Identification of biomarkers based on ubiquitin-correlated genes for predicting immune profile and drug sensitivity in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) shows high recurrence rate and poor prognosis. Genes associated with ubiquitin play a role in the onset and advancement of cancers; however, they have yet to be employed for the diagnosis and prognosis of LUAD. Methods: First, gene modules correlated with ubiquitin were identified by WGCNA. The expression profiles obtained were intersected with differential genes taken between the LUAD and control samples. The genes were then further compressed using univariate and multifactorial Cox regression analyses and risk models. In addition, the model was validated by constructing a nomogram using clinical characteristics and Riskscore. Next, the differences in immune infiltration between different subgroups were explored, and immunotherapy and drug sensitivity evaluations were performed. The biological role of Results: The intersection between the module genes between LUAD samples and control samples and differentially expressed genes (DEGs) yielded 197 intersected genes after we screened three particular modules with the strongest ubiquitin association by WGCNA. 32 genes associated with LUAD prognosis were screened, and Conclusion: This study is the first to systematically integrate the ubiquitin pathway with multi-omics data, constructing a robust risk model for LUAD prognosis and immune characteristics, providing a theoretical reference for future exploration of potential biomarkers for LUAD patients' diagnosis.