The prognostic value of arachidonic acid metabolism in breast cancer by integrated bioinformatics

Abstract

Abstract Background As the second cause of cancer death in women, breast cancer has become a worldwide priority. Previous studies based on tumour cell lines demonstrated that arachidonic acid (AA) and its metabolites promote cancer development. However, recent studies based on the tumour microenvironment revealed the antitumour effect of AA metabolism. Therefore, it is essential to reevaluate and elucidate the effect of AA metabolism on breast cancer. Methods Raw data were obtained from The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO) databases. The AA metabolic score of each sample, enrichment of differentially expressed genes (DEGs) and immune infiltration were analysed by bioinformatics. Cox regression and least absolute shrinkage and selection operator regression were performed to establish an AA metabolism prognostic signature. An AA metabolism related nomogram for predicting the survival probability of patients was built. Result AA metabolism was related to good prognosis in the TCGA-BRCA and METABRIC cohort. DEGs enrichment suggested that the upregulated DEGs of the high AA metabolism group were significantly enriched in immune-related pathways. The high AA metabolism group was infiltrated with more CD8+ T cells and activated NK cells. An AA metabolic signature (SPINK8, KLRB1, APOD and PIGR) was constructed for breast cancer prognosis. Conclusion The study indicated that a high level of AA metabolism may be a biomarker for good prognosis in breast cancer, providing a possible explanation for the discouraging effect of cyclooxygenase inhibitors in cancer therapy. Moreover, a novel AA metabolic prognostic signature was constructed in the study, providing a novel strategy for breast cancer.

Keywords

• Breast cancer
• Arachidonic acid metabolism
• Bioinformatics
• Immune