Title:Screening Co-Diagnostic Genes for Lung Adenocarcinoma and Myocardial Infarction and Analysis of the Molecular Functions and Drug Value of the Genes
Volume: 26
Issue: 1
Author(s): Nannan Du, Mengting Liang and Zongjun Liu*
Affiliation:
- Department of Cardiology, Shanghai Putuo District Central Hospital, Shanghai, 200062, China
Keywords:
Lung adenocarcinoma, myocardial infarction, PPI network, molecular docking, MMP9, drug.
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.
Aims: 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.
