Abstract
The relationship between atherosclerosis (AS) and lung cancer has garnered growing interest recently, as their frequent co-occurrence jointly drives global mortality and worsens prognosis. Current observational evidence is inconclusive and remains vulnerable to residual confounding and reverse causality, underscoring the imperative for methodologically rigorous causal inference. The potential causal relationship between AS and lung cancer was investigated using Mendelian randomization (MR). Subsequently, transcriptomic analysis was conducted using public datasets, followed by the construction of an AS-associated lung cancer prognostic model using LASSO-Cox regression and the evaluation of its performance. Finally, ESTIMATE and ssGSEA algorithms were used to evaluate the 2 groups of immune infiltration. A significant inverse causal association between AS and lung cancer was demonstrated by MR analysis (P = .01, OR = 0.896, CI = 0.825 - 0.974). Furthermore, 2 risk groups of patients with lung cancer, characterized by different prognoses and immune landscapes, were stratified using a risk scoring model that comprised 3 AS-related genes (CD52, FABP5, and FCGR3A). The tumor microenvironment in the low-risk group of lung cancer had a higher proportion of immune cells, and the infiltration levels of neutrophils and mast cells were significantly higher than those in high-risk patients. The MR analysis in this study revealed that genetic alterations in AS were significantly associated with a reduced risk of lung cancer. Transcriptomic data indicated that chronic inflammation linked AS and lung cancer: inflammatory mediators drove AS yet restrained lung cancer progression in the tumor microenvironment, while AS-derived immune molecules and pathways further suppressed tumor growth.