Validating linalool as a potential drug for breast cancer treatment based on machine learning and molecular docking

Abstract

Breast cancer (BC) is a common cancer for women. This study aims to construct a prognostic risk model of BC and identify prognostic biomarkers through machine learning approaches, and clarify the mechanism by which linalool exerts tumor-suppressive function. Three mRNA microarray/RNA sequencing data sets (GSE25055, GSE103091, and TCGA-BRCA) were obtained from Gene Expression Omnibus database and The Cancer Genome Atlas database, and prognostic genes were obtained by univariate COX analysis. Multiple machine learning methods were used to screen core genes and construct prognostic risk models. The enrichment analysis of crucial genes was analyzed using the DAVID database. UALCAN, human protein atlas, geneMANIA, and LinkedOmics databases were used to analyze gene expression and co-expressed genes. Molecular docking and molecular dynamics simulation was applied to verify the binding affinity between linalool and phosphoglycerate kinase 1 (PGK1). Cell counting kit 8 (CCK-8, Edu, transwell, flow cytometry, and Western blot assay were used to analyze cell activity, apoptosis, cell cycle and protein expression. Eight prognostic genes were obtained by bioinformatics analysis and machine learning, and prognostic risk models were constructed. This model could well predict the prognosis of patients, and the risk score could be used as an independent risk factor for BC. Overall survival (OS) and immune cell infiltration characteristics were distinct between high and low risk groups. PGK1 was highly expressed in BC and the OS of patients with high PGK1 expression was shorter. PGK1 was related to cell cycle and PPAR signaling pathway. Linalool and PGK1 had good binding activity, and linalool could inhibit the viability, proliferation, migration, and invasion of BC cells, promote cell apoptosis, and induce G0/G1 arrest. In addition, linalool can promote PPARγ protein expression and inhibit PGK1 expression. Machine learning and molecular docking were promising for exploration of new drug targets for BC, and linalool exerts tumor-suppressive effects in BC by inhibiting PGK1 expression and activating PPAR signaling pathway.

Keywords: breast cancer; cell cycle; machine learning; molecular docking.