Multi-omics analysis of the effects of pla2g4a on the prognosis of various cancers and its experimental validation in breast cancer cell lines

作者：Yao Qian, Quan Yuan, Hao Yu, Rongjie Ye, Ming Niu, Feng Liu · 发表于：Discover Oncology · 年份：2025 · DOI：10.1007/s12672-025-03118-6 · 被引用次数：3 · 研究领域：Ferroptosis and cancer prognosis、Extracellular vesicles in disease、Immune cells in cancer

BACKGROUND: Platelet-related exosomes (PREs) are microparticles secreted by platelets into the bloodstream and are implicated in various cancer processes. This study aims to identify critical genes involved in Breast Cancer (BC)-associated PREs and to evaluate their role in cancer prognosis. PLA2G4A was identified as a key gene through the use of machine learning techniques and various genomic analyses, providing a foundation for precision medicine in BC treatment. METHODS: Download cancer-related data from databases such as UCSC Xena and ExMdb, use LASSO Cox regression and various machine learning algorithms to screen genes associated with BC survival, and perform functional and pathway enrichment analysis. The expression, immune relevance, diagnostic efficacy, and drug sensitivity of the PLA2G4A gene in pan-cancer and BC were specifically analyzed. The function of PLA2G4A in BC was validated through experiments, and its drug response and molecular docking were predicted using various databases and software tools. RESULTS: Machine learning methods and LASSO Cox regression were applied to analyze the relationship between gene expression and BC survival. PLA2G4A was identified as a key gene associated with cancer prognosis, supported by analyses of differential gene expression, survival outcomes, single nucleotide variations (SNVs), and copy number variations (CNVs). Biological pathway analyses through KEGG, GO, and GSEA highlighted PLA2G4A's involvement in key cancer-related ...