Identification of key genes and biological pathways in lung adenocarcinoma by integrated bioinformatics analysis

ARTICLE HIGHLIGHTS

Research background

Adenocarcinoma of the lung (LUAD) is currently a cancer with high mortality. This study identified the biomarkers and therapeutic targets related to LUAD through bioinformatics analysis.

Research motivation

As of now, there are few biological analyses related to LUAD. Therefore, this study hopes to further study through big data analysis.

Research objectives

To determine reliable prognostic biomarkers for early diagnosis and treatment of Adenocarcinoma of the lung.

Research methods

This article adopts bioinformatics methods such as gene Expression Omnibus (GEO) database, weighted gene co-expression network analysis, GEO2R, Gene Ontology analysis, protein-protein interaction network construction, University of Alabama at Birmingham Cancer data analysis portal database, etc.

Research results

We found three genes, namely, cellular retinoic acid binding protein 2, matrix Metalloprotein peptidase 12 and DNA Topoisomerase II α. The high expression of these genes is related to the poor prognosis of LUAD, and these Gene expression have high diagnostic value.

Research conclusions

We identified genes related to LUAD treatment and prognosis through bioinformatics methods, providing important information for the complete cure of LUAD.

Research perspectives

At present, there is little bioinformatics research related to LUAD. Through Big data screening, this study has more accurately identified the biomarkers and therapeutic targets related to LUAD, providing important information for the complete cure of LUAD in the future.