating abnormal glycolysis in breast cancer using bioinformatics analysis. Differential genes expression analysis, gene ontology analysis, Kyoto encyclopedia of genes and genomes analysis, gene set enrichment analyses, and correlation analysis were performed to explore the expression and prognostic implications of glycolysis-related genes. We effectively integrated 4 genes to construct a prognostic model of shorter survival in the high-risk versus low-risk group. The prognostic model showed promising predictive value and may be an integral part of the prognosis of BC. The survival analysis and receiver operating characteristic curves suggested that the signature showed a good predictive performance in both the The Cancer Genome Atlas training set and 2 gene expression omnibus validation sets. Multivariable analysis demonstrated that the 4-gene signature had an independent prognostic value. Furthermore, all calibration curves exhibited robust validity in prognostic prediction. We established an optimized 4-gene signature to clarify the connection between glycolysis and BC, and offered an attractive platform for risk stratification and prognosis predication of BC patients.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.