Identification of gene signatures associated with lactation for predicting prognosis and treatment response in breast cancer patients through machine learning.

ABSTRACT: As a newly discovered histone modification, abnormal lactation has been found to be present in and contribute to the development of various cancers. The aim of this study was to investigate the potential role between lactylation and the prognosis of breast cancer patients. Lactylation-associated subtypes were obtained by unsupervised consensus clustering analysis. Lactylation-related gene signature (LRS) was constructed by 15 machine learning algorithms, and the relationship between LRS and tumor microenvironment (TME) as well as drug sensitivity was analyzed. In addition, the expression of genes in the LRS in different cells was explored by single-cell analysis and spatial transcriptome. The expression levels of genes in LRS in clinical tissues were verified by RT-PCR. Finally, the potent

SUBMITTER: Zhao J 

PROVIDER: S-EPMC12009422 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature