Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells

Abstract Background: Cardioembolic stroke (CS) and atherosclerosis (AS) are closely related diseases. Ferroptosis, a novel form of programmed cell death, may play a key role in CS and AS. However, the pathophysiological mechanisms underlying their coexistence remain unclear. This study aims to identify the hub genes and pathways involved in developing both diseases. Methods: CS (GSE58294) and AS (GSE20129) datasets were obtained from the Gene Expression Omnibus database, and a ferroptosis (FR)-related gene dataset was downloaded from the FR database.