Screening Co-Diagnostic Genes for Lung Adenocarcinoma and Myocardial Infarction and Analysis of the Molecular Functions and Drug Value of the Genes.

Abstract

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer, and myocardial infarction (MI) is an acute cardiovascular disease resulting from the disruption of coronary blood supply. Recent studies have suggested that these two diseases may share common molecular mechanisms.

Aim: The aim of this study was to discover common diagnostic genes for LUAD and MI and analyze their molecular functions and potential drug values by applying bioinformatics analysis.

Objective: The objective was to provide a theoretical basis for further research on the pathological mechanisms of LUAD and MI, contributing to the development of novel diagnostic and therapeutic strategies for the two diseases.

Methods: In this study, the datasets of LUAD and MI were obtained from TCGA and GEO databases, and differential expression analysis was performed to screen significantly differentially expressed genes (DEGs). Subsequently, disease-related genes were identified using WGCNA analysis, and the biological functions of these genes were explored by functional enrichment analysis. After screening key genes using the protein-protein interaction (PPI) network and the cytoHubba algorithm, biomarkers were determined by LASSO and SVM-RFE machine-learning methods. Finally, immune infiltration analysis and drug prediction were performed, and biomarker expression was verified by single-cell sequencing analysis.

Results: A total of 158 differentially upregulated genes were identified between LUAD and MI. WGCNA analysis screened 86 genes that were significantly associated with both diseases and were enriched in an inflammatory response and immune regulation-related pathways, such as the IL-17 signaling pathway. Ten significant genes were identified by the PPI network and cytoHubba and then reduced to 4 using LASSO and SVM-RFE. Noticeably, MMP9 was significantly overexpressed in both diseases. Immune infiltration analysis showed that MMP9 was significantly related to multiple immune cell infiltration. Drug prediction and molecular docking analysis predicted Ilomastat and Osthole as the potential target drugs. Single-cell sequencing analysis revealed that MMP9 was high-expressed in the macrophages in LUAD tissues.

Conclusion: This study identified MMP9 as a common diagnostic gene and potential therapeutic target for both LUAD and MI and revealed its role in inflammation and immune regulation through comprehensive bioinformatics analysis. These findings provided a theoretical basis for further research on the pathological mechanisms of LUAD and MI, contributing to the development of novel diagnostic and therapeutic strategies.